DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High Resolution Video

Video Subject Inpainting: A Posture-Based Method

Despite recent advances in video inpainting techniques, reconstructing large missing regions of a moving subject while its scale changes remains an elusive goal. In this paper, we have introduced a scale-change invariant method for large missing regions to tackle this problem. Using this framework, first the moving foreground is separated from the background and its scale is equalized. Then, a ...

A Temporally-Aware Interpolation Network for Video Frame Inpainting

We propose the first deep learning solution to video frame inpainting, a challenging instance of the general video inpainting problem with applications in video editing, manipulation, and forensics. Our task is less ambiguous than frame interpolation and video prediction because we have access to both the temporal context and a partial glimpse of the future, allowing us to better evaluate the q...

Video Inpainting

Video Inpainting

This Video inpainting is an important video enhancement technique used to facilitate the repair or editing of digital videos. In this paper, we propose a video inpainting algorithm for repairing damaged content in digitized video films, focusing on maintaining good spatiotemporal continuity. The proposed algorithm utilizes key techniques.

Image Inpainting for High-Resolution Textures using CNN Texture Synthesis

Deep neural networks have been successfully applied to problems such as image segmentation, image super-resolution, coloration and image inpainting. In this work we propose the use of convolutional neural networks (CNN) for image inpainting of large regions in high-resolution textures. Due to limited computational resources processing high-resolution images with neural networks is still an open...