Papers with Code 아카이브
Image Denoising
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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/LucasElbert/FFDNet
FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising
https://github.com/Lucien66/LIPT
https://github.com/MC-E/COLA-Net-Collaborative-Attention-Network-for-Image-Restoration
COLA-Net: Collaborative Attention Network for Image Restoration
https://github.com/MKFMIKU/VIDM
Restormer: Efficient Transformer for High-Resolution Image Restoration
https://github.com/MLI-lab/Robustness-CS
https://github.com/MNaseerSubhani/MVTec-Anomaly-Detection-For-Industry
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
https://github.com/MS-Mind/MS-Code-08/tree/main/Neighbor2Neighbor
Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images
https://github.com/MatusPilnan/nsiete-project
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Deep_Image_Prior
https://github.com/Mind23-2/MindCode-101/tree/main/IndexNet
https://github.com/Mind23-2/MindCode-101/tree/main/LearningToSeeInTheDark
https://github.com/Mind23-2/MindCode-101/tree/main/Neighbor2Neighbor
Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images
https://github.com/Mind23-2/MindCode-3/tree/main/HiFaceGAN
HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
https://github.com/Mind23-2/MindCode-3/tree/main/IndexNet
https://github.com/Mind23-2/MindCode-3/tree/main/LearningToSeeInTheDark
https://github.com/Mind23-2/MindCode-3/tree/main/Neighbor2Neighbor
Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images
https://github.com/MindSpore-MS-Code2/code0/tree/main/DnCNN
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/MindSpore-paper-code-3/code4/tree/main/HiFaceGAN
HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
https://github.com/MindSpore-paper-code-3/code6/tree/main/brdnet
A Multi-Head Convolutional Neural Network With Multi-path Attention improves Image Denoising
https://github.com/MindSpore-paper-code-3/code8/tree/main/DnCNN
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/MindSpore-scientific-2/code-10/tree/main/NBNet-Noise-Basis-Learning-for-Image-Denoising-with-Subspace-Projection
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
https://github.com/MindSpore-scientific-2/code-4/tree/main/NBNet-Noise-Basis-Learning-for-Image-Denoising-with-Subspace-Projection
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
https://github.com/MindSpore-scientific-2/code-5/tree/main/NBNet-Noise-Basis-Learning-for-Image-Denoising-with-Subspace-Projection
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
https://github.com/MindSpore-scientific-2/code-8/tree/main/NBNet-Noise-Basis-Learning-for-Image-Denoising-with-Subspace-Projection
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
https://github.com/MindSpore-scientific/code-13/tree/main/NBNet-Noise-Basis-Learning-for-Image-Denoising-with-Subspace-Projection
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
https://github.com/NVlabs/selfsupervised-denoising
https://github.com/NatiOfir/DeepFaintEdges
Multi-scale Processing of Noisy Images using Edge Preservation Losses
https://github.com/OlafChrist-github/Image-Denoising-using-Keras
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
https://github.com/Ourshanabi/Burst-denoising
https://github.com/QLinhHub/Image-super-resolution
https://github.com/Rishit-dagli/MIRNet-TFJS
Learning Enriched Features for Real Image Restoration and Enhancement
https://github.com/Ryosaeba8/DLMI
https://github.com/Ryosaeba8/Medical-Imaging-LOW-DOSE-CT-DENOISING
https://github.com/SSinyu/WGAN-VGG
https://github.com/SamirMitha/Denoising
FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.