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In-Context Forcing: Uncovering Context Effects in Autoregressive Video Diffusion
Lingxiao Yang, Liu Liu, Moran Li +4
Current few-step autoregressive video diffusion models depend on previous fully denoised clean frames as context for all denoising steps of the current frame. However, these clean…
Diffusion Bridge or Flow Matching? A Unifying Framework and Comparative Analysis
Kaizhen Zhu, Mokai Pan, Zhechuan Yu +3
Diffusion Bridge and Flow Matching have both demonstrated compelling empirical performance in transformation between arbitrary distributions. However, there remains confusion about…
DiscoForcing: A Unified Framework for Real-Time Audio-Driven Character Control with Diffusion Forcing
Kaiyang Ji, Bingsheng Qian, Binghuan Wu +3
We study real-time audio-responsive character control as a deployment-faithful problem: strictly causal, bounded-latency streaming that must generate coherent full-body motion at i…
Gaze-guided Hand-Object Interaction Synthesis: Dataset and Method
Jie Tian, Ran Ji, Lingxiao Yang +6
Gaze plays a crucial role in revealing human attention and intention, particularly in hand-object interaction scenarios, where it guides and synchronizes complex tasks that require…
Human-Object Interaction via Automatically Designed VLM-Guided Motion Policy
Zekai Deng, Ye Shi, Kaiyang Ji +3
Human-object interaction (HOI) synthesis is crucial for applications in animation, simulation, and robotics. However, existing approaches either rely on expensive motion capture da…
OpenHOI: Open-World Hand-Object Interaction Synthesis with Multimodal Large Language Model
Zhenhao Zhang, Ye Shi, Lingxiao Yang +3
Understanding and synthesizing realistic 3D hand-object interactions (HOI) is critical for applications ranging from immersive AR/VR to dexterous robotics. Existing methods struggl…