Video Inpainting

23 papers with code • 2 benchmarks • 6 datasets

The goal of Video Inpainting is to fill in missing regions of a given video sequence with contents that are both spatially and temporally coherent. Video Inpainting, also known as video completion, has many real-world applications such as undesired object removal and video restoration.

Source: Deep Flow-Guided Video Inpainting

Most implemented papers

Free-form Video Inpainting with 3D Gated Convolution and Temporal PatchGAN

amjltc295/Free-Form-Video-Inpainting ICCV 2019

Free-form video inpainting is a very challenging task that could be widely used for video editing such as text removal.

Deep Video Inpainting

mcahny/Deep-Video-Inpainting CVPR 2019

Video inpainting aims to fill spatio-temporal holes with plausible content in a video.

Deep Flow-Guided Video Inpainting

nbei/Deep-Flow-Guided-Video-Inpainting CVPR 2019

Then the synthesized flow field is used to guide the propagation of pixels to fill up the missing regions in the video.

Learnable Gated Temporal Shift Module for Deep Video Inpainting

amjltc295/Free-Form-Video-Inpainting 2 Jul 2019

How to efficiently utilize temporal information to recover videos in a consistent way is the main issue for video inpainting problems.

DVI: Depth Guided Video Inpainting for Autonomous Driving

sibozhang/Depth-Guided-Inpainting ECCV 2020

To get clear street-view and photo-realistic simulation in autonomous driving, we present an automatic video inpainting algorithm that can remove traffic agents from videos and synthesize missing regions with the guidance of depth/point cloud.

Learning Joint Spatial-Temporal Transformations for Video Inpainting

researchmm/STTN ECCV 2020

In this paper, we propose to learn a joint Spatial-Temporal Transformer Network (STTN) for video inpainting.

Improving Video Generation for Multi-functional Applications

bernhard2202/improved-video-gan 30 Nov 2017

In this paper, we aim to improve the state-of-the-art video generative adversarial networks (GANs) with a view towards multi-functional applications.

A Temporally-Aware Interpolation Network for Video Frame Inpainting

sunxm2357/TAI_video_frame_inpainting 20 Mar 2018

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.

Fast and Accurate Tensor Completion with Total Variation Regularized Tensor Trains

IRENEKO/TTC 17 Apr 2018

We propose a new tensor completion method based on tensor trains.

Deep Blind Video Decaptioning by Temporal Aggregation and Recurrence

shwoo93/video_decaptioning CVPR 2019

Blind video decaptioning is a problem of automatically removing text overlays and inpainting the occluded parts in videos without any input masks.