In recent years, many deep learning techniques have been applied to the image inpainting
problem: the task of filling incomplete regions of an image. However, these models struggle …

Over the last few years, deep learning techniques have yielded significant improvements in
image inpainting. However, many of these techniques fail to reconstruct reasonable …

Image inpainting is a challenging computer vision task that aims to fill in missing regions of
corrupted images with realistic contents. With the development of convolutional neural …

Image inpainting has been presented to complete missing content according to the content
of the known region. This paper proposes a novel and efficient algorithm for image …

Recently, learning-based algorithms for image inpainting achieve remarkable progress
dealing with squared or irregular holes. However, they fail to generate plausible textures …

In this paper, we propose a novel prediction-based reversible steganographic scheme
based on image inpainting. First, reference pixels are chosen adaptively according to the …

Deep learning-based methods especially using convolutional neural network (CNN) and
generative adversarial network (GAN) have achieved certain success for the task of image …

Occlusion is one of the key factors affecting the success rate of vision‐based fruit‐picking
robots. It is important to accurately locate and grasp the occluded fruit in field applications …

We present a novel formulation of exemplar-based inpainting as a global energy
optimization problem, written in terms of the offset map. The proposed energy function …

A systematic methodology is proposed for a chaotic map-based real-time video encryption
and decryption system with advanced Reduced Instruction Set Computer machine (ARM) …