42 citations · 95 across the 7 of their papers we have counts for
8 papers
DG-STGCN: Dynamic Spatial-Temporal Modeling for Skeleton-based Action Recognition
Haodong Duan, Jiaqi Wang, Kai Chen +1
Graph convolution networks (GCN) have been widely used in skeleton-based action recognition. We note that existing GCN-based approaches primarily rely on prescribed graphical struc…
Mitigating Representation Bias in Action Recognition: Algorithms and Benchmarks
Haodong Duan, Yue Zhao, Kai Chen +2
Deep learning models have achieved excellent recognition results on large-scale video benchmarks. However, they perform poorly when applied to videos with rare scenes or objects, p…
PYSKL: Towards Good Practices for Skeleton Action Recognition
Haodong Duan, Jiaqi Wang, Kai Chen +1
We present PYSKL: an open-source toolbox for skeleton-based action recognition based on PyTorch. The toolbox supports a wide variety of skeleton action recognition algorithms, incl…
TransRank: Self-supervised Video Representation Learning via Ranking-based Transformation Recognition
Haodong Duan, Nanxuan Zhao, Kai Chen +1
Recognizing transformation types applied to a video clip (RecogTrans) is a long-established paradigm for self-supervised video representation learning, which achieves much inferior…
OCSampler: Compressing Videos to One Clip with Single-step Sampling
Jintao Lin, Haodong Duan, Kai Chen +2
In this paper, we propose a framework named OCSampler to explore a compact yet effective video representation with one short clip for efficient video recognition. Recent works pref…
Omni-sourced Webly-supervised Learning for Video Recognition
Haodong Duan, Yue Zhao, Yuanjun Xiong +2
We introduce OmniSource, a novel framework for leveraging web data to train video recognition models. OmniSource overcomes the barriers between data formats, such as images, short…