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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/ahendriksen/noise2inverse

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Noise2Inverse: Self-supervised deep convolutional denoising for tomography

https://github.com/akshaydudhane16/dynet

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Dynamic Pre-training: Towards Efficient and Scalable All-in-One Image Restoration

https://github.com/albarji/proxTV

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Modular proximal optimization for multidimensional total-variation regularization

https://github.com/albblgb/pusnet

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Purified and Unified Steganographic Network

https://github.com/albrateanu/AKDT

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The Tenth NTIRE 2025 Image Denoising Challenge Report

https://github.com/alexiglad/EBT

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Energy-Based Transformers are Scalable Learners and Thinkers

https://github.com/algolzw/daclip-uir

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Controlling Vision-Language Models for Multi-Task Image Restoration

https://github.com/algolzw/image-restoration-sde

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Image Restoration with Mean-Reverting Stochastic Differential Equations

https://github.com/alirezaafzalaghaei/fKAN

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fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functions

https://github.com/alwaysuu/CLIPDenoising

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Transfer CLIP for Generalizable Image Denoising

https://github.com/alwaysuu/ScoreDVI

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Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoising

https://github.com/anciukevicius/renderdiffusion

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RenderDiffusion: Image Diffusion for 3D Reconstruction, Inpainting and Generation

https://github.com/anvuongb/sde_multiplicative_noise_removal

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Perception-based multiplicative noise removal using SDEs

https://github.com/ari-dasci/autoencoder-case-studies

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An analysis on the use of autoencoders for representation learning: fundamentals, learning task case studies, explainability and challenges

https://github.com/arnisha-k/instance-specific-param

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Learning Instance-Specific Parameters of Black-Box Models Using Differentiable Surrogates

https://github.com/aurangau/ICIP2024

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A Dictionary Based Approach for Removing Out-of-Focus Blur

https://github.com/axeldavy/vnlnet

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Non-Local Video Denoising by CNN

https://github.com/benMen87/AppriximateConvolutionalSparseCoding

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Learned Convolutional Sparse Coding

https://github.com/berkiskender/RED-PSM

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RED-PSM: Regularization by Denoising of Factorized Low Rank Models for Dynamic Imaging

https://github.com/bghojogh/Curvature-Anomaly-Detection

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Anomaly Detection and Prototype Selection Using Polyhedron Curvature

https://github.com/bguedj/cobra_denoising

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Non-linear aggregation of filters to improve image denoising

https://github.com/binhpht/flashlightCNN

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Flashlight CNN Image Denoising

https://github.com/bregaldo/stat_comp_sep

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Statistical Component Separation for Targeted Signal Recovery in Noisy Mixtures

https://github.com/btolooshams/stable-interpretable-unrolled-dl

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Stable and Interpretable Unrolled Dictionary Learning

https://github.com/callsys/genpromp

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Generative Prompt Model for Weakly Supervised Object Localization

https://github.com/cammarasana123/weightedconvolution

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Optimal Density Functions for Weighted Convolution in Learning Models

https://github.com/cammarasana123/weightedconvolution2.0

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Optimal Weighted Convolution for Classification and Denosing

https://github.com/cao-cong/RViDeNet

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Supervised Raw Video Denoising with a Benchmark Dataset on Dynamic Scenes

https://github.com/cardio-ai/mfvi-dip-mia

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Posterior temperature optimized Bayesian models for inverse problems in medical imaging

https://github.com/charlesglucas/sugar_dms

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Hyperparameter selection for Discrete Mumford-Shah

https://github.com/chjinny/LAN

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LAN: Learning to Adapt Noise for Image Denoising

https://github.com/chqwer2/multi-view-self-supervised-disentanglement-denoising

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Multi-view Self-supervised Disentanglement for General Image Denoising

https://github.com/cityu-aim-group/gfbs

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Exploring Gradient Flow Based Saliency for DNN Model Compression

https://github.com/cjlee94/slice2slice

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Self-supervised OCT Image Denoising with Slice-to-Slice Registration and Reconstruction

https://github.com/conor-horgan/spectrai

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spectrai: A deep learning framework for spectral data

https://github.com/csguoh/adaptir

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Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts

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