Good Noise Makes Good Edits: A Training-Free Diffusion-Based Video Editing with Image and Text Prompts
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866914211481780224 |
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| author | Choi, Saemee Jeong, Sohyun Jang, Hyojin Choo, Jaegul Kim, Jinhee |
| author_facet | Choi, Saemee Jeong, Sohyun Jang, Hyojin Choo, Jaegul Kim, Jinhee |
| contents | We propose VINO, the first zero-shot, training-free video editing method conditioned on both image and text. Our approach introduces $ρ$-start sampling and dilated dual masking to construct structured noise maps that enable coherent and accurate edits. To further enhance visual fidelity, we present zero image guidance, a controllable negative prompt strategy. Extensive experiments demonstrate that VINO faithfully incorporates the reference image into video edits, achieving strong performance compared to state-of-the-art baselines, all without any test-time or instance-specific training. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_12520 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Good Noise Makes Good Edits: A Training-Free Diffusion-Based Video Editing with Image and Text Prompts Choi, Saemee Jeong, Sohyun Jang, Hyojin Choo, Jaegul Kim, Jinhee Computer Vision and Pattern Recognition We propose VINO, the first zero-shot, training-free video editing method conditioned on both image and text. Our approach introduces $ρ$-start sampling and dilated dual masking to construct structured noise maps that enable coherent and accurate edits. To further enhance visual fidelity, we present zero image guidance, a controllable negative prompt strategy. Extensive experiments demonstrate that VINO faithfully incorporates the reference image into video edits, achieving strong performance compared to state-of-the-art baselines, all without any test-time or instance-specific training. |
| title | Good Noise Makes Good Edits: A Training-Free Diffusion-Based Video Editing with Image and Text Prompts |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2506.12520 |