EffiVED:Efficient Video Editing via Text-instruction Diffusion Models

arXiv:2403.11568v1 Announce Type: new
Abstract: Large-scale text-to-video models have shown remarkable abilities, but their direct application in video editing remains challenging due to limited available datasets. Current video editing methods commonly require per-video fine-tuning of diffusion models or specific inversion optimization to ensure high-fidelity edits. In this paper, we introduce EffiVED, an efficient diffusion-based model that directly supports instruction-guided video editing. To achieve this, we present two efficient workflows to gather video editing pairs, utilizing augmentation and fundamental vision-language techniques. …

abstract application arxiv cs.cv current datasets diffusion diffusion models editing fidelity fine-tuning optimization paper per scale text text-to-video type via video