TokenHSI: Unified Synthesis of Physical Human-Scene Interactions through Task Tokenization
Liang Pan, Zeshi Yang, Zhiyang Dou, Wenjia Wang, Buzhen Huang, Bo Dai, Taku Komura, Jingbo Wang
2025年份
21顶会引用
摘要
Synthesizing diverse and physically plausible Human-Scene Interactions (HSI) is pivotal for both computer animation and embodied AI. Despite encouraging progress, current methods mainly focus on developing separate controllers, each specialized for a specific interaction task. This significantly hinders the ability to tackle a wide variety of challenging HSI tasks that require the integration of multiple skills, e.g. sitting down while carrying an object (see Fig. 1). To address this issue, we present TokenHSI, a single, unified transformer-based policy capable of multi-skill unification
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引用它的顶会 Paper21
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- InterPrior: Scaling Generative Control for Physics-Based Human-Object InteractionsSirui Xu, Samuel Schulter, Morteza Ziyadi, Xialin He 等CVPR 2026 · 被引用 14 次
- 🎧MOSPA: Human Motion Generation Driven by Spatial AudioShuyang Xu, Zhiyang Dou, Mingyi Shi, Liang Pan 等NeurIPS 2025 · 被引用 13 次
- Go to Zero: Towards Zero-Shot Motion Generation with Million-Scale DataKe Fan, Shunlin Lu, Minyue Dai, Runyi Yu 等ICCV 2025 · 被引用 11 次
- MotionStreamer: Streaming Motion Generation via Diffusion-Based Autoregressive Model in Causal Latent SpaceLixing Xiao, Shunlin Lu, Huaijin Pi, Ke Fan 等ICCV 2025 · 被引用 11 次
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