A Versatile Instructional Video Editing Framework with Auto-Generated Narratives

View the PDF file from the paper entitled Raccoon: Automatically used video editing framework with novels created automatically, by Jaehong Yoon and 2 other authors

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a summary:Modern video models are primarily based on carefully written text claims for specific tasks, such as editing or style editing. It requires intense text descriptions for input videos, which hinders their flexibility to adapting personal/raw videos with user specifications. This Raccoon paper, which is a multi -use and easy -to -use generation frame for the video to the video, supports multiple video editing capabilities such as removal, addition and modification, through a unified pipeline. Raccope consists of two main phases: the video to the vertebra (V2P) and the paragraph to the pheno (P2V). In the V2P stage, automatically, video scenes are well organized well, and we pick up both the comprehensive context and concentrated object details. After that, in the P2V stage, users can improve these descriptions optional to direct the video publishing form, providing various adjustments to the input video, such as removing themes, and/or adding new objects. The proposed approach from other ways is highlighted through many important contributions: (1) Raccons refer to a multi -spatial spatial assembly strategy to generate good video descriptions, capturing both wide details and the object details without the need for complicated humanitarian comments, and simplifying accurate video content based on the text for users. (2) Our obstetric model of the video includes novels or instructions that have been automatically created to enhance the quality and accuracy of the created content. (3) Raccoon also plans to imagine new objects in a specific video clip, so users are simply demanding the model to receive a detailed video editing plan to edit the complex video. The proposed frame shows great use capabilities to generate video to the paragraph, editing video content, and can be combined into other Sota video generation models for more improvement.