activity
20182022
most citedWeakly-Supervised Discovery of Geometry-Aware Representation for 3D Human Pose Estimation

43 citations · 123 across the 14 of their papers we have counts for

collaborators

20 papers

cs.CV202210 cited

Not All Tokens Are Equal: Human-centric Visual Analysis via Token Clustering Transformer

Wang Zeng, Sheng Jin, Wentao Liu +4

Vision transformers have achieved great successes in many computer vision tasks. Most methods generate vision tokens by splitting an image into a regular and fixed grid and treatin…

cs.CV20228 cited

Pseudo-Labeled Auto-Curriculum Learning for Semi-Supervised Keypoint Localization

Can Wang, Sheng Jin, Yingda Guan +4

Localizing keypoints of an object is a basic visual problem. However, supervised learning of a keypoint localization network often requires a large amount of data, which is expensi…

cs.CV20216 cited

Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images

Size Wu, Sheng Jin, Wentao Liu +4

This paper studies the task of estimating the 3D human poses of multiple persons from multiple calibrated camera views. Following the top-down paradigm, we decompose the task into…

cs.CV20211 cited

Joint Depth and Normal Estimation from Real-world Time-of-flight Raw Data

Rongrong Gao, Na Fan, Changlin Li +2

We present a novel approach to joint depth and normal estimation for time-of-flight (ToF) sensors. Our model learns to predict the high-quality depth and normal maps jointly from T…

cs.CV2021

Human Pose Regression with Residual Log-likelihood Estimation

Jiefeng Li, Siyuan Bian, Ailing Zeng +4

Heatmap-based methods dominate in the field of human pose estimation by modelling the output distribution through likelihood heatmaps. In contrast, regression-based methods are mor…

cs.CV20213 cited

ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search

Lumin Xu, Yingda Guan, Sheng Jin +5

Human pose estimation has achieved significant progress in recent years. However, most of the recent methods focus on improving accuracy using complicated models and ignoring real-…