all AI news
AnyV2V: A Plug-and-Play Framework For Any Video-to-Video Editing Tasks
March 22, 2024, 4:45 a.m. | Max Ku, Cong Wei, Weiming Ren, Huan Yang, Wenhu Chen
cs.CV updates on arXiv.org arxiv.org
Abstract: Video-to-video editing involves editing a source video along with additional control (such as text prompts, subjects, or styles) to generate a new video that aligns with the source video and the provided control. Traditional methods have been constrained to certain editing types, limiting their ability to meet the wide range of user demands. In this paper, we introduce AnyV2V, a novel training-free framework designed to simplify video editing into two primary steps: (1) employing an …
abstract arxiv control cs.ai cs.cv cs.mm editing framework generate prompts tasks text type types video video-to-video
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
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
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Principal Data Engineering Manager
@ Microsoft | Redmond, Washington, United States
Machine Learning Engineer
@ Apple | San Diego, California, United States