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Jin-Tao Chen

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#machine learning Preprint Sep 2026

Vidu S2: Real-Time Interactive, Editable, and Spatial Video Generation

Vidu S2, which comprises Vidu S2-Avatar, a real-time interactive digital-character model, and Vidu S2-Editing, a real-time video editing model, is presented and the feasibility of real-time spatial video generation for both Vidu S2-Avatar and Vidu S2-Editing is explored.

Jintao Zhang, Kai Jiang, Jin-Tao Chen et al. · 3 citations
Jul 2026

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation

PhyParam is presented, a physics-guided image-to-video diffusion model that conditions on object-level forces, masses, friction, restitution, and scene-level gravity via a lightweight physical-attention routing mechanism, and further improves motion learning with semantic-structural feature-space supervision.

Yan-Xun Li, Hao Wen, Bingze Song et al. · 0 citations

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