In particular the architecture and the loss function used for the model have been thought on the basis of the project's requirements and instructions: The purpose of this project is to build and train ...

Recent deep learning approaches to Image Inpainting have taken over the statistical methods which solely were based on searching for identical patches in the valid regions. These methods fail to ...

Abstract: Image inpainting is one of the most important ways to enhance corrupted digital images or pictures with missing pixels. For this purpose, different methods have been proposed. Some methods ...

Image inpainting is one of the classic problems in computer vision ... The BrushNet framework then extracts the masked image latent from the masked image using a Variational AutoEncoder. Furthermore, ...

and finally we arrive at the inpainting-specific super resolution technique. Stable Diffusion is a diffusion model that operates within the latent space of an autoencoder. For text to image synthesis, ...

Learn how to use different approaches and techniques to improve the speed and efficiency of image inpainting algorithms for photo editing, restoration, and enhancement. Skip to main content LinkedIn ...