A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.852441, 0.228219, -0.470383], [0.522431, 0.337001, -0.78326], [-0.020235, -0.913426, -0.406502]] and translation vector: [1.798405, 5.320803, 1.619482], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.850776, 0.231102, -0.471988], [0.52508, 0.336676, -0.781627], [-0.021728, -0.91282, -0.407783]] and translation vector: [1.793927, 5.32593, 1.618758], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.999494, 0.005595, 0.031322], [-0.029883, 0.172936, -0.98448], [-0.010925, -0.984917, -0.172681]] and translation vector: [6.687301, 5.436423, 1.742894], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.999393, 0.00615, 0.034285], [-0.032681, 0.175053, -0.984017], [-0.012053, -0.98454, -0.174746]] and translation vector: [6.681215, 5.427393, 1.75699], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.99336, -0.011945, -0.114427], [0.103059, -0.349694, 0.931178], [-0.051137, -0.936788, -0.346141]] and translation vector: [2.948285, 4.432959, 1.460427], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.99314, -0.016022, -0.115825], [0.102925, -0.35027, 0.930977], [-0.055486, -0.936512, -0.346218]] and translation vector: [2.949102, 4.433566, 1.463483], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.40936, -0.486807, 0.77165], [-0.912164, 0.236459, -0.334729], [-0.019515, -0.840896, -0.540844]] and translation vector: [1.412713, 1.214489, 1.390939], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.417972, -0.487805, 0.766384], [-0.908352, 0.237425, -0.344277], [-0.014019, -0.840045, -0.542336]] and translation vector: [1.411881, 1.212071, 1.390231], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.442667, -0.46733, 0.765277], [-0.896368, 0.253361, -0.363776], [-0.023888, -0.847001, -0.531054]] and translation vector: [2.453469, 1.905797, 1.451684], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.441405, -0.472001, 0.763136], [-0.897015, 0.253848, -0.361837], [-0.022933, -0.844261, -0.535442]] and translation vector: [2.45238, 1.90449, 1.449179], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.88123, -0.188698, 0.433389], [-0.470321, -0.258404, 0.843816], [-0.047237, -0.947428, -0.316462]] and translation vector: [1.061636, 1.321782, 1.457525], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.879526, -0.187337, 0.437423], [-0.473303, -0.249401, 0.844857], [-0.049179, -0.950107, -0.308022]] and translation vector: [1.052651, 1.315727, 1.459226], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.15851, 0.420096, -0.893529], [0.981106, -0.034663, -0.190342], [-0.110934, -0.906817, -0.406664]] and translation vector: [4.004256, 0.910349, 2.578562], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.153085, 0.419732, -0.894645], [0.982322, -0.034068, -0.184071], [-0.107739, -0.907009, -0.407097]] and translation vector: [4.005316, 0.908549, 2.574668], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.565317, -0.50256, 0.654103], [-0.824719, 0.328974, -0.460017], [0.016003, -0.799506, -0.600445]] and translation vector: [4.07549, 5.065369, 1.281872], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.538132, -0.502349, 0.676801], [-0.842747, 0.30749, -0.441846], [0.013851, -0.808143, -0.588824]] and translation vector: [4.054681, 5.042427, 1.283033], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.998162, -0.007354, -0.06016], [0.055338, 0.294228, -0.954132], [0.024717, -0.955707, -0.293281]] and translation vector: [1.687981, 4.43329, 1.569003], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.998237, -0.004775, -0.059163], [0.055295, 0.287523, -0.956176], [0.021577, -0.957762, -0.286752]] and translation vector: [1.687716, 4.435163, 1.571974], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.30056, -0.511506, 0.805], [-0.953151, 0.130866, -0.272721], [0.034151, -0.849256, -0.526876]] and translation vector: [-0.281614, 2.924112, 1.306122], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.318531, -0.50267, 0.803655], [-0.947336, 0.139247, -0.288383], [0.033055, -0.85319, -0.520551]] and translation vector: [-0.284617, 2.924129, 1.305331], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.815869, 0.244354, -0.524069], [0.578211, -0.336271, 0.743367], [0.005416, -0.909513, -0.415641]] and translation vector: [2.358014, 1.230078, 1.369842], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.817563, 0.244526, -0.521342], [0.575764, -0.332513, 0.746947], [0.009295, -0.910847, -0.41264]] and translation vector: [2.355037, 1.229076, 1.372478], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.971613, -0.06682, 0.226943], [-0.235147, 0.378036, -0.89543], [-0.02596, -0.923376, -0.383017]] and translation vector: [2.775299, 4.618156, 1.427592], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.969099, -0.066923, 0.237421], [-0.244849, 0.377786, -0.892932], [-0.029937, -0.923471, -0.382498]] and translation vector: [2.770648, 4.620754, 1.418404], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.117057, -0.769276, 0.628102], [-0.987232, -0.021336, 0.157855], [-0.108033, -0.638561, -0.761951]] and translation vector: [1.032686, 1.226834, 2.186959], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.111522, -0.769903, 0.628341], [-0.98843, -0.020525, 0.150284], [-0.102807, -0.637831, -0.763284]] and translation vector: [1.037875, 1.232625, 2.186027], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.053762, 0.423971, -0.904079], [0.99709, -0.071809, 0.025618], [-0.05406, -0.902825, -0.426597]] and translation vector: [3.696534, 7.381392, 1.65485], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.059051, 0.424044, -0.903714], [0.996629, -0.076693, 0.029136], [-0.056954, -0.902388, -0.427143]] and translation vector: [3.693501, 7.384472, 1.654036], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.255196, -0.436856, 0.862573], [-0.966393, 0.143834, -0.213066], [-0.030988, -0.887958, -0.45888]] and translation vector: [1.734999, 0.744851, 1.432124], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.254375, -0.435236, 0.863634], [-0.966628, 0.142475, -0.21291], [-0.03038, -0.888972, -0.456953]] and translation vector: [1.735377, 0.747301, 1.433656], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.299058, 0.37418, -0.877812], [0.95368, -0.085842, 0.288314], [0.032528, -0.923375, -0.38252]] and translation vector: [3.908031, 4.993837, 1.41318], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.301871, 0.365699, -0.880419], [0.952911, -0.087746, 0.290279], [0.028901, -0.926588, -0.374966]] and translation vector: [3.903484, 4.991583, 1.422828], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.349467, 0.022881, -0.936669], [0.936944, -0.011774, 0.349282], [-0.003037, -0.999669, -0.025553]] and translation vector: [3.08553, 2.787215, 1.609269], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.348555, 0.021762, -0.937036], [0.937279, -0.012701, 0.34835], [-0.00432, -0.999682, -0.024824]] and translation vector: [3.086167, 2.787834, 1.610474], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.187285, -0.627824, 0.755488], [-0.982305, 0.118515, -0.145025], [0.001514, -0.76928, -0.63891]] and translation vector: [1.001752, 1.17634, 1.437838], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.187139, -0.630563, 0.75324], [-0.982328, 0.117514, -0.14568], [0.003345, -0.767191, -0.64141]] and translation vector: [1.00191, 1.178201, 1.437088], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.052123, 0.492225, -0.868906], [0.996177, 0.08671, -0.010637], [0.070107, -0.866138, -0.494863]] and translation vector: [3.27549, 2.071379, 1.287401], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.035278, 0.492309, -0.869705], [0.997133, 0.075637, 0.002369], [0.066948, -0.867128, -0.493566]] and translation vector: [3.286684, 2.076202, 1.285681], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.721847, -0.019511, -0.691778], [0.690918, -0.036893, 0.721991], [-0.039608, -0.999129, -0.013151]] and translation vector: [1.871862, 0.815296, 1.594356], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.723033, -0.022358, -0.690452], [0.689637, -0.034974, 0.723311], [-0.04032, -0.999138, -0.009869]] and translation vector: [1.872181, 0.815734, 1.596287], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.112591, -0.547395, 0.829266], [-0.992672, 0.098819, -0.069547], [-0.043877, -0.83102, -0.55451]] and translation vector: [1.18498, 1.814175, 1.496605], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.111637, -0.546351, 0.830083], [-0.992679, 0.100057, -0.067648], [-0.046096, -0.831558, -0.553521]] and translation vector: [1.186424, 1.810214, 1.495373], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.59597, 0.482312, -0.642025], [0.802979, -0.35126, 0.4815], [0.006716, -0.802491, -0.596626]] and translation vector: [3.449961, 1.112515, 1.412234], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.596047, 0.483799, -0.640833], [0.802896, -0.349913, 0.482617], [0.009254, -0.802184, -0.597005]] and translation vector: [3.451157, 1.111087, 1.411899], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.132001, -0.567775, 0.812532], [-0.991224, 0.069667, -0.112349], [0.007182, -0.820231, -0.571988]] and translation vector: [2.407685, 4.450429, 1.359714], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.130918, -0.563466, 0.8157], [-0.991376, 0.069526, -0.111087], [0.005882, -0.823209, -0.567709]] and translation vector: [2.40989, 4.444678, 1.359228], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.443363, -0.325026, 0.835337], [-0.895367, 0.117125, -0.429651], [0.041809, -0.938424, -0.342946]] and translation vector: [2.190343, 3.392878, 1.594635], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.439336, -0.32163, 0.838772], [-0.897253, 0.111545, -0.427195], [0.043838, -0.940272, -0.337589]] and translation vector: [2.183471, 3.393708, 1.586874], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.985254, -0.134646, 0.105573], [-0.142287, -0.302097, 0.942599], [-0.095024, -0.94372, -0.3168]] and translation vector: [1.134605, 1.549487, 1.505245], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.985752, -0.13049, 0.106142], [-0.141062, -0.297585, 0.944216], [-0.091624, -0.945736, -0.311752]] and translation vector: [1.131707, 1.551058, 1.506377], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.753053, 0.123809, -0.646206], [0.619922, -0.462608, 0.633791], [-0.220471, -0.877875, -0.42512]] and translation vector: [4.259223, 3.769218, 1.505729], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.760823, 0.125761, -0.636658], [0.611756, -0.466381, 0.638939], [-0.216572, -0.875599, -0.431768]] and translation vector: [4.257898, 3.775608, 1.505422], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.924746, 0.145405, -0.351715], [0.379908, 0.407811, -0.830277], [0.022707, -0.901414, -0.432362]] and translation vector: [3.891577, 4.106122, 1.335216], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.925289, 0.144931, -0.350479], [0.378485, 0.412032, -0.828842], [0.024284, -0.899569, -0.436102]] and translation vector: [3.892777, 4.104329, 1.336806], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.748873, -0.374013, 0.547087], [-0.662404, -0.447673, 0.600675], [0.020256, -0.812221, -0.582998]] and translation vector: [3.709567, 4.406117, 1.261793], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.747082, -0.370975, 0.551585], [-0.664465, -0.440253, 0.603874], [0.018814, -0.817652, -0.575405]] and translation vector: [3.708719, 4.403161, 1.261416], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.934222, -0.219071, 0.281493], [-0.356558, -0.595286, 0.72007], [0.009823, -0.773073, -0.634241]] and translation vector: [0.331108, 1.989283, 1.551545], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.93341, -0.222981, 0.281114], [-0.358788, -0.589093, 0.724045], [0.004154, -0.776691, -0.629868]] and translation vector: [0.338532, 1.98258, 1.554168], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.52463, -0.231347, 0.819293], [-0.850589, 0.102279, -0.515789], [0.03553, -0.96748, -0.25044]] and translation vector: [5.897326, 2.792535, 1.553822], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.52763, -0.228151, 0.818263], [-0.84888, 0.105585, -0.517933], [0.03177, -0.967884, -0.249382]] and translation vector: [5.897463, 2.790525, 1.551499], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.699126, -0.324611, 0.637064], [-0.713802, 0.265353, -0.648131], [0.041344, -0.907863, -0.417224]] and translation vector: [0.050403, 3.78209, 1.506908], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.698648, -0.327666, 0.636024], [-0.713993, 0.262294, -0.649166], [0.045885, -0.907654, -0.417203]] and translation vector: [0.047406, 3.786517, 1.504266], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.990268, -0.101591, 0.095124], [-0.135934, -0.559426, 0.817658], [-0.029851, -0.822631, -0.567792]] and translation vector: [6.679901, 2.488796, 1.402653], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.989948, -0.105417, 0.094292], [-0.137296, -0.556168, 0.819651], [-0.033963, -0.824357, -0.565051]] and translation vector: [6.681146, 2.493639, 1.408598], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.311411, -0.45253, 0.835607], [-0.948656, 0.199362, -0.245576], [-0.055457, -0.869179, -0.491379]] and translation vector: [2.299133, 2.388773, 1.459468], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.314195, -0.454542, 0.833471], [-0.947818, 0.20019, -0.248124], [-0.05407, -0.867937, -0.493722]] and translation vector: [2.299448, 2.389842, 1.45904], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.789457, 0.162095, -0.592016], [0.613764, 0.197318, -0.764434], [-0.007096, -0.966846, -0.255262]] and translation vector: [5.114759, 3.17533, 1.386193], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.785271, 0.158609, -0.598492], [0.619131, 0.193201, -0.761151], [-0.005096, -0.968255, -0.249915]] and translation vector: [5.11251, 3.170745, 1.383731], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.408988, -0.323891, 0.853126], [-0.912443, -0.158736, 0.37716], [0.013263, -0.932683, -0.360453]] and translation vector: [3.672612, 2.990265, 1.494339], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.403714, -0.307769, 0.861564], [-0.914697, -0.154884, 0.373283], [0.018558, -0.93877, -0.344045]] and translation vector: [3.67724, 2.998002, 1.501107], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.831143, 0.312948, -0.459636], [0.555586, 0.43327, -0.709649], [-0.022937, -0.845187, -0.533978]] and translation vector: [2.360292, 3.05803, 1.315354], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.8108, 0.328121, -0.484706], [0.584922, 0.423558, -0.691711], [-0.021664, -0.844355, -0.535346]] and translation vector: [2.374215, 3.08026, 1.318953], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.802837, 0.056561, -0.593509], [0.596192, 0.071654, -0.799638], [-0.002701, -0.995825, -0.091248]] and translation vector: [2.583219, 4.008804, 1.439254], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.802466, 0.056012, -0.594063], [0.59669, 0.070227, -0.799393], [-0.003056, -0.995957, -0.089777]] and translation vector: [2.583684, 4.008714, 1.434935], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.032646, 0.194727, -0.980314], [0.998594, -0.034636, -0.040135], [-0.04177, -0.980246, -0.193322]] and translation vector: [3.506056, 2.493951, 1.706783], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.038857, 0.192835, -0.980462], [0.998032, -0.040846, -0.047587], [-0.049225, -0.980381, -0.190868]] and translation vector: [3.502031, 2.499079, 1.701362], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.573389, -0.355745, 0.738018], [-0.818965, 0.223754, -0.528424], [0.02285, -0.907403, -0.419641]] and translation vector: [2.061407, 3.857203, 1.382209], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.569689, -0.351701, 0.742806], [-0.821614, 0.221591, -0.525212], [0.020118, -0.909508, -0.4152]] and translation vector: [2.058259, 3.848013, 1.384733], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.863619, -0.252896, 0.436126], [-0.502889, 0.371124, -0.780621], [0.03556, -0.893482, -0.447688]] and translation vector: [2.007098, 3.82416, 1.536992], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.862677, -0.255046, 0.436739], [-0.504412, 0.370978, -0.779707], [0.036841, -0.892932, -0.448682]] and translation vector: [2.007321, 3.81907, 1.542811], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.986418, -0.051155, 0.156087], [-0.152905, 0.633099, -0.758819], [-0.060001, -0.772379, -0.632322]] and translation vector: [2.055195, 1.600374, 1.268236], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.986809, -0.050817, 0.15371], [-0.151071, 0.630346, -0.761474], [-0.058194, -0.77465, -0.629707]] and translation vector: [2.054364, 1.600927, 1.26836], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.436119, -0.427186, 0.79203], [-0.89981, 0.218659, -0.377532], [-0.011909, -0.877326, -0.479747]] and translation vector: [1.992302, 3.72193, 1.553249], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.436462, -0.426736, 0.792084], [-0.899636, 0.219226, -0.377618], [-0.012502, -0.877403, -0.47959]] and translation vector: [1.991236, 3.722176, 1.553282], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.996429, -0.081152, -0.023325], [-0.01119, 0.400709, -0.916137], [0.083693, -0.912604, -0.400187]] and translation vector: [7.365378, 2.610504, 1.343957], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.997089, -0.075007, -0.013671], [-0.016913, 0.392439, -0.919623], [0.074343, -0.916715, -0.392565]] and translation vector: [7.36531, 2.61944, 1.344548], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.896132, -0.052356, 0.440688], [-0.436974, -0.277444, 0.855616], [0.07747, -0.959314, -0.271505]] and translation vector: [3.211431, 3.110947, 1.584554], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.889709, -0.065096, 0.451863], [-0.451099, -0.277541, 0.848222], [0.070195, -0.958506, -0.276295]] and translation vector: [3.215954, 3.116336, 1.570817], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.643628, -0.362528, 0.674031], [-0.765241, -0.290748, 0.574345], [-0.012243, -0.88546, -0.464555]] and translation vector: [2.632762, 2.243425, 1.452714], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.642371, -0.361874, 0.675579], [-0.76623, -0.285016, 0.575898], [-0.015852, -0.887589, -0.460364]] and translation vector: [2.634792, 2.237319, 1.452971], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[-0.612656, -0.411508, 0.674769], [-0.789543, 0.280105, -0.546043], [0.035694, -0.867296, -0.496511]] and translation vector: [1.897828, 2.372103, 1.388776], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[-0.615876, -0.406578, 0.674826], [-0.787242, 0.284147, -0.547275], [0.03076, -0.868305, -0.495075]] and translation vector: [1.892345, 2.36762, 1.390764], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image

Question: Given the first color image view of the scene with the corresponding camera pose, i.e., rotation matrix: [[0.752445, 0.275595, -0.598225], [0.657828, -0.35994, 0.661593], [-0.032994, -0.891342, -0.452129]] and translation vector: [2.633805, 2.70906, 1.31733], and the second color image view of the same scene with the corresponding camera pose, i.e., rotation matrix: [[0.746128, 0.269733, -0.608718], [0.664676, -0.35493, 0.657443], [-0.038718, -0.895136, -0.444108]] and translation vector: [2.667176, 2.689206, 1.310347], please estimate the depth map for the first view of the RGB image. The provided camera poses represent the the transformation from the camera coordinate system to the world coordinate system.

Context:
Your task is to estimate the depth map for a color image based on two color images captured from two viewpoints, along with the corresponding camera poses.The input images are the first 2 images
Select from the following choices.
A: The 3th image
B: The 4th image
C: The 5th image
D: The 6th image


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: [[0.86482, -0.183466, 0.467362], [-0.501092, -0.256948, 0.826368], [-0.031523, -0.948851, -0.314147]]; the translation vector: [3.012278, 2.022242, 1.442339], 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, -2.343, -0.119, 0.31, 0.062, 0.564], [-0.682, 2.2, 0.854, 0.245, 0.21, 0.887], [1.912, 1.405, 1.111, 0.468, 0.452, 0.649], [1.666, 2.151, 1.319, 0.566, 0.243, 0.586], [1.68, 1.827, 0.754, -0.048, 0.681, 0.119], [1.224, 1.284, 0.947, -0.031, 0.464, 0.194], [1.776, 1.335, 0.376, 0.886, 0.055, 0.335], [1.559, 1.179, 1.34, -0.063, -0.136, -0.017], [0.95, 0.255, 1.046, -0.137, 0.36, -0.187], [1.987, 0.956, 0.62, 0.226, -0.239, 0.309], [1.652, 0.525, 1.179, 0.104, 0.539, -0.125], [1.409, 0.711, 0.681, 0.259, 0.215, 0.643], [1.086, -0.177, -0.123, 0.706, 0.621, 0.551], [1.203, 1.982, 0.324, 0.158, 0.718, -0.1], [-1.373, -0.521, 0.674, -0.225, 0.726, 0.299], [-0.949, 2.103, 0.551, 0.314, 0.298, 0.513], [-0.76, 1.491, 2.338, 0.158, -0.084, 0.396], [1.233, -0.382, 0.447, 0.091, 0.059, -0.038], [1.9, -1.181, 1.39, 0.188, -0.114, -0.011]]
B: [[-0.029, -1.923, 0.096, 0.249, 0.113, 0.317], [-0.92, 1.815, 0.646, 0.107, 0.184, 0.516], [1.611, 1.619, 0.954, 0.253, 0.266, 0.249], [1.544, 1.826, 0.949, 0.149, 0.178, 0.182], [1.432, 1.79, 0.87, 0.251, 0.301, 0.054], [1.423, 1.326, 0.897, 0.087, 0.104, 0.188], [1.554, 0.837, 0.836, 0.609, 0.432, 0.17], [1.27, 0.844, 0.842, 0.093, 0.107, 0.179], [1.248, 0.676, 0.764, 0.25, 0.269, 0.064], [1.848, 0.645, 0.825, 0.074, 0.102, 0.07], [1.69, 0.454, 0.837, 0.248, 0.167, 0.182], [1.715, 0.276, 0.86, 0.335, 0.399, 0.17], [1.4, -0.193, 0.037, 0.353, 0.275, 0.161], [1.684, 1.781, 0.29, 0.433, 0.395, 0.339], [-1.62, -0.65, 0.742, 0.272, 0.321, 0.114], [-0.975, 1.832, 0.171, 0.262, 0.195, 0.125], [-1.021, 1.599, 2.098, 0.217, 0.273, 0.221], [1.433, 0.084, 0.074, 0.398, 0.344, 0.176], [1.733, -1.208, 1.076, 0.125, 0.108, 0.327]]
C: [[0.373, -2.148, -0.291, 0.339, 0.018, 0.694], [-0.499, 2.165, 0.993, 0.276, 0.335, 0.775], [1.74, 1.478, 1.323, -0.069, 0.758, 0.607], [1.532, 2.302, 1.262, 0.285, 0.22, -0.252], [1.323, 1.537, 0.593, 0.351, 0.467, 0.392], [1.364, 1.041, 1.236, 0.12, 0.57, 0.444], [1.442, 1.263, 1.284, 1.004, 0.007, 0.304], [1.115, 0.536, 0.672, -0.113, -0.219, -0.082], [1.743, 0.762, 0.395, 0.159, 0.41, 0.323], [2.121, 0.573, 0.527, -0.324, 0.247, 0.462], [1.447, 0.752, 1.299, 0.299, 0.347, 0.233], [1.92, 0.62, 0.769, -0.13, 0.686, -0.059], [0.942, 0.049, -0.066, 0.316, 0.607, 0.459], [2.077, 2.024, 0.781, 0.373, -0.058, 0.752], [-1.491, -0.599, 0.622, 0.707, -0.171, -0.319], [-1.023, 1.772, -0.236, 0.203, 0.47, 0.117], [-0.596, 1.76, 1.726, 0.197, 0.073, 0.18], [1.574, 0.398, 0.118, 0.732, 0.235, 0.24], [1.654, -1.081, 1.126, -0.043, 0.128, 0.085]]
D: [[-0.016, -2.182, 0.529, 0.012, -0.234, 0.082], [-0.638, 1.532, 1.107, 0.49, 0.648, 0.861], [1.27, 1.262, 1.438, 0.461, 0.457, 0.658], [1.731, 1.955, 1.411, 0.079, 0.038, 0.636], [1.916, 1.8, 0.455, 0.749, 0.555, 0.441], [1.273, 0.97, 0.909, 0.183, -0.155, 0.402], [1.478, 1.046, 1.305, 0.37, 0.729, 0.224], [1.279, 0.48, 0.354, 0.143, -0.211, 0.086], [1.055, 0.494, 1.055, -0.029, 0.559, -0.151], [2.256, 0.151, 1.167, -0.326, -0.138, 0.075], [1.326, 0.605, 0.815, -0.119, 0.42, 0.177], [2.172, 0.341, 0.688, 0.742, 0.292, 0.566], [1.621, -0.605, 0.175, 0.538, -0.117, 0.628], [1.477, 1.542, -0.082, 0.684, 0.168, -0.065], [-1.675, -0.211, 0.417, 0.169, -0.09, -0.164], [-1.277, 1.624, 0.657, -0.231, 0.334, -0.097], [-0.751, 1.371, 1.707, -0.044, 0.702, 0.452], [1.41, -0.207, 0.284, 0.114, 0.651, -0.312], [1.447, -0.888, 1.553, -0.369, 0.402, 0.174]]


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: [[-0.060487, 0.154719, -0.986105], [0.998165, 0.006603, -0.060191], [-0.002801, -0.987936, -0.154835]]; the translation vector: [6.630666, 2.572317, 1.44523], 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: [[-2.373, -1.08, 0.874, 0.298, 4.385, 1.982], [2.17, -0.036, 1.086, 0.309, 6.903, 1.887], [0.087, 4.155, 1.455, 2.931, 0.24, 1.054], [-2.394, 2.523, 0.998, 0.208, 1.864, 1.096]]
B: [[-2.011, -0.956, 1.222, 0.755, 4.764, 2.451], [2.068, 0.255, 0.587, 0.436, 7.258, 1.991], [0.329, 4.55, 1.265, 3.421, 0.529, 1.367], [-2.081, 2.555, 0.715, 0.343, 1.488, 1.021]]
C: [[-2.751, -0.591, 0.65, -0.115, 4.495, 2.351], [1.978, 0.331, 1.034, 0.171, 7.03, 2.051], [0.03, 3.84, 1.693, 3.348, 0.554, 1.247], [-2.636, 2.957, 1.408, -0.018, 1.435, 1.132]]
D: [[-2.401, -1.35, 0.706, 0.08, 4.387, 2.134], [2.651, -0.401, 0.766, 0.612, 6.557, 1.511], [0.041, 3.914, 1.655, 3.173, 0.701, 0.821], [-2.147, 2.752, 0.898, 0.388, 2.028, 1.081]]


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: [[-0.610102, 0.375008, -0.697958], [0.791763, 0.255448, -0.554849], [-0.029781, -0.891132, -0.452767]]; the translation vector: [2.349929, 1.419923, 1.358478], 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: [[0.552, 0.743, 0.817, 1.009, -0.013, 1.113], [0.943, 1.174, 0.929, -0.18, 0.779, 1.068]]
B: [[0.748, 0.782, 0.621, 0.556, 0.127, 0.839], [1.697, 1.131, 0.375, -0.273, 1.039, 1.495]]
C: [[0.612, 1.202, 0.708, 0.529, 0.114, 0.821], [1.612, 1.184, 0.198, 0.419, 0.977, 0.647]]
D: [[0.368, 1.181, 0.615, 0.989, 0.028, 1.271], [1.284, 0.726, 0.504, 0.067, 0.905, 1.037]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the speaker in the scene. The camera pose information includes: the rotation matrix: [[-0.283698, -0.38675, 0.877463], [-0.95878, 0.129662, -0.252839], [-0.015988, -0.913024, -0.407593]]; the translation vector: [3.69525, 3.551647, 1.352095], 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: [[1.47, 0.453, 0.894, 0.2, 0.52, 0.291], [1.542, -0.676, 0.862, 0.217, 0.405, 0.289], [-1.666, -1.034, 0.158, 0.332, 0.363, 0.294]]
B: [[1.471, 0.336, 1.375, -0.216, 0.786, 0.736], [1.469, -0.24, 1.152, 0.44, 0.255, 0.196], [-1.84, -1.112, 0.203, 0.586, 0.569, 0.159]]
C: [[1.315, 0.861, 1.294, -0.145, 0.334, 0.615], [1.166, -0.686, 1.016, 0.2, 0.258, 0.346], [-2.029, -1.236, -0.071, 0.818, 0.37, 0.684]]
D: [[1.59, 0.904, 1.331, 0.394, 0.302, 0.781], [1.626, -0.262, 1.266, -0.178, 0.337, 0.326], [-1.34, -1.047, 0.45, -0.149, 0.438, 0.179]]


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: [[-0.857694, 0.203115, -0.472341], [0.513544, 0.293426, -0.806333], [-0.025181, -0.934155, -0.355978]]; the translation vector: [3.161674, 3.662206, 1.335287], 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: [[0.415, 0.474, 0.662, 0.608, 0.318, 0.607], [0.137, 1.366, 0.214, 0.809, 0.687, 0.563], [-0.119, -1.513, 0.412, 0.991, 0.469, 0.436], [0.958, -1.756, 0.374, 0.393, 0.461, 0.273]]
B: [[0.097, 0.337, 0.367, 0.736, 0.669, 0.76], [-0.118, 0.915, 0.406, 0.54, 0.71, 0.78], [0.039, -1.273, 0.366, 0.52, 0.703, 0.787], [0.484, -2.107, 0.393, 0.516, 0.773, 0.731]]
C: [[-0.145, 0.33, 0.215, 0.329, 0.397, 1.235], [-0.041, 1.377, -0.008, 0.173, 0.698, 1.043], [0.354, -0.822, 0.479, 0.306, 0.474, 0.987], [0.885, -2.559, 0.576, 0.548, 1.045, 0.546]]
D: [[-0.062, 0.608, 0.646, 1.11, 1.056, 0.374], [0.266, 1.23, 0.893, 0.95, 0.801, 1.268], [-0.368, -1.641, 0.003, 0.257, 0.709, 0.427], [0.563, -2.189, 0.486, 0.531, 1.025, 0.714]]


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: [[0.199941, 0.263531, -0.943703], [0.979453, -0.027844, 0.19974], [0.026362, -0.964249, -0.263683]]; the translation vector: [3.611549, 3.757055, 1.562045], 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: [[1.3, -0.383, 0.923, -0.356, 3.02, 2.635], [-2.115, 1.383, 0.841, 0.469, 0.927, 1.856], [-0.097, 1.484, 1.187, 3.044, -0.119, 1.807], [-1.377, 2.117, 0.899, -0.033, 1.21, 1.808], [1.159, -1.198, 1.874, 0.555, 0.176, 1.325]]
B: [[1.941, -0.755, 1.598, -0.121, 2.674, 2.518], [-2.423, 1.211, 1.402, 0.192, 0.868, 2.164], [0.169, 1.203, 1.223, 2.673, -0.21, 2.157], [-1.688, 1.565, 0.939, 0.535, 1.926, 1.811], [1.734, -1.649, 1.385, 0.714, 0.109, 1.38]]
C: [[1.696, -0.287, 1.129, 0.119, 2.8, 2.268], [-2.577, 1.535, 1.204, 0.613, 1.32, 2.198], [0.155, 1.133, 1.131, 3.032, 0.104, 2.204], [-1.285, 1.824, 1.154, 0.225, 1.437, 2.219], [1.488, -1.695, 1.419, 0.405, 0.098, 1.172]]
D: [[1.453, -0.695, 1.348, 0.547, 3.272, 2.434], [-2.777, 1.417, 1.534, 1.007, 1.19, 1.834], [-0.034, 0.735, 1.208, 2.75, 0.551, 2.499], [-1.311, 1.97, 1.046, -0.151, 1.928, 1.721], [1.211, -2.136, 1.037, 0.829, -0.033, 1.518]]


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: [[-0.156961, 0.257294, -0.953501], [0.986843, 0.002956, -0.161652], [-0.038773, -0.966329, -0.254373]]; the translation vector: [1.838324, 1.205476, 1.480452], 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: [[2.228, -1.379, 0.968, 0.05, 0.868, 0.876]]
B: [[1.972, -1.363, 0.684, 0.094, 1.002, 1.369]]
C: [[2.421, -1.068, 1.034, 0.177, 1.167, 1.478]]
D: [[2.274, -1.598, 1.168, 0.52, 1.421, 1.228]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the jacket in the scene. The camera pose information includes: the rotation matrix: [[0.999847, -0.004634, 0.01689], [-0.017397, -0.374134, 0.927211], [0.002023, -0.927363, -0.374157]]; the translation vector: [3.310194, 3.16458, 1.506432], 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: [[-0.821, -1.627, 0.918, 0.317, 0.52, -0.34]]
B: [[-1.196, -1.892, 0.539, 0.329, 0.374, 0.146]]
C: [[-1.472, -2.353, 0.745, 0.703, 0.302, -0.352]]
D: [[-1.33, -1.906, 0.911, -0.061, 0.797, -0.104]]


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: [[0.977181, 0.077241, -0.197866], [0.211774, -0.426158, 0.879512], [-0.016388, -0.901345, -0.432791]]; the translation vector: [0.977323, 0.877303, 1.40232], 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: [[1.441, 1.064, 0.78, 0.6, 1.194, 1.759]]
B: [[0.806, 1.175, 0.723, 1.145, 0.857, 1.307]]
C: [[1.47, 1.204, 0.738, 1.161, 1.149, 1.298]]
D: [[1.013, 1.023, 0.774, 0.913, 1.329, 1.578]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the floor in the scene. The camera pose information includes: the rotation matrix: [[-0.30056, -0.511506, 0.805], [-0.953151, 0.130866, -0.272721], [0.034151, -0.849256, -0.526876]]; the translation vector: [-0.281614, 2.924112, 1.306122], 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: [[-1.32, 0.548, 0.015, 3.907, 5.219, 0.432]]
B: [[-0.869, 0.661, -0.307, 3.672, 4.614, -0.069]]
C: [[-0.885, 0.436, 0.066, 3.44, 4.871, 0.305]]
D: [[-1.228, 0.813, -0.025, 3.355, 4.94, 0.54]]


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: [[-0.255196, -0.436856, 0.862573], [-0.966393, 0.143834, -0.213066], [-0.030988, -0.887958, -0.45888]]; the translation vector: [1.734999, 0.744851, 1.432124], 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: [[0.236, 0.438, 2.571, 1.376, 1.585, 0.296]]
B: [[0.105, 0.071, 2.209, 1.375, 1.269, -0.259]]
C: [[-0.082, 0.088, 2.553, 1.257, 1.665, 0.102]]
D: [[-0.566, -0.056, 2.979, 1.134, 1.904, -0.21]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the floor in the scene. The camera pose information includes: the rotation matrix: [[-0.436119, -0.427186, 0.79203], [-0.89981, 0.218659, -0.377532], [-0.011909, -0.877326, -0.479747]]; the translation vector: [1.992302, 3.72193, 1.553249], 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: [[-0.043, 0.444, 0.066, 3.645, 4.94, 0.241]]
B: [[0.071, 0.025, -0.197, 3.897, 4.771, 0.696]]
C: [[-0.523, 0.143, -0.403, 3.288, 4.973, 0.134]]
D: [[0.378, 0.809, 0.444, 3.764, 4.725, 0.036]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the curtain in the scene. The camera pose information includes: the rotation matrix: [[-0.112591, -0.547395, 0.829266], [-0.992672, 0.098819, -0.069547], [-0.043877, -0.83102, -0.55451]]; the translation vector: [1.18498, 1.814175, 1.496605], 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: [[-0.786, -1.469, 1.112, 0.86, 0.176, 1.647]]
B: [[-0.914, -1.825, 1.495, 0.394, 0.281, 2.141]]
C: [[-1.155, -1.563, 0.935, 0.81, 0.246, 1.235]]
D: [[-0.398, -1.079, 1.275, 0.659, -0.007, 1.932]]


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: [[0.645842, -0.099101, 0.757012], [-0.761541, -0.013148, 0.647984], [-0.054263, -0.994991, -0.083961]]; the translation vector: [3.729951, 1.432448, 1.733539], 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: [[0.187, -2.136, 1.49, 0.407, 0.4, 0.612], [0.6, -1.205, 1.939, 0.176, 0.133, -0.205]]
B: [[0.434, -1.704, 1.717, 0.327, 0.549, 0.278], [0.752, -1.616, 1.803, 0.403, 0.362, 0.211]]
C: [[0.158, -1.92, 1.36, -0.055, 0.096, 0.484], [0.44, -1.879, 1.563, 0.594, 0.374, 0.673]]
D: [[-0.017, -1.973, 1.957, -0.127, 0.324, 0.483], [0.88, -1.365, 2.154, 0.664, 0.083, -0.049]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the window in the scene. The camera pose information includes: the rotation matrix: [[0.14018, 0.443083, -0.885453], [0.989985, -0.07783, 0.117782], [-0.016727, -0.893096, -0.449556]]; the translation vector: [3.549726, 0.935059, 1.485921], 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: [[1.798, -1.611, 1.132, 0.285, 0.531, 1.165]]
B: [[1.687, -1.332, 1.2, 0.199, 0.988, 0.799]]
C: [[1.357, -0.901, 1.518, -0.194, 0.606, 1.017]]
D: [[1.876, -1.168, 0.737, 0.277, 1.058, 1.074]]


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: [[0.988959, -0.006087, -0.148062], [0.148117, 0.009943, 0.98892], [-0.004548, -0.999932, 0.010735]]; the translation vector: [3.911582, 2.672538, 1.565046], 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: [[-0.819, -0.006, 0.434, 0.452, 1.821, 0.691], [-2.563, 0.098, 0.464, 0.939, 2.679, 0.721]]
B: [[-1.198, -0.018, -0.225, 0.953, 2.14, 0.57], [-3.038, 0.583, 0.16, 0.212, 2.66, 1.39]]
C: [[-1.115, -0.366, 0.124, 1.037, 1.922, 0.126], [-3.074, 0.098, -0.014, 0.214, 2.71, 0.451]]
D: [[-0.889, -0.312, 0.236, 0.943, 2.266, 0.443], [-3.042, 0.305, 0.458, 0.511, 3.034, 0.927]]


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: [[-0.767458, -0.265442, 0.583565], [-0.640543, 0.35536, -0.680752], [-0.026676, -0.896248, -0.442751]]; the translation vector: [3.343537, 3.697402, 1.375352], 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: [[1.003, 1.71, 2.094, 0.541, 0.263, 0.118], [1.203, 1.68, 0.477, 1.133, 0.414, 1.172]]
B: [[1.233, 1.735, 1.724, 0.591, 0.58, 0.487], [0.701, 1.63, 0.882, 0.862, 0.077, 0.96]]
C: [[0.897, 1.469, 2.006, 0.732, 0.251, 0.23], [0.896, 1.321, 0.509, 1.078, 0.563, 0.956]]
D: [[1.067, 1.911, 1.889, 0.58, 0.392, -0.26], [1.382, 1.503, 0.381, 1.083, 0.31, 0.478]]


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: [[-0.311411, -0.45253, 0.835607], [-0.948656, 0.199362, -0.245576], [-0.055457, -0.869179, -0.491379]]; the translation vector: [2.299133, 2.388773, 1.459468], 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: [[1.138, 0.124, 0.676, -0.24, 4.388, 1.6], [-0.991, 0.479, 1.092, 0.412, 4.521, 1.772], [0.357, 1.729, 0.48, 2.481, 0.664, 1.17]]
B: [[1.22, 0.284, 0.605, 0.161, 4.409, 2.133], [-1.442, 0.481, 1.313, -0.024, 4.063, 1.777], [-0.203, 2.498, 0.224, 1.968, 0.299, 1.17]]
C: [[0.938, 0.113, 0.929, -0.179, 3.724, 1.454], [-0.685, 0.25, 0.853, -0.017, 3.941, 2.536], [-0.076, 2.502, 0.394, 2.11, -0.271, 0.712]]
D: [[1.264, 0.297, 0.846, 0.212, 3.931, 1.71], [-1.088, 0.197, 1.004, 0.293, 4.063, 2.062], [0.059, 2.138, 0.489, 2.4, 0.176, 0.937]]


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: [[-0.305635, -0.390507, 0.868385], [-0.952144, 0.122302, -0.280116], [0.003183, -0.91244, -0.409198]]; the translation vector: [4.266061, 1.773856, 1.285079], 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: [[-1.286, 0.023, 0.43, 0.149, 0.955, 0.837], [-1.223, 1.506, 0.654, 0.172, 1.002, 1.099]]
B: [[-1.716, 0.263, -0.049, 0.591, 1.354, 0.711], [-1.546, 1.706, 0.156, 0.078, 0.869, 0.807]]
C: [[-0.94, -0.207, 0.36, 0.417, 1.226, 0.947], [-1.061, 1.683, 0.653, 0.491, 0.617, 1.297]]
D: [[-1.505, -0.176, 0.438, -0.283, 0.675, 1.3], [-1.566, 1.679, 1.013, -0.274, 0.726, 0.998]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the floor in the scene. The camera pose information includes: the rotation matrix: [[-0.934582, -0.143102, 0.325696], [-0.355737, 0.383069, -0.852473], [-0.002774, -0.912568, -0.408916]]; the translation vector: [2.694367, 2.483235, 1.465763], 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: [[-0.301, -0.248, -0.183, 3.399, 5.209, 0.282]]
B: [[0.089, -0.015, -0.009, 3.337, 5.518, 0.258]]
C: [[0.396, -0.159, 0.362, 3.257, 5.951, -0.2]]
D: [[0.093, 0.115, -0.474, 3.284, 5.168, 0.122]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the cabinet in the scene. The camera pose information includes: the rotation matrix: [[-0.928375, -0.17783, 0.326339], [-0.371449, 0.415395, -0.830345], [0.012101, -0.892089, -0.451697]]; the translation vector: [2.096006, 1.919092, 1.36174], 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: [[-0.264, 0.68, 0.463, 0.725, 0.55, 0.967], [1.225, 0.142, 2.156, 0.68, 2.62, 0.669]]
B: [[0.179, 0.182, 0.661, 0.23, 1.022, 0.617], [1.51, -0.031, 1.909, 0.955, 2.219, 0.647]]
C: [[0.069, 0.653, 0.766, 0.622, 0.263, 0.911], [0.908, 0.073, 1.898, 0.615, 2.442, 0.579]]
D: [[-0.094, 1.133, 0.833, 0.562, 0.551, 0.493], [1.073, 0.074, 2.645, 0.407, 2.814, 0.994]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the books in the scene. The camera pose information includes: the rotation matrix: [[0.725417, 0.297171, -0.620854], [0.687848, -0.279954, 0.669695], [0.025203, -0.912861, -0.407492]]; the translation vector: [3.434752, 3.057745, 1.556519], 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: [[-1.718, -0.44, 1.96, 0.228, 0.897, 0.293], [-1.706, -1.293, 1.868, 0.22, 0.846, 0.362], [-1.707, -1.314, 0.762, 0.375, 0.826, 0.302], [-1.691, 1.543, 1.626, 0.337, 0.697, 0.437], [-1.573, 1.406, 1.291, 0.181, 0.564, 0.313]]
B: [[-1.988, -0.706, 1.585, 0.615, 0.861, 0.547], [-1.403, -1.309, 1.785, -0.129, 1.049, -0.092], [-1.749, -1.25, 0.92, 0.869, 1.088, 0.428], [-1.92, 1.941, 1.694, 0.669, 1.107, 0.403], [-1.483, 1.056, 1.615, 0.417, 0.387, 0.739]]
C: [[-1.546, -0.182, 1.499, 0.527, 1.029, 0.605], [-1.401, -1.244, 2.308, -0.222, 0.467, 0.206], [-2.193, -1.361, 0.929, 0.133, 0.525, 0.091], [-1.321, 1.865, 1.781, -0.053, 0.666, 0.358], [-1.503, 1.488, 1.689, 0.165, 0.203, 0.17]]
D: [[-1.94, -0.345, 2.215, 0.028, 0.642, 0.092], [-2.035, -1.654, 1.937, 0.612, 1.134, -0.102], [-1.249, -1.385, 0.367, 0.613, 1.003, 0.682], [-2.01, 1.507, 1.513, 0.614, 0.573, 0.003], [-1.183, 1.016, 0.985, -0.012, 0.86, 0.417]]


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: [[0.205292, 0.226186, -0.952205], [0.97316, -0.150555, 0.174048], [-0.103992, -0.962379, -0.251024]]; the translation vector: [4.876985, 2.837537, 1.671042], 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: [[-2.266, 0.688, 1.427, 0.645, 4.144, 1.891], [1.793, 0.377, 0.356, 0.744, 3.81, 1.61], [-0.941, -1.334, 0.579, 2.335, 0.039, 1.673], [0.362, -1.428, 0.335, 0.484, 0.146, 1.101], [0.403, -1.616, 0.92, 1.722, 0.842, 1.057], [1.194, 3.045, 0.588, 0.013, 0.929, 1.121], [1.761, 2.38, 0.509, 0.767, -0.159, 0.975]]
B: [[-2.307, 0.099, 1.206, 0.234, 3.804, 1.593], [2.401, 0.098, 0.732, 0.485, 3.642, 1.662], [-1.38, -1.427, 1.26, 2.485, 0.117, 1.419], [0.047, -1.412, 0.542, 0.454, 0.56, 1.109], [0.451, -2.029, 0.885, 1.313, 0.841, 0.961], [1.821, 2.284, 0.965, -0.181, 0.842, 1.118], [1.675, 2.553, 0.956, 0.491, 0.104, 1.591]]
C: [[-1.548, 0.69, 1.589, 0.293, 3.816, 1.624], [2.411, 0.459, 0.334, 0.543, 4.513, 1.336], [-0.832, -2.051, 0.999, 1.925, 0.593, 1.075], [-0.217, -1.618, 0.815, -0.295, 0.494, 0.985], [1.068, -1.834, 1.273, 1.646, 0.657, 0.959], [1.898, 2.458, 0.543, 0.44, 1.518, 1.452], [2.071, 1.877, 0.293, 1.12, 0.358, 1.716]]
D: [[-1.964, 0.397, 1.135, 0.305, 4.04, 1.813], [2.143, 0.114, 0.673, 0.413, 4.08, 1.439], [-0.926, -1.676, 0.892, 2.284, 0.231, 1.529], [0.195, -1.875, 0.811, 0.153, 0.424, 1.364], [0.78, -1.998, 0.788, 1.226, 0.36, 1.309], [1.439, 2.685, 0.692, 0.249, 1.216, 1.435], [1.802, 2.098, 0.616, 0.629, 0.105, 1.315]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the ottoman in the scene. The camera pose information includes: the rotation matrix: [[0.133825, -0.39571, 0.908573], [-0.990975, -0.046263, 0.125813], [-0.007752, -0.91721, -0.398329]]; the translation vector: [4.990516, 4.227292, 1.32289], 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: [[0.121, -0.501, -0.221, 0.439, 0.387, 0.089], [1.109, -1.077, -0.06, 0.221, 0.081, 0.556]]
B: [[-0.019, -0.497, 0.389, 1.016, 0.944, 0.39], [1.279, -1.542, -0.239, 0.195, 0.216, 0.872]]
C: [[0.21, -0.049, -0.032, 0.947, 0.552, 0.204], [0.617, -0.987, 0.392, 0.284, 0.553, 0.828]]
D: [[0.392, -0.219, 0.176, 0.595, 0.63, 0.481], [0.882, -1.099, 0.197, 0.524, 0.524, 0.466]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the book in the scene. The camera pose information includes: the rotation matrix: [[0.999403, 0.004498, 0.03425], [-0.034232, -0.004158, 0.999405], [0.004638, -0.999981, -0.004001]]; the translation vector: [2.393484, 5.775056, 1.371464], 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: [[0.923, 3.072, 1.641, 0.406, 0.224, 0.224], [0.852, 2.684, 1.628, 0.411, 0.369, 0.342], [0.952, 2.353, 1.591, 0.332, 0.315, 0.303], [0.919, 1.934, 1.549, 0.278, 0.356, 0.3], [0.991, 1.596, 1.521, 0.302, 0.285, 0.248], [1.083, 1.197, 1.51, 0.2, 0.428, 0.292], [1.067, 0.874, 1.479, 0.258, 0.387, 0.349], [1.029, 0.682, 1.414, 0.27, 0.238, 0.229], [1.041, 0.446, 1.386, 0.31, 0.355, 0.267], [1.007, 0.119, 1.367, 0.313, 0.297, 0.251], [1.072, -0.152, 1.331, 0.368, 0.301, 0.196], [0.978, -0.542, 1.366, 0.293, 0.411, 0.344], [1.038, -0.846, 1.349, 0.398, 0.352, 0.371], [0.995, -1.285, 1.277, 0.273, 0.319, 0.287], [1.051, -1.623, 1.317, 0.372, 0.433, 0.346], [1.016, -1.909, 1.267, 0.375, 0.379, 0.355], [1.01, -2.206, 1.239, 0.32, 0.305, 0.33], [1.021, -2.389, 1.248, 0.292, 0.375, 0.256], [0.945, -2.669, 1.168, 0.312, 0.307, 0.249], [0.986, -2.904, 1.157, 0.265, 0.331, 0.203]]
B: [[1.16, 2.801, 1.566, 0.581, 0.486, -0.268], [0.756, 2.458, 1.347, -0.04, 0.522, 0.189], [0.535, 2.032, 1.866, 0.051, 0.318, 0.012], [0.896, 2.321, 1.823, -0.143, 0.711, 0.696], [1.3, 1.485, 1.216, 0.089, 0.474, 0.726], [1.333, 1.63, 1.281, 0.587, 0.639, -0.131], [1.034, 0.752, 1.496, 0.694, 0.45, 0.002], [1.132, 0.488, 1.903, -0.121, -0.068, 0.586], [1.244, 0.056, 1.06, 0.343, 0.366, 0.492], [0.523, 0.369, 1.091, 0.036, 0.297, 0.341], [0.945, -0.379, 1.231, -0.009, 0.698, 0.282], [0.742, -0.538, 1.804, 0.143, 0.887, 0.377], [1.245, -0.568, 1.71, 0.143, 0.603, 0.41], [1.356, -0.879, 1.397, 0.576, 0.048, 0.554], [1.47, -2.036, 1.112, 0.54, 0.795, 0.096], [1.472, -1.52, 0.829, 0.648, 0.598, 0.49], [0.775, -2.633, 1.506, -0.16, -0.139, -0.099], [0.838, -2.702, 1.211, 0.137, 0.331, -0.011], [1.261, -2.818, 1.474, 0.679, -0.005, 0.352], [0.793, -2.949, 1.566, -0.008, 0.477, 0.693]]
C: [[1.056, 2.871, 1.196, 0.82, -0.168, 0.476], [1.086, 3.168, 1.177, -0.05, 0.768, 0.624], [1.078, 2.314, 1.991, 0.481, -0.014, 0.382], [0.899, 1.855, 1.409, -0.073, 0.065, 0.078], [0.796, 1.846, 1.026, -0.008, 0.461, 0.294], [0.96, 0.751, 1.316, 0.52, 0.805, 0.752], [1.18, 1.031, 1.766, 0.673, 0.119, 0.034], [1.398, 0.505, 1.118, -0.168, 0.16, -0.249], [0.838, 0.65, 1.392, 0.173, 0.458, 0.332], [1.111, -0.328, 1.396, 0.558, 0.481, 0.366], [0.597, -0.355, 1.146, 0.623, 0.368, 0.632], [0.691, -0.514, 1.338, -0.157, 0.304, -0.124], [0.696, -1.125, 1.476, 0.501, 0.757, 0.356], [0.907, -0.859, 1.385, 0.656, 0.571, -0.029], [1.035, -1.127, 1.219, 0.093, 0.841, 0.704], [0.635, -1.763, 1.501, -0.076, -0.097, 0.162], [0.614, -1.848, 1.062, 0.328, 0.483, 0.674], [0.692, -2.453, 1.556, 0.665, 0.718, 0.625], [1.074, -2.937, 1.026, 0.776, 0.224, 0.639], [0.852, -3.222, 1.01, 0.571, -0.139, 0.12]]
D: [[1.022, 3.318, 1.189, 0.205, -0.146, 0.042], [0.815, 2.622, 1.239, 0.213, 0.653, 0.265], [1.051, 2.623, 1.858, 0.743, -0.174, 0.425], [1.36, 1.47, 1.216, -0.071, -0.098, -0.074], [1.312, 2.017, 2.002, -0.015, 0.439, 0.124], [0.798, 1.663, 1.184, 0.218, 0.773, 0.512], [1.438, 0.663, 1.321, 0.334, 0.497, 0.799], [1.496, 1.067, 1.009, 0.492, 0.69, -0.197], [0.673, 0.916, 1.137, 0.692, -0.115, 0.537], [0.588, 0.319, 1.507, 0.723, 0.486, 0.106], [0.938, -0.596, 1.384, 0.378, 0.487, -0.284], [0.718, -0.867, 0.941, 0.405, 0.388, -0.074], [1.365, -0.417, 1.613, 0.897, 0.508, -0.003], [1.124, -1.228, 1.16, 0.374, 0.651, 0.692], [0.872, -1.666, 1.25, 0.857, 0.612, -0.1], [0.693, -1.777, 1.038, 0.754, 0.733, 0.072], [1.133, -1.714, 1.626, 0.475, -0.192, 0.478], [1.392, -2.804, 1.671, -0.124, 0.18, 0.524], [1.024, -2.671, 1.235, 0.602, 0.29, 0.162], [0.636, -2.621, 1.52, -0.11, 0.64, 0.18]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the rail in the scene. The camera pose information includes: the rotation matrix: [[0.631332, 0.312126, -0.709927], [0.775472, -0.26347, 0.573784], [-0.007951, -0.912776, -0.408382]]; the translation vector: [1.600176, 0.624978, 1.327739], 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: [[0.127, 1.263, 0.842, 1.099, 0.165, 0.151], [0.899, 0.349, 0.833, 0.078, 0.633, 0.087]]
B: [[-0.285, 1.099, 0.515, 1.523, 0.256, -0.319], [0.56, 0.838, 0.875, -0.327, 0.985, 0.228]]
C: [[0.446, 1.442, 1.259, 1.427, 0.331, 0.006], [0.446, 0.556, 0.643, 0.276, 0.563, -0.341]]
D: [[-0.356, 1.631, 0.612, 0.864, 0.511, -0.226], [0.523, 0.674, 0.57, 0.567, 0.594, 0.019]]


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: [[-0.386761, -0.304254, 0.870543], [-0.920043, 0.191539, -0.34181], [-0.062746, -0.933136, -0.354007]]; the translation vector: [2.082368, 4.008438, 1.845888], 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: [[0.787, 2.876, 1.457, 2.063, -0.079, 1.518], [-0.953, 1.998, 0.997, 0.069, 3.579, 2.369], [0.693, -0.876, 1.265, 0.33, 4.219, 2.072], [0.345, -2.632, 0.88, 1.928, -0.067, 1.565], [-0.455, -2.068, 1.068, 0.08, 1.617, 2.382], [-0.899, -1.196, 0.623, 0.651, 0.095, 2.066]]
B: [[0.116, 3.687, 0.955, 2.711, 0.51, 1.785], [-0.801, 1.888, 0.628, 0.573, 3.732, 2.205], [1.093, -0.187, 0.521, -0.148, 5.045, 2.538], [0.42, -2.481, 1.79, 1.307, 0.36, 0.947], [-0.514, -1.855, 0.567, 0.468, 1.76, 1.511], [-1.181, -1.155, 0.753, 0.267, -0.268, 1.847]]
C: [[0.302, 3.207, 1.219, 2.255, 0.306, 1.414], [-0.871, 1.59, 0.966, 0.239, 3.492, 2.066], [0.732, -0.454, 0.961, 0.242, 4.576, 2.069], [-0.078, -2.664, 1.355, 1.624, 0.192, 1.303], [-0.886, -1.849, 0.913, 0.175, 1.703, 1.972], [-1.091, -1.016, 0.816, 0.518, 0.228, 1.826]]
D: [[0.349, 2.764, 1.178, 2.112, -0.17, 1.603], [-1.032, 1.356, 0.914, 0.415, 3.877, 2.097], [0.285, -0.798, 1.205, 0.303, 4.409, 2.223], [-0.233, -2.574, 1.577, 1.241, 0.359, 1.513], [-1.059, -2.05, 1.259, 0.503, 1.807, 1.753], [-1.108, -1.393, 0.584, 0.052, -0.001, 1.469]]


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: [[-0.565317, -0.50256, 0.654103], [-0.824719, 0.328974, -0.460017], [0.016003, -0.799506, -0.600445]]; the translation vector: [4.07549, 5.065369, 1.281872], 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: [[-2.506, 0.209, 0.255, 0.924, 1.928, 0.478], [0.463, -1.087, 0.626, 1.179, 0.62, 0.996], [2.049, 0.799, -0.061, 0.618, 1.041, 1.191]]
B: [[-2.054, 0.6, 0.688, 1.044, 1.508, 0.567], [0.964, -1.042, 0.495, 1.122, 0.573, 0.421], [2.453, 0.513, 0.739, 0.463, 1.578, 0.424]]
C: [[-2.686, -0.003, 0.374, 0.562, 1.486, 0.489], [1.084, -0.733, 0.31, 1.073, 1.131, 0.967], [1.7, 0.788, 0.091, 0.433, 1.461, 1.21]]
D: [[-2.225, 0.184, 0.565, 0.652, 1.867, 0.966], [0.89, -0.986, 0.428, 1.537, 0.782, 0.844], [2.106, 0.485, 0.423, 0.73, 1.476, 0.84]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the water bottle in the scene. The camera pose information includes: the rotation matrix: [[0.684823, -0.326379, 0.651532], [-0.728707, -0.304485, 0.613413], [-0.001823, -0.894855, -0.446353]]; the translation vector: [2.86358, 2.414664, 1.549631], 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: [[-0.787, -0.535, 0.927, 0.017, -0.194, -0.206]]
B: [[-1.049, -0.444, 0.739, 0.127, 0.097, 0.179]]
C: [[-1.148, -0.307, 0.649, -0.194, 0.004, 0.501]]
D: [[-1.423, -0.784, 0.923, 0.285, 0.539, 0.33]]


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: [[0.935902, 0.160482, -0.313582], [0.351212, -0.493772, 0.795512], [-0.027173, -0.854655, -0.518485]]; the translation vector: [4.465, -0.226232, 1.550028], 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: [[-0.125, -0.371, 0.52, 0.921, 0.949, 1.032], [-0.05, 0.47, 0.51, 0.929, 1.055, 1.018]]
B: [[-0.03, 0.021, 0.629, 1.294, 0.744, 0.853], [0.141, 0.523, 0.057, 0.461, 0.601, 1.102]]
C: [[-0.027, -0.543, 0.255, 1.392, 0.459, 1.351], [-0.542, 0.241, 0.854, 1.099, 1.281, 1.01]]
D: [[-0.353, -0.617, 0.621, 0.568, 1.229, 1.321], [-0.327, 0.58, 0.56, 0.835, 0.644, 0.683]]


Question: Given a RGB image and a depth image, please detect the 3D bounding box of the dresser in the scene. The camera pose information includes: the rotation matrix: [[0.993306, 0.029023, -0.111812], [0.110831, -0.512349, 0.851596], [-0.032571, -0.858287, -0.512136]]; the translation vector: [2.482234, 1.391135, 1.348064], 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: [[-1.113, 1.152, 0.299, 1.212, 0.824, 1.479], [-0.739, -1.761, 0.838, 1.759, 0.908, 0.436]]
B: [[-1.686, 0.962, 0.402, 1.418, 0.984, 0.915], [-0.524, -1.303, 0.377, 1.429, 0.342, 0.995]]
C: [[-1.37, 1.148, 0.616, 1.114, 0.537, 1.159], [-0.283, -1.543, 0.412, 1.531, 0.506, 0.887]]
D: [[-1.358, 1.603, 0.665, 1.495, 0.045, 1.488], [0.077, -1.171, 0.113, 1.245, 0.683, 1.338]]


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: [[-0.32152, -0.4706, 0.821681], [-0.946681, 0.178549, -0.268172], [-0.020508, -0.864092, -0.502915]]; the translation vector: [2.120097, 2.367636, 1.494245], 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: [[1.429, 0.564, 1.259, 0.514, 4.432, 2.586], [-1.998, 0.309, 1.385, 0.292, 3.896, 2.792], [0.693, 2.704, 1.079, 1.949, 0.124, 2.2]]
B: [[1.111, 0.098, 1.082, 0.466, 4.575, 2.917], [-1.93, 0.083, 1.425, -0.025, 4.078, 2.389], [0.372, 3.074, 1.309, 1.613, 0.349, 2.653]]
C: [[1.746, 0.141, 1.259, 0.14, 4.199, 2.418], [-1.8, 0.062, 1.744, -0.163, 3.558, 2.447], [0.931, 3.17, 1.18, 1.489, -0.095, 2.336]]
D: [[1.116, 0.433, 1.412, 0.515, 4.324, 2.69], [-1.509, 0.174, 1.744, -0.053, 3.532, 2.532], [0.744, 2.248, 0.965, 1.964, 0.231, 1.764]]