FLAME: Free-form Language-based Motion Synthesis & Editing
원문 초록
Text-based motion generation models are drawing a surge of interest for their potential for automating the motion-making process in the game, animation, or robot industries. In this paper, we propose a diffusion-based motion synthesis and editing model named FLAME. Inspired by the recent successes in diffusion models, we integrate diffusion-based generative models into the motion domain. FLAME can generate high-fidelity motions well aligned with the given text. Also, it can edit the parts of the motion, both frame-wise and joint-wise, without any fine-tuning. FLAME involves a new transformer-based architecture we devise to better handle motion data, which is found to be crucial to manage variable-length motions and well attend to free-form text. In experiments, we show that FLAME achieves state-of-the-art generation performances on three text-motion datasets: HumanML3D, BABEL, and KIT. We also demonstrate that editing capability of FLAME can be extended to other tasks such as motion prediction or motion in-betweening, which have been previously covered by dedicated models.
함께 살펴볼 논문
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AnyMoLe: Any Character Motion In-betweening Leveraging Video Diffusion Models
Human Motion Prediction, Reconstruction, and Generation
Cross-Conditioned Recurrent Networks for Long-Term Synthesis of Inter-Person Human Motion Interactions
Motion Anything: Any to Motion Generation
Controllable Motion Generation via Diffusion Modal Coupling
Free-T2M: Frequency Enhanced Text-to-Motion Diffusion Model With Consistency Loss
토론
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