https://github.com/yunhaoyang234/patch-subspace-learning-autoencoder
공식 코드Deep Contrastive Patch-Based Subspace Learning for Camera Image Signal Processing
Papers with Code 아카이브
Image Denoising
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 보존된 평가 기록
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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/yutazhuo/diffusereg
공식 코드https://github.com/yyqqss09/ldct_denoising
공식 코드https://github.com/z-bingo/Attention-Mechanism-Enhanced-KPN
공식 코드Attention Mechanism Enhanced Kernel Prediction Networks for Denoising of Burst Images
https://github.com/zeqiang-lai/hsdt
공식 코드https://github.com/zeqiang-lai/man
공식 코드https://github.com/zfu006/tap
공식 코드Temporal As a Plugin: Unsupervised Video Denoising with Pre-Trained Image Denoisers
https://github.com/zh460045050/v2l-tokenizer
공식 코드Beyond Text: Frozen Large Language Models in Visual Signal Comprehension
https://github.com/zhangyi-3/idr
공식 코드IDR: Self-Supervised Image Denoising via Iterative Data Refinement
https://github.com/zhangyi-3/kbnet
공식 코드https://github.com/zhangyi-3/noise-synthesis
공식 코드https://github.com/zhaohaoyu376/wi-ld2nd
공식 코드WIA-LD2ND: Wavelet-based Image Alignment for Self-supervised Low-Dose CT Denoising
https://github.com/zhaomingkong/gcp-id
공식 코드https://github.com/zhaowenzhao/mcg_cnn
공식 코드https://github.com/zhengdharia/LUD-VAE
공식 코드Learn from Unpaired Data for Image Restoration: A Variational Bayes Approach
https://github.com/zhengdharia/SeNM-VAE
공식 코드SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder
https://github.com/zsyOAOA/DANet
공식 코드Dual Adversarial Network: Toward Real-world Noise Removal and Noise Generation
https://github.com/zsyOAOA/VDNet
공식 코드Variational Denoising Network: Toward Blind Noise Modeling and Removal
https://github.com/zsyOAOA/VIRNet
공식 코드https://github.com/zubaerimran/SSWL-IDN
공식 코드https://github.com/zy2219105/ct-mamba
공식 코드CT-Mamba: A Hybrid Convolutional State Space Model for Low-Dose CT Denoising
https://github.com/zylipku/IterativeImaging
공식 코드Spend Wisely: Maximizing Post-Training Gains in Iterative Synthetic Data Boostrapping
https://gitlab.telecom-paris.fr/RING/MERLIN
공식 코드As if by magic: self-supervised training of deep despeckling networks with MERLIN
https://gitlab.telecom-paris.fr/RING/SAR-CNN
공식 코드https://gitlab.telecom-paris.fr/RING/SAR2SAR
공식 코드SAR2SAR: a semi-supervised despeckling algorithm for SAR images
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/DnCNN
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HiFaceGAN
HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/IndexNet
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/RDN
https://github.com/2023-MindSpore-1/ms-code-220/tree/main/EDCN
EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising
https://github.com/2023-MindSpore-1/ms-code-6/tree/main/brdnet
A Multi-Head Convolutional Neural Network With Multi-path Attention improves Image Denoising
https://github.com/2023-MindSpore-4/Code-5/tree/main/HiFaceGAN
HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
https://github.com/2023-MindSpore-4/Code-5/tree/main/IndexNet
https://github.com/2023-MindSpore-4/Code-5/tree/main/LearningToSeeInTheDark
https://github.com/2023-MindSpore-4/Code-5/tree/main/MIMO-UNet
https://github.com/2024-MindSpore-1/Code6/tree/main/brdnet
A Multi-Head Convolutional Neural Network With Multi-path Attention improves Image Denoising
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.