Video Denoising

30 papers with code • 12 benchmarks • 6 datasets

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Most implemented papers

FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation

m-tassano/fastdvdnet 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

anchen1011/toflow 24 Nov 2017

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

Modular proximal optimization for multidimensional total-variation regularization

albarji/proxTV 3 Nov 2014

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 26 Jan 2021

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 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

jingyunliang/rvrt 5 Jun 2022

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 30 Nov 2018

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 15 Apr 2019

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 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

wenbihan/salt_iccv2017 ICCV 2017

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.