March 19, 2024, 4:42 a.m. | Anton Pelykh, Ozge Mercanoglu Sincan, Richard Bowden

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.10731v1 Announce Type: cross
Abstract: Recent years have seen significant progress in human image generation, particularly with the advancements in diffusion models. However, existing diffusion methods encounter challenges when producing consistent hand anatomy and the generated images often lack precise control over the hand pose. To address this limitation, we introduce a novel approach to pose-conditioned human image generation, dividing the process into two stages: hand generation and subsequent body out-painting around the hands. We propose training the hand generator …

arxiv cs.cv cs.lg diffusion diffusion models giving human image image generation stage type

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne