BAMM: Bidirectional Autoregressive Motion Model

arXiv:2403.19435v1 Announce Type: new
Abstract: Generating human motion from text has been dominated by denoising motion models either through diffusion or generative masking process. However, these models face great limitations in usability by requiring prior knowledge of the motion length. Conversely, autoregressive motion models address this limitation by adaptively predicting motion endpoints, at the cost of degraded generation quality and editing capabilities. To address these challenges, we propose Bidirectional Autoregressive Motion Model (BAMM), a novel text-to-motion generation framework. BAMM consists …

abstract arxiv cost cs.cv denoising diffusion endpoints face generative however human knowledge limitations masking prior process text through type usability