Video Enhancement

37 papers with code • 1 benchmarks • 4 datasets

This task has no description! Would you like to contribute one?

Most implemented papers

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

xinntao/EDVR 7 May 2019

In this work, we propose a novel Video Restoration framework with Enhanced Deformable networks, termed EDVR, to address these challenges.

Video Enhancement with Task-Oriented Flow

anchen1011/toflow 24 Nov 2017

Many video enhancement algorithms rely on optical flow to register frames in a video sequence.

Low-Light Image and Video Enhancement Using Deep Learning: A Survey

Li-Chongyi/Lighting-the-Darkness-in-the-Deep-Learning-Era-Open 21 Apr 2021

Low-light image enhancement (LLIE) aims at improving the perception or interpretability of an image captured in an environment with poor illumination.

BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment

open-mmlab/mmediting CVPR 2022

We show that by empowering the recurrent framework with the enhanced propagation and alignment, one can exploit spatiotemporal information across misaligned video frames more effectively.

Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement

ZitongYu/STVEN_rPPGNet ICCV 2019

The method includes two parts: 1) a Spatio-Temporal Video Enhancement Network (STVEN) for video enhancement, and 2) an rPPG network (rPPGNet) for rPPG signal recovery.

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Dataset and Study

RenYang-home/NTIRE21_VEnh 21 Apr 2021

In our study, we analyze the proposed methods of the challenge and several methods in previous works on the proposed LDV dataset.

Multi-Frame Quality Enhancement for Compressed Video

ryangBUAA/MFQE CVPR 2018

In this paper, we investigate that heavy quality fluctuation exists across compressed video frames, and thus low quality frames can be enhanced using the neighboring high quality frames, seen as Multi-Frame Quality Enhancement (MFQE).

MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and Enhancement

baowenbo/MEMC-Net 20 Oct 2018

Recently, a number of data-driven frame interpolation methods based on convolutional neural networks have been proposed.

MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Frame Interpolation and Enhancement

baowenbo/MEMC-Net arXiv 2018

In this work, we propose a motion estimation and motion compensation driven neural network for video frame interpolation.

MFQE 2.0: A New Approach for Multi-frame Quality Enhancement on Compressed Video

RyanXingQL/MFQEv2.0 26 Feb 2019

Finally, experiments validate the effectiveness and generalization ability of our MFQE approach in advancing the state-of-the-art quality enhancement of compressed video.