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2024

Fill in the ____ (a Diffusion-based Image Inpainting Pipeline)

Gebre, Eyoel, Saxena, Krishna, Tran, Timothy

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Understand

Image inpainting is the process of taking an image and generating lost or intentionally occluded portions.

Inpainting has countless applications including restoring previously damaged pictures, restoring the quality of images that have been degraded due to compression, and removing unwanted objects/text.
Modern inpainting techniques have shown remarkable ability in generating sensible completions for images with mask occlusions.
In our paper, an overview of the progress of inpainting techniques will be provided, along with identifying current leading approaches, focusing on their strengths and weaknesses.

Fill in the ____ (a Diffusion-based Image Inpainting Pipeline) · Around

Built on

Deep residual learning for image recognition, 2015
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Earlier work this paper cites.
Diffusion models beat gans on image synthesis, 2021
Prafulla Dhariwal and Alex Nichol · 2021
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