activity
20232026
most citedInterweaved Graph and Attention Network for 3D Human Pose Estimation

1 citations · 2 across the 6 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Learning to Evolve: Multi-modal Interactive Fields for Robust Humanoid Navigation in Dynamic Environments

Peifeng Jiang, Hong Liu, Jin Jin +2

Safe manipulation-oriented navigation for humanoid robots requires scene memory that remains reliable under locomotion-induced perceptual distortion, environmental changes, and int…

cs.CV2024

VG4D: Vision-Language Model Goes 4D Video Recognition

Zhichao Deng, Xiangtai Li, Xia Li +3

Understanding the real world through point cloud video is a crucial aspect of robotics and autonomous driving systems. However, prevailing methods for 4D point cloud recognition ha…

cs.CV2024

UVMap-ID: A Controllable and Personalized UV Map Generative Model

Weijie Wang, Jichao Zhang, Chang Liu +5

Recently, diffusion models have made significant strides in synthesizing realistic 2D human images based on provided text prompts. Building upon this, researchers have extended 2D…

cs.CV2024

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…

cs.CV2023★ 1 cited

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…

cs.CV2023★ 1 cited

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…

cs.CV2023

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…