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cs.CV2026
PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation
Yidong Huang, Zun Wang, Han Lin +6
Generating realistic human motion is a central yet unsolved challenge in video generation. While reinforcement learning (RL)-based post-training has driven recent gains in general…
cs.CV2025
GrndCtrl: Grounding World Models via Self-Supervised Reward Alignment
Haoyang He, Jay Patrikar, Dong-Ki Kim +5
Recent advances in video world modeling have enabled large-scale generative models to simulate embodied environments with high visual fidelity, providing strong priors for predicti…
cs.CV2025
Planning with Sketch-Guided Verification for Physics-Aware Video Generation
Yidong Huang, Zun Wang, Han Lin +5
Recent video generation approaches increasingly rely on planning intermediate control signals such as object trajectories to improve temporal coherence and motion fidelity. However…