85 citations · 167 across the 21 of their papers we have counts for
9 papers · 1 filter
A Single 2D Pose with Context is Worth Hundreds for 3D Human Pose Estimation
Qitao Zhao, Ce Zheng, Mengyuan Liu +1
The dominant paradigm in 3D human pose estimation that lifts a 2D pose sequence to 3D heavily relies on long-term temporal clues (i.e., using a daunting number of video frames) for…
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…
Annotation-efficient learning for OCT segmentation
Haoran Zhang, Jianlong Yang, Ce Zheng +2
Deep learning has been successfully applied to OCT segmentation. However, for data from different manufacturers and imaging protocols, and for different regions of interest (ROIs),…
Monocular 3D Object Detection with Bounding Box Denoising in 3D by Perceiver
Xianpeng Liu, Ce Zheng, Kelvin Cheng +3
The main challenge of monocular 3D object detection is the accurate localization of 3D center. Motivated by a new and strong observation that this challenge can be remedied by a 3D…
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…
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…