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arXiv (Cornell University)
Single Motion Diffusion
February 2023 • Sigal Raab, Inbal Leibovitch, Guy Tevet, Moab Arar, Amit H. Bermano, Daniel Cohen‐Or
Synthesizing realistic animations of humans, animals, and even imaginary creatures, has long been a goal for artists and computer graphics professionals. Compared to the imaging domain, which is rich with large available datasets, the number of data instances for the motion domain is limited, particularly for the animation of animals and exotic creatures (e.g., dragons), which have unique skeletons and motion patterns. In this work, we present a Single Motion Diffusion Model, dubbed SinMDM, a model designed to lea…
Animation
Artificial Intelligence
Computer Science
Overfitting
Computer Graphics
Motion
Computer Vision
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