76 citations · 216 across the 19 of their papers we have counts for
6 papers · 1 filter
Group Pose: A Simple Baseline for End-to-End Multi-person Pose Estimation
Huan Liu, Qiang Chen, Zichang Tan +9
In this paper, we study the problem of end-to-end multi-person pose estimation. State-of-the-art solutions adopt the DETR-like framework, and mainly develop the complex decoder, e.…
Learning Structure-Guided Diffusion Model for 2D Human Pose Estimation
Zhongwei Qiu, Qiansheng Yang, Jian Wang +7
One of the mainstream schemes for 2D human pose estimation (HPE) is learning keypoints heatmaps by a neural network. Existing methods typically improve the quality of heatmaps by c…
Exploring Effective Factors for Improving Visual In-Context Learning
Yanpeng Sun, Qiang Chen, Xiaofan Li +3
The In-Context Learning (ICL) is to understand a new task via a few demonstrations (aka. prompt) and predict new inputs without tuning the models. While it has been widely studied…
PSVT: End-to-End Multi-person 3D Pose and Shape Estimation with Progressive Video Transformers
Zhongwei Qiu, Yang Qiansheng, Jian Wang +6
Existing methods of multi-person video 3D human Pose and Shape Estimation (PSE) typically adopt a two-stage strategy, which first detects human instances in each frame and then per…
Temporal Segment Transformer for Action Segmentation
Zhichao Liu, Leshan Wang, Desen Zhou +5
Recognizing human actions from untrimmed videos is an important task in activity understanding, and poses unique challenges in modeling long-range temporal relations. Recent works…
Graph Contrastive Learning for Skeleton-based Action Recognition
Xiaohu Huang, Hao Zhou, Jian Wang +7
In the field of skeleton-based action recognition, current top-performing graph convolutional networks (GCNs) exploit intra-sequence context to construct adaptive graphs for featur…