├── .gitattributes ├── LICENSE └── README.md /.gitattributes: -------------------------------------------------------------------------------- 1 | # Auto detect text files and perform LF normalization 2 | * text=auto 3 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | This is free and unencumbered software released into the public domain. 2 | 3 | Anyone is free to copy, modify, publish, use, compile, sell, or 4 | distribute this software, either in source code form or as a compiled 5 | binary, for any purpose, commercial or non-commercial, and by any 6 | means. 7 | 8 | In jurisdictions that recognize copyright laws, the author or authors 9 | of this software dedicate any and all copyright interest in the 10 | software to the public domain. We make this dedication for the benefit 11 | of the public at large and to the detriment of our heirs and 12 | successors. We intend this dedication to be an overt act of 13 | relinquishment in perpetuity of all present and future rights to this 14 | software under copyright law. 15 | 16 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, 17 | EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF 18 | MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. 19 | IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR 20 | OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, 21 | ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR 22 | OTHER DEALINGS IN THE SOFTWARE. 23 | 24 | For more information, please refer to 25 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Introduction 2 | 3 | A collection of papers on skeleton-based human action recognition. 4 | 5 | # Paper 6 | 7 | ## 2020 8 | 9 | **Context Aware Graph Convolution for Skeleton-Based Action Recognition.** *Xikun Zhang, Chang Xu and Dacheng Tao. CVPR 2020.* [[PDF](http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhang_Context_Aware_Graph_Convolution_for_Skeleton-Based_Action_Recognition_CVPR_2020_paper.pdf)] 10 | 11 | **Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recoginition.** *Ziyu Liu, Hongwen Zhang, Zhenghao Chen, Zhiyong Wang and Wanli Ouyang. CVPR 2020.* [[PDF](http://openaccess.thecvf.com/content_CVPR_2020/papers/Liu_Disentangling_and_Unifying_Graph_Convolutions_for_Skeleton-Based_Action_Recognition_CVPR_2020_paper.pdf)][[GitHub](https://github.com/kenziyuliu/ms-g3d)] 12 | 13 | **PREDICT & CLUSTER: Unsupervised Skeleton Based Action Recognition.** *Kun Su, Xiulong Liu and Eli Shlizerman. CVPR 2020.* [[PDF](http://openaccess.thecvf.com/content_CVPR_2020/papers/Su_PREDICT__CLUSTER_Unsupervised_Skeleton_Based_Action_Recognition_CVPR_2020_paper.pdf)] 14 | 15 | **Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition.** *Pengfei Zhang, Cuiling Lan, Wenjun Zeng, Junliang Xing, Jianru Xue and Nanning Zheng. CVPR 2020.* [[PDF](http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhang_Semantics-Guided_Neural_Networks_for_Efficient_Skeleton-Based_Human_Action_Recognition_CVPR_2020_paper.pdf)] 16 | 17 | **Self-Attention Network for Skeleton-based Human Action Recognition.** *Sangwoo Cho, Muhammad Hasan Maqbool, Fei Liu and Hassan Foroosh. WACV 2020.* [[arXiv](https://arxiv.org/abs/1912.08435)] 18 | 19 | **Skeleton-Based Action Recognition With Shift Graph Convolutional Network.** *Ke Cheng, Yifan Zhang, Xiangyu He, Weihan Chen, Jian Cheng, and Hanqing Lu. CVPR 2020.* [[PDF](http://openaccess.thecvf.com/content_CVPR_2020/papers/Cheng_Skeleton-Based_Action_Recognition_With_Shift_Graph_Convolutional_Network_CVPR_2020_paper.pdf)][[GitHub](https://github.com/kchengiva/Shift-GCN)] 20 | 21 | ## 2019 22 | 23 | **Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition.** *Maosen Li, Siheng Chen, Xu Chen, Ya Zhang, Yanfeng Wang, and Qi Tian. CVPR 2019.* [[PDF](http://openaccess.thecvf.com/content_CVPR_2019/papers/Li_Actional-Structural_Graph_Convolutional_Networks_for_Skeleton-Based_Action_Recognition_CVPR_2019_paper.pdf)] 24 | 25 | **An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition.** *Chenyang Si, Wentao Chen, Wei Wang, Liang Wang, and Tieniu Tan. CVPR 2019.* [[PDF](http://openaccess.thecvf.com/content_CVPR_2019/papers/Si_An_Attention_Enhanced_Graph_Convolutional_LSTM_Network_for_Skeleton-Based_Action_CVPR_2019_paper.pdf)] 26 | 27 | **Bayesian Graph Convolution LSTM for Skeleton Based Action Recognition.** *Rui Zhao, Kang Wang, Hui Su and Qiang Ji. ICCV2019.* [[PDF](http://openaccess.thecvf.com/content_ICCV_2019/papers/Zhao_Bayesian_Graph_Convolution_LSTM_for_Skeleton_Based_Action_Recognition_ICCV_2019_paper.pdf)] 28 | 29 | **Bayesian Hierarchical Dynamic Model for Human Action Recognition.** *Rui Zhao, Wanru Xu, Hui Su and Qiang Ji. CVPR 2019.* [[PDF](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhao_Bayesian_Hierarchical_Dynamic_Model_for_Human_Action_Recognition_CVPR_2019_paper.pdf)] 30 | 31 | **Making the Invisible Visible: Action Recognition Through Walls and Occlusions.** *Tianhong Li, Lijie Fan, Mingmin Zhao, Yingcheng Liu and Dina Katabi. ICCV 2019.* [[PDF](http://openaccess.thecvf.com/content_ICCV_2019/papers/Li_Making_the_Invisible_Visible_Action_Recognition_Through_Walls_and_Occlusions_ICCV_2019_paper.pdf)] 32 | 33 | **Multi-task Deep Learning for Real-Time 3D Human Pose Estimation and Action Recognition.** *Diogo C Luvizon, Hedi Tabia and David Picard. Submitted to TPAMI.* [[arXiv](https://arxiv.org/abs/1912.08077)] 34 | 35 | **Skeleton-Based Action Recognition with Directed Graph Neural Networks.** *Lei Shi, Yifan Zhang, Jian Cheng, and Hanqing Lu. CVPR 2019.* [[PDF](http://openaccess.thecvf.com/content_CVPR_2019/papers/Shi_Skeleton-Based_Action_Recognition_With_Directed_Graph_Neural_Networks_CVPR_2019_paper.pdf)] 36 | 37 | **Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks.** *Lei Shi, Yifan Zhang, Jian Cheng and Hanqing Lu.* [[arXiv](https://arxiv.org/abs/1912.06971)] 38 | 39 | **Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition.** *Lei Shi, Yifan Zhang, Jian Cheng and Hanqing Lu. CVPR 2019.* [[PDF](http://openaccess.thecvf.com/content_CVPR_2019/papers/Shi_Two-Stream_Adaptive_Graph_Convolutional_Networks_for_Skeleton-Based_Action_Recognition_CVPR_2019_paper.pdf)] [[GitHub](https://github.com/lshiwjx/2s-AGCN)] 40 | 41 | ## 2018 42 | 43 | **2D/3D Pose Estimation and Action Recognition using Multitask Deep Learning.** *CVPR 2018.* [[PDF](http://openaccess.thecvf.com/content_cvpr_2018/papers/Luvizon_2D3D_Pose_Estimation_CVPR_2018_paper.pdf)] 44 | 45 | **Deep Progressive Reinforcement Learning for Skeleton-based Action Recognition.** *CVPR 2018.* [[PDF](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tang_Deep_Progressive_Reinforcement_CVPR_2018_paper.pdf)] 46 | 47 | **Skeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning.** *Chenyang Si, Ya Jing, Wei Wang, Liang Wang, and Tieniu Tan. ECCV 2018.* [[PDF](http://openaccess.thecvf.com/content_ECCV_2018/papers/Chenyang_Si_Skeleton-Based_Action_Recognition_ECCV_2018_paper.pdf)] 48 | 49 | **Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition.** *Sijie Yan, Yuanjun Xiong and Dahua Lin. AAAI 2018.* [[arXiv](https://arxiv.org/pdf/1801.07455.pdf)] [[GitHub](https://github.com/open-mmlab/mmskeleton)] 50 | --------------------------------------------------------------------------------