activity
20242026
most citedTokenHSI: Unified Synthesis of Physical Human-Scene Interactions through Task Tokenization

2 citations · 2 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2026

EgoReAct: Egocentric Video-Driven 3D Human Reaction Generation

Libo Zhang, Zekun Li, Tianyu Li +10

Humans exhibit adaptive, context-sensitive responses to egocentric visual input. However, faithfully modeling such reactions from egocentric video remains challenging due to the du…

cs.CV2025

Motion2Motion: Cross-topology Motion Transfer with Sparse Correspondence

Ling-Hao Chen, Yuhong Zhang, Zixin Yin +5

This work studies the challenge of transfer animations between characters whose skeletal topologies differ substantially. While many techniques have advanced retargeting techniques…

cs.GR2025

MOSPA: Human Motion Generation Driven by Spatial Audio

Shuyang Xu, Zhiyang Dou, Mingyi Shi +8

Enabling virtual humans to dynamically and realistically respond to diverse auditory stimuli remains a key challenge in character animation, demanding the integration of perceptual…

cs.CV20252 cited

TokenHSI: Unified Synthesis of Physical Human-Scene Interactions through Task Tokenization

Liang Pan, Zeshi Yang, Zhiyang Dou +5

Synthesizing diverse and physically plausible Human-Scene Interactions (HSI) is pivotal for both computer animation and embodied AI. Despite encouraging progress, current methods m…

cs.CV2024

A Plug-and-Play Physical Motion Restoration Approach for In-the-Wild High-Difficulty Motions

Youliang Zhang, Ronghui Li, Yachao Zhang +4

Extracting physically plausible 3D human motion from videos is a critical task. Although existing simulation-based motion imitation methods can enhance the physical quality of dail…

cs.CV2024

MotionWavelet: Human Motion Prediction via Wavelet Manifold Learning

Yuming Feng, Zhiyang Dou, Ling-Hao Chen +7

Modeling temporal characteristics and the non-stationary dynamics of body movement plays a significant role in predicting human future motions. However, it is challenging to captur…