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RF-Inversion Semantic Image Inversion and Editing using Stochastic Rectified Differential Equations Litu Rout 1,2 Yujia Chen 2 Nataniel Ruiz 2 Constantine Caramanis 1 Sanjay Shakkottai 1 Wen-Sheng Chu 2 1 The University of Texas at Austin,    2 Google ICLR 2025 [Paper] [arXiv] [Code] [ComfyUI] [Diffusers] Rectified flows for image inversion and editing . Our approach efficiently inverts reference style images in (a) and (b) without requiring text descriptions of the images and applies desired edits based on new prompts (e.g. “a girl” or “a dwarf”). For a reference content image (e.g. a cat in (c) or a face in (d)), it performs semantic image editing e.g. “sleeping cat”) and stylization (e.g. “a photo of a cat in origmai style”) based on prompts, without leaking unwanted content from the reference image. Input images have orange borders. Abstract Generative models transform random noise into images; their inver...
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