@@ -140,9 +140,12 @@ SparseConvNet is BSD licensed, as found in the LICENSE file. [Terms of use](http
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@@ -140,9 +140,12 @@ SparseConvNet is BSD licensed, as found in the LICENSE file. [Terms of use](http
7.[Submanifold Sparse Convolutional Networks, 2017](https://arxiv.org/abs/1706.01307) Introduces deep 'submanifold' SparseConvNets.
7.[Submanifold Sparse Convolutional Networks, 2017](https://arxiv.org/abs/1706.01307) Introduces deep 'submanifold' SparseConvNets.
8.[Workshop on Learning to See from 3D Data, 2017](https://shapenet.cs.stanford.edu/iccv17workshop/) First place in the [semantic segmentation](https://shapenet.cs.stanford.edu/iccv17/) competition. [Report](https://arxiv.org/pdf/1710.06104)
8.[Workshop on Learning to See from 3D Data, 2017](https://shapenet.cs.stanford.edu/iccv17workshop/) First place in the [semantic segmentation](https://shapenet.cs.stanford.edu/iccv17/) competition. [Report](https://arxiv.org/pdf/1710.06104)
9.[3D Semantic Segmentation with Submanifold Sparse Convolutional Networks, 2017](https://arxiv.org/abs/1711.10275) Semantic segmentation for the ShapeNet Core55 and NYU-DepthV2 datasets, CVPR 2018
9.[3D Semantic Segmentation with Submanifold Sparse Convolutional Networks, 2017](https://arxiv.org/abs/1711.10275) Semantic segmentation for the ShapeNet Core55 and NYU-DepthV2 datasets, CVPR 2018
10.[ScanNet 3D semantic label benchmark 2018](http://kaldir.vc.in.tum.de/scannet_benchmark/semantic_label_3d) 0.726 average IOU.
10.[Unsupervised learning with sparse space-and-time autoencoders](https://arxiv.org/abs/1811.10355)(3+1)D space-time autoencoders
11.[MinkowskiEngine](https://github.com/StanfordVL/MinkowskiEngine) is an alternative implementation of SparseConvNet.
11.[ScanNet 3D semantic label benchmark 2018](http://kaldir.vc.in.tum.de/scannet_benchmark/semantic_label_3d) 0.726 average IOU.
12.[OccuSeg](https://arxiv.org/abs/2003.06537) object detection using SparseConvNets
12.[MinkowskiEngine](https://github.com/StanfordVL/MinkowskiEngine) is an alternative implementation of SparseConvNet; [0.736 average IOU for ScanNet](https://github.com/chrischoy/SpatioTemporalSegmentation).
13.[SpConv: PyTorch Spatially Sparse Convolution Library](https://github.com/traveller59/spconv) is an alternative implementation of SparseConvNet.
14.[Live Semantic 3D Perception for Immersive Augmented Reality](https://ieeexplore.ieee.org/document/8998140) describes a way to optimize memory access for SparseConvNet.
15.[OccuSeg](https://arxiv.org/abs/2003.06537) real-time object detection using SparseConvNets.
