Video Enhancement
39 papers with code • 1 benchmarks • 5 datasets
Benchmarks
These leaderboards are used to track progress in Video Enhancement
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
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BVI-DVC
LDV
Vident-lab
Most implemented papers
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
xinntao/EDVR
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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
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
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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
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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
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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
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
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
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
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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
Finally, experiments validate the effectiveness and generalization ability of our MFQE approach in advancing the state-of-the-art quality enhancement of compressed video.
