Papers
1–4 of 4CIGPose: Causal Intervention Graph Neural Network for Whole-Body Pose Estimation
State-of-the-art whole-body pose estimators often lack robustness, producing anatomically implausible predictions in challenging scenes. We posit this failure stems from spurious correlations learned ...
mmGAT: Pose Estimation by Graph Attention with Mutual Features from mmWave Radar Point Cloud
Pose estimation and human action recognition (HAR) are pivotal technologies spanning various domains. While the image-based pose estimation and HAR are widely admired for their superior performance, t...
Beyond Static Frames: Temporal Aggregate-and-Restore Vision Transformer for Human Pose Estimation
Vision Transformers (ViTs) have recently achieved state-of-the-art performance in 2D human pose estimation due to their strong global modeling capability. However, existing ViT-based pose estimators a...
Multi-Person Pose Estimation Evaluation Using Optimal Transportation and Improved Pose Matching
In Multi-Person Pose Estimation, many metrics place importance on ranking of pose detection confidence scores. Current metrics tend to disregard false-positive poses with low confidence, focusing prim...