5 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.…
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…
RMD: A Simple Baseline for More General Human Motion Generation via Training-free Retrieval-Augmented Motion Diffuse
Zhouyingcheng Liao, Mingyuan Zhang, Wenjia Wang +2
While motion generation has made substantial progress, its practical application remains constrained by dataset diversity and scale, limiting its ability to handle out-of-distribut…
It Takes Two: Real-time Co-Speech Two-person's Interaction Generation via Reactive Auto-regressive Diffusion Model
Mingyi Shi, Dafei Qin, Leo Ho +4
Conversational scenarios are very common in real-world settings, yet existing co-speech motion synthesis approaches often fall short in these contexts, where one person's audio and…
EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion Generation
Wenyang Zhou, Zhiyang Dou, Zeyu Cao +7
We introduce Efficient Motion Diffusion Model (EMDM) for fast and high-quality human motion generation. Current state-of-the-art generative diffusion models have produced impressiv…