2 citations · 5 across the 7 of their papers we have counts for
7 papers
Dual-Branch Graph Transformer Network for 3D Human Mesh Reconstruction from Video
Tao Tang, Hong Liu, Yingxuan You +2
Human Mesh Reconstruction (HMR) from monocular video plays an important role in human-robot interaction and collaboration. However, existing video-based human mesh reconstruction m…
ARTS: Semi-Analytical Regressor using Disentangled Skeletal Representations for Human Mesh Recovery from Videos
Tao Tang, Hong Liu, Yingxuan You +2
Although existing video-based 3D human mesh recovery methods have made significant progress, simultaneously estimating human pose and shape from low-resolution image features limit…
Uncertainty-Aware Testing-Time Optimization for 3D Human Pose Estimation
Ti Wang, Mengyuan Liu, Hong Liu +5
Although data-driven methods have achieved success in 3D human pose estimation, they often suffer from domain gaps and exhibit limited generalization. In contrast, optimization-bas…
Co-Evolution of Pose and Mesh for 3D Human Body Estimation from Video
Yingxuan You, Hong Liu, Ti Wang +3
Despite significant progress in single image-based 3D human mesh recovery, accurately and smoothly recovering 3D human motion from a video remains challenging. Existing video-based…
Interweaved Graph and Attention Network for 3D Human Pose Estimation
Ti Wang, Hong Liu, Runwei Ding +3
Despite substantial progress in 3D human pose estimation from a single-view image, prior works rarely explore global and local correlations, leading to insufficient learning of hum…
GATOR: Graph-Aware Transformer with Motion-Disentangled Regression for Human Mesh Recovery from a 2D Pose
Yingxuan You, Hong Liu, Xia Li +3
3D human mesh recovery from a 2D pose plays an important role in various applications. However, it is hard for existing methods to simultaneously capture the multiple relations dur…
Semantic Dense Reconstruction with Consistent Scene Segments
Yingcai Wan, Yanyan Li, Yingxuan You +3
In this paper, a method for dense semantic 3D scene reconstruction from an RGB-D sequence is proposed to solve high-level scene understanding tasks. First, each RGB-D pair is consi…