Official PyTorch Code and Models of "RePaint: Inpainting using Denoising Diffusion Probabilistic Models", CVPR 2022 - andreas128/RePaint Jan 24, 2022 · In this work, we propose RePaint: A Denoising Diffusion Probabilistic Model (DDPM) based inpainting approach that is applicable to even extreme masks. We employ a pretrained . 1 RePaint [1] RePaint是2022年CVPR上一种利用 DDPM 模型做Inpainting的算法，其最关键的就是如何将已知信息融入到DDPM的逆向过程中去，从而得到带有已知信息的新的采样完成修复。
Jun 17, 2025 · RePaint 是由 Lugmayr 等人在《RePaint: Inpainting using Denoising Diffusion Probabilistic Models》中提出的用于图像 Inpainting 的扩散方法。 其主要创新在于 非单调采样调度机 . We propose RePaint: an inpainting method that solely leverages an off-the-shelf unconditionally trained DDPM. Specifically, instead of learning a mask-conditional gener-ative model, we condition the . Free-form inpainting is the task of adding new content to an image in the regions specified by an arbitrary binary mask. Most existing approaches train for a certain distribution of masks, which limits .
Repaint is an AI website builder that creates fully designed, multi-page websites from a conversation. You describe your business, Repaint asks follow-up questions, researches your business online, and . 在这项工作中，提出了 RePaint：一种基于去噪扩散概率模型 (DDPM) 的修复方法，甚至适用于极端掩码。 采用预训练的无条件DDPM作为生成先验，为了条件生成只使用给定的图像信息对未屏蔽区域进 . We validate our method for both faces and general-purpose image inpainting using standard and extreme masks. RePaint outperforms state-of-the-art Autoregressive, and GAN approaches for at .
In this work, we propose RePaint.
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