Feb. 14, 2024, 5:46 a.m. | Yunji Jung Seokju Lee Tair Djanibekov Hyunjung Shim Jongchul Ye

cs.CV updates on arXiv.org arxiv.org

Text-guided non-rigid editing involves complex edits for input images, such as changing motion or compositions within their surroundings. Since it requires manipulating the input structure, existing methods often struggle with preserving object identity and background, particularly when combined with Stable Diffusion. In this work, we propose a training-free approach for non-rigid editing with Stable Diffusion, aimed at improving the identity preservation quality without compromising editability. Our approach comprises three stages: text optimization, latent inversion, and timestep-aware text injection sampling. Inspired …

cs.cv diffusion editing free identity images sampling stable diffusion struggle text training work

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