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Awesome-Denoise
One-paper-one-short-contribution-summary of all latest image/burst/video Denoising papers with code & citation published in top conference and journal.
https://github.com/oneTaken/Awesome-Denoise
Last synced: 5 days ago
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benchmark dataset
- A High-Quality Denoising Dataset for Smartphone Cameras
- broken dataset link
- Real-world Noisy Image Denoising: A New Benchmark
- Learning to see in the dark
- Benchmarking Denoising Algorithms with Real Photographs
- homepage
- A Holistic Approach to Cross-Channel Image Noise Modeling and its Application to Image Denoising
- Unsupervised deep video denoising
- code
- Noise2void-learning denoising from single noisy images
- Noise2self: Blind denoising by self-supervision
- High-quality self-supervised deep image denoising
- Unsupervised image noise modeling with self-consistent GAN
- Noisy-as-clean: Learning self-supervised denoising from corrupted image
- Self2self with dropout: Learning self-supervised denoising from single image
- Noisier2noise: Learning to denoise from unpaired noisy data
- Noise2Same: Optimizing a self-supervised bound for image denoising
- Noise2score: tweedie's approach to self-supervised image denoising without clean images
- Neighbor2neighbor: Self-supervised denoising from single noisy images
- Recorrupted-to-recorrupted: unsupervised deep learning for image denoising
- Ap-bsn: Self-supervised denoising for real-world images via asymmetric pd and blind-spot network
- CVF-SID: Cyclic multi-variate function for self-supervised image denoising by disentangling noise from image
- Self-supervised deep image restoration via adaptive stochastic gradient langevin dynamics
- Noise distribution adaptive self-supervised image denoising using tweedie distribution and score matching
- Blind2unblind: Self-supervised image denoising with visible blind spots
- Idr: Self-supervised image denoising via iterative data refinement
- Spatially Adaptive Self-Supervised Learning for Real-World Image Denoising
- LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising
- Zero-Shot Noise2Noise: Efficient Image Denoising Without Any Data
- Patch-Craft Self-Supervised Training for Correlated Image Denoising
- Unleashing the Power of Self-Supervised Image Denoising: A Comprehensive Review
- Random Sub-Samples Generation for Self-Supervised Real Image Denoising
- Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoising
- Unsupervised Image Denoising in Real-World Scenarios via Self-Collaboration Parallel Generative Adversarial Branches
- Matlab
- Matlab
- Tensorflow
- RENOIR–A dataset for real low-light image noise reduction
- Real-world Noisy Image Denoising: A New Benchmark
- Noisy-as-clean: Learning self-supervised denoising from corrupted image
- Unsupervised image noise modeling with self-consistent GAN
- Probabilistic noise2void: Unsupervised content-aware denoising
-
2020
- Noisy-As-Clean: Learning Self-supervised Denoising from Corrupted Image - As-Clean-TIP2020)|47|
- Blind universal Bayesian image denoising with Gaussian noise level learning - |43|
- Deep Graph-Convolutional Image Denoising - |64|
- NLH : A Blind Pixel-level Non-local Method for Real-world Image Denoising - |34|
- Image Denoising via Sequential Ensemble Learning - |13|
- Memory-Efficient Hierarchical Neural Architecture Search for Image Denoising - |33|
- A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising
- Supervised Raw Video Denoising With a Benchmark Dataset on Dynamic Scenes - cong/RViDeNet)|26|Both|Video|Real|
- Transfer Learning From Synthetic to Real-Noise Denoising With Adaptive Instance Normalization - |60|
- Self2Self With Dropout: Learning Self-Supervised Denoising From Single Image - |73|
- Noisier2Noise: Learning to Denoise From Unpaired Noisy Data - |40|
- Joint Demosaicing and Denoising With Self Guidance - |26|
- FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation - |72|RGB|Video|AWGN|
- CycleISP: Real Image Restoration via Improved Data Synthesis
- Basis Prediction Networks for Effective Burst Denoising With Large Kernels - |18|
- Superkernel Neural Architecture Search for Image Denoising - |5|
- Spatial-Adaptive Network for Single Image Denoising - |34|
- A Decoupled Learning Scheme for Real-world Burst Denoising from Raw Images - |3|
- Burst Denoising via Temporally Shifted Wavelet Transforms - |0|
- Unpaired Learning of Deep Image Denoising
- Dual Adversarial Network: Toward Real-world Noise Removal and Noise Generation
- Learning Camera-Aware Noise Models - NoiseGAN)|9|
- Practical Deep Raw Image Denoising on Mobile Devices - research/PMRID)|15|Raw|Single|PG|
- Reconstructing the Noise Manifold for Image Denoising - |2|
- Deep Learning on Image Denoising : An Overview - |247|
- Identifying recurring patterns with deep neural networks for natural image denoising - |11|
- Attention Mechanism Enhanced Kernel Prediction Networks for Denoising of Burst Images - bingo/Attention-Mechanism-Enhanced-KPN)|4|
- Low-light Image Restoration with Short- and Long-exposure Raw Pairs - |6|
- Learning Deformable Kernels for Image and Video Denoising - |24|
-
2019
- Optimal combination of image denoisers - |13|
- High ISO JPEG Image Denoising by Deep Fusion of Collaborative and Convolutional Filtering - |6|
- Texture variation adaptive image denoising with nonlocal PCA - |11|
- Color Image and Multispectral Image Denoising Using Block Diagonal Representation - |7|
- Real-world Image Denoising with Deep Boosting
- Variational Denoising Network: Toward Blind Noise Modeling and Removal - |110|
- High-Quality Self-Supervised Deep Image Denoising - |138|
- Noise2Self: Blind Denoising by Self-Supervision
- Plug-and-play methods provably converge with properly trained denoisers - |125|
- Unsupervised Domain Adaptation for ToF Data Denoising with Adversarial Learning - |26|
- Robust Subspace Clustering with Independent and Piecewise Identically Distributed Noise Modeling - |15|
- Toward convolutional blind denoising of real photographs
- FOCNet: A Fractional Optimal Control Network for Image Denoising - |62|
- Noise2void-learning denoising from single noisy images - |406|
- Unprocessing images for learned raw denoising - |186|
- Training deep learning based image denoisers from undersampled measurements without ground truth and without image prior - |28|
- Model-blind video denoising via frame-to-frame training - denoising)|44|
- Self-Guided Network for Fast Image Denoising - |78|
- Noise flow: Noise modeling with conditional normalizing flows - |74|
- Joint Demosaicking and Denoising by Fine-Tuning of Bursts of Raw Images - |34|
- Fully Convolutional Pixel Adaptive Image Denoiser - AIDE-Keras)|27|
- Enhancing Low Light Videos by Exploring High Sensitivity Camera Noise - |14|
- CIIDefence: Defeating Adversarial Attacks by Fusing Class-Specific Image Inpainting and Image Denoising - |21|
- Real Image Denoising with Feature Attention - |192|
- GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise Modeling - |65|
- Learning raw image denoising with bayer pattern unification and bayer preserving augmentation - |29|
- Deep iterative down-up CNN for image denoising - |69|
- Densely Connected Hierarchical Network for Image Denoising - |55|
- ViDeNN: Deep Blind Video Denoising - |42|
- Real Photographs Denoising With Noise Domain Adaptation and Attentive Generative Adversarial Network - |15|
- Learning Deep Image Priors for Blind Image Denoising - |4|
- DVDnet: A fast network for deep video denoising - tassano/dvdnet)|45|RGB|Video|AWGN|
- Multi-kernel prediction networks for denoising of burst images - |17|
- When AWGN-based Denoiser Meets Real Noises - Denoising-pytorch)|29|
- Generating training data for denoising real rgb images via camera pipeline simulation - |19|
- Gan2gan: Generative noise learning for blind image denoising with single noisy images - |12|
- Learning Deformable Kernels for Image and Video Denoising - |24|
- Gan2gan: Generative noise learning for blind image denoising with single noisy images - |12|
- Optimal combination of image denoisers - |13|
- Variational Denoising Network: Toward Blind Noise Modeling and Removal - |110|
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2018
- Time-of-Flight Range Measurement in Low- sensing Environment : Noise Analysis and Complex-domain Non-local Denoising - |10|
- Statistical Nearest Neighbors for Image Denoising - |29|
- Joint Denoising / Compression of Image Contours via Shape Prior and Context Tree - |5|
- Image Restoration by Iterative Denoising and Backward Projections - |110|
- FFDNet: Toward a fast and flexible solution for CNN-based image denoising
- External prior guided internal prior learning for real-world noisy image denoising - |92|
- Class-aware fully convolutional Gaussian and Poisson denoising
- VIDOSAT: High-dimensional sparsifying transform learning for online video denoising - |23|
- Effective and fast estimation for image sensor noise via constrained weighted least squares - |20|
- Training deep learning based denoisers without ground truth data - |75|
- Burst denoising with kernel prediction networks - |224|
- Image Blind Denoising With Generative Adversarial Network Based Noise Modeling - |352|
- Universal Denoising Networks : A Novel CNN Architecture for Image Denoising - skoltech/UDNet)|209|
- Deep burst denoising - |74|
- Deep boosting for image denoising - |50|
- A trilateral weighted sparse coding scheme for real-world image denoising - |180|
- Deep image demosaicking using a cascade of convolutional residual denoising networks - |68|
- When image denoising meets high-level vision tasks: A deep learning approach - |160|
- Convolutional neural networks for noniterative reconstruction of compressively sensed images - |83|
- Dn-resnet: Efficient deep residual network for image denoising - |22|
- Image Denoising for Image Retrieval by Cascading a Deep Quality Assessment Network - |9|
- Correction by projection: Denoising images with generative adversarial networks - |47|
- Non-local video denoising by CNN
- Fully convolutional pixel adaptive image denoiser - |27|
- Fast, trainable, multiscale denoising - |6|
- Deep learning for image denoising: a survey - |90|
- RENOIR–A dataset for real low-light image noise reduction - |106|
- Noise2Noise: Learning Image Restoration without Clean Data - |758|
- Connecting image denoising and high-level vision tasks via deep learning - |70|
- Time-of-Flight Range Measurement in Low- sensing Environment : Noise Analysis and Complex-domain Non-local Denoising - |10|
- Effective and fast estimation for image sensor noise via constrained weighted least squares - |20|
- Iterative residual network for deep joint image demosaicking and denoising - |9|
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2017
- Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising - |4387|
- Affine Non-Local Means Image Denoising - |39|
- Image Denoising via CNNs: An Adversarial Approach - |71|
- Non-local color image denoising with convolutional neural networks - |274|
- Learning Deep CNN Denoiser Prior for Image Restoration - |1277|
- Learning Proximal Operators : Using Denoising Networks for Regularizing Inverse Imaging Problems - |246|
- Multi-channel Weighted Nuclear Norm Minimization for Real Color Image Denoising - |230|
- Joint Adaptive Sparsity and Low-Rankness on the Fly: An Online Tensor Reconstruction Scheme for Video Denoising - |40|
- Blob Reconstruction Using Unilateral Second Order Gaussian Kernels with Application to High-ISO Long-Exposure Image Denoising - |10|
- Image denoising using group sparsity residual and external nonlocal self-similarity prior - |7|
- Block-matching convolutional neural network for image denoising - |50|
- Learning pixel-distribution prior with wider convolution for image denoising
- Chaining identity mapping modules for image denoising - |12|
- Dilated deep residual network for image denoising - |73|
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before 2017
- Deep Gaussian conditional random field network: A model-based deep network for discriminative denoising - |68|
- From Noise Modeling to Blind Image Denoising - |67|
- An efficient statistical method for image noise level estimation - |184|
- The noise clinic: a blind image denoising algorithm - |112|
- Photon, Poisson Noise - |107|
- Image denoising: Can plain neural networks compete with BM3D? - |1246|
- Clipped noisy images: Heteroskedastic modeling and practical denoising - |129|
- Practical Poissonian-Gaussian noise modeling and fitting for single-image raw-data
- Image denoising by sparse 3-D transform-domain collaborative filtering - |7357|
- Automatic estimation and removal of noise from a single image - |599|
- A non-local algorithm for image denoising - |7477|
- Clipped noisy images: Heteroskedastic modeling and practical denoising - |129|
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