7 papers
EmbodMocap: In-the-Wild 4D Human-Scene Reconstruction for Embodied Agents
Wenjia Wang, Liang Pan, Huaijin Pi +8
Human behaviors in the real world naturally encode rich, long-term contextual information that can be leveraged to train embodied agents for perception, understanding, and acting.…
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…
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…
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…
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…
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…