{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T17:55:06Z","timestamp":1786038906256,"version":"3.56.0"},"publisher-location":"New York, NY, USA","reference-count":37,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,10,12]]},"DOI":"10.1145\/3394171.3413941","type":"proceedings-article","created":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T12:26:18Z","timestamp":1602505578000},"page":"55-63","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":309,"title":["Dynamic GCN: Context-enriched Topology Learning for Skeleton-based Action Recognition"],"prefix":"10.1145","author":[{"given":"Fanfan","family":"Ye","sequence":"first","affiliation":[{"name":"Hikvision Research Institute &amp; Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiliang","family":"Pu","sequence":"additional","affiliation":[{"name":"Hikvision Research Institute, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiaoyong","family":"Zhong","sequence":"additional","affiliation":[{"name":"Hikvision Research Institute, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Li","sequence":"additional","affiliation":[{"name":"Hikvision Research Institute, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Di","family":"Xie","sequence":"additional","affiliation":[{"name":"Hikvision Research Institute, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huiming","family":"Tang","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-2604-3_16"},{"key":"e_1_3_2_2_2_1","first-page":"60","article-title":"A non-local algorithm for image denoising","volume":"2","author":"Buades Antoni","year":"2005","journal-title":"CVPR"},{"key":"e_1_3_2_2_3_1","volume-title":"GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond. arXiv preprint arXiv:1904","author":"Cao Yue","year":"2019"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"crossref","unstructured":"Zhe Cao Gines Hidalgo Tomas Simon Shih-En Wei and Yaser Sheikh. 2018. OpenPose: realtime multi-person 2D pose estimation using Part Affinity Fields. arXiv preprint arXiv:1812.08008 (2018).  Zhe Cao Gines Hidalgo Tomas Simon Shih-En Wei and Yaser Sheikh. 2018. OpenPose: realtime multi-person 2D pose estimation using Part Affinity Fields. arXiv preprint arXiv:1812.08008 (2018).","DOI":"10.1109\/CVPR.2017.143"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"crossref","unstructured":"Yilun Chen Zhicheng Wang Yuxiang Peng Zhiqiang Zhang Gang Yu and Jian Sun. 2018. Cascaded pyramid network for multi-person pose estimation. In CVPR. 7103--7112.  Yilun Chen Zhicheng Wang Yuxiang Peng Zhiqiang Zhang Gang Yu and Jian Sun. 2018. Cascaded pyramid network for multi-person pose estimation. In CVPR. 7103--7112.","DOI":"10.1109\/CVPR.2018.00742"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351170"},{"key":"e_1_3_2_2_7_1","unstructured":"Jian-Fang Hu Wei-Shi Zheng Jianhuang Lai and Jianguo Zhang. 2015. Jointly learning heterogeneous features for RGB-D activity recognition. In CVPR. 5344--5352.  Jian-Fang Hu Wei-Shi Zheng Jianhuang Lai and Jianguo Zhang. 2015. Jointly learning heterogeneous features for RGB-D activity recognition. In CVPR. 5344--5352."},{"key":"e_1_3_2_2_8_1","unstructured":"Will Kay Joao Carreira Karen Simonyan Brian Zhang Chloe Hillier Sudheendra Vijayanarasimhan Fabio Viola Tim Green Trevor Back Paul Natsev etal 2017. The kinetics human action video dataset. arXiv preprint arXiv:1705.06950 (2017).  Will Kay Joao Carreira Karen Simonyan Brian Zhang Chloe Hillier Sudheendra Vijayanarasimhan Fabio Viola Tim Green Trevor Back Paul Natsev et al. 2017. The kinetics human action video dataset. arXiv preprint arXiv:1705.06950 (2017)."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2812099"},{"key":"e_1_3_2_2_10_1","unstructured":"Tae Soo Kim and Austin Reiter. 2017. Interpretable 3d human action analysis with temporal convolutional networks. In CVPRW. 1623--1631.  Tae Soo Kim and Austin Reiter. 2017. Interpretable 3d human action analysis with temporal convolutional networks. In CVPRW. 1623--1631."},{"key":"e_1_3_2_2_11_1","unstructured":"Thomas N Kipf and Max Welling. 2017. Semi-supervised classification with graph convolutional networks. ICLR (2017).  Thomas N Kipf and Max Welling. 2017. Semi-supervised classification with graph convolutional networks. ICLR (2017)."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"crossref","unstructured":"Bin Li Xi Li Zhongfei Zhang and Fei Wu. 2019 b. Spatio-Temporal Graph Routing for Skeleton-based Action Recognition. (2019).  Bin Li Xi Li Zhongfei Zhang and Fei Wu. 2019 b. Spatio-Temporal Graph Routing for Skeleton-based Action Recognition. (2019).","DOI":"10.1109\/ITSC.2019.8916929"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"crossref","unstructured":"Chao Li Qiaoyong Zhong Di Xie and Shiliang Pu. 2017. Skeleton-based action recognition with convolutional neural networks. In ICMEW. 597--600.  Chao Li Qiaoyong Zhong Di Xie and Shiliang Pu. 2017. Skeleton-based action recognition with convolutional neural networks. In ICMEW. 597--600.","DOI":"10.1109\/ICMEW.2017.8026285"},{"key":"e_1_3_2_2_14_1","unstructured":"Chao Li Qiaoyong Zhong Di Xie and Shiliang Pu. 2018. Co-occurrence feature learning from skeleton data for action recognition and detection with hierarchical aggregation. IJCAI (2018).  Chao Li Qiaoyong Zhong Di Xie and Shiliang Pu. 2018. Co-occurrence feature learning from skeleton data for action recognition and detection with hierarchical aggregation. IJCAI (2018)."},{"key":"e_1_3_2_2_15_1","unstructured":"Maosen Li Siheng Chen Xu Chen Ya Zhang Yanfeng Wang and Qi Tian. 2019 a. Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition. In CVPR. 3595--3603.  Maosen Li Siheng Chen Xu Chen Ya Zhang Yanfeng Wang and Qi Tian. 2019 a. Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition. In CVPR. 3595--3603."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"crossref","unstructured":"Jun Liu Amir Shahroudy Mauricio Lisboa Perez Gang Wang Ling-Yu Duan and Alex Kot Chichung. 2019 a. NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding. IEEE transactions on pattern analysis and machine intelligence (2019).  Jun Liu Amir Shahroudy Mauricio Lisboa Perez Gang Wang Ling-Yu Duan and Alex Kot Chichung. 2019 a. NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding. IEEE transactions on pattern analysis and machine intelligence (2019).","DOI":"10.1109\/TPAMI.2019.2916873"},{"key":"e_1_3_2_2_17_1","unstructured":"Jun Liu Amir Shahroudy Gang Wang Ling-Yu Duan and Alex Kot Chichung. 2019 b. Skeleton-based online action prediction using scale selection network. IEEE transactions on pattern analysis and machine intelligence (2019).  Jun Liu Amir Shahroudy Gang Wang Ling-Yu Duan and Alex Kot Chichung. 2019 b. Skeleton-based online action prediction using scale selection network. IEEE transactions on pattern analysis and machine intelligence (2019)."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"crossref","unstructured":"Jun Liu Amir Shahroudy Dong Xu and Gang Wang. 2016. Spatio-temporal lstm with trust gates for 3d human action recognition. In ECCV. Springer 816--833.  Jun Liu Amir Shahroudy Dong Xu and Gang Wang. 2016. Spatio-temporal lstm with trust gates for 3d human action recognition. In ECCV. Springer 816--833.","DOI":"10.1007\/978-3-319-46487-9_50"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2785279"},{"key":"e_1_3_2_2_20_1","unstructured":"Mengyuan Liu and Junsong Yuan. 2018. Recognizing human actions as the evolution of pose estimation maps. In CVPR. 1159--1168.  Mengyuan Liu and Junsong Yuan. 2018. Recognizing human actions as the evolution of pose estimation maps. In CVPR. 1159--1168."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"crossref","unstructured":"Ziyu Liu Hongwen Zhang Zhenghao Chen Zhiyong Wang and Wanli Ouyang. 2020. Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition. arXiv preprint arXiv:2003.14111 (2020).  Ziyu Liu Hongwen Zhang Zhenghao Chen Zhiyong Wang and Wanli Ouyang. 2020. Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition. arXiv preprint arXiv:2003.14111 (2020).","DOI":"10.1109\/CVPR42600.2020.00022"},{"key":"e_1_3_2_2_22_1","volume-title":"Automatic Differentiation in PyTorch. In NIPS Autodiff Workshop .","author":"Paszke Adam","year":"2017"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"crossref","unstructured":"Amir Shahroudy Jun Liu Tian-Tsong Ng and Gang Wang. 2016. Ntu rgb+d: A large scale dataset for 3d human activity analysis. In CVPR. 1010--1019.  Amir Shahroudy Jun Liu Tian-Tsong Ng and Gang Wang. 2016. Ntu rgb+d: A large scale dataset for 3d human activity analysis. In CVPR. 1010--1019.","DOI":"10.1109\/CVPR.2016.115"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"crossref","unstructured":"Lei Shi Yifan Zhang Jian Cheng and Hanqing Lu. 2019 a. Skeleton-Based Action Recognition with Directed Graph Neural Networks. In CVPR. 7912--7921.  Lei Shi Yifan Zhang Jian Cheng and Hanqing Lu. 2019 a. Skeleton-Based Action Recognition with Directed Graph Neural Networks. In CVPR. 7912--7921.","DOI":"10.1109\/CVPR.2019.00810"},{"key":"e_1_3_2_2_25_1","unstructured":"Lei Shi Yifan Zhang Jian Cheng and Hanqing LU. 2019 b. Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks. arXiv preprint arXiv:1912.06971 (2019).  Lei Shi Yifan Zhang Jian Cheng and Hanqing LU. 2019 b. Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks. arXiv preprint arXiv:1912.06971 (2019)."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"Lei Shi Yifan Zhang Jian Cheng and Hanqing Lu. 2019 c. Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition. In CVPR. 12026--12035.  Lei Shi Yifan Zhang Jian Cheng and Hanqing Lu. 2019 c. Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition. In CVPR. 12026--12035.","DOI":"10.1109\/CVPR.2019.01230"},{"key":"e_1_3_2_2_27_1","unstructured":"Chenyang Si Wentao Chen Wei Wang Liang Wang and Tieniu Tan. [n.d.]. An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition.  Chenyang Si Wentao Chen Wei Wang Liang Wang and Tieniu Tan. [n.d.]. An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"crossref","unstructured":"Yansong Tang Yi Tian Jiwen Lu Peiyang Li and Jie Zhou. 2018. Deep progressive reinforcement learning for skeleton-based action recognition. In CVPR. 5323--5332.  Yansong Tang Yi Tian Jiwen Lu Peiyang Li and Jie Zhou. 2018. Deep progressive reinforcement learning for skeleton-based action recognition. In CVPR. 5323--5332.","DOI":"10.1109\/CVPR.2018.00558"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"crossref","unstructured":"Raviteja Vemulapalli Felipe Arrate Rama Chellappa Felipe Arrate and Felipe DDD. 2014. Human action recognition by representing 3d skeletons as points in a lie group. In CVPR. 588--595.  Raviteja Vemulapalli Felipe Arrate Rama Chellappa Felipe Arrate and Felipe DDD. 2014. Human action recognition by representing 3d skeletons as points in a lie group. In CVPR. 588--595.","DOI":"10.1109\/CVPR.2014.82"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"crossref","unstructured":"Jiang Wang Zicheng Liu Ying Wu and Junsong Yuan. 2012. Mining actionlet ensemble for action recognition with depth cameras. In CVPR. 1290--1297.  Jiang Wang Zicheng Liu Ying Wu and Junsong Yuan. 2012. Mining actionlet ensemble for action recognition with depth cameras. In CVPR. 1290--1297.","DOI":"10.1109\/CVPR.2012.6247813"},{"key":"e_1_3_2_2_31_1","unstructured":"Shih-En Wei Varun Ramakrishna Takeo Kanade and Yaser Sheikh. 2016. Convolutional pose machines. In CVPR. 4724--4732.  Shih-En Wei Varun Ramakrishna Takeo Kanade and Yaser Sheikh. 2016. Convolutional pose machines. In CVPR. 4724--4732."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2012.6239233"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"crossref","unstructured":"Sijie Yan Yuanjun Xiong and Dahua Lin. 2018. Spatial temporal graph convolutional networks for skeleton-based action recognition. In Thirty-Second AAAI .  Sijie Yan Yuanjun Xiong and Dahua Lin. 2018. Spatial temporal graph convolutional networks for skeleton-based action recognition. In Thirty-Second AAAI .","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"crossref","unstructured":"Pengfei Zhang Cuiling Lan Junliang Xing Wenjun Zeng Jianru Xue and Nanning Zheng. 2017. View adaptive recurrent neural networks for high performance human action recognition from skeleton data. In ICCV. 2117--2126.  Pengfei Zhang Cuiling Lan Junliang Xing Wenjun Zeng Jianru Xue and Nanning Zheng. 2017. View adaptive recurrent neural networks for high performance human action recognition from skeleton data. In ICCV. 2117--2126.","DOI":"10.1109\/ICCV.2017.233"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"crossref","unstructured":"Pengfei Zhang Cuiling Lan Junliang Xing Wenjun Zeng Jianru Xue and Nanning Zheng. 2019 a. View adaptive neural networks for high performance skeleton-based human action recognition. IEEE transactions on pattern analysis and machine intelligence (2019).  Pengfei Zhang Cuiling Lan Junliang Xing Wenjun Zeng Jianru Xue and Nanning Zheng. 2019 a. View adaptive neural networks for high performance skeleton-based human action recognition. IEEE transactions on pattern analysis and machine intelligence (2019).","DOI":"10.1109\/TPAMI.2019.2896631"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"crossref","unstructured":"Pengfei Zhang Cuiling Lan Wenjun Zeng Jianru Xue and Nanning Zheng. 2019 b. Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition. arXiv preprint arXiv:1904.01189 (2019).  Pengfei Zhang Cuiling Lan Wenjun Zeng Jianru Xue and Nanning Zheng. 2019 b. Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition. arXiv preprint arXiv:1904.01189 (2019).","DOI":"10.1109\/CVPR42600.2020.00119"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"crossref","unstructured":"Pengfei Zhang Jianru Xue Cuiling Lan Wenjun Zeng Zhanning Gao and Nanning Zheng. 2018. Adding attentiveness to the neurons in recurrent neural networks. In ECCV. 135--151.  Pengfei Zhang Jianru Xue Cuiling Lan Wenjun Zeng Zhanning Gao and Nanning Zheng. 2018. Adding attentiveness to the neurons in recurrent neural networks. In ECCV. 135--151.","DOI":"10.1007\/978-3-030-01240-3_9"}],"event":{"name":"MM '20: The 28th ACM International Conference on Multimedia","location":"Seattle WA USA","acronym":"MM '20","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 28th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3413941","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394171.3413941","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:32:07Z","timestamp":1750195927000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3413941"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,12]]},"references-count":37,"alternative-id":["10.1145\/3394171.3413941","10.1145\/3394171"],"URL":"https:\/\/doi.org\/10.1145\/3394171.3413941","relation":{},"subject":[],"published":{"date-parts":[[2020,10,12]]},"assertion":[{"value":"2020-10-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}