Video Denoising
30 papers with code • 12 benchmarks • 6 datasets
Benchmarks
These leaderboards are used to track progress in Video Denoising
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DAVIS
CRVD
VideoLQ
Most implemented papers
Efficient Multi-Stage Video Denoising with Recurrent Spatio-Temporal Fusion
Baymax-chen/EMVD
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CVPR 2021
Then, a denoising stage removes the noise in the fused frame.
Patch Craft: Video Denoising by Deep Modeling and Patch Matching
grishavak/PaCNet-denoiser
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ICCV 2021
Our algorithm augments video sequences with patch-craft frames and feeds them to a CNN.
VRT: A Video Restoration Transformer
jingyunliang/vrt
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Besides, parallel warping is used to further fuse information from neighboring frames by parallel feature warping.
MANet: Improving Video Denoising with a Multi-Alignment Network
In video denoising, the adjacent frames often provide very useful information, but accurate alignment is needed before such information can be harnassed.
Unidirectional Video Denoising by Mimicking Backward Recurrent Modules with Look-ahead Forward Ones
nagejacob/flornn
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However, BiRNN is intrinsically offline because it uses backward recurrent modules to propagate from the last to current frames, which causes high latency and large memory consumption.
A Simple Baseline for Video Restoration with Grouped Spatial-temporal Shift
dasongli1/shift-net
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CVPR 2023
In this study, we propose a simple yet effective framework for video restoration.
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super Resolution
xiaogang00/dp3df
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Despite the quality improvement brought by the recent methods, video super-resolution (SR) is still very challenging, especially for videos that are low-light and noisy.
Real-time Streaming Video Denoising with Bidirectional Buffers
Recent multi-output inference works propagate the bidirectional temporal feature with a parallel or recurrent framework, which either suffers from performance drops on the temporal edges of clips or can not achieve online inference.
Real-time Controllable Denoising for Image and Video
Controllable image denoising aims to generate clean samples with human perceptual priors and balance sharpness and smoothness.
Toward Accurate and Temporally Consistent Video Restoration from Raw Data
Extensive experiments demonstrate the leading VJDD performance of our method in term of restoration accuracy, perceptual quality and temporal consistency.
