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New AID method improves image inpainting with diffusion models

Researchers have developed a new method called Amortized Inpainting with Diffusion (AID) for image inpainting using pretrained diffusion models. AID trains a small, reusable guidance module offline, which can then be applied to masked images without per-instance optimization. This approach offers an improved quality-speed trade-off compared to existing methods, with minimal trainable overhead. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Offers a more efficient approach to image inpainting, potentially improving generative model applications.

RANK_REASON The cluster contains an academic paper detailing a new method for image inpainting using diffusion models. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

COVERAGE [1]

  1. arXiv cs.CV TIER_1 · Xun Yu Zhou ·

    Amortized Guidance for Image Inpainting with Pretrained Diffusion Models

    We study image inpainting with generative diffusion models. Existing methods typically either train dedicated task-specific models, or adapt a pretrained diffusion model separately for each masked image at deployment. We introduce a middle-ground model, termed Amortized Inpaintin…