AI RESEARCH
StreamGVE: Training-Free Video Editing via Few-Step Streaming Video Generation
arXiv CS.CV
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ArXi:2605.21466v1 Announce Type: new Although existing video editing methods are generally feasible, they often require many costly iterations and still struggle to deliver high-quality yet satisfying editing results. We attribute this limitation to the prevalent data-to-data paradigm, which is less compatible with modern generative models than noise-to-data generation.