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DiverseMotion: Towards Diverse Human Motion Generation via Discrete Diffusion
We present DiverseMotion, a new approach for synthesizing high-quality human motions conditioned on textual descriptions while preserving motion diversity. Despite the recent significant process in text-based human motion generation, existing methods often prioritize fitting training motions at the expense of action diversity.
Ranked #3 on
Motion Synthesis
on HumanML3D
(using extra training data)
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