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Self-attention networks have revolutionized natural language processing and are making impressive strides in image analysis tasks such as image classification and object detection.
Voxnet: A 3d convolutional neural network for real-time object recognition
Daniel Maturana and Sebastian Scherer · 2015
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Multi-view convolutional neural networks for 3d shape recognition
Hang Su, Subhransu Maji, Evangelos Kalogerakis, and Erik G. Learned-Miller · 2015
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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3D semantic parsing of large-scale indoor spaces
Iro Armeni, Ozan Sener, Amir R. Zamir, Helen Jiang, Ioannis Brilakis, Martin Fischer, and Silvio Savarese · 2016
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Vehicle detection from 3d lidar using fully convolutional network
Bo Li, Tianlei Zhang, and Tian Xia · 2016
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Volumetric and multi-view cnns for object classification on 3d data
Charles Ruizhongtai Qi, Hao Su, Matthias Nießner, Angela Dai, Mengyuan Yan, and Leonidas Guibas · 2016
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A scalable active framework for region annotation in 3d shape collections
Li Yi, Vladimir G Kim, Duygu Ceylan, I-Chao Shen, Mengyan Yan, Hao Su, Cewu Lu, Qixing Huang, Alla Sheffer, and Leonidas Guibas · 2016
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Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles Ruizhongtai Qi, Hao Su, Kaichun Mo, and Leonidas J. Guibas · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J. Guibas · 2017
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Octnet: Learning deep 3d representations at high resolutions
Gernot Riegler, Ali Osman Ulusoy, and Andreas Geiger · 2017
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Dynamic edge-conditioned filters in convolutional neural networks on graphs
Martin Simonovsky and Nikos Komodakis · 2017
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Semantic scene completion from a single depth image
Shuran Song, Fisher Yu, Andy Zeng, Angel X Chang, Manolis Savva, and Thomas Funkhouser · 2017
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Segcloud: Semantic segmentation of 3d point clouds
Lyne P. Tchapmi, Christopher B. Choy, Iro Armeni, JunYoung Gwak, and Silvio Savarese · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Learning so (3) equivariant representations with spherical cnns
Carlos Esteves, Christine Allen-Blanchette, Ameesh Makadia, and Kostas Daniilidis · 2018
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3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens Van Der Maaten · 2018
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Recurrent slice networks for 3d segmentation of point clouds
Qiangui Huang, Weiyue Wang, and Ulrich Neumann · 2018
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Rotationnet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints
Asako Kanezaki, Yasuyuki Matsushita, and Yoshifumi Nishida · 2018
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Large-scale point cloud semantic segmentation with superpoint graphs
Loic Landrieu and Martin Simonovsky · 2018
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Pointcnn: Convolution on
Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 2018
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Mining point cloud local structures by kernel correlation and graph pooling
Yiru Shen, Chen Feng, Yaoqing Yang, and Dong Tian · 2018
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Splatnet: Sparse lattice networks for point cloud processing
Hang Su, Varun Jampani, Deqing Sun, Subhransu Maji, Evangelos Kalogerakis, Ming-Hsuan Yang, and Jan Kautz · 2018
Cited alongside, same era.
Tangent convolutions for dense prediction in 3d
Maxim Tatarchenko, Jaesik Park, Vladlen Koltun, and Qian-Yi Zhou · 2018
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Local spectral graph convolution for point set feature learning
Chu Wang, Babak Samari, and Kaleem Siddiqi · 2018
Deepgcns: Can gcns go as deep as cnns?
Guohao Li, Matthias Muller, Ali Thabet, and Bernard Ghanem · 2019
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Point2sequence: Learning the shape representation of 3d point clouds with an attention-based sequence to sequence network
Xinhai Liu, Zhizhong Han, Yu-Shen Liu, and Matthias Zwicker · 2019
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Interpolated convolutional networks for 3d point cloud understanding
Jiageng Mao, Xiaogang Wang, and Hongsheng Li · 2019
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PyTorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Stand-alone self-attention in vision models
Prajit Ramachandran, Niki Parmar, Ashish Vaswani, Irwan Bello, Anselm Levskaya, and Jonathon Shlens · 2019
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Cited alongside, same era.
Deep parametric continuous convolutional neural networks
Shenlong Wang, Simon Suo, Wei-Chiu Ma, Andrei Pokrovsky, and Raquel Urtasun · 2018
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Sgpn: Similarity group proposal network for 3d point cloud instance segmentation
Weiyue Wang, Ronald Yu, Qiangui Huang, and Ulrich Neumann · 2018
Cited alongside, same era.
Attentional shapecontextnet for point cloud recognition
Saining Xie, Sainan Liu, Zeyu Chen, and Zhuowen Tu · 2018
Cited alongside, same era.
Spidercnn: Deep learning on point sets with parameterized convolutional filters
Yifan Xu, Tianqi Fan, Mingye Xu, Long Zeng, and Yu Qiao · 2018
Cited alongside, same era.
4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Choy, JunYoung Gwak, and Silvio Savarese · 2019
Cited alongside, same era.
Transformer-XL: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc V. Le, and Ruslan Salakhutdinov · 2019
Cited alongside, same era.
Hugues Thomas, Charles R Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui, François Goulette, and Leonidas J Guibas · 2019
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Graph attention convolution for point cloud semantic segmentation
Lei Wang, Yuchun Huang, Yaolin Hou, Shenman Zhang, and Jie Shan · 2019
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Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, and Justin M. Solomon · 2019
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Pay less attention with lightweight and dynamic convolutions
Felix Wu, Angela Fan, Alexei Baevski, Yann N Dauphin, and Michael Auli · 2019
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Pointconv: Deep convolutional networks on 3d point clouds
Wenxuan Wu, Zhongang Qi, and Li Fuxin · 2019
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Modeling point clouds with self-attention and gumbel subset sampling
Jiancheng Yang, Qiang Zhang, Bingbing Ni, Linguo Li, Jinxian Liu, Mengdie Zhou, and Qi Tian · 2019
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XLNet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, and Quoc V. Le · 2019
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Shellnet: Efficient point cloud convolutional neural networks using concentric shells statistics
Zhiyuan Zhang, Binh-Son Hua, and Sai-Kit Yeung · 2019
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PointWeb: Enhancing local neighborhood features for point cloud processing
Hengshuang Zhao, Li Jiang, Chi-Wing Fu, and Jiaya Jia · 2019
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Randla-net: Efficient semantic segmentation of large-scale point clouds
Qingyong Hu, Bo Yang, Linhai Xie, Stefano Rosa, Yulan Guo, Zhihua Wang, Niki Trigoni, and Andrew Markham · 2020
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Lagrangian fluid simulation with continuous convolutions
Benjamin Ummenhofer, Lukas Prantl, Nils Thuerey, and Vladlen Koltun · 2020
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Exploring self-attention for image recognition
Hengshuang Zhao, Jiaya Jia, and Vladlen Koltun · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2021
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