36 citations · 109 across the 18 of their papers we have counts for
14 papers
DOAD: Decoupled One Stage Action Detection Network
Shuning Chang, Pichao Wang, Fan Wang +2
Localizing people and recognizing their actions from videos is a challenging task towards high-level video understanding. Existing methods are mostly two-stage based, with one stag…
PoseFormerV2: Exploring Frequency Domain for Efficient and Robust 3D Human Pose Estimation
Qitao Zhao, Ce Zheng, Mengyuan Liu +2
Recently, transformer-based methods have gained significant success in sequential 2D-to-3D lifting human pose estimation. As a pioneering work, PoseFormer captures spatial relation…
Making Vision Transformers Efficient from A Token Sparsification View
Shuning Chang, Pichao Wang, Ming Lin +4
The quadratic computational complexity to the number of tokens limits the practical applications of Vision Transformers (ViTs). Several works propose to prune redundant tokens to a…
Selective Structured State-Spaces for Long-Form Video Understanding
Jue Wang, Wentao Zhu, Pichao Wang +4
Effective modeling of complex spatiotemporal dependencies in long-form videos remains an open problem. The recently proposed Structured State-Space Sequence (S4) model with its lin…
Revisit Parameter-Efficient Transfer Learning: A Two-Stage Paradigm
Hengyuan Zhao, Hao Luo, Yuyang Zhao +3
Parameter-Efficient Transfer Learning (PETL) aims at efficiently adapting large models pre-trained on massive data to downstream tasks with limited task-specific data. In view of t…
Head-Free Lightweight Semantic Segmentation with Linear Transformer
Bo Dong, Pichao Wang, Fan Wang
Existing semantic segmentation works have been mainly focused on designing effective decoders; however, the computational load introduced by the overall structure has long been ign…