https://github.com/tehret/vbm3d
Implementation of the VBM3D Video Denoising Method and Some Variants
Papers with Code 아카이브
Image Denoising
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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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/theotziol/Depth-images-Denoising
https://github.com/titu1994/Image-Super-Resolution
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
https://github.com/trougnouf/mthesis-denoise
https://github.com/tum-vision/learn_prox_ops
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/tuvovan/MIRNet---Keras
Learning Enriched Features for Real Image Restoration and Enhancement
https://github.com/txyugood/Neighbor2Neighbor_Paddle
Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images
https://github.com/txyugood/Restormer_Paddle
Restormer: Efficient Transformer for High-Resolution Image Restoration
https://github.com/utsav-akhaury/SUNet
https://github.com/ved27/RED-net
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
https://github.com/venkat2319/Mirnet
Learning Enriched Features for Real Image Restoration and Enhancement
https://github.com/vishwa91/wire
https://github.com/vztu/maxim-pytorch
https://github.com/wdayang/TED-net
https://github.com/wdayang/ctformer
https://github.com/wenbihan/vidosat_icip2015
VIDOSAT: High-dimensional Sparsifying Transform Learning for Online Video Denoising
https://github.com/wooramkang/FITVNet
First image then video: A two-stage network for spatiotemporal video denoising
https://github.com/wwhio/megmodels
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/xuxy09/texformer
Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video Denoising
https://github.com/yangyucheng000/ms_cv/tree/main/Neighbor2Neighbor
Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images
https://github.com/ys-koshelev/lgd
https://github.com/yunpeng-shi/fast-cryoem-pca
Ab-initio Contrast Estimation and Denoising of Cryo-EM Images
https://github.com/yyunon/reproducibility-project-group-71
https://github.com/z-bingo/Deformable-Kernels-For-Video-Denoising
https://github.com/z-bingo/Recurrent-Fully-Convolutional-Networks
End-to-End Denoising of Dark Burst Images Using Recurrent Fully Convolutional Networks
https://github.com/z-bingo/kernel-prediction-networks-PyTorch
Multi-Kernel Prediction Networks for Denoising of Burst Images
https://github.com/zcablii/sardet_100k
DenoDet: Attention as Deformable Multi-Subspace Feature Denoising for Target Detection in SAR Images
https://github.com/zekedran/deep_image_prior
https://github.com/zhangximing213/denoise
CycleISP: Real Image Restoration via Improved Data Synthesis
https://github.com/zhengchen1999/cat
Spatial-Spectral Transformer for Hyperspectral Image Denoising
https://github.com/zhuangpeiyu/reloc
Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis
https://github.com/zou-longkun/Depth_Denoising
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.