Fetching the paper…
Reading the bibliography…
Graph convolutional networks (GCNs) have emerged as dominant methods for skeleton-based action recognition.
“Microsoft kinect sensor and its effect,”
Zhengyou Zhang, · 2012
Earlier work this paper cites.
“Ntu rgb+ d: A large scale dataset for 3d human activity analysis,”
Amir Shahroudy, Jun Liu, Tian-Tsong Ng, and Gang Wang, · 2016
Earlier work this paper cites.
“Attention is all you need,”
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin, · 2017
Earlier work this paper cites.
“Spatial temporal graph convolutional networks for skeleton-based action recognition,”
Sijie Yan, Yuanjun Xiong, and Dahua Lin, · 2018
Earlier work this paper cites.
“Openpose: realtime multi-person 2d pose estimation using part affinity fields,”
Zhe Cao, Gines Hidalgo, Tomas Simon, Shih-En Wei, and Yaser Sheikh, · 2019
Earlier work this paper cites.
“Two-stream adaptive graph convolutional networks for skeleton-based action recognition,”
Lei Shi, Yifan Zhang, Jian Cheng, and Hanqing Lu, · 2019
Earlier work this paper cites.
“Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding,”
Jun Liu, Amir Shahroudy, Mauricio Perez, Gang Wang, Ling-Yu Duan, and Alex C Kot, · 2019
Cited alongside, same era.
“Spatio-temporal graph routing for skeleton-based action recognition,”
Bin Li, Xi Li, Zhongfei Zhang, and Fei Wu, · 2019
Cited alongside, same era.
“Actional-structural graph convolutional networks for skeleton-based action recognition,”
Maosen Li, Siheng Chen, Xu Chen, Ya Zhang, Yanfeng Wang, and Qi Tian, · 2019
Cited alongside, same era.
“Disentangling and unifying graph convolutions for skeleton-based action recognition,”
Ziyu Liu, Hongwen Zhang, Zhenghao Chen, Zhiyong Wang, and Wanli Ouyang, · 2020
Cited alongside, same era.
“Skeleton-based action recognition with shift graph convolutional network,”
Ke Cheng, Yifan Zhang, Xiangyu He, Weihan Chen, Jian Cheng, and Hanqing Lu, · 2020
Cited alongside, same era.
“Dynamic gcn: Context-enriched topology learning for skeleton-based action recognition,”
Fanfan Ye, Shiliang Pu, Qiaoyong Zhong, Chao Li, Di Xie, and Huiming Tang, · 2020
Later among the works it cites.
“Stronger, faster and more explainable: A graph convolutional baseline for skeleton-based action recognition,”
Yi-Fan Song, Zhang Zhang, Caifeng Shan, and Liang Wang, · 2020
Later among the works it cites.
“Graph attention convolutional network with motion tempo enhancement for skeleton-based action recognition,”
Ruwen Bai, Xiang Meng, Bo Meng, Miao Jiang, Junxing Ren, Yang Yang, Min Li, and Degang Sun, · 2021
Closest in time.
“Localvit: Bringing locality to vision transformers,”
Yawei Li, Kai Zhang, Jiezhang Cao, Radu Timofte, and Luc Van Gool, · 2021
Closest in time.
“Spatial temporal transformer network for skeleton-based action recognition,”
Chiara Plizzari, Marco Cannici, and Matteo Matteucci, · 2021
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…