FlashEdit: Decoupling Speed, Structure, and Semantics for Precise Image Editing
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866918508449759232 |
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| author | Wu, Junyi Li, Zhiteng Qin, Haotong Zhang, Yulun Yang, Xiaokang |
| author_facet | Wu, Junyi Li, Zhiteng Qin, Haotong Zhang, Yulun Yang, Xiaokang |
| contents | Text-guided image editing with diffusion models has achieved remarkable quality but often suffers from prohibitive latency. We introduce \textbf{FlashEdit}, a real-time localized image editing framework for the standard inversion-based editing setting. Its efficiency and precision stem from three key innovations: (1) a \textbf{Cycle-Consistent One-Step Inversion (COSI)} pipeline that encourages manifold-aligned one-step inversion through cycle consistency; (2) a \textbf{Background Shield (BG-Shield)} technique that improves preservation of non-edited regions via structural self-attention intervention; and (3) a \textbf{Sparsified Spatial Cross-Attention (SSCA)} mechanism that promotes precise edits by suppressing semantic leakage. Experiments on PIE-Bench demonstrate a strong preservation-efficiency trade-off, with edits completed in under 0.2 seconds and an over 150$\times$ speedup over DDIM-based multi-step editing. Our code will be made publicly available at \url{https://github.com/JunyiWuCode/FlashEdit}. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_22244 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | FlashEdit: Decoupling Speed, Structure, and Semantics for Precise Image Editing Wu, Junyi Li, Zhiteng Qin, Haotong Zhang, Yulun Yang, Xiaokang Computer Vision and Pattern Recognition Text-guided image editing with diffusion models has achieved remarkable quality but often suffers from prohibitive latency. We introduce \textbf{FlashEdit}, a real-time localized image editing framework for the standard inversion-based editing setting. Its efficiency and precision stem from three key innovations: (1) a \textbf{Cycle-Consistent One-Step Inversion (COSI)} pipeline that encourages manifold-aligned one-step inversion through cycle consistency; (2) a \textbf{Background Shield (BG-Shield)} technique that improves preservation of non-edited regions via structural self-attention intervention; and (3) a \textbf{Sparsified Spatial Cross-Attention (SSCA)} mechanism that promotes precise edits by suppressing semantic leakage. Experiments on PIE-Bench demonstrate a strong preservation-efficiency trade-off, with edits completed in under 0.2 seconds and an over 150$\times$ speedup over DDIM-based multi-step editing. Our code will be made publicly available at \url{https://github.com/JunyiWuCode/FlashEdit}. |
| title | FlashEdit: Decoupling Speed, Structure, and Semantics for Precise Image Editing |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2509.22244 |