https://github.com/GuillermoCarbajal/NonUniformBlurKernelEstimation
Non-uniform Blur Kernel Estimation via Adaptive Basis Decomposition
Papers with Code 아카이브
Image Restoration
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 13
- 평가표
- 3
- 보존된 평가 기록
- 17
Image Restoration is a family of inverse problems for obtaining a high quality image from a corrupted input image. Corruption may occur due to the image-capture process (e.g., noise, lens blur), post-processing (e.g., JPEG compression), or photography in non-ideal conditions (e.g., haze, motion blur).
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/HDCVLab/MC-Blur-Dataset
DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better
https://github.com/HedgehogCode/deep-plug-and-play-prior
https://github.com/HedgehogCode/denoising-gan
https://github.com/HilaManor/Generative-deep-features
https://github.com/House-Leo/DnSwin
DnSwin: Toward Real-World Denoising via Continuous Wavelet Sliding-Transformer
https://github.com/House-Leo/FoundIR
FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration
https://github.com/Hsintao/CAR
https://github.com/IMPLabUniPr/swin2-mose
https://github.com/IRVLab/UGAN
Enhancing Underwater Imagery using Generative Adversarial Networks
https://github.com/IRVLab/funie-gan
Fast Underwater Image Enhancement for Improved Visual Perception
https://github.com/IVRL/w2s
Fully Unsupervised Diversity Denoising with Convolutional Variational Autoencoders
https://github.com/IlyaKodua/dncnn
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/ImportPaddle/Old2Life
https://github.com/Intelligent-Imaging-Center/Spectral-Reconstruction
https://github.com/JHLew/PerPix
https://github.com/JVision/Handheld-Multi-Frame-Super-Resolution
https://github.com/JaguAroo/DASR
Unsupervised Degradation Representation Learning for Blind Super-Resolution
https://github.com/Jiamian-Wang/IST_for_SR_pruning
https://github.com/JimmyChame/The-State-of-the-Art-in-HDR-Deghosting
NTIRE 2021 Challenge on High Dynamic Range Imaging: Dataset, Methods and Results
https://github.com/JingHao99/IDR-Ingredients-oriented-Degradation-Reformulation
https://github.com/Joostdambrink/GeniusAI
Enhanced Deep Residual Networks for Single Image Super-Resolution
https://github.com/KunStats/Paddle-DIP
https://github.com/L4TTiCe/SAR2SAR
SAR2SAR: a semi-supervised despeckling algorithm for SAR images
https://github.com/L4TTiCe/SAR2SAR_v2
SAR2SAR: a semi-supervised despeckling algorithm for SAR images
https://github.com/LEEPEIQIN/EDSR
Enhanced Deep Residual Networks for Single Image Super-Resolution
https://github.com/LWChen20/RCAN
Enhanced Deep Residual Networks for Single Image Super-Resolution
https://github.com/LabForComputationalVision/bias_free_denoising
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/Li-Chongyi/Ucolor
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding
https://github.com/Lillian1082/IRAE_pytorch
Are Deep Neural Architectures Losing Information? Invertibility Is Indispensable
https://github.com/Lornatang/KernelGAN
Blind Super-Resolution Kernel Estimation using an Internal-GAN
https://github.com/Lornatang/SFTMD-PyTorch
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/RAW2RGBNet
HighEr-Resolution Network for Image Demosaicing and Enhancing
https://github.com/MKFMIKU/VIDM
Restormer: Efficient Transformer for High-Resolution Image Restoration
https://github.com/MLI-lab/Robustness-CS
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.