Video Denoising
30 papers with code • 12 benchmarks • 5 datasets
Benchmarks
These leaderboards are used to track progress in Video Denoising
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DAVIS
CRVD
VideoLQ
Most implemented papers
FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation
m-tassano/fastdvdnet
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CVPR 2020
In this paper, we propose a state-of-the-art video denoising algorithm based on a convolutional neural network architecture.
Video Enhancement with Task-Oriented Flow
Many video enhancement algorithms rely on optical flow to register frames in a video sequence.
Modular proximal optimization for multidimensional total-variation regularization
We study \emph{TV regularization}, a widely used technique for eliciting structured sparsity.
Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video Denoising
jojo23333/STPAN
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We present a spatial pixel aggregation network and learn the pixel sampling and averaging strategies for image denoising.
NeRV: Neural Representations for Videos
haochen-rye/nerv
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NeurIPS 2021
In contrast, with NeRV, we can use any neural network compression method as a proxy for video compression, and achieve comparable performance to traditional frame-based video compression approaches (H. 264, HEVC \etc).
Recurrent Video Restoration Transformer with Guided Deformable Attention
Specifically, RVRT divides the video into multiple clips and uses the previously inferred clip feature to estimate the subsequent clip feature.
Non-Local Video Denoising by CNN
axeldavy/vnlnet
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To the best of our knowledge, this is the first successful application of a CNN to video denoising.
Learning Deformable Kernels for Image and Video Denoising
jojo23333/STPAN
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Most of the classical denoising methods restore clear results by selecting and averaging pixels in the noisy input.
Deep Video Inpainting
mcahny/Deep-Video-Inpainting
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CVPR 2019
Video inpainting aims to fill spatio-temporal holes with plausible content in a video.
Joint Adaptive Sparsity and Low-Rankness on the Fly: An Online Tensor Reconstruction Scheme for Video Denoising
In this work, we propose a novel video denoising method, based on an online tensor reconstruction scheme with a joint adaptive sparse and low-rank model, dubbed SALT.
