Recently proposed image inpainting method LaMa builds its network upon Fast Fourier
Convolution (FFC), which was originally proposed for high-level vision tasks like image …

Although existing image inpainting approaches have been able to produce visually realistic
and semantically correct results, they produce only one result for each masked input. In …

Currently, most image inpainting algorithms based on deep learning cause information loss
when acquiring deep level features. It is not conducive to the image inpainting of texture …

Image inpainting aims to generate realistic content for missing regions of an image. Existing
methods often struggle to produce visually coherent content for missing regions of an image …

The latest methods based on deep learning have achieved amazing results regarding the
complex work of inpainting large missing areas in an image. But this type of method …

Image Inpainting has recently become an important research problem due to the rise of
generative image synthesis models. While many solutions have been proposed for this …

Existing image inpainting methods often produce artifacts when dealing with large holes in
real applications. To address this challenge, we propose an iterative inpainting method with …

Patch-based methods and deep networks have been employed to tackle image inpainting
problem, with their own strengths and weaknesses. Patch-based methods are capable of …

Image inpainting aims to complete the missing or corrupted regions of images with realistic
contents. The prevalent approaches adopt a hybrid objective of reconstruction and …

Image inpainting is an ill-posed problem to recover missing or damaged image content
based on incomplete images with masks. Previous works usually predict the auxiliary …