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Image Denoising

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하위 태스크: 2
평가표: 21
보존된 평가 기록: 110

Image Denoising is a computer vision task that involves removing noise from an image. Noise can be introduced into an image during acquisition or processing, and can reduce image quality and make it difficult to interpret. Image denoising techniques aim to restore an image to its original quality by reducing or removing the noise, while preserving the important features of the image.

<span style="color:grey; opacity: 0.6">( Image credit: Wide Inference Network for Image Denoising via Learning Pixel-distribution Prior )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/csjunxu/Noisy-As-Clean

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Noisy-As-Clean: Learning Self-supervised Denoising from the Corrupted Image

https://github.com/csjunxu/PolyUDataset

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Real-world Noisy Image Denoising: A New Benchmark

https://github.com/csm9493/FC-AIDE-Keras

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Fully Convolutional Pixel Adaptive Image Denoiser

https://github.com/csm9493/GAN2GAN

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GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images

https://github.com/cswin/RC-Nets

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Image Restoration Using Deep Regulated Convolutional Networks

https://github.com/cswin/WIN

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Wide Inference Network for Image Denoising via Learning Pixel-distribution Prior

https://github.com/cszn/DnCNN

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Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

https://github.com/cszn/FFDNet

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FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising

https://github.com/cszn/ircnn

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Learning Deep CNN Denoiser Prior for Image Restoration

https://github.com/cszn/scunet

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Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis

https://github.com/cubeyoung/Noise2Score

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Noise2Score: Tweedie's Approach to Self-Supervised Image Denoising without Clean Images

https://github.com/cvc-lab/patch-subspace-learning-autoencoder

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Deep Contrastive Patch-Based Subspace Learning for Camera Image Signal Processing

https://github.com/danielement321/fm2s

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FM2S: Towards Spatially-Correlated Noise Modeling in Zero-Shot Fluorescence Microscopy Image Denoising

https://github.com/dannie125/mm-bsn

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MM-BSN: Self-Supervised Image Denoising for Real-World with Multi-Mask based on Blind-Spot Network

https://github.com/daqians/charformer

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CharFormer: A Glyph Fusion based Attentive Framework for High-precision Character Image Denoising

https://github.com/dasongli1/learning_degradation

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Learning Degradation Representations for Image Deblurring

https://github.com/daviddmc/Deform2Self

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Deformed2Self: Self-Supervised Denoising for Dynamic Medical Imaging

https://github.com/deepxuan/dn-dp

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Diffusion Probabilistic Priors for Zero-Shot Low-Dose CT Image Denoising

https://github.com/demonsjin/blind2unblind

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Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots

https://github.com/dennishein/cpfgmpp_pcct_denoising

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PPFM: Image denoising in photon-counting CT using single-step posterior sampling Poisson flow generative models

https://github.com/dhryougit/learning-to-translate-noise

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Learning to Translate Noise for Robust Image Denoising

https://github.com/dichao-liu/anti-noise_fgvr

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Progressive Multi-task Anti-Noise Learning and Distilling Frameworks for Fine-grained Vehicle Recognition

https://github.com/diegovalsesia/gcdn

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Image Denoising with Graph-Convolutional Neural Networks

https://github.com/divelab/Noise2Same

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Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising

https://github.com/ds2p/crsae

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Deep Residual Autoencoders for Expectation Maximization-inspired Dictionary Learning

https://github.com/ds2p/dea

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Convolutional dictionary learning based auto-encoders for natural exponential-family distributions

https://github.com/duanhuiyu/maeip_csformer

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Masked Autoencoders as Image Processors

https://github.com/duanlab123/curvpnp

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CurvPnP: Plug-and-play Blind Image Restoration with Deep Curvature Denoiser

https://github.com/duanlab123/mgmc

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Fast Multi-grid Methods for Minimizing Curvature Energy

https://github.com/dujiazhi/CFMNet

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Flexible Image Denoising with Multi-layer Conditional Feature Modulation

https://github.com/dvlab-research/Simple-SR

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LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and Beyond

https://github.com/echonet/image_quality

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EchoNet-Quality: Denoising Echocardiograms via Deep Generative Modeling of Ultrasound Noise

https://github.com/edibert4imagemanipulation/edibert

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EdiBERT, a generative model for image editing

https://github.com/eth-siplab/rap

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Restore Anything Pipeline: Segment Anything Meets Image Restoration

https://github.com/faebstn96/helix2fan

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On the Benefit of Dual-domain Denoising in a Self-supervised Low-dose CT Setting

https://github.com/fahimzaman/ldseg

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Latent Diffusion for Medical Image Segmentation: End to end learning for fast sampling and accuracy

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