Papers with Code 아카이브
Image Denoising
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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/jiaxi-jiang/fbcnn
공식 코드https://github.com/jingyunliang/swinir
공식 코드https://github.com/jjhuangcs/WINNet
공식 코드WINNet: Wavelet-inspired Invertible Network for Image Denoising
https://github.com/jojo23333/STPAN
공식 코드https://github.com/jonathanventura/self-supervised-poisson-gaussian
공식 코드https://github.com/jsshin98/ssgnet
공식 코드https://github.com/juglab/ppn2v
공식 코드https://github.com/junaidmalik09/rwdenoise
공식 코드Convolutional versus Self-Organized Operational Neural Networks for Real-World Blind Image Denoising
https://github.com/junyuchen245/Active-Contour-Wavelet-Seg
공식 코드Feature-Based Image Clustering and Segmentation Using Wavelets
https://github.com/jwen307/quality_uq
공식 코드Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems
https://github.com/jzsherlock4869/denoise-ignet
공식 코드Exploring Inter-frequency Guidance of Image for Lightweight Gaussian Denoising
https://github.com/k-radlak/IDCNN
공식 코드Deep Learning based Switching Filter for Impulsive Noise Removal in Color Images
https://github.com/kaiyangshi-ito/nonconvexag
공식 코드Accelerated Gradient Methods for Sparse Statistical Learning with Nonconvex Penalties
https://github.com/kimiandj/slicedwass_abc
공식 코드Approximate Bayesian Computation with the Sliced-Wasserstein Distance
https://github.com/kornia/kornia
공식 코드Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
https://github.com/krennic999/mpi
공식 코드https://github.com/krulllab/DVLAE
공식 코드Unsupervised Denoising for Signal-Dependent and Row-Correlated Imaging Noise
https://github.com/krulllab/cosdd
공식 코드Unsupervised Denoising for Signal-Dependent and Row-Correlated Imaging Noise
https://github.com/krulllab/gap
공식 코드https://github.com/labforcomputationalvision/memorization_generalization_in_diffusion_models
공식 코드Generalization in diffusion models arises from geometry-adaptive harmonic representations
https://github.com/laowangbobo/residual_mlp_cnn_mixer
공식 코드https://github.com/lcbkmm/tc-kanrecon
공식 코드https://github.com/li-tong-621/dmid
공식 코드Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling
https://github.com/linxin0/scpgabnet
공식 코드https://github.com/liuhanze623/adarenet
공식 코드Rotation-Equivariant Self-Supervised Method in Image Denoising
https://github.com/liwenchao0615/zerrinnet
공식 코드Zero-Shot Enhancement of Low-Light Image Based on Retinex Decomposition
https://github.com/liyinibristol/Zero-TIG
공식 코드Zero-TIG: Temporal Consistency-Aware Zero-Shot Illumination-Guided Low-light Video Enhancement
https://github.com/lll143653/amsnet
공식 코드Asymmetric Mask Scheme for Self-Supervised Real Image Denoising
https://github.com/longzilicart/pip_universal
공식 코드https://github.com/lpj-github-io/MWCNNv2
공식 코드https://github.com/lpj0/MWCNN
공식 코드https://github.com/lpj0/bde
공식 코드https://github.com/lronkitty/ssrt
공식 코드Hyperspectral Image Denoising via Spatial-Spectral Recurrent Transformer
https://github.com/lronkitty/ssumamba
공식 코드SSUMamba: Spatial-Spectral Selective State Space Model for Hyperspectral Image Denoising
https://github.com/lucatirel/pix2pix-wgangp
공식 코드Novel Hybrid Integrated Pix2Pix and WGAN Model with Gradient Penalty for Binary Images Denoising
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.