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Binary diffusion models typically require a large number of function evaluations (NFEs) to generate high-quality samples, making practical inference computationally expensive. Reducing NFEs while preserving sample quality without distillation or additional training remains a significant challenge. Existing binary diffu...
Uni4R is a framework that unifies 4D reconstruction and point tracking by learning continuous velocity fields through the synergy of Optimal Transport (OT) and Ordinary Differential Equation (ODE), and acts as a kinematic prior that mutually benefits both 4D reconstruction and point tracking.
Experimental results show that training with Human4K consistently improves whole-body reconstruction on standard benchmarks, with particularly large gains for hands, feet and depth-ambiguous limb configurations.
This work introduces MotionPhys, a lightweight and interpretable framework that treats sparse motion trajectories as physical evidence rather than relying on appearance artifacts or generator-specific traces and reveals subtle motion inconsistencies that are difficult to capture with conventional visual cues and transf...
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