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title
Zero-shot Image-to-Image Translation
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Zero-shot Image-to-Image Translation
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site name
author
updated
2026-03-04 12:16:01
raw text
Zero-shot Image-to-Image Translation Zero-shot Image-to-Image Translation Gaurav Parmar 1 Krishna Kumar Singh 2 Richard Zhang 2 Yijun Li 2 Jingwan Lu 2 Jun-Yan Zhu 1 1 Carnegie Mellon University 2 Adobe Research SIGGRAPH 2023 [Paper] | [Code] | [Demo] | [Talk] We propose pix2pix-zero , a diffusion-based image-to-image approach that allows users to specify the edit direction on-the-fly (e.g., cat to dog). Our method can directly use pre-trained text-to-image diffusion models, such as Stable Diffusion, for editing real and synthetic images while preserving the input image's structure. Our method is training-free and prompt-free, as it requires neither manual text prompting for each input image nor costly fine-tuning for each task. TL;DR: no finetuning required; no text input needed; input structure preserved . Abstract Large-scale text-to-image generative models have shown thei...
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