OPSD-V: On-Policy Self-Distillation for Post-Training Few-Step Autoregressive Video Generators
OPSD-V enhances few-step autoregressive video diffusion models by using real long-video data for temporal context during training, providing dense trajectory-level supervision that…
Hugging Face · Daily Papers
·Hongyu Liu, Chun Wang
·
·▲ 8 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Hongyu Liu, Chun Wang, Feng Gao, Xuanhua He, Yue Ma, Ziyu Wan
- 8 upvotes da comunidade
- Temas: on-policy self-distillation, autoregressive video diffusion models, error accumulation, motion dynamics, temporal context, dense trajectory-level supervision
Resumo
Resumo original (em inglês), extraído do paper:
OPSD-V enhances few-step autoregressive video diffusion models by using real long-video data for temporal context during training, providing dense trajectory-level supervision that improves visual quality and motion dynamics without altering inference mechanisms.Onde ler
// relacionados
Leia também
Editorial
EditBridge: edição de imagem em 4K sem inventar o que não estava lá
Blog
Coarse-to-Fine Multi-Resolution Diffusion Models for Trajectory Generation in Urban Systems
Blog
DiSCO: Defending text-to-image generation through distribution-guided contrastive prompt optimization
Blog