Papers with Code 아카이브

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/MohammadSadeghSalehi/ISGD

공식 코드

Bilevel Learning with Inexact Stochastic Gradients

https://github.com/ND-HowardGroup/JPP_review_code_2020

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Machine learning for faster and smarter fluorescence lifetime imaging microscopy

https://github.com/ND-HowardGroup/SPIE-CNN-FLIM-Denoising

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Convolutional Neural Network Denoising in Fluorescence Lifetime Imaging Microscopy (FLIM)

https://github.com/NesterukSergey/segmentation_image_augmentation

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Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-Case

https://github.com/NicholasJohnson2020/LearningLowRankMatrices

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Predictive Low Rank Matrix Learning under Partial Observations: Mixed-Projection ADMM

https://github.com/OpenImagingLab/DualDn

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DualDn: Dual-domain Denoising via Differentiable ISP

https://github.com/RK621/Unsupervised-Restoration-PLD

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Unsupervised Image Restoration Using Partially Linear Denoisers

https://github.com/SHI-Labs/Pyramid-Attention-Networks

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Pyramid Attention Networks for Image Restoration

https://github.com/Shakarim94/Net-SURE

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Training Deep Learning Based Denoisers without Ground Truth Data

https://github.com/TalRemez/deep_class_aware_denoising

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Deep Class Aware Denoising

https://github.com/TaoHuang2018/Neighbor2Neighbor

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Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images

https://github.com/TingweiMeng/HJ_nonadditive_denoise

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On Hamilton-Jacobi PDEs and image denoising models with certain non-additive noise

https://github.com/Vandermode/NoiseModel

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A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising

https://github.com/Vandermode/QRNN3D

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3D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising

https://github.com/WHUQZhang/HSID-CNN

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Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network

https://github.com/WaveOpt-Lab/YES-bound

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Data-Aware Training Quality Monitoring and Certification for Reliable Deep Learning

https://github.com/WeishengDong/DPDNN_PyTorch

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Denoising Prior Driven Deep Neural Network for Image Restoration

https://github.com/WenCongWu/DCBDNet

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Image Blind Denoising Using Dual Convolutional Neural Network with Skip Connection

https://github.com/WenCongWu/DRANet

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Dual Residual Attention Network for Image Denoising

https://github.com/XHWXD/DBSN

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Unpaired Learning of Deep Image Denoising

https://github.com/XLearning-SCU/2025-CVPR-MaIR

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MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration

https://github.com/Yang-Liu1082/FDN

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Disentangling Noise from Images: A Flow-Based Image Denoising Neural Network

https://github.com/Yang-Liu1082/InvDN

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Invertible Denoising Network: A Light Solution for Real Noise Removal

https://github.com/Ydo-W/DparNet

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Infrared Image Deturbulence Restoration Using Degradation Parameter-Assisted Wide & Deep Learning

https://github.com/YilinLiu97/Faster-DIP-Recon

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The Devil is in the Upsampling: Architectural Decisions Made Simpler for Denoising with Deep Image Prior

https://github.com/YoungJooHan/NM-FlowGAN

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NM-FlowGAN: Modeling sRGB Noise without Paired Images using a Hybrid Approach of Normalizing Flows and GAN

https://github.com/Yuan-Jinghui/Riemannian-Optimization-on-Relaxed-Indicator-Matrix-Manifold

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Riemannian Optimization on Relaxed Indicator Matrix Manifold

https://github.com/ZHKKKe/PixelSSL

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Guided Collaborative Training for Pixel-wise Semi-Supervised Learning

https://github.com/ZhaomingKong/Denoising-Comparison

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A Comparison of Image Denoising Methods

https://github.com/ZhaomingKong/color_image_denoising

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A Brief Review of Real-World Color Image Denoising

https://github.com/ZhendongWang6/Uformer

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Uformer: A General U-Shaped Transformer for Image Restoration

https://github.com/aaberdam/AdaLISTA

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Ada-LISTA: Learned Solvers Adaptive to Varying Models

https://github.com/absDL/absDL.github.io

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Single-exposure absorption imaging of ultracold atoms using deep learning

https://github.com/abtahimajeed/checkerboarddenoiser

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Contextual Checkerboard Denoise -- A Novel Neural Network-Based Approach for Classification-Aware OCT Image Denoising

https://github.com/ader47/jittor-jieke-semantic_images_synthesis

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IIDM: Image-to-Image Diffusion Model for Semantic Image Synthesis

https://github.com/adigasu/FDPMNet

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FPD-M-net: Fingerprint Image Denoising and Inpainting Using M-Net Based Convolutional Neural Networks

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.