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Title: GitHub - facebookresearch/SparseConvNet: Submanifold sparse convolutional networks

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Description: Submanifold sparse convolutional networks. Contribute to facebookresearch/SparseConvNet development by creating an account on GitHub.

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https://patch-diff.githubusercontent.com/facebookresearch/SparseConvNet#submanifold-sparse-convolutional-networks
https://opensource.fb.com/support-ukraine
https://patch-diff.githubusercontent.com/facebookresearch/SparseConvNet#spatial-sparsity
Spatially-sparse convolutional networkshttps://github.com/btgraham/SparseConvNet
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https://patch-diff.githubusercontent.com/facebookresearch/SparseConvNet#dimensionality-and-submanifolds
Sparse 3D convolutional neural networkshttp://arxiv.org/abs/1505.02890
https://patch-diff.githubusercontent.com/facebookresearch/SparseConvNet#hello-world
defining a function that inherits from torch.nn.Modulehttps://patch-diff.githubusercontent.com/facebookresearch/SparseConvNet/blob/main/examples/Assamese_handwriting/VGGplus.py
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https://patch-diff.githubusercontent.com/facebookresearch/SparseConvNet#examples
Assamese handwriting recognitionhttps://archive.ics.uci.edu/ml/datasets/Online+Handwritten+Assamese+Characters+Dataset
Chinese handwriting for recognitionhttp://www.nlpr.ia.ac.cn/databases/handwriting/Online_database.html
3D Segmentationhttps://shapenet.cs.stanford.edu/iccv17/
ScanNethttp://www.scan-net.org/
https://patch-diff.githubusercontent.com/facebookresearch/SparseConvNet#setup
Condahttps://www.anaconda.com/
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https://patch-diff.githubusercontent.com/facebookresearch/SparseConvNet#links
ICDAR 2013 Chinese Handwriting Recognition Competition 2013https://web.archive.org/web/20160418143451/http://www.nlpr.ia.ac.cn/events/CHRcompetition2013/competition/Home.html
Reporthttps://web.archive.org/web/20160910012723/http://www.nlpr.ia.ac.cn/events/CHRcompetition2013/competition/ICDAR%202013%20CHR%20competition.pdf
Spatially-sparse convolutional neural networks, 2014http://arxiv.org/abs/1409.6070
Fractional max-pooling, 2014http://arxiv.org/abs/1412.6071
Sparse 3D convolutional neural networks, BMVC 2015http://arxiv.org/abs/1505.02890
Kaggle plankton recognition competition, 2015https://www.kaggle.com/c/datasciencebowl
EcoTaxahttp://ecotaxa.obs-vlfr.fr/
Kaggle Diabetic Retinopathy Detection, 2015https://www.kaggle.com/c/diabetic-retinopathy-detection/
SparseConvNet 'classic'https://github.com/btgraham/SparseConvNet-archived
Submanifold Sparse Convolutional Networks, 2017https://arxiv.org/abs/1706.01307
Workshop on Learning to See from 3D Data, 2017https://shapenet.cs.stanford.edu/iccv17workshop/
semantic segmentationhttps://shapenet.cs.stanford.edu/iccv17/
Reporthttps://arxiv.org/pdf/1710.06104
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks, 2017https://arxiv.org/abs/1711.10275
Unsupervised learning with sparse space-and-time autoencodershttps://arxiv.org/abs/1811.10355
ScanNet 3D semantic label benchmark 2018http://kaldir.vc.in.tum.de/scannet_benchmark/semantic_label_3d
MinkowskiEnginehttps://github.com/StanfordVL/MinkowskiEngine
0.736 average IOU for ScanNethttps://github.com/chrischoy/SpatioTemporalSegmentation
SpConv: PyTorch Spatially Sparse Convolution Libraryhttps://github.com/traveller59/spconv
Live Semantic 3D Perception for Immersive Augmented Realityhttps://ieeexplore.ieee.org/document/8998140
OccuSeghttps://arxiv.org/abs/2003.06537
TorchSparsehttps://github.com/mit-han-lab/torchsparse
TensorFlow 3Dhttps://github.com/google-research/google-research/tree/master/tf3d
VoTrhttps://github.com/PointsCoder/VOTR
voxel transformershttps://openaccess.thecvf.com/content/ICCV2021/papers/Mao_Voxel_Transformer_for_3D_Object_Detection_ICCV_2021_paper.pdf
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MixUphttps://openreview.net/forum?id=r1Ddp1-Rb
Point Transformer V3https://arxiv.org/abs/2312.10035
https://patch-diff.githubusercontent.com/facebookresearch/SparseConvNet#citations
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks, CVPR 2018https://arxiv.org/abs/1711.10275
Benjamin Grahamhttps://research.fb.com/people/graham-benjamin/
Martin Engelckehttp://ori.ox.ac.uk/mrg_people/martin-engelcke/
Laurens van der Maatenhttps://lvdmaaten.github.io/
Submanifold Sparse Convolutional Networks, https://arxiv.org/abs/1706.01307https://arxiv.org/abs/1706.01307
Benjamin Grahamhttps://research.fb.com/people/graham-benjamin/
Laurens van der Maatenhttps://lvdmaaten.github.io/
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