AI RESEARCH
RDM: Recurrent Diffusion Model for Human Motion Generation
arXiv CS.CV
•
ArXi:2406.07169v2 Announce Type: replace Human motion generation is a challenging task due to its high dimensionality and the difficulty of generating fine-grained motions. Diffusion methods have been proposed due to their high sample quality and expressiveness. Early approaches treat the entire sequence as a whole, which is computationally expensive and restricts sequence length. In contrast, autoregressive diffusion models generate longer sequences. However, their reliance on fully denoising previous frames complicates