Edicho: Consistent Image Editing in the Wild

• URL: http://arxiv.org/abs/2412.21079v3
• Date: Tue, 14 Jan 2025 08:23:30 GMT
• Title: Edicho: Consistent Image Editing in the Wild
• Authors: Qingyan Bai, Hao Ouyang, Yinghao Xu, Qiuyu Wang, Ceyuan Yang, Ka Leong Cheng, Yujun Shen, Qifeng Chen,
• Abstract summary: Edicho steps in with a training-free solution based on diffusion models. It features a fundamental design principle of using explicit image correspondence to direct editing.
• Score: 90.42395533938915
• License:
• Abstract: As a verified need, consistent editing across in-the-wild images remains a technical challenge arising from various unmanageable factors, like object poses, lighting conditions, and photography environments. Edicho steps in with a training-free solution based on diffusion models, featuring a fundamental design principle of using explicit image correspondence to direct editing. Specifically, the key components include an attention manipulation module and a carefully refined classifier-free guidance (CFG) denoising strategy, both of which take into account the pre-estimated correspondence. Such an inference-time algorithm enjoys a plug-and-play nature and is compatible to most diffusion-based editing methods, such as ControlNet and BrushNet. Extensive results demonstrate the efficacy of Edicho in consistent cross-image editing under diverse settings. We will release the code to facilitate future studies.

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