Video Restoration

20 papers with code • 0 benchmarks • 3 datasets

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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.

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.

Progressive Training of A Two-Stage Framework for Video Restoration

ryanxingql/winner-ntire22-vqe 21 Apr 2022

As a widely studied task, video restoration aims to enhance the quality of the videos with multiple potential degradations, such as noises, blurs and compression artifacts.

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.

Spatio-temporal deformable convolution for compressed video quality enhancement

RyanXingQL/STDF-PyTorch 3 Apr 2020

Recent years have witnessed remarkable success of deep learning methods in quality enhancement for compressed video.

Influence-guided Data Augmentation for Neural Tensor Completion

srijankr/dain 23 Aug 2021

In this paper, we propose DAIN, a general data augmentation framework that enhances the prediction accuracy of neural tensor completion methods.

DeMFI: Deep Joint Deblurring and Multi-Frame Interpolation with Flow-Guided Attentive Correlation and Recursive Boosting

JihyongOh/DeMFI 19 Nov 2021

In this paper, we propose a novel joint deblurring and multi-frame interpolation (DeMFI) framework, called DeMFI-Net, which accurately converts blurry videos of lower-frame-rate to sharp videos at higher-frame-rate based on flow-guided attentive-correlation-based feature bolstering (FAC-FB) module and recursive boosting (RB), in terms of multi-frame interpolation (MFI).

Revisiting Temporal Alignment for Video Restoration

redrock303/revisiting-temporal-alignment-for-video-restoration CVPR 2022

Long-range temporal alignment is critical yet challenging for video restoration tasks.

Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring

xjtu-cvlab-lowlevel/rnn-mbp 9 Dec 2021

Instead of estimating alignment information, we propose a simple and effective deep Recurrent Neural Network with Multi-scale Bi-directional Propagation (RNN-MBP) to effectively propagate and gather the information from unaligned neighboring frames for better video deblurring.

Transcoded Video Restoration by Temporal Spatial Auxiliary Network

icecherylxuli/tsan 15 Dec 2021

In most video platforms, such as Youtube, and TikTok, the played videos usually have undergone multiple video encodings such as hardware encoding by recording devices, software encoding by video editing apps, and single/multiple video transcoding by video application servers.