Question: Given a RGB image and a depth image, please detect the 3D bounding box of the seat in the scene. The camera pose information includes: the rotation matrix: [[0.000188, -0.47362, 0.88073], [-0.997828, 0.057931, 0.031365], [-0.065877, -0.878822, -0.47258]]; the translation vector: [4.366519, 5.511691, 1.307889], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[0.985, 1.36, 0.323, 0.802, 0.423, -0.124], [2.422, 0.684, 0.754, 0.948, 0.198, 0.546], [-0.687, -2.501, -0.196, 0.73, 0.321, 0.703]]
B: [[1.365, 1.983, 0.034, 0.504, 0.741, 0.248], [1.92, 1.004, 0.632, 0.401, 0.542, 0.139], [-0.839, -2.927, -0.163, 0.351, 0.752, 0.304]]
C: [[1.454, 1.792, 0.377, 0.63, 0.637, 0.263], [2.367, 0.546, 0.29, 0.458, 0.434, 0.427], [-1.072, -2.953, 0.222, 0.398, 0.377, 0.406]]
D: [[1.15, 1.795, -0.026, 0.476, 0.371, 0.563], [2.092, 0.112, 0.084, 0.025, 0.591, 0.3], [-1.071, -3.278, 0.072, 0.031, 0.342, 0.689]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the door in the scene. The camera pose information includes: the rotation matrix: [[0.927869, -0.125596, 0.351119], [-0.372891, -0.32108, 0.870551], [0.003399, -0.938687, -0.344754]]; the translation vector: [5.442723, 4.031985, 1.348893], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-1.531, 1.811, 0.438, 0.96, -0.248, 1.075], [-1.41, -1.002, 0.77, 0.47, 1.246, 1.71]]
B: [[-0.951, 1.545, 0.971, 1.428, 0.629, 1.104], [-2.05, -1.043, 0.695, 0.095, 1.11, 1.626]]
C: [[-1.029, 1.273, 0.377, 1.0, 0.707, 1.651], [-1.265, -0.353, 1.355, -0.02, 0.917, 2.297]]
D: [[-1.312, 1.674, 0.691, 1.103, 0.228, 1.421], [-1.753, -0.603, 0.956, 0.349, 1.091, 2.04]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the shelf in the scene. The camera pose information includes: the rotation matrix: [[-0.070416, -0.411804, 0.908548], [-0.99671, 0.065705, -0.047468], [-0.040148, -0.908901, -0.415075]]; the translation vector: [2.214543, 1.806687, 1.391502], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-2.1, -0.155, 0.488, 0.884, 0.762, 1.139]]
B: [[-1.609, -0.239, 0.938, 0.096, 1.426, 1.078]]
C: [[-1.861, -0.273, 0.81, 0.598, 0.82, 0.783]]
D: [[-1.644, -0.605, 0.583, 0.402, 1.231, 1.185]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the ceiling in the scene. The camera pose information includes: the rotation matrix: [[-0.955421, 0.119616, -0.269932], [0.295248, 0.388339, -0.872939], [0.000408, -0.91372, -0.406343]]; the translation vector: [2.65583, 2.981598, 1.368648], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-0.605, -0.075, 2.599, 6.78, 7.188, 0.753]]
B: [[-0.136, -0.074, 2.664, 7.091, 7.331, 0.624]]
C: [[-0.11, -0.067, 2.645, 6.713, 7.047, 0.627]]
D: [[-0.59, -0.552, 3.048, 6.673, 7.52, 0.884]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the ceiling in the scene. The camera pose information includes: the rotation matrix: [[-0.454685, 0.144673, -0.878824], [0.890085, 0.109034, -0.442562], [0.031795, -0.983454, -0.178347]]; the translation vector: [3.311996, 2.119304, 1.59409], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[1.773, 0.999, 2.176, 3.762, 2.16, 0.713]]
B: [[1.402, 0.542, 2.42, 3.544, 2.145, 0.268]]
C: [[0.962, 0.894, 1.956, 3.984, 2.23, 0.213]]
D: [[1.508, 0.544, 2.14, 3.898, 2.009, 0.701]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the coffee table in the scene. The camera pose information includes: the rotation matrix: [[0.990268, -0.101591, 0.095124], [-0.135934, -0.559426, 0.817658], [-0.029851, -0.822631, -0.567792]]; the translation vector: [6.679901, 2.488796, 1.402653], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[1.445, -1.591, 0.401, 1.208, 0.362, 0.709], [0.85, 1.846, 0.287, 0.495, 1.135, -0.015]]
B: [[1.318, -1.383, 0.256, 0.782, 0.724, 0.542], [1.339, 2.155, 0.239, 0.765, 0.899, 0.445]]
C: [[1.731, -1.727, 0.665, 0.715, 0.694, 0.718], [0.941, 2.531, -0.018, 1.235, 0.51, 0.14]]
D: [[1.454, -1.414, -0.024, 0.443, 0.46, 0.088], [0.989, 2.555, 0.477, 1.003, 1.282, 0.286]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the object in the scene. The camera pose information includes: the rotation matrix: [[0.246516, -0.470365, 0.847341], [-0.959136, 0.006886, 0.282862], [-0.138884, -0.882445, -0.449446]]; the translation vector: [3.043058, 2.955299, 1.551102], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[1.849, -1.336, 0.075, 0.117, 0.119, 0.051]]
B: [[1.779, -1.476, 0.442, 0.485, 0.615, 0.395]]
C: [[1.904, -1.448, 0.152, 0.474, 0.108, -0.174]]
D: [[1.427, -1.203, 0.391, 0.059, -0.193, -0.208]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[0.424269, -0.366439, 0.828081], [-0.894198, -0.025281, 0.446957], [-0.142848, -0.930098, -0.338395]]; the translation vector: [2.638367, 6.760901, 1.41712], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[1.487, 1.645, 0.382, 0.302, 0.482, 0.482], [0.998, 1.485, 0.258, 0.64, 0.279, 0.771], [0.516, 1.799, 0.05, 0.639, 0.719, 0.616], [0.027, 2.307, 0.334, 0.459, 0.957, 1.087], [-0.766, 2.114, 0.879, 0.637, 0.926, 1.186], [-1.637, 1.716, 0.195, 0.889, 0.178, 0.887], [-1.878, 1.498, 0.042, 1.014, 0.211, 0.465], [-2.168, 2.812, 0.748, 0.089, 0.133, 0.111], [-2.511, -0.128, 0.278, 0.262, 0.627, 1.122], [-3.252, -1.403, 0.351, 0.543, 0.875, 0.964], [-2.67, -1.518, 0.047, 0.142, 0.368, 0.87], [-0.679, -1.008, 0.86, 0.74, 0.76, 1.005], [-0.054, -1.776, 0.013, 0.602, 0.383, 0.483], [0.442, -1.702, 0.129, 0.294, 0.491, 1.264], [-0.906, -1.527, 0.588, 0.773, 1.129, 1.323], [1.797, -0.711, 0.306, 0.186, 0.995, 1.019], [1.694, -1.236, 0.46, 0.778, 1.151, 1.284], [1.24, -1.901, 0.667, 0.364, 1.023, 0.918], [2.398, -1.858, 0.981, 0.284, 0.726, 0.83], [3.224, -1.673, 0.285, 0.245, 0.491, 0.975], [1.768, 2.317, 0.9, 0.325, 1.027, 1.062], [1.496, 2.661, 0.93, -0.007, 0.819, 0.169]]
B: [[1.146, 0.948, 0.122, 0.95, 1.005, 0.549], [0.748, 0.973, 0.155, 0.6, 0.484, 0.381], [0.549, 2.17, 0.091, 0.666, 0.717, 0.866], [0.554, 2.811, 0.815, 0.733, 0.125, 0.7], [-0.925, 2.187, 0.558, 0.622, 0.213, 0.874], [-1.744, 1.277, 0.001, 0.646, 0.973, 0.704], [-1.809, 2.353, 0.808, 0.048, 0.797, 0.7], [-1.256, 2.641, 1.036, 0.522, 0.609, 0.158], [-1.879, -0.087, 0.596, 0.81, 0.571, 0.463], [-3.345, -0.961, 0.298, 0.354, 0.59, 1.207], [-2.802, -1.895, 0.135, 0.976, 1.183, 0.764], [-0.847, -1.618, 0.508, 0.783, 0.348, 1.292], [-0.511, -1.056, 0.376, 0.73, 0.392, 1.159], [-0.024, -2.057, 0.759, 0.532, 0.455, 0.817], [-0.251, -2.214, 0.173, 1.127, 0.862, 0.708], [2.174, -0.228, 0.822, 0.364, 0.554, 0.827], [1.928, -1.877, 0.198, 0.653, 1.131, 1.053], [1.218, -2.319, 0.663, 0.163, 0.153, 0.793], [2.951, -1.156, 0.405, 1.011, 0.624, 0.772], [3.153, -1.986, 0.421, 0.263, 0.33, 0.7], [1.367, 2.28, 0.547, 1.058, 0.935, 1.287], [2.006, 2.966, 0.782, 0.332, 0.619, 0.04]]
C: [[1.346, 1.054, 0.767, 0.951, 0.758, 0.769], [0.659, 1.706, 0.684, 0.913, 0.914, 1.319], [0.805, 2.288, 0.288, 0.155, 0.839, 0.635], [0.287, 2.236, 0.545, 0.587, 0.976, 0.783], [-1.118, 2.319, 0.772, 1.192, 0.851, 0.415], [-1.552, 1.463, 0.231, 0.636, 0.79, 0.457], [-1.992, 2.15, 0.851, 0.919, 1.11, 0.624], [-1.923, 2.253, 1.26, 0.407, 0.257, 0.58], [-2.064, -0.023, 0.196, 0.32, 0.999, 0.859], [-3.224, -1.369, 0.324, 1.046, 0.849, 0.941], [-2.953, -2.153, 0.953, 0.315, 0.426, 0.39], [-0.29, -1.189, 0.464, 0.368, 1.039, 1.28], [-0.098, -2.0, 0.391, 0.817, 0.212, 1.036], [0.365, -1.822, 0.164, 0.214, 0.365, 0.378], [-0.847, -2.191, 0.875, 0.968, 0.479, 0.553], [2.332, -0.438, 0.431, 0.138, 0.956, 1.041], [1.345, -2.004, 0.538, 0.439, 0.287, 0.73], [1.393, -1.64, 0.88, 0.322, 0.297, 1.16], [3.052, -1.259, 0.761, 0.943, 0.828, 0.5], [2.735, -2.476, 0.875, 0.335, 1.087, 0.495], [1.336, 2.088, 0.504, 0.673, 1.053, 0.469], [1.386, 2.116, 0.605, 0.191, 0.61, 0.101]]
D: [[1.518, 1.271, 0.394, 0.605, 0.594, 0.849], [0.943, 1.353, 0.378, 0.619, 0.666, 0.828], [0.701, 1.955, 0.404, 0.648, 0.696, 0.84], [0.523, 2.479, 0.454, 0.541, 0.563, 0.792], [-1.051, 2.117, 0.448, 0.79, 0.709, 0.804], [-1.341, 1.248, 0.462, 0.57, 0.622, 0.853], [-1.574, 1.994, 0.519, 0.538, 0.675, 0.779], [-1.737, 2.403, 0.858, 0.16, 0.317, 0.168], [-2.078, -0.466, 0.495, 0.568, 0.586, 0.801], [-2.925, -1.082, 0.538, 0.66, 0.66, 0.803], [-3.037, -1.752, 0.519, 0.574, 0.705, 0.845], [-0.539, -1.191, 0.375, 0.64, 0.637, 0.843], [-0.068, -1.536, 0.384, 0.646, 0.641, 0.825], [-0.052, -2.09, 0.408, 0.661, 0.773, 0.824], [-0.669, -1.919, 0.395, 0.676, 0.647, 0.832], [2.151, -0.689, 0.438, 0.636, 0.62, 0.802], [1.695, -1.528, 0.421, 0.589, 0.733, 0.82], [1.703, -2.028, 0.457, 0.561, 0.65, 0.798], [2.65, -1.483, 0.534, 0.701, 0.712, 0.852], [2.844, -2.087, 0.588, 0.548, 0.714, 0.804], [1.775, 1.985, 0.459, 0.664, 0.67, 0.811], [1.768, 2.603, 0.602, 0.329, 0.514, 0.537]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the box in the scene. The camera pose information includes: the rotation matrix: [[0.764638, 0.028658, -0.643823], [0.64431, -0.055554, 0.762744], [-0.013909, -0.998044, -0.060944]]; the translation vector: [3.061982, 3.98913, 1.495508], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[2.682, 0.363, 0.619, 1.02, 0.762, 0.226], [0.295, -1.101, 1.206, 0.33, 0.677, 0.052], [-2.902, 0.765, -0.248, 0.755, 0.487, 0.427]]
B: [[2.599, 0.763, 0.355, 0.291, 0.253, 0.563], [0.364, -0.942, 0.366, 0.823, 0.285, 0.293], [-3.251, -0.039, 0.534, 0.204, 0.315, 0.125]]
C: [[2.754, 0.716, 0.728, 0.739, 0.536, 0.095], [-0.308, -0.319, 1.147, 0.102, 0.805, 0.177], [-3.102, -0.022, 0.312, 0.658, 0.474, 0.358]]
D: [[2.461, 0.569, 0.328, 0.546, 0.491, 0.37], [-0.048, -0.818, 0.757, 0.462, 0.439, 0.351], [-2.848, 0.285, 0.131, 0.472, 0.5, 0.37]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[-0.711391, -0.463973, 0.527875], [-0.700286, 0.531398, -0.476672], [-0.059349, -0.708763, -0.702945]]; the translation vector: [2.53321, 4.394931, 1.530427], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[0.116, -0.769, 0.665, 0.588, 1.197, 1.025], [-0.796, -1.178, 0.171, 0.576, 0.604, 0.431], [-0.822, 1.221, 0.066, 0.696, 1.356, 0.542], [0.425, 0.671, 0.344, 0.824, 1.179, 0.866]]
B: [[0.608, -0.936, 0.413, 0.854, 0.8, 0.77], [-0.425, -0.856, 0.339, 0.897, 0.767, 0.762], [-0.451, 1.126, 0.358, 0.838, 0.91, 0.764], [0.774, 1.047, 0.416, 0.815, 0.841, 0.775]]
C: [[0.288, -1.283, 0.655, 0.817, 0.674, 0.566], [-0.233, -0.57, 0.023, 0.569, 0.942, 1.169], [-0.037, 0.77, 0.308, 0.824, 1.383, 0.685], [0.662, 1.515, 0.896, 0.594, 0.416, 0.9]]
D: [[1.018, -1.113, 0.375, 0.665, 0.803, 1.039], [-0.701, -1.19, 0.042, 0.611, 0.648, 0.566], [-0.236, 1.15, 0.63, 1.12, 1.165, 0.969], [0.285, 0.606, 0.443, 1.268, 0.881, 0.591]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[-0.236277, -0.452541, 0.859872], [-0.970097, 0.160455, -0.182119], [-0.055554, -0.877189, -0.47692]]; the translation vector: [1.575898, 1.961144, 1.314442], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[0.097, 1.124, 0.669, 0.502, 0.516, 0.549], [-0.719, 0.622, 0.51, 0.696, 0.696, 1.008], [0.747, 0.329, 0.449, 0.568, 0.565, 0.934], [0.72, 0.839, 0.522, 0.626, 0.707, 0.997], [-0.373, -0.636, 0.467, 0.582, 0.551, 0.906]]
B: [[0.297, 0.852, 0.7, 0.103, 0.44, 0.966], [-0.93, 0.904, 0.062, 0.986, 0.828, 0.767], [0.468, 0.69, 0.657, 0.758, 0.619, 1.108], [0.682, 0.702, 0.346, 0.75, 0.569, 0.847], [-0.423, -0.68, 0.291, 0.082, 0.385, 1.192]]
C: [[0.512, 0.853, 0.312, 0.021, 0.921, 0.339], [-0.518, 0.57, 0.844, 1.067, 0.275, 1.347], [0.721, 0.423, 0.574, 0.387, 0.991, 1.286], [0.648, 0.46, 0.149, 0.657, 0.835, 0.53], [-0.541, -0.731, 0.203, 0.127, 0.654, 0.996]]
D: [[0.168, 0.81, 1.159, 0.247, 0.182, 0.73], [-0.91, 0.423, 0.9, 0.946, 0.519, 0.547], [1.221, 0.571, 0.284, 0.571, 0.987, 1.376], [1.146, 0.534, 0.507, 0.778, 0.702, 1.372], [-0.13, -0.402, 0.492, 0.884, 0.774, 1.331]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the whiteboard in the scene. The camera pose information includes: the rotation matrix: [[-0.997074, 0.061747, -0.045056], [0.074474, 0.651998, -0.754554], [-0.017215, -0.755702, -0.654689]]; the translation vector: [1.815792, 5.369752, 1.288561], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[2.094, 0.511, 1.124, 0.123, 2.188, 0.539]]
B: [[2.081, 0.516, 0.947, 0.355, 2.545, 0.592]]
C: [[1.732, 0.343, 0.947, 0.511, 2.586, 0.308]]
D: [[1.989, 0.949, 0.649, -0.276, 2.128, 0.539]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the piano bench in the scene. The camera pose information includes: the rotation matrix: [[-0.804945, -0.278842, 0.523748], [-0.593014, 0.407765, -0.694307], [-0.019964, -0.869468, -0.493585]]; the translation vector: [4.871809, 2.494869, 1.402737], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-1.228, -1.39, 0.131, 0.85, 0.551, 0.683]]
B: [[-1.305, -1.508, 0.232, 0.822, 0.566, 0.435]]
C: [[-0.824, -1.786, 0.652, 1.27, 0.727, -0.053]]
D: [[-0.844, -1.175, 0.453, 0.328, 0.627, 0.359]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.032646, 0.194727, -0.980314], [0.998594, -0.034636, -0.040135], [-0.04177, -0.980246, -0.193322]]; the translation vector: [3.506056, 2.493951, 1.706783], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[0.141, 1.242, 1.15, 2.629, 0.737, 2.324], [-1.855, -0.469, 1.171, 0.539, 3.779, 2.772], [0.841, 0.114, 0.787, 0.691, 3.588, 2.223], [0.571, -1.772, 1.52, 1.679, 0.887, 2.594]]
B: [[-0.097, 1.504, 1.106, 3.029, 0.358, 2.218], [-1.545, 0.258, 1.211, 0.132, 3.756, 2.16], [0.905, 0.283, 1.397, -0.093, 3.002, 2.004], [0.394, -1.669, 1.139, 2.247, 0.169, 2.208]]
C: [[-0.253, 1.653, 1.522, 3.078, 0.478, 2.791], [-1.503, -0.37, 1.376, 0.691, 4.127, 2.703], [1.422, -0.022, 0.986, 0.339, 3.887, 2.497], [-0.134, -1.344, 0.891, 2.344, 0.714, 2.451]]
D: [[-0.058, 1.533, 1.269, 2.876, 0.624, 2.668], [-1.389, 0.007, 1.251, 0.231, 3.638, 2.637], [1.275, 0.042, 1.086, 0.289, 3.412, 2.272], [0.358, -1.537, 1.122, 1.906, 0.425, 2.129]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the couch in the scene. The camera pose information includes: the rotation matrix: [[-0.205964, -0.505778, 0.837716], [-0.978495, 0.11627, -0.170378], [-0.011228, -0.854792, -0.518849]]; the translation vector: [2.901534, 4.292832, 1.280844], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-2.22, -0.005, 0.817, 1.09, 2.894, 0.662], [-2.657, -0.552, 1.11, 0.97, 1.155, 0.566]]
B: [[-1.955, 0.127, 0.536, 1.492, 2.79, 1.348], [-2.155, 0.305, 0.66, 0.159, 1.455, 0.072]]
C: [[-1.433, 0.186, 1.02, 1.626, 2.332, 1.534], [-2.448, -0.356, 0.853, 0.017, 1.445, 0.618]]
D: [[-1.798, 0.428, 0.571, 1.201, 2.441, 1.114], [-2.518, -0.083, 1.081, 0.488, 1.535, 0.157]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[-0.830629, 0.239867, -0.502514], [0.556756, 0.37214, -0.742654], [0.008867, -0.896647, -0.442658]]; the translation vector: [4.849209, 2.614689, 1.447477], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-1.442, -1.133, 0.562, 0.636, 0.657, 0.49], [-0.931, -0.023, 0.592, 0.548, 0.635, 0.449], [1.185, -0.67, 0.523, 0.55, 0.618, 0.447], [-0.778, 1.905, 0.84, 0.606, 0.538, 0.514], [-0.723, -1.153, 0.514, 0.657, 0.632, 0.473], [-1.434, -0.489, 0.591, 0.567, 0.545, 0.458], [-1.479, -1.704, 0.547, 0.555, 0.643, 0.506], [-1.06, 0.579, 0.646, 0.554, 0.57, 0.426], [1.728, -0.095, 0.592, 0.547, 0.596, 0.473], [-1.358, 1.889, 0.774, 0.643, 0.662, 0.446], [2.187, 1.992, 0.739, 0.592, 0.503, 0.463], [-0.349, 1.313, 0.568, 0.481, 0.31, 0.827], [0.659, 1.035, 0.643, 0.561, 0.458, 0.449], [1.351, 1.116, 0.663, 0.567, 0.545, 0.469], [1.67, 0.521, 0.73, 0.179, 0.508, 0.285], [0.482, -0.974, 0.492, 0.592, 0.586, 0.475]]
B: [[-1.049, -1.529, 1.034, 0.201, 0.822, 0.539], [-0.9, 0.339, 0.327, 0.273, 0.766, 0.553], [0.737, -1.05, 0.211, 0.082, 0.504, 0.933], [-1.047, 2.226, 0.838, 0.996, 0.859, 0.972], [-0.719, -0.678, 0.784, 0.49, 0.145, 0.261], [-1.882, -0.392, 0.818, 0.955, 0.143, 0.713], [-1.551, -2.013, 0.366, 0.53, 0.75, 0.368], [-1.315, 0.463, 0.891, 0.81, 0.604, 0.638], [2.147, -0.334, 0.803, 0.499, 0.844, 0.692], [-1.677, 2.042, 0.864, 0.402, 1.157, 0.639], [1.976, 2.077, 0.904, 0.918, 0.711, 0.254], [-0.187, 1.603, 0.781, 0.267, -0.088, 1.027], [0.26, 0.795, 0.514, 0.847, -0.04, 0.297], [1.756, 1.456, 0.644, 0.597, 0.817, 0.47], [1.242, 0.068, 0.373, 0.448, 0.149, 0.381], [0.319, -0.553, 0.655, 0.691, 0.359, 0.589]]
C: [[-0.988, -1.282, 0.732, 0.336, 0.483, 0.927], [-0.442, -0.073, 0.808, 0.229, 0.772, 0.639], [1.548, -1.036, 0.108, 0.525, 0.245, 0.035], [-1.266, 1.685, 1.335, 0.956, 0.747, 0.267], [-1.079, -1.607, 1.01, 0.83, 1.062, 0.521], [-1.264, -0.925, 0.343, 1.047, 0.715, 0.269], [-1.458, -1.958, 0.337, 0.66, 0.161, 0.546], [-0.733, 0.312, 0.474, 0.521, 0.178, -0.061], [2.105, 0.263, 0.727, 0.39, 0.976, 0.108], [-1.707, 1.787, 0.496, 0.472, 1.062, 0.821], [2.45, 1.544, 0.321, 1.018, 0.15, 0.075], [-0.837, 1.59, 0.268, 0.538, 0.245, 0.497], [0.297, 1.19, 0.423, 0.185, 0.686, 0.323], [0.857, 1.058, 0.937, 0.887, 0.209, 0.519], [1.802, 0.184, 0.797, 0.22, 0.094, 0.637], [0.094, -0.987, 0.725, 0.553, 1.059, 0.036]]
D: [[-1.227, -0.819, 0.642, 0.301, 0.736, 0.894], [-1.335, 0.35, 0.132, 0.881, 0.202, 0.441], [1.374, -0.345, 0.698, 0.363, 1.089, 0.667], [-0.963, 1.843, 0.91, 0.493, 0.498, 0.35], [-1.186, -1.506, 0.169, 0.581, 0.638, 0.951], [-1.772, -0.025, 0.967, 0.473, 0.884, -0.032], [-1.614, -1.94, 0.374, 0.725, 0.441, 0.512], [-1.408, 0.285, 1.05, 0.486, 0.297, 0.835], [2.021, -0.535, 0.654, 0.219, 0.759, 0.901], [-1.57, 2.203, 0.527, 0.16, 0.291, 0.718], [1.825, 2.298, 0.457, 1.052, 0.655, 0.73], [-0.153, 1.778, 0.354, 0.514, 0.609, 0.42], [0.512, 1.223, 0.597, 0.407, 0.628, 0.692], [1.022, 1.172, 0.206, 0.702, 0.301, 0.176], [1.64, 0.74, 0.55, 0.197, 0.956, 0.52], [0.38, -0.727, 0.278, 0.877, 0.781, 0.837]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the bucket in the scene. The camera pose information includes: the rotation matrix: [[-0.819759, -0.274444, 0.502669], [-0.572709, 0.39303, -0.719397], [-0.00013, -0.877615, -0.479366]]; the translation vector: [2.765326, 1.370172, 1.355227], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[1.285, 2.094, 0.223, 0.8, -0.126, 0.725], [0.89, 2.46, 0.447, -0.137, 0.338, 0.037]]
B: [[0.378, 1.664, -0.029, 0.245, 0.007, 0.518], [0.551, 2.153, -0.045, 0.073, 0.825, 0.641]]
C: [[0.842, 1.796, 0.181, 0.339, 0.338, 0.37], [0.768, 2.073, 0.205, 0.294, 0.394, 0.403]]
D: [[0.562, 2.17, 0.079, 0.501, 0.638, 0.525], [0.42, 1.956, 0.647, 0.731, 0.278, 0.487]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the table in the scene. The camera pose information includes: the rotation matrix: [[-0.119369, -0.433868, 0.893034], [-0.990549, 0.113242, -0.077387], [-0.067553, -0.893832, -0.443285]]; the translation vector: [3.407035, 4.679209, 1.397058], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[0.351, 1.709, 0.416, 3.301, 3.462, -0.205]]
B: [[0.748, 1.385, 0.703, 3.676, 3.587, 0.247]]
C: [[0.285, 1.079, 0.707, 4.151, 3.525, -0.098]]
D: [[0.437, 1.63, 0.992, 3.864, 3.856, 0.472]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.924746, 0.145405, -0.351715], [0.379908, 0.407811, -0.830277], [0.022707, -0.901414, -0.432362]]; the translation vector: [3.891577, 4.106122, 1.335216], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-2.171, -0.049, 0.811, 0.067, 1.74, 1.931], [2.378, 0.912, 0.851, 0.596, 2.524, 1.349], [0.415, -1.4, 0.688, 3.856, 0.243, 1.685], [2.428, -1.301, 0.364, 0.307, 0.039, 1.588], [-1.851, -0.771, 1.131, 0.437, 0.879, 1.981]]
B: [[-2.124, 0.402, 0.972, 0.336, 1.814, 2.055], [2.714, 0.714, 0.306, -0.022, 2.698, 1.287], [0.218, -0.935, 0.625, 3.775, 0.411, 1.982], [2.74, -0.719, 0.42, -0.08, 0.24, 0.945], [-2.083, -0.772, 1.329, 0.652, 0.37, 2.117]]
C: [[-2.229, 0.152, 1.164, 0.205, 1.859, 2.109], [2.442, 0.667, 0.678, 0.238, 2.976, 1.311], [0.131, -1.186, 0.807, 4.198, 0.217, 1.596], [2.311, -0.918, 0.648, 0.343, 0.478, 1.211], [-2.036, -0.925, 1.234, 0.571, 0.559, 1.867]]
D: [[-2.234, 0.572, 0.912, 0.309, 1.595, 2.084], [2.569, 0.682, 1.117, -0.182, 2.613, 1.651], [-0.058, -0.811, 0.697, 4.093, -0.122, 2.058], [2.792, -1.246, 0.764, 0.753, 0.799, 0.76], [-1.948, -0.836, 1.559, 0.97, 0.14, 2.126]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the door in the scene. The camera pose information includes: the rotation matrix: [[-0.996429, -0.081152, -0.023325], [-0.01119, 0.400709, -0.916137], [0.083693, -0.912604, -0.400187]]; the translation vector: [7.365378, 2.610504, 1.343957], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-1.059, -1.275, 0.883, 0.298, 1.018, 2.01], [0.236, 1.462, 0.631, 0.873, 0.486, 1.281], [1.1, -1.001, 0.952, 1.349, 0.172, 2.338], [-0.839, 2.079, 0.96, 0.395, 0.842, 1.983], [1.955, -4.485, 1.036, 0.141, 0.98, 2.593], [-0.255, -0.481, 0.905, 0.161, 0.928, 1.969]]
B: [[-0.954, -1.046, 0.462, 0.658, 0.618, 2.138], [-0.213, 1.899, 0.694, 0.708, 0.841, 1.686], [1.362, -1.133, 1.001, 1.465, -0.084, 2.501], [-0.862, 2.364, 0.854, 0.124, 0.853, 2.159], [2.413, -4.964, 0.774, -0.345, 1.16, 3.015], [0.156, -0.554, 0.434, -0.07, 0.695, 2.392]]
C: [[-0.732, -1.166, 0.44, 0.739, 0.991, 1.593], [0.338, 1.95, 0.672, 0.941, 0.589, 1.757], [0.743, -0.963, 1.147, 1.448, -0.135, 2.517], [-1.129, 2.483, 1.375, 0.132, 1.054, 2.43], [1.587, -4.551, 0.847, 0.35, 0.965, 2.767], [-0.661, -0.507, 0.612, -0.243, 0.847, 1.515]]
D: [[-0.907, -1.27, 0.42, -0.059, 1.138, 1.561], [0.626, 1.256, 1.105, 1.202, 0.216, 1.006], [0.877, -0.877, 1.149, 0.987, -0.045, 2.737], [-0.783, 1.691, 0.606, 0.081, 0.643, 2.205], [2.363, -4.049, 1.139, 0.229, 0.955, 2.439], [-0.196, -0.854, 0.721, 0.566, 0.583, 2.254]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the desk in the scene. The camera pose information includes: the rotation matrix: [[0.51864, -0.44867, 0.727811], [-0.853934, -0.229463, 0.467059], [-0.04255, -0.863738, -0.502143]]; the translation vector: [1.002297, 1.98866, 1.344191], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[0.662, -1.551, 0.955, 1.174, 1.083, 1.423]]
B: [[0.488, -1.177, 0.89, 1.089, 0.729, 1.751]]
C: [[0.483, -0.736, 0.965, 0.958, 0.277, 1.886]]
D: [[0.649, -1.283, 0.609, 1.143, 1.139, 2.193]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[0.931668, 0.072515, -0.356001], [0.362912, -0.231685, 0.902561], [-0.017031, -0.970084, -0.24217]]; the translation vector: [5.886859, 3.543659, 1.354971], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[1.285, -1.171, 0.463, 0.532, 0.611, 0.923], [1.223, 1.763, 0.56, 0.667, 0.631, 0.966], [-0.307, 1.833, 0.5, 0.619, 0.589, 0.922], [-0.406, -0.951, 0.39, 0.539, 0.611, 0.908], [0.655, 1.709, 0.525, 0.699, 0.634, 0.947], [1.269, -2.956, 0.836, 0.629, 0.557, 0.393], [1.192, 0.557, 0.457, 0.623, 0.615, 0.94], [0.416, -2.765, 0.677, 0.614, 0.452, 0.612], [-0.522, 0.635, 0.418, 0.585, 0.574, 0.905], [-0.363, -3.094, 0.495, 0.715, 0.612, 0.912], [0.336, 0.66, 0.438, 0.602, 0.623, 0.904], [-2.007, -0.347, 0.408, 0.521, 0.585, 0.891], [0.411, -1.036, 0.417, 0.682, 0.634, 0.922], [-2.039, -2.805, 0.495, 0.561, 0.631, 0.9], [-1.956, -1.834, 0.436, 0.597, 0.728, 0.922], [-2.754, 1.479, 0.509, 0.58, 0.603, 0.892]]
B: [[0.94, -0.734, 0.86, 0.847, 0.174, 1.366], [1.047, 1.724, 0.337, 1.114, 0.725, 1.18], [-0.446, 1.839, 0.399, 1.0, 0.211, 0.928], [-0.224, -0.996, 0.671, 0.902, 0.396, 0.957], [0.648, 2.199, 0.865, 0.644, 0.899, 0.978], [1.601, -3.15, 1.071, 0.541, 0.264, 0.224], [0.709, 0.399, 0.396, 0.628, 0.643, 1.257], [0.103, -2.816, 0.184, 1.095, 0.871, 0.909], [-0.735, 1.113, 0.158, 0.968, 0.355, 1.244], [-0.793, -3.536, 0.957, 0.881, 0.306, 1.233], [-0.114, 0.863, 0.498, 0.236, 0.716, 1.116], [-1.845, -0.397, 0.53, 0.528, 0.958, 0.727], [0.156, -0.653, 0.083, 0.658, 1.129, 0.686], [-2.166, -2.74, 0.163, 0.166, 0.842, 0.447], [-2.421, -1.954, 0.206, 0.882, 0.734, 0.761], [-3.119, 1.809, 0.685, 0.543, 0.98, 1.284]]
C: [[0.87, -1.386, 0.953, 0.148, 0.539, 1.241], [0.822, 1.276, 0.128, 0.239, 0.572, 1.227], [-0.508, 2.214, 0.373, 0.683, 0.2, 1.183], [-0.547, -1.349, -0.07, 0.231, 0.312, 1.389], [0.457, 1.367, 0.965, 0.768, 0.185, 1.088], [1.563, -2.649, 0.498, 0.756, 0.364, 0.362], [1.083, 0.345, 0.921, 0.769, 0.695, 1.386], [0.143, -3.095, 0.202, 0.278, 0.051, 0.502], [-0.474, 0.978, 0.872, 0.559, 0.082, 1.262], [-0.01, -3.401, 0.115, 1.005, 0.452, 1.143], [-0.106, 1.086, 0.284, 0.105, 0.131, 0.844], [-2.44, -0.304, -0.054, 0.667, 0.457, 0.703], [0.747, -1.031, -0.051, 0.551, 0.84, 0.909], [-2.101, -2.554, 0.473, 1.017, 0.994, 1.065], [-1.883, -2.033, 0.423, 0.644, 1.201, 0.726], [-3.109, 1.24, 0.812, 0.728, 1.099, 0.829]]
D: [[1.585, -0.899, 0.099, 0.724, 0.912, 0.466], [0.799, 2.074, 0.967, 0.764, 0.821, 0.506], [-0.531, 1.393, 0.134, 0.737, 1.022, 1.024], [-0.008, -0.984, -0.095, 0.085, 0.528, 0.524], [0.362, 2.074, 0.189, 0.835, 0.387, 0.74], [1.446, -2.709, 0.927, 0.329, 0.916, 0.373], [1.078, 0.299, 0.482, 0.303, 0.612, 0.521], [0.439, -2.308, 0.3, 0.788, 0.517, 0.416], [-0.314, 0.386, 0.749, 0.588, 0.522, 1.244], [-0.739, -2.845, 0.766, 0.695, 1.017, 0.779], [-0.116, 0.704, 0.487, 0.148, 0.185, 0.776], [-1.607, 0.118, 0.862, 0.934, 0.609, 0.752], [-0.074, -0.593, 0.062, 0.851, 0.522, 0.762], [-2.188, -3.11, 0.134, 0.427, 0.414, 0.637], [-1.911, -1.906, 0.292, 0.873, 0.728, 0.955], [-2.793, 1.335, 0.084, 0.946, 0.494, 0.463]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the table in the scene. The camera pose information includes: the rotation matrix: [[0.987126, 0.106622, -0.119219], [0.159938, -0.652529, 0.740693], [0.00118, -0.750225, -0.661181]]; the translation vector: [4.64166, 4.052867, 1.404314], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-0.185, -1.981, 0.71, 1.746, 1.931, 1.092]]
B: [[0.263, -1.622, 0.402, 1.389, 1.64, 0.804]]
C: [[0.151, -1.735, 0.574, 1.767, 1.715, 0.631]]
D: [[0.262, -2.035, 0.645, 1.006, 2.054, 1.049]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the armchair in the scene. The camera pose information includes: the rotation matrix: [[0.68967, 0.288211, -0.664297], [0.724122, -0.27239, 0.633602], [0.001663, -0.918008, -0.396559]]; the translation vector: [2.530043, 2.005069, 1.437417], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[0.648, -0.593, 0.364, 0.758, 0.748, 0.835], [-1.189, -0.998, 0.388, 0.711, 0.664, 0.751], [-0.106, -0.14, 0.366, 0.681, 0.668, 0.806], [-0.467, -1.537, 0.381, 0.682, 0.66, 0.781]]
B: [[0.715, -1.041, 0.651, 0.471, 0.834, 0.809], [-1.555, -0.972, 0.209, 0.39, 0.675, 1.08], [0.331, 0.337, 0.451, 0.906, 1.083, 1.138], [-0.367, -1.309, -0.086, 0.84, 1.029, 0.958]]
C: [[0.76, -0.428, 0.328, 0.718, 0.602, 0.917], [-1.301, -1.169, 0.677, 0.824, 0.61, 0.712], [0.1, -0.045, 0.084, 0.878, 0.367, 0.431], [-0.14, -1.88, 0.43, 0.418, 0.474, 0.77]]
D: [[0.587, -1.036, 0.299, 1.076, 1.171, 0.475], [-1.011, -1.458, 0.499, 0.276, 1.067, 0.759], [-0.487, -0.498, 0.17, 1.114, 0.58, 1.041], [-0.116, -1.819, 0.569, 0.961, 0.364, 1.204]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.964843, 0.186346, -0.185345], [0.252505, 0.461537, -0.850426], [-0.07293, -0.867329, -0.492364]]; the translation vector: [3.779865, 2.337391, 1.461827], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-0.678, -1.667, 1.218, 1.055, -0.26, 2.418], [-1.464, 1.094, 0.83, 1.262, -0.304, 1.673], [0.614, 2.399, 0.708, 1.662, -0.241, 1.035], [0.965, -0.058, 1.477, 0.773, 4.136, 2.578], [-1.154, 1.558, 1.248, -0.057, 1.091, 2.617], [-1.717, -0.255, 1.603, -0.126, 2.491, 0.5]]
B: [[-1.352, -1.046, 1.599, 1.44, 0.136, 2.792], [-1.654, 0.816, 0.791, 1.207, 0.132, 1.881], [0.521, 2.259, 1.273, 1.597, -0.332, 0.736], [0.806, 0.159, 1.62, 0.393, 4.568, 2.678], [-1.081, 1.507, 1.378, -0.253, 1.151, 2.742], [-1.495, -0.107, 1.278, 0.325, 1.906, 1.086]]
C: [[-1.166, -1.418, 1.14, 1.061, 0.184, 2.392], [-1.606, 0.642, 1.143, 0.781, 0.159, 2.172], [0.167, 2.007, 1.118, 1.797, 0.138, 0.569], [0.908, -0.132, 1.206, 0.513, 4.305, 2.258], [-1.326, 1.1, 1.19, 0.242, 0.968, 2.282], [-1.838, -0.447, 1.348, 0.372, 2.121, 0.908]]
D: [[-0.864, -1.506, 1.526, 0.637, 0.64, 2.228], [-1.745, 0.647, 0.899, 0.933, -0.243, 2.211], [-0.21, 1.507, 1.578, 2.065, 0.587, 0.484], [1.157, 0.294, 0.85, 0.968, 4.125, 2.603], [-1.113, 0.941, 1.165, 0.239, 0.756, 2.423], [-2.32, -0.87, 1.844, 0.517, 2.303, 0.518]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the door in the scene. The camera pose information includes: the rotation matrix: [[-0.08083, -0.463089, 0.882618], [-0.994842, 0.091929, -0.042874], [-0.061284, -0.881531, -0.468131]]; the translation vector: [4.543997, 3.147744, 1.235262], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-1.143, 1.32, 0.902, 0.946, 0.582, 0.814], [1.314, 2.961, 1.36, 1.125, 0.499, 2.359]]
B: [[-1.164, 1.549, 1.101, 1.224, -0.166, 1.131], [1.215, 3.687, 1.039, 0.93, -0.333, 2.264]]
C: [[-1.48, 1.652, 0.846, 0.755, 0.321, 1.167], [1.066, 3.327, 1.091, 1.04, 0.081, 1.998]]
D: [[-1.81, 1.616, 0.892, 0.552, 0.779, 1.45], [1.382, 3.534, 1.284, 1.152, 0.521, 2.312]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[0.286652, 0.220257, -0.932372], [0.958024, -0.061246, 0.28007], [0.004584, -0.973517, -0.228568]]; the translation vector: [3.76659, 1.676076, 1.452194], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-0.277, 2.29, 0.603, 1.696, 0.522, 1.643], [-1.375, -0.321, 0.794, 0.343, 5.813, 1.671], [1.159, 0.472, 1.342, 0.486, 3.254, 0.972], [0.747, -2.391, 1.046, 0.652, 1.455, 1.87], [1.085, -1.961, 0.723, 1.174, -0.018, 1.576], [0.586, 1.92, 1.575, 0.646, -0.32, 2.439], [0.415, 2.748, 1.312, -0.384, 0.485, 2.051]]
B: [[-0.351, 2.608, 0.955, 1.541, 0.097, 1.824], [-1.089, -0.096, 0.669, 0.099, 5.464, 1.395], [1.127, 0.133, 1.411, 0.212, 3.643, 0.932], [0.392, -2.442, 0.754, 0.163, 1.609, 1.541], [0.746, -1.664, 0.806, 0.833, 0.085, 1.637], [0.806, 1.971, 1.104, 0.829, 0.129, 2.13], [0.393, 2.271, 1.106, 0.064, 0.665, 2.126]]
C: [[-0.013, 2.804, 0.64, 1.604, -0.241, 1.907], [-0.99, 0.257, 0.762, -0.167, 5.28, 1.868], [1.095, -0.318, 1.309, 0.698, 4.021, 0.652], [0.346, -2.805, 0.465, -0.167, 2.086, 1.213], [0.527, -1.307, 1.185, 0.733, -0.294, 1.468], [1.191, 1.911, 1.165, 0.69, 0.519, 1.853], [0.342, 2.498, 1.557, -0.047, 0.494, 2.435]]
D: [[-0.612, 2.451, 1.013, 1.076, 0.146, 2.285], [-0.642, -0.043, 0.498, -0.353, 5.408, 1.585], [1.099, -0.043, 0.972, -0.204, 4.141, 1.05], [0.087, -2.832, 0.317, 0.167, 1.848, 1.113], [0.399, -1.498, 0.656, 1.117, 0.566, 1.989], [0.495, 2.449, 0.82, 0.411, 0.228, 2.522], [0.507, 2.378, 1.381, -0.184, 0.771, 1.769]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[-0.895509, 0.17248, -0.410263], [0.444823, 0.375965, -0.812886], [0.014038, -0.91044, -0.413402]]; the translation vector: [2.818061, 5.409916, 1.54775], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-0.457, -0.683, 0.495, 0.679, 0.597, 0.903], [0.426, 0.843, 0.458, 0.566, 0.562, 0.949], [-0.336, 0.792, 0.461, 0.555, 0.539, 0.932], [0.926, -0.823, 0.62, 0.473, 0.568, 0.621], [-1.992, 0.348, 0.596, 0.635, 0.634, 0.647], [1.1, 0.858, 0.465, 0.529, 0.569, 0.952], [-0.253, -1.834, 0.689, 0.639, 0.561, 0.602], [-0.397, 2.119, 0.473, 0.759, 0.651, 0.94], [-1.254, -0.965, 0.657, 0.558, 0.592, 0.636], [-1.564, -0.168, 0.649, 0.462, 0.615, 0.611], [-0.169, -2.406, 0.711, 0.757, 0.669, 0.597], [1.375, -1.924, 0.508, 0.658, 0.509, 0.96], [0.214, -0.572, 0.651, 0.695, 0.494, 0.584], [-2.356, 2.053, 0.675, 0.673, 0.595, 0.536], [-0.799, -2.241, 0.541, 0.662, 0.673, 0.96], [1.941, -1.89, 0.718, 0.565, 0.56, 0.52], [2.571, -0.575, 0.472, 0.572, 0.595, 0.956], [-0.865, 2.028, 0.487, 0.583, 0.461, 0.128], [0.361, -2.459, 0.78, 0.536, 0.269, 0.489], [1.938, -1.474, 0.649, 0.57, 0.554, 0.6], [0.743, -2.15, 0.817, 0.526, 0.164, 0.344], [2.542, -1.129, 0.644, 0.598, 0.586, 0.612], [1.955, 0.145, 0.785, 0.141, 0.509, 0.304], [-1.685, 2.109, 0.449, 0.566, 0.486, 0.153], [-2.437, -1.918, 0.584, 0.515, 0.45, 0.203]]
B: [[-0.004, -0.217, 0.058, 0.956, 0.104, 0.992], [0.634, 0.895, 0.282, 0.697, 0.893, 1.438], [-0.387, 0.349, 0.019, 0.239, 0.901, 0.96], [1.064, -1.168, 0.964, 0.374, 1.0, 0.253], [-1.606, 0.8, 0.112, 0.967, 0.862, 0.256], [1.288, 0.417, 0.225, 0.427, 0.112, 1.268], [-0.365, -1.988, 0.842, 0.932, 0.117, 0.21], [0.056, 2.617, 0.694, 0.602, 0.776, 0.848], [-1.173, -1.184, 0.2, 0.567, 0.839, 0.497], [-1.108, -0.485, 0.838, 0.382, 0.723, 1.057], [0.031, -2.18, 0.477, 1.078, 0.774, 0.574], [1.32, -1.614, 0.5, 0.512, 0.791, 1.227], [0.57, -1.002, 0.878, 0.861, 0.739, 0.347], [-2.072, 2.433, 1.143, 0.504, 1.054, 0.551], [-0.569, -2.64, 0.278, 0.616, 1.122, 1.078], [2.089, -1.691, 0.769, 0.97, 0.148, 0.992], [2.274, -0.687, 0.634, 0.56, 0.654, 0.811], [-1.223, 2.009, 0.495, 1.006, -0.028, 0.186], [0.145, -2.547, 0.54, 0.793, 0.387, 0.825], [1.744, -1.228, 0.533, 0.139, 0.886, 1.027], [1.123, -2.589, 1.183, 0.079, 0.187, 0.548], [2.235, -0.842, 0.485, 0.73, 0.575, 0.903], [1.694, -0.054, 1.249, 0.468, 0.557, 0.748], [-1.216, 2.107, 0.803, 0.764, 0.267, 0.274], [-2.623, -2.077, 1.01, 0.838, 0.106, -0.148]]
C: [[-0.042, -0.277, 0.622, 0.349, 0.954, 1.11], [0.421, 0.801, 0.437, 0.094, 0.078, 1.2], [-0.436, 0.855, 0.625, 0.341, 0.737, 1.353], [0.599, -0.582, 0.28, 0.836, 0.717, 0.357], [-2.398, -0.135, 0.951, 0.429, 1.038, 0.502], [1.554, 0.709, 0.624, 0.144, 0.967, 1.304], [-0.666, -1.374, 0.422, 0.517, 0.122, 0.8], [-0.203, 1.908, 0.093, 1.027, 0.556, 0.76], [-1.532, -0.535, 0.437, 0.57, 0.41, 0.413], [-1.535, -0.307, 0.814, 0.936, 0.544, 1.082], [-0.39, -2.044, 0.309, 0.76, 0.801, 0.62], [1.044, -2.393, 0.932, 1.048, 0.287, 1.261], [0.664, -0.294, 1.14, 0.882, 0.176, 0.207], [-2.135, 2.211, 0.272, 0.963, 0.668, 0.76], [-1.028, -2.103, 1.016, 0.918, 0.609, 1.31], [1.579, -2.37, 0.458, 0.202, 0.159, 0.166], [2.079, -0.505, 0.945, 0.57, 0.86, 0.725], [-0.396, 2.379, 0.489, 0.77, 0.063, 0.52], [0.423, -2.492, 0.598, 0.788, 0.241, 0.406], [2.219, -1.548, 0.415, 0.429, 0.702, 0.329], [1.236, -1.961, 0.849, 0.371, 0.256, -0.039], [2.93, -1.099, 1.108, 0.393, 0.388, 0.187], [1.738, -0.099, 0.354, 0.013, 0.06, 0.667], [-1.711, 2.599, 0.36, 0.548, 0.69, -0.323], [-1.988, -1.796, 0.232, 0.609, 0.912, -0.043]]
D: [[-0.117, -0.712, 0.165, 0.707, 0.749, 0.416], [0.663, 1.109, 0.92, 0.786, 0.382, 0.761], [-0.485, 1.276, -0.006, 0.122, 0.579, 0.562], [0.651, -1.033, 0.48, 0.012, 0.291, 0.281], [-1.67, 0.137, 0.785, 1.091, 0.142, 0.851], [1.44, 0.455, 0.476, 0.133, 0.572, 0.925], [-0.342, -1.74, 0.35, 0.646, 0.394, 0.443], [-0.793, 2.134, 0.146, 1.105, 0.456, 0.742], [-1.574, -0.65, 0.985, 0.2, 0.168, 1.102], [-1.526, 0.104, 0.427, 0.23, 0.555, 0.818], [-0.21, -2.447, 0.593, 1.166, 1.051, 0.465], [1.11, -2.085, 0.532, 0.952, 0.334, 0.936], [-0.231, -0.532, 0.895, 0.826, 0.523, 0.78], [-2.843, 1.728, 0.764, 0.92, 0.672, 0.101], [-0.845, -1.905, 0.458, 0.184, 0.635, 1.348], [1.844, -1.433, 1.033, 0.147, 0.968, 0.118], [2.166, -0.542, 0.733, 0.117, 0.957, 0.814], [-0.92, 1.743, 0.237, 0.993, 0.477, 0.227], [0.31, -2.458, 0.659, 0.782, 0.696, 0.669], [1.626, -1.353, 0.953, 0.579, 0.517, 0.513], [0.856, -2.414, 0.37, 0.927, 0.46, -0.04], [2.564, -1.512, 0.576, 0.167, 0.528, 0.323], [2.064, -0.007, 0.399, -0.022, 0.444, 0.68], [-1.281, 1.93, 0.706, 0.411, 0.266, -0.223], [-2.823, -2.037, 0.823, 0.649, 0.539, 0.078]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the object in the scene. The camera pose information includes: the rotation matrix: [[0.330673, -0.328207, 0.884837], [-0.942686, -0.070458, 0.326157], [-0.044703, -0.941975, -0.332694]]; the translation vector: [3.753276, 4.481459, 1.345242], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-0.878, 0.793, 0.525, 0.307, 1.138, 0.24], [-1.741, 1.942, 0.919, 0.374, 0.284, 0.479], [-0.97, -1.167, 0.396, 0.145, 0.451, -0.19], [-1.083, -1.878, 0.816, 0.138, 0.403, 0.089], [-0.905, -1.314, 0.204, 0.196, 0.671, 0.614], [0.896, -0.37, -0.05, 0.065, 0.48, 0.052], [-0.311, 2.442, 0.913, 0.38, 0.489, 1.491]]
B: [[-0.86, 0.987, 0.429, 0.753, 0.659, 0.935], [-1.179, 1.249, 1.101, 0.219, 0.461, 0.432], [-1.149, -1.648, 0.72, 0.293, 0.482, 0.205], [-0.806, -1.928, 1.378, 0.631, 0.665, 0.667], [-0.762, -1.463, 0.175, -0.154, 0.327, 0.058], [1.471, -0.937, 0.34, 0.631, 0.439, 0.05], [0.043, 1.928, 0.641, 0.637, 0.49, 0.81]]
C: [[-0.458, 0.879, 0.858, 0.541, 0.86, 0.578], [-1.685, 1.754, 1.421, 0.241, 0.756, -0.241], [-1.527, -1.671, 0.922, 0.635, 0.013, 0.552], [-1.217, -1.15, 1.123, 0.142, 0.166, 0.441], [-1.042, -1.813, 0.54, 0.438, 0.445, 0.211], [1.239, -0.633, 0.179, 0.181, 0.23, 0.74], [-0.011, 2.472, 1.042, 0.129, 0.472, 1.438]]
D: [[-0.55, 0.944, 0.644, 0.68, 1.046, 0.521], [-1.267, 1.712, 1.229, 0.359, 0.367, 0.165], [-1.24, -1.459, 0.828, 0.501, 0.283, 0.305], [-1.303, -1.553, 1.014, 0.399, 0.228, 0.178], [-0.73, -1.694, 0.629, 0.212, 0.251, 0.137], [1.337, -0.693, 0.283, 0.145, 0.467, 0.539], [0.135, 2.342, 0.574, 0.546, 0.62, 1.068]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the monitor in the scene. The camera pose information includes: the rotation matrix: [[0.054781, -0.427281, 0.902458], [-0.998013, -0.051617, 0.036143], [0.031139, -0.902644, -0.429259]]; the translation vector: [1.328526, 0.849821, 1.501181], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-0.565, -1.185, 1.353, 0.464, 0.006, 0.118], [0.412, -0.591, 0.819, 0.036, 0.543, 0.322], [0.775, 0.247, 0.843, 0.919, 0.864, 0.389]]
B: [[-0.648, -1.262, 0.922, 0.446, 0.433, 0.522], [0.437, -0.235, 0.949, 0.366, 0.445, 0.454], [0.764, 0.145, 0.941, 0.483, 0.409, 0.473]]
C: [[-0.794, -1.422, 1.325, 0.646, -0.011, 0.511], [0.55, -0.124, 0.97, 0.767, 0.276, 0.151], [0.692, 0.134, 0.818, 0.04, 0.142, 0.775]]
D: [[-0.888, -1.602, 1.373, 0.357, 0.797, 0.596], [0.014, -0.496, 0.808, 0.816, 0.004, 0.14], [0.932, 0.14, 0.871, 0.799, 0.355, 0.358]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the dishwasher in the scene. The camera pose information includes: the rotation matrix: [[0.752445, 0.275595, -0.598225], [0.657828, -0.35994, 0.661593], [-0.032994, -0.891342, -0.452129]]; the translation vector: [2.633805, 2.70906, 1.31733], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-1.353, -1.905, 0.542, 0.198, 0.811, 0.866]]
B: [[-1.69, -2.015, 0.887, 0.014, 0.72, 0.41]]
C: [[-1.178, -2.25, 0.868, 0.547, 0.466, 0.935]]
D: [[-1.26, -1.838, 0.523, -0.212, 0.311, 0.619]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the clothes in the scene. The camera pose information includes: the rotation matrix: [[0.88123, -0.188698, 0.433389], [-0.470321, -0.258404, 0.843816], [-0.047237, -0.947428, -0.316462]]; the translation vector: [1.061636, 1.321782, 1.457525], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[0.575, -1.33, 0.913, 0.422, 0.222, 1.282], [-1.133, -0.569, 0.691, 0.502, 1.733, 0.362], [-1.177, -0.378, 1.14, 0.427, 2.109, 0.616], [-1.073, 1.114, 1.403, 0.582, 1.219, 1.213], [-0.205, 1.471, 1.068, 1.327, 0.559, 1.11], [0.394, 0.971, 1.401, 0.368, 1.532, 0.97], [0.465, 0.918, 0.399, 0.657, 1.295, 0.944], [-1.033, 0.855, 0.494, 0.561, 0.838, 0.96]]
B: [[0.612, -1.146, 1.029, 0.876, 0.249, 1.097], [-1.186, -0.558, 0.781, 0.832, 1.793, 0.11], [-0.68, -0.259, 1.327, 0.321, 2.085, 0.39], [-0.751, 1.462, 1.244, 1.064, 1.13, 1.071], [-0.245, 1.694, 1.448, 1.271, 0.405, 0.826], [0.501, 1.197, 1.032, 0.635, 1.295, 1.137], [0.575, 1.298, 0.738, 0.961, 1.68, 0.895], [-1.135, 0.586, 0.775, 0.711, 1.079, 0.526]]
C: [[0.678, -1.206, 0.812, 0.848, -0.174, 1.369], [-1.023, -0.705, 0.492, 0.502, 1.434, -0.09], [-1.388, -0.068, 1.103, 0.59, 1.707, 0.559], [-1.152, 1.027, 1.347, 0.752, 0.971, 1.412], [-0.198, 1.443, 1.383, 1.532, 0.499, 1.267], [0.854, 0.79, 1.691, 0.351, 1.682, 0.641], [0.791, 0.546, 0.687, 0.219, 1.088, 1.252], [-0.634, 1.336, 0.286, 0.814, 1.197, 1.221]]
D: [[0.82, -1.281, 0.96, -0.009, 0.662, 1.248], [-1.615, -0.505, 0.267, 0.866, 1.991, 0.496], [-0.964, -0.4, 1.176, 0.247, 2.442, 0.894], [-1.088, 1.358, 1.232, 0.782, 1.082, 0.821], [0.043, 1.718, 1.49, 1.508, 0.835, 1.275], [0.739, 1.084, 1.461, 0.376, 1.382, 1.444], [0.407, 0.623, 0.633, 0.434, 1.281, 1.107], [-1.311, 0.453, 0.839, 0.768, 1.093, 0.774]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the washcloth in the scene. The camera pose information includes: the rotation matrix: [[-0.922168, 0.178823, -0.342969], [0.38661, 0.453076, -0.803278], [0.011746, -0.873352, -0.486947]]; the translation vector: [3.207336, 1.959871, 1.267555], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-1.405, 0.601, 0.764, -0.233, 0.102, -0.396]]
B: [[-1.074, 0.387, 1.003, 0.303, 0.098, -0.079]]
C: [[-1.416, 1.278, 0.402, -0.026, 0.472, 0.541]]
D: [[-1.238, 0.875, 0.853, 0.207, 0.18, 0.059]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[0.984594, -0.069457, 0.160469], [-0.174127, -0.305795, 0.936039], [-0.015944, -0.949561, -0.313178]]; the translation vector: [3.941113, 2.817773, 1.559826], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[1.762, -1.555, 0.827, 2.184, 0.001, 1.66], [-1.543, -2.246, 0.687, 2.166, 0.538, 1.705], [-0.782, 1.874, 0.612, 0.36, -0.393, 2.288], [-2.462, 0.204, 1.234, 0.129, 3.712, 1.462], [-0.383, -1.635, 0.309, 0.432, -0.146, 1.237], [2.291, 0.002, 1.16, 0.467, 3.329, 1.816], [1.638, 1.427, 0.73, 2.104, 0.102, 1.563], [-1.67, 1.91, 0.562, 0.741, 0.507, 1.714]]
B: [[1.374, -1.714, 0.725, 2.507, 0.169, 1.413], [-1.211, -1.757, 0.826, 2.443, 0.176, 1.694], [-0.519, 1.79, 0.908, 0.294, 0.099, 1.833], [-2.419, 0.035, 0.987, 0.337, 3.555, 1.874], [0.072, -1.69, 0.634, 0.2, 0.284, 1.225], [2.688, 0.023, 0.867, 0.191, 3.55, 1.732], [1.91, 1.763, 0.852, 1.655, 0.149, 1.762], [-2.022, 1.78, 0.984, 1.051, 0.126, 1.927]]
C: [[0.908, -1.987, 1.173, 2.894, 0.341, 1.45], [-1.176, -1.625, 1.254, 2.938, 0.258, 1.218], [-0.734, 1.406, 1.146, 0.597, 0.342, 1.626], [-2.253, 0.34, 1.308, 0.063, 3.579, 1.568], [-0.079, -1.858, 0.689, 0.18, 0.741, 0.85], [2.904, 0.375, 0.691, 0.079, 3.103, 2.186], [1.824, 1.499, 0.728, 1.255, 0.079, 1.787], [-2.124, 1.899, 1.164, 1.019, 0.481, 1.863]]
D: [[1.462, -1.527, 0.599, 2.871, 0.537, 1.876], [-0.801, -1.454, 1.05, 2.817, -0.258, 1.392], [-0.063, 2.202, 0.566, 0.693, 0.023, 1.708], [-2.869, -0.081, 1.48, 0.816, 3.209, 2.127], [0.07, -1.284, 0.825, -0.242, 0.304, 1.406], [2.798, 0.497, 1.202, 0.386, 3.591, 2.066], [1.458, 2.138, 0.37, 1.504, 0.6, 1.542], [-2.145, 1.824, 0.999, 1.206, 0.504, 1.867]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.355681, -0.20797, 0.911175], [-0.934036, 0.113197, -0.338769], [-0.032689, -0.971563, -0.234514]]; the translation vector: [0.539195, 4.841905, 1.636959], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-0.548, -0.723, 1.702, 0.029, 0.56, 0.548], [0.99, -0.353, 1.798, 0.254, 0.406, 1.307], [0.157, -0.505, 0.811, 2.866, -0.08, 2.257], [-1.059, 0.22, 1.187, 0.204, 1.96, 1.609], [-1.515, 1.374, 1.432, 0.39, 0.462, 2.145], [-1.181, 2.329, 0.518, 0.161, 0.641, 1.327], [1.31, 1.368, 1.072, 1.078, 3.27, 1.707]]
B: [[-0.408, -0.944, 1.285, 0.383, 0.855, 1.329], [1.037, -1.048, 1.113, 0.346, 0.92, 1.337], [0.631, -0.546, 1.683, 2.674, 0.421, 2.371], [-1.406, 0.284, 0.493, 0.426, 1.745, 1.616], [-0.913, 1.243, 0.625, 0.944, -0.159, 1.495], [-0.749, 1.827, 0.664, -0.223, 0.933, 1.793], [1.27, 1.253, 1.221, 0.403, 2.724, 2.094]]
C: [[-0.454, -0.86, 2.026, 0.451, 0.358, 1.257], [1.65, -0.511, 2.057, 0.183, 0.13, 0.645], [0.357, -0.781, 1.143, 3.085, -0.312, 2.705], [-1.785, 0.873, 0.92, 0.414, 1.805, 1.915], [-0.907, 0.946, 0.648, 1.086, 0.063, 2.046], [-0.884, 1.711, 1.057, -0.048, 0.722, 0.964], [1.337, 0.641, 0.462, 0.296, 3.312, 2.01]]
D: [[-0.751, -0.786, 1.574, 0.095, 0.444, 1.034], [1.18, -0.773, 1.574, 0.094, 0.433, 1.033], [0.142, -0.562, 1.184, 3.142, 0.116, 2.394], [-1.437, 0.419, 0.848, 0.139, 1.974, 1.688], [-1.083, 1.379, 1.042, 0.807, 0.163, 1.776], [-0.694, 1.837, 0.766, 0.107, 0.954, 1.459], [1.355, 0.889, 0.903, 0.788, 2.903, 1.82]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the bookshelf in the scene. The camera pose information includes: the rotation matrix: [[-0.941243, -0.209403, 0.264975], [-0.336113, 0.504116, -0.795548], [0.033012, -0.837865, -0.544878]]; the translation vector: [4.828751, 9.008894, 1.463441], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[1.515, -3.241, 1.128, 2.444, 0.863, 2.298], [1.577, 0.871, 1.235, 2.218, 0.709, 2.09], [1.099, 3.677, 1.424, 1.498, 0.813, 2.316], [1.686, -0.521, 1.08, 2.449, 0.774, 1.941], [1.48, 2.234, 1.312, 2.224, 0.696, 2.161], [0.71, 4.953, 0.833, 0.669, 0.644, 1.154], [1.678, -1.888, 1.095, 2.523, 0.759, 2.102]]
B: [[1.269, -3.321, 1.076, 2.021, 0.959, 2.397], [1.664, 1.284, 1.204, 2.329, 1.065, 2.182], [1.189, 3.832, 1.394, 1.94, 1.033, 1.829], [2.066, -0.941, 0.589, 2.315, 1.169, 1.455], [1.915, 2.253, 1.321, 2.418, 0.57, 2.378], [0.213, 5.41, 0.898, 0.409, 1.093, 1.517], [1.55, -2.082, 1.024, 2.82, 0.884, 2.344]]
C: [[1.118, -3.575, 0.993, 1.946, 0.682, 2.318], [1.412, 0.928, 1.006, 2.495, 0.73, 2.187], [0.774, 3.36, 0.968, 1.482, 0.922, 2.574], [1.295, -0.734, 1.167, 2.189, 0.383, 1.587], [1.325, 2.548, 0.999, 2.413, 1.015, 2.532], [0.98, 5.017, 0.875, 0.448, 0.455, 0.917], [2.018, -1.5, 1.046, 2.717, 0.819, 2.55]]
D: [[1.259, -3.521, 1.143, 2.894, 0.867, 2.663], [1.362, 1.016, 1.431, 2.314, 0.878, 2.2], [0.748, 3.481, 1.025, 1.495, 1.271, 2.75], [1.85, -0.752, 1.348, 2.468, 0.657, 1.566], [1.513, 2.006, 1.345, 1.751, 0.827, 2.159], [0.635, 4.802, 1.263, 0.202, 1.111, 1.501], [1.353, -2.331, 1.563, 2.89, 1.228, 2.108]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the picture in the scene. The camera pose information includes: the rotation matrix: [[0.623567, 0.536294, -0.568817], [0.781209, -0.455034, 0.427384], [-0.029628, -0.710867, -0.702702]]; the translation vector: [1.790477, 1.816361, 1.229059], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-1.126, -0.51, 1.73, -0.359, 0.479, 0.324]]
B: [[-1.548, -0.135, 1.59, 0.021, 0.457, 0.386]]
C: [[-1.508, -0.035, 1.589, -0.436, 0.071, 0.171]]
D: [[-1.888, -0.563, 1.28, -0.393, 0.688, 0.046]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the whiteboard in the scene. The camera pose information includes: the rotation matrix: [[-0.341382, 0.594812, -0.727775], [0.932196, 0.11517, -0.343142], [-0.120287, -0.795572, -0.593798]]; the translation vector: [7.151203, 3.587152, 1.581923], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-2.08, 0.154, 1.005, 0.283, 1.414, 1.731]]
B: [[-1.974, 0.286, 1.416, 0.341, 1.457, 1.235]]
C: [[-1.941, 0.29, 1.24, -0.098, 1.307, 1.381]]
D: [[-1.581, 0.374, 0.521, 0.311, 1.136, 1.526]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the doorframe in the scene. The camera pose information includes: the rotation matrix: [[-0.40936, -0.486807, 0.77165], [-0.912164, 0.236459, -0.334729], [-0.019515, -0.840896, -0.540844]]; the translation vector: [1.412713, 1.214489, 1.390939], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-0.65, 1.626, 0.952, 1.426, 0.125, 1.867]]
B: [[-0.34, 1.647, 1.105, 1.036, 0.294, 2.092]]
C: [[-0.202, 1.219, 1.248, 1.308, -0.28, 1.829]]
D: [[-1.114, 1.711, 0.518, 0.996, 0.291, 2.172]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[0.977514, -0.102294, 0.184398], [-0.210796, -0.497303, 0.841578], [0.005613, -0.861525, -0.507684]]; the translation vector: [3.555602, 1.207732, 1.356493], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[-1.253, 0.185, 0.949, 0.229, 3.97, 1.922], [-0.174, 1.794, 1.044, 2.121, 0.218, 2.116], [0.873, -0.38, 1.281, 0.158, 4.352, 2.497], [0.476, -2.537, 0.593, 0.677, 0.042, 1.129], [0.122, -2.616, 0.312, 0.063, 0.188, 0.596]]
B: [[-1.703, -0.184, 0.581, -0.118, 3.494, 2.053], [0.248, 1.316, 1.102, 2.022, 0.319, 1.655], [1.35, -0.101, 1.108, 0.315, 4.473, 2.489], [0.441, -2.72, 0.688, 0.321, 0.469, 1.1], [-0.308, -2.248, -0.131, 0.362, 0.498, 0.335]]
C: [[-1.001, 0.387, 0.855, 0.13, 4.223, 1.808], [-0.121, 2.25, 1.058, 2.216, 0.377, 2.185], [0.489, 0.025, 0.85, -0.341, 3.971, 2.77], [0.668, -2.895, 0.381, 0.972, 0.18, 1.122], [0.223, -2.648, 0.118, -0.29, 0.288, 0.814]]
D: [[-1.615, 0.237, 0.631, 0.113, 3.734, 2.164], [-0.111, 1.6, 1.257, 2.2, 0.658, 1.704], [0.468, -0.376, 0.97, -0.134, 3.943, 2.668], [0.083, -2.476, 0.49, 0.836, 0.329, 1.629], [-0.101, -2.949, 0.022, 0.48, 0.426, 0.711]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the toilet paper holder in the scene. The camera pose information includes: the rotation matrix: [[-0.566304, -0.590941, 0.574533], [-0.823945, 0.423135, -0.376925], [-0.020365, -0.686838, -0.726526]]; the translation vector: [2.143516, 1.760119, 1.343188], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[1.561, -0.516, 0.43, 0.03, 0.264, 0.023]]
B: [[1.307, -0.077, 0.927, 0.18, 0.373, 0.438]]
C: [[1.232, 0.339, 1.368, -0.266, 0.794, 0.386]]
D: [[1.366, 0.134, 0.662, 0.477, 0.375, 0.57]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the ceiling in the scene. The camera pose information includes: the rotation matrix: [[-0.999494, 0.005595, 0.031322], [-0.029883, 0.172936, -0.98448], [-0.010925, -0.984917, -0.172681]]; the translation vector: [6.687301, 5.436423, 1.742894], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[0.989, -2.867, 2.62, 3.827, 5.879, 0.215]]
B: [[0.557, -2.629, 2.447, 3.868, 5.161, -0.064]]
C: [[0.767, -2.57, 3.32, 4.124, 4.999, -0.179]]
D: [[0.538, -2.391, 2.899, 4.263, 5.407, 0.187]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the paper towel dispenser in the scene. The camera pose information includes: the rotation matrix: [[0.207705, 0.494542, -0.843971], [0.97739, -0.069996, 0.199524], [0.039599, -0.866331, -0.497898]]; the translation vector: [4.53083, 2.291093, 1.52739], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.

Context:
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair.
Select from the following choices.
A: [[0.728, -0.216, 1.391, -0.233, 0.319, 0.888]]
B: [[1.382, -0.434, 1.41, 0.62, 0.036, 0.847]]
C: [[1.017, -0.314, 0.963, 0.261, 0.326, 0.441]]
D: [[1.373, -0.033, 0.749, 0.246, 0.609, 0.097]]


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.9999860986788529, -0.0029206102888043426, 0.004512150995140729], [0.0029125077264400548, 0.9999942525374551, 0.0017791916930172049], [-0.004515929331115238, -0.0017660484162836249, 0.9999884136529374]], 'translation vector': [0.00035121537956284143, -0.00211204147587285, 0.0015269971399166637]}
B: {'rotation matrix': [[0.992252, 0.033516, -0.119639], [0.120006, -0.507929, 0.852999], [-0.032179, -0.860747, -0.508015]], 'translation vector': [2.483829, 1.386735, 1.351847]}
C: {'rotation matrix': [[0.992393, 0.03365, -0.118424], [0.118928, -0.510671, 0.851511], [-0.031822, -0.859118, -0.510788]], 'translation vector': [2.483625, 1.389348, 1.348027]}
D: {'rotation matrix': [[0.992358, 0.033913, -0.118638], [0.11923, -0.511103, 0.85121], [-0.031769, -0.85885, -0.511241]], 'translation vector': [2.484339, 1.38954, 1.351903]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[-0.947387, 0.126025, -0.294239], [0.319939, 0.401221, -0.858289], [0.009889, -0.90727, -0.420431]], 'translation vector': [2.649368, 2.97856, 1.365403]}
B: {'rotation matrix': [[0.9999009689053274, -0.0005834477726320058, -0.014081260252404066], [0.0005185811040898338, 0.9999892566550749, -0.004650674323837413], [0.014082812752834694, 0.004642499383147887, 0.9998897887510193]], 'translation vector': [-0.0001697198246333187, -0.006057464737030116, -0.0030857621071840313]}
C: {'rotation matrix': [[-0.946914, 0.131611, -0.293313], [0.321456, 0.400409, -0.858102], [0.004509, -0.906836, -0.42146]], 'translation vector': [2.644349, 2.98006, 1.361572]}
D: {'rotation matrix': [[-0.946851, 0.128282, -0.294988], [0.321573, 0.400396, -0.858064], [0.008037, -0.907318, -0.420367]], 'translation vector': [2.647634, 2.978188, 1.36466]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.932535, 0.164547, -0.321407], [0.359784, -0.498771, 0.788533], [-0.030558, -0.850971, -0.524323]], 'translation vector': [4.48804, -0.229774, 1.538571]}
B: {'rotation matrix': [[0.999974189934778, 0.00023654440835110308, 0.007205305592304459], [-0.00021900350048315587, 0.9999974076812913, -0.002394096534537237], [-0.00720576870446999, 0.0023924811533001236, 0.9999711271279352]], 'translation vector': [-0.011672688463027825, -0.012243066982587869, 0.0020668703552249035]}
C: {'rotation matrix': [[0.930699, 0.167887, -0.324983], [0.364431, -0.502007, 0.784334], [-0.031464, -0.848412, -0.5284]], 'translation vector': [4.497419, -0.228559, 1.538943]}
D: {'rotation matrix': [[0.928253, 0.171766, -0.329913], [0.370592, -0.502789, 0.780939], [-0.031738, -0.847172, -0.53037]], 'translation vector': [4.506209, -0.230888, 1.537021]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.9999922186975153, -0.0004929414354074684, -0.003990843308659959], [0.0004944153894448021, 1.0000000788246688, 0.0002887878542439764], [0.0039912978026401735, -0.00029052347125931846, 0.9999922538344134]], 'translation vector': [0.0015230291799757656, -0.0023232322897525567, 0.004482115182110835]}
B: {'rotation matrix': [[-0.597501, 0.375338, -0.7086], [0.801649, 0.25893, -0.538808], [-0.018758, -0.889987, -0.4556]], 'translation vector': [2.357092, 1.421442, 1.358509]}
C: {'rotation matrix': [[-0.595396, 0.37569, -0.710183], [0.803242, 0.259116, -0.536341], [-0.017478, -0.889784, -0.456047]], 'translation vector': [2.35612, 1.420569, 1.361782]}
D: {'rotation matrix': [[-0.600812, 0.375021, -0.705963], [0.799114, 0.258529, -0.542752], [-0.021031, -0.890237, -0.455012]], 'translation vector': [2.356618, 1.42274, 1.357666]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.690346, 0.288159, -0.663616], [0.723477, -0.272947, 0.634098], [0.001589, -0.917858, -0.396905]], 'translation vector': [2.536332, 2.010734, 1.438743]}
B: {'rotation matrix': [[0.691208, 0.288183, -0.662708], [0.722652, -0.27257, 0.635201], [0.00242, -0.917963, -0.396658]], 'translation vector': [2.535653, 2.009964, 1.439474]}
C: {'rotation matrix': [[0.9999995587474457, 0.00024022036499647738, 0.0007957711644081506], [-0.00023933007530568237, 0.9999998633783928, -0.0007108069241564525], [-0.0007964539455043593, 0.0007109455644655081, 1.000000560983507]], 'translation vector': [-0.004770728985455719, 0.002959587174171885, 0.0013885111462622612]}
D: {'rotation matrix': [[0.690426, 0.287793, -0.663692], [0.723401, -0.272862, 0.634222], [0.001429, -0.917999, -0.396581]], 'translation vector': [2.53477, 2.009069, 1.43814]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.9999658530200795, -0.008162385048605073, -0.000989578606081076], [0.008166400906506959, 0.9999603758313507, 0.0035456278045154508], [0.000960099553273771, -0.0035536229934212678, 0.9999930725472598]], 'translation vector': [0.0005115289741049189, -0.00032414464705918244, 0.0017902118924140176]}
B: {'rotation matrix': [[-0.221487, 0.417059, -0.881479], [0.974313, 0.13239, -0.182174], [0.040721, -0.899186, -0.435668]], 'translation vector': [3.156802, 0.483491, 1.355875]}
C: {'rotation matrix': [[-0.223193, 0.415497, -0.881786], [0.973999, 0.131126, -0.184746], [0.038864, -0.900094, -0.43396]], 'translation vector': [3.157208, 0.483314, 1.355186]}
D: {'rotation matrix': [[-0.22378, 0.416079, -0.881363], [0.973939, 0.129755, -0.18603], [0.036958, -0.900023, -0.434273]], 'translation vector': [3.157156, 0.483591, 1.355072]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[-0.294979, -0.395497, 0.869811], [-0.955406, 0.135138, -0.26256], [-0.013703, -0.908472, -0.417722]], 'translation vector': [4.231627, 1.757554, 1.314948]}
B: {'rotation matrix': [[0.9999859365705687, 3.1558862291102445e-05, 0.005361241460385626], [2.1367515200134227e-05, 0.9999509201368397, -0.009913096398898577], [-0.0053616455101250845, 0.009912181817668633, 0.9999368747200875]], 'translation vector': [-0.00185453480108011, 0.004425119632380792, 0.004740673653586214]}
C: {'rotation matrix': [[-0.295231, -0.385219, 0.874325], [-0.955253, 0.136423, -0.262452], [-0.018176, -0.912686, -0.408258]], 'translation vector': [4.225714, 1.76129, 1.315325]}
D: {'rotation matrix': [[-0.297898, -0.402478, 0.865603], [-0.954572, 0.132313, -0.266996], [-0.007071, -0.905817, -0.42361]], 'translation vector': [4.239912, 1.761582, 1.310375]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[-0.43634, -0.426945, 0.792039], [-0.899692, 0.219464, -0.377346], [-0.012718, -0.877242, -0.47988]], 'translation vector': [1.991026, 3.721216, 1.553809]}
B: {'rotation matrix': [[0.9999994163271791, 0.0007055386419518741, -5.183687097418444e-05], [-0.0007048159396394524, 1.0000001700794185, 0.00017964949547958028], [5.299300853873026e-05, -0.00017925701598013347, 1.000000048079148]], 'translation vector': [-0.0002435455336966541, -0.00047987538941862695, 0.0009530826592798469]}
C: {'rotation matrix': [[-0.436198, -0.427205, 0.791977], [-0.899763, 0.219364, -0.377235], [-0.012574, -0.877141, -0.480069]], 'translation vector': [1.990491, 3.720783, 1.55354]}
D: {'rotation matrix': [[-0.436159, -0.427335, 0.791928], [-0.899792, 0.218686, -0.377559], [-0.011839, -0.877246, -0.479894]], 'translation vector': [1.98993, 3.720837, 1.552023]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.9999987261495074, 0.0004975354064711766, -0.0014612465343166485], [-0.0004956714882147159, 0.9999976114101617, 0.002168145916521647], [0.0014629580715452147, -0.002166812264256858, 0.9999963843096157]], 'translation vector': [-0.0006911004437073487, 0.0010681685362672333, 0.00045340774962232544]}
B: {'rotation matrix': [[0.254029, -0.222698, 0.941209], [-0.965413, 0.000689, 0.260725], [-0.058712, -0.974887, -0.21482]], 'translation vector': [0.927676, 4.785758, 1.499229]}
C: {'rotation matrix': [[0.261058, -0.219751, 0.939978], [-0.963311, 0.003543, 0.268366], [-0.062304, -0.97555, -0.210763]], 'translation vector': [0.925951, 4.784105, 1.497862]}
D: {'rotation matrix': [[0.253006, -0.222602, 0.941507], [-0.965684, 0.00092, 0.259721], [-0.058681, -0.974909, -0.21473]], 'translation vector': [0.928139, 4.78494, 1.499076]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.298773, 0.351612, -0.887189], [0.953749, -0.077747, 0.290375], [0.033123, -0.932912, -0.358578]], 'translation vector': [3.912279, 4.982921, 1.420651]}
B: {'rotation matrix': [[0.29932, 0.353357, -0.88631], [0.953697, -0.082092, 0.289349], [0.029485, -0.93188, -0.361567]], 'translation vector': [3.9112, 4.98563, 1.419169]}
C: {'rotation matrix': [[0.999988451223679, 0.004467367701975065, -0.0013038134525021694], [-0.00445692043483639, 0.9999572940857223, 0.008125240965736606], [0.0013398420675200973, -0.008118916964061989, 0.9999668442244075]], 'translation vector': [0.0032416245875248606, 0.010404768814489485, 0.0002686970709979697]}
D: {'rotation matrix': [[0.298213, 0.352721, -0.886937], [0.953989, -0.07977, 0.289034], [0.031197, -0.932323, -0.36028]], 'translation vector': [3.912466, 4.985029, 1.419803]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.9999651962705811, 0.003066448737415877, 0.007690547235694275], [-0.003089438182273661, 0.9999915450229314, 0.002959839315488226], [-0.007681501308992471, -0.0029840343790842917, 0.999966014383214]], 'translation vector': [-0.009845168086086709, -0.005623772397939042, 0.0006148134083248102]}
B: {'rotation matrix': [[-0.998744, -0.022866, -0.044595], [0.034706, 0.326335, -0.944617], [0.036152, -0.944977, -0.325132]], 'translation vector': [2.332638, 2.988529, 1.390534]}
C: {'rotation matrix': [[-0.998733, -0.022769, -0.044885], [0.035006, 0.326505, -0.944547], [0.036161, -0.944921, -0.325294]], 'translation vector': [2.335994, 2.987912, 1.391848]}
D: {'rotation matrix': [[-0.998702, -0.02238, -0.045764], [0.035975, 0.326219, -0.94461], [0.03607, -0.945029, -0.32499]], 'translation vector': [2.340556, 2.987934, 1.391904]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.088289, -0.769037, 0.633078], [-0.992448, -0.013575, 0.121917], [-0.085165, -0.63906, -0.764427]], 'translation vector': [1.06143, 1.251586, 2.183495]}
B: {'rotation matrix': [[0.095281, -0.770575, 0.630187], [-0.991458, -0.016816, 0.129342], [-0.08907, -0.637128, -0.765594]], 'translation vector': [1.056131, 1.246655, 2.184574]}
C: {'rotation matrix': [[0.101903, -0.771131, 0.628469], [-0.990357, -0.019031, 0.13723], [-0.093862, -0.636392, -0.765634]], 'translation vector': [1.04909, 1.241123, 2.18482]}
D: {'rotation matrix': [[0.9999704077161121, 0.0009465902067394159, -0.007647096819155797], [-0.0009526969531251086, 0.9999995333260298, -0.0008216172460913287], [0.00764682863028495, 0.0008292870802229541, 0.9999701657998578]], 'translation vector': [0.005049491112872229, 0.003519427946364395, -0.004842133831311157]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.236859, -0.585227, 0.775504], [-0.967029, -0.065142, 0.246196], [-0.093563, -0.808248, -0.581361]], 'translation vector': [0.85633, 3.124968, 1.418476]}
B: {'rotation matrix': [[0.9999986227118945, -0.0014386707321173084, -0.0013720086731618905], [0.0014396405048904127, 0.9999985343757846, 0.0002480174905685849], [0.0013722163701430706, -0.00024858511187529484, 0.9999990039875143]], 'translation vector': [0.0014743108378150183, 9.881450519233503e-05, 0.00010772367212419365]}
C: {'rotation matrix': [[0.234228, -0.586349, 0.775456], [-0.967526, -0.06262, 0.244894], [-0.095034, -0.807635, -0.581975]], 'translation vector': [0.858687, 3.12069, 1.418757]}
D: {'rotation matrix': [[0.234642, -0.58546, 0.776002], [-0.967537, -0.063552, 0.24461], [-0.093893, -0.808206, -0.581366]], 'translation vector': [0.856906, 3.122666, 1.417663]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.582104, 0.470868, -0.662901], [0.81311, -0.339656, 0.472743], [-0.002559, -0.814197, -0.580583]], 'translation vector': [4.229822, 1.596572, 1.425168]}
B: {'rotation matrix': [[0.9999560146697009, 0.003230475520535795, -0.00886892770497088], [-0.0032175833964298243, 0.9999942676924473, 0.0014734023416888033], [0.008873986014087454, -0.001444906579376565, 0.9999590747869875]], 'translation vector': [0.0012149381321875374, 0.0024560981455157282, -0.00010287317760537817]}
C: {'rotation matrix': [[0.582444, 0.471641, -0.662053], [0.812867, -0.340629, 0.472461], [-0.002682, -0.813343, -0.581779]], 'translation vector': [4.230144, 1.598887, 1.426125]}
D: {'rotation matrix': [[0.583525, 0.471082, -0.661499], [0.812092, -0.340805, 0.473665], [-0.002307, -0.813593, -0.58143]], 'translation vector': [4.230429, 1.59898, 1.426046]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.990893, 0.057008, -0.121987], [0.134304, -0.353431, 0.92577], [0.009662, -0.933722, -0.357869]], 'translation vector': [2.186028, 2.144782, 1.462596]}
B: {'rotation matrix': [[0.991569, 0.053062, -0.11822], [0.129357, -0.351493, 0.927211], [0.007646, -0.934686, -0.355393]], 'translation vector': [2.183204, 2.143093, 1.462234]}
C: {'rotation matrix': [[0.9999874902969159, 0.004379197439594465, -0.002403723493325247], [-0.004372650351021444, 0.9999870005118716, 0.0026700250405810233], [0.0024158589744238553, -0.0026609890925621414, 0.9999939599581709]], 'translation vector': [-0.003672033476809222, -0.0017027412429904132, -0.0003357999980959647]}
D: {'rotation matrix': [[0.991257, 0.055775, -0.119575], [0.131602, -0.352888, 0.926364], [0.009471, -0.934002, -0.357143]], 'translation vector': [2.184101, 2.143995, 1.46179]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.9999986691328494, -0.001073261840895818, -0.0008802624854347336], [0.001080335550453663, 0.9999723432097648, 0.00736012496129083], [0.0008730903166935182, -0.007359768837914202, 0.9999729147693108]], 'translation vector': [0.0010486658094048806, -0.004009939681768326, 0.0017973568614269853]}
B: {'rotation matrix': [[-0.386299, -0.298688, 0.872673], [-0.920393, 0.186791, -0.343491], [-0.060411, -0.935893, -0.347067]], 'translation vector': [2.08048, 4.009937, 1.840847]}
C: {'rotation matrix': [[-0.383122, -0.307436, 0.871034], [-0.921947, 0.185316, -0.340108], [-0.056855, -0.933349, -0.354438]], 'translation vector': [2.080896, 4.009106, 1.847586]}
D: {'rotation matrix': [[-0.384424, -0.301178, 0.872645], [-0.921297, 0.185141, -0.341959], [-0.058572, -0.935422, -0.348647]], 'translation vector': [2.077995, 4.010322, 1.837904]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.9999787823940977, 0.006347499783107699, -0.0013436878206843045], [-0.006341718624184496, 0.9999688828294876, 0.004625015892328648], [0.0013735202687803576, -0.004616292980016383, 0.9999878757602079]], 'translation vector': [-0.006298849286503927, 0.01405890593176995, 0.0007444533799123576]}
B: {'rotation matrix': [[0.999733, -0.006694, 0.022129], [-0.023039, -0.368118, 0.929494], [0.001924, -0.929755, -0.368173]], 'translation vector': [3.317142, 3.173762, 1.523565]}
C: {'rotation matrix': [[0.999731, -0.010083, 0.02088], [-0.023127, -0.369367, 0.928996], [-0.001654, -0.929229, -0.3695]], 'translation vector': [3.314788, 3.169853, 1.521514]}
D: {'rotation matrix': [[0.999712, -0.007131, 0.022924], [-0.023946, -0.364324, 0.930964], [0.001713, -0.931245, -0.36439]], 'translation vector': [3.320507, 3.174599, 1.524876]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[-0.998283, -0.004041, -0.058434], [0.054839, 0.286044, -0.956646], [0.020581, -0.958208, -0.285332]], 'translation vector': [1.688122, 4.435732, 1.572228]}
B: {'rotation matrix': [[0.9999952600112642, 0.0029895442027471574, 0.0009673920050112699], [-0.0029953662693526914, 0.9999719574782809, 0.006845684012961962], [-0.000945954294544353, -0.006847856485920328, 0.9999767653082445]], 'translation vector': [-0.00043220364465224037, 0.0023057137872921907, 0.0026271806076847426]}
C: {'rotation matrix': [[-0.998336, -0.002848, -0.057597], [0.054423, 0.283794, -0.95734], [0.019072, -0.958881, -0.283167]], 'translation vector': [1.687961, 4.436946, 1.571062]}
D: {'rotation matrix': [[-0.998358, -0.001309, -0.057275], [0.054546, 0.284027, -0.957264], [0.017521, -0.958815, -0.283489]], 'translation vector': [1.688286, 4.43679, 1.571851]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[-0.083515, 0.422666, -0.902429], [0.995888, 0.067297, -0.060645], [0.035099, -0.903783, -0.426549]], 'translation vector': [4.26049, 5.866284, 1.66918]}
B: {'rotation matrix': [[-0.080848, 0.422553, -0.902725], [0.996028, 0.068154, -0.057302], [0.037311, -0.903772, -0.426385]], 'translation vector': [4.26043, 5.866841, 1.668667]}
C: {'rotation matrix': [[-0.081468, 0.422714, -0.902594], [0.995995, 0.068006, -0.058049], [0.036844, -0.903708, -0.426561]], 'translation vector': [4.260486, 5.864969, 1.669529]}
D: {'rotation matrix': [[0.9999996666026792, 0.0007024902365725143, 0.00045309895052521656], [-0.0007041385629428506, 0.9999945142012453, 0.003060691886503368], [-0.00045146230549075186, -0.0030616184704849174, 0.9999957671575359]], 'translation vector': [-0.008238592634347341, 0.0026712907326988944, 0.0010534554726602252]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[0.192624, -0.379717, 0.904826], [-0.981148, -0.059825, 0.183766], [-0.015648, -0.923166, -0.384082]], 'translation vector': [4.984646, 4.164808, 1.32267]}
B: {'rotation matrix': [[0.9993897560101446, -0.009672092115768357, 0.033569058676964116], [0.00944513640094131, 0.9999317047122397, 0.006930507743012298], [-0.033634032991460915, -0.006610261888877057, 0.9994127816547865]], 'translation vector': [-0.03424616147212767, -0.0027538632482175807, 0.008124405533084023]}
C: {'rotation matrix': [[0.180272, -0.384554, 0.905329], [-0.983511, -0.056947, 0.171651], [-0.014453, -0.921344, -0.388479]], 'translation vector': [4.987018, 4.177592, 1.323464]}
D: {'rotation matrix': [[0.205405, -0.377617, 0.902892], [-0.978531, -0.0633, 0.196139], [-0.016912, -0.923796, -0.382512]], 'translation vector': [4.985321, 4.152791, 1.324267]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[-0.084118, -0.329466, 0.940413], [-0.993483, 0.100574, -0.05363], [-0.076912, -0.938795, -0.335779]], 'translation vector': [4.338453, 2.933071, 1.462896]}
B: {'rotation matrix': [[0.9999984493090167, 0.0015295352178733802, -0.0012886089849350254], [-0.0015301527829556035, 0.9999993364831051, -0.0007407082576259022], [0.0012866367449453698, 0.0007417730730382566, 0.99999926268211]], 'translation vector': [-0.001971799758651027, -0.003988184523042726, -0.0019001345524003455]}
C: {'rotation matrix': [[-0.084181, -0.324678, 0.942071], [-0.993543, 0.09952, -0.054482], [-0.076066, -0.940574, -0.330959]], 'translation vector': [4.337488, 2.935505, 1.461639]}
D: {'rotation matrix': [[-0.083371, -0.331462, 0.939778], [-0.993645, 0.099215, -0.053156], [-0.075621, -0.938238, -0.337627]], 'translation vector': [4.338066, 2.933557, 1.453891]}


Question: Given a pair of a RGB image and a depth image for scan 0, along with another pair of a RGB image and a depth image for scan 1, please estimate the relative camera pose from scan 0 to scan 1. The output should indicate the rotation matrix and the translation vector.

Context:
Your task is to estimate the relative camera pose between two scans.
Select from the following choices.
A: {'rotation matrix': [[-0.486704, 0.327719, -0.809765], [0.869935, 0.097394, -0.483454], [-0.079571, -0.939742, -0.332496]], 'translation vector': [4.437128, 2.283443, 1.465507]}
B: {'rotation matrix': [[0.9999935589617881, -0.0023123151478069903, 0.002638162918517237], [0.0023036775758451737, 0.9999925417720922, 0.0032437850296420778], [-0.0026449296307575294, -0.0032387699437697024, 0.9999912244700261]], 'translation vector': [0.0032199017210038927, 0.0001093759992842891, 0.0024338106134420556]}
C: {'rotation matrix': [[-0.494127, 0.32769, -0.805269], [0.866163, 0.105829, -0.488427], [-0.074832, -0.938839, -0.336126]], 'translation vector': [4.441189, 2.279036, 1.469096]}
D: {'rotation matrix': [[-0.489836, 0.32797, -0.807773], [0.868301, 0.100425, -0.485767], [-0.078196, -0.939335, -0.333968]], 'translation vector': [4.439312, 2.280933, 1.467607]}