62 citations · 99 across the 16 of their papers we have counts for
8 papers · 1 filter
Source-free Domain Adaptive Human Pose Estimation
Qucheng Peng, Ce Zheng, Chen Chen
Human Pose Estimation (HPE) is widely used in various fields, including motion analysis, healthcare, and virtual reality. However, the great expenses of labeled real-world datasets…
LAMP: Leveraging Language Prompts for Multi-person Pose Estimation
Shengnan Hu, Ce Zheng, Zixiang Zhou +2
Human-centric visual understanding is an important desideratum for effective human-robot interaction. In order to navigate crowded public places, social robots must be able to inte…
Part Aware Contrastive Learning for Self-Supervised Action Recognition
Yilei Hua, Wenhan Wu, Ce Zheng +4
In recent years, remarkable results have been achieved in self-supervised action recognition using skeleton sequences with contrastive learning. It has been observed that the seman…
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…
POTTER: Pooling Attention Transformer for Efficient Human Mesh Recovery
Ce Zheng, Xianpeng Liu, Guo-Jun Qi +1
Transformer architectures have achieved SOTA performance on the human mesh recovery (HMR) from monocular images. However, the performance gain has come at the cost of substantial m…
A Large-scale Study of Spatiotemporal Representation Learning with a New Benchmark on Action Recognition
Andong Deng, Taojiannan Yang, Chen Chen
The goal of building a benchmark (suite of datasets) is to provide a unified protocol for fair evaluation and thus facilitate the evolution of a specific area. Nonetheless, we poin…
DiffMesh: A Motion-aware Diffusion Framework for Human Mesh Recovery from Videos
Ce Zheng, Xianpeng Liu, Qucheng Peng +3
Human mesh recovery (HMR) provides rich human body information for various real-world applications. While image-based HMR methods have achieved impressive results, they often strug…
AIM: Adapting Image Models for Efficient Video Action Recognition
Taojiannan Yang, Yi Zhu, Yusheng Xie +3
Recent vision transformer based video models mostly follow the ``image pre-training then finetuning" paradigm and have achieved great success on multiple video benchmarks. However,…