MotionV2V: Precise Motion Editing for Video
Автор: AI Research Roundup
Загружено: 2025-11-27
Просмотров: 17
Описание: In this AI Research Roundup episode, Alex discusses the paper: 'MotionV2V: Editing Motion in a Video(2511.20640v1)' This work introduces MotionV2V, a video-to-video framework for precisely editing motion in existing videos by directly modifying sparse point trajectories extracted from the input. The authors define motion edits as deviations between original and edited trajectories, and pair this representation with a motion-conditioned video diffusion model. They also propose a pipeline for generating motion counterfactuals, where video pairs share the same content but have different motion patterns, enabling powerful and natural motion edits that can start at any timestamp. In user studies, MotionV2V significantly outperforms prior video editing methods, showing strong preference for its realism and controllability. Paper URL: https://arxiv.org/pdf/2511.20640 #AI #MachineLearning #DeepLearning #VideoEditing #DiffusionModels #ComputerVision #GenerativeModels
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