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/lbc12345/promptcir-ntire24
공식 코드PromptCIR: Blind Compressed Image Restoration with Prompt Learning
https://github.com/ldkong1205/robodepth
공식 코드The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation
https://github.com/leon-bungert/blind_remote_sensing
공식 코드Blind Image Fusion for Hyperspectral Imaging with the Directional Total Variation
https://github.com/leonmakise/prores
공식 코드ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration
https://github.com/lgs195/olvd
공식 코드Efficient Polarization Demosaicking via Low-cost Edge-aware and Inter-channel Correlation
https://github.com/liamkuo/sair
공식 코드Self-Supervised Face Image Restoration with a One-Shot Reference
https://github.com/liar-zzy/benchmarking-ultra-high-definition-single-image-reflection-removal
공식 코드https://github.com/lichen14/tower
공식 코드https://github.com/lifengcs/blinddiff
공식 코드BlindDiff: Empowering Degradation Modelling in Diffusion Models for Blind Image Super-Resolution
https://github.com/lifengshiwo/DIN
공식 코드Learning Deep Interleaved Networks with Asymmetric Co-Attention for Image Restoration
https://github.com/lincoln20030413/ddsr
공식 코드https://github.com/lingyanruan/DRBNet
공식 코드Learning to Deblur using Light Field Generated and Real Defocus Images
https://github.com/linxin0/low_light_rainy
공식 코드Dual Degradation Representation for Joint Deraining and Low-Light Enhancement in the Dark
https://github.com/linxin0/rscp2gan
공식 코드Re-boosting Self-Collaboration Parallel Prompt GAN for Unsupervised Image Restoration
https://github.com/lipang/hirdiff
공식 코드HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion Models
https://github.com/liruoteng/HeavyRainRemoval
공식 코드Heavy Rain Image Restoration: Integrating Physics Model and Conditional Adversarial Learning
https://github.com/littleyaang/hq-50k
공식 코드HQ-50K: A Large-scale, High-quality Dataset for Image Restoration
https://github.com/liu-vis/DualResidualNetworks
공식 코드Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
https://github.com/liutongkun/fair
공식 코드FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection
https://github.com/liuyang12/PnP-SCI_python
공식 코드Plug-and-Play Algorithms for Video Snapshot Compressive Imaging
https://github.com/liuyixin-louis/diffshortcut
공식 코드Rethinking and Defending Protective Perturbation in Personalized Diffusion Models
https://github.com/lixinustc/awesome-diffusion-model-for-image-processing
공식 코드Diffusion Models for Image Restoration and Enhancement -- A Comprehensive Survey
https://github.com/lixinustc/casual-ir-dil
공식 코드Learning Distortion Invariant Representation for Image Restoration from A Causality Perspective
https://github.com/lixinustc/causal-ir-dil
공식 코드Learning Distortion Invariant Representation for Image Restoration from A Causality Perspective
https://github.com/lizhemin15/zmtools
공식 코드A regularized deep matrix factorized model of matrix completion for image restoration
https://github.com/lizs17/gip_cardiac_mri
공식 코드Graph Image Prior for Unsupervised Dynamic Cardiac Cine MRI Reconstruction
https://github.com/lll143653/amsnet
공식 코드Asymmetric Mask Scheme for Self-Supervised Real Image Denoising
https://github.com/lodew920/eretinex
공식 코드ERetinex: Event Camera Meets Retinex Theory for Low-Light Image Enhancement
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/ssumamba
공식 코드SSUMamba: Spatial-Spectral Selective State Space Model for Hyperspectral Image Denoising
https://github.com/lsmlovefm/GAMD-Net
공식 코드https://github.com/luowyang/defusion
공식 코드Visual-Instructed Degradation Diffusion for All-in-One Image Restoration
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.