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

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

collaborators

6 papers

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.CV2025

MotionStreamer: Streaming Motion Generation via Diffusion-based Autoregressive Model in Causal Latent Space

Lixing Xiao, Shunlin Lu, Huaijin Pi +7

This paper addresses the challenge of text-conditioned streaming motion generation, which requires us to predict the next-step human pose based on variable-length historical motion…

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

ChatDyn: Language-Driven Multi-Actor Dynamics Generation in Street Scenes

Yuxi Wei, Jingbo Wang, Yuwen Du +6

Generating realistic and interactive dynamics of traffic participants according to specific instruction is critical for street scene simulation. However, there is currently a lack…

cs.CV2024

SIMS: Simulating Stylized Human-Scene Interactions with Retrieval-Augmented Script Generation

Wenjia Wang, Liang Pan, Zhiyang Dou +7

Simulating stylized human-scene interactions (HSI) in physical environments is a challenging yet fascinating task. Prior works emphasize long-term execution but fall short in achie…