https://github.com/aitical/cplir
공식 코드Beyond Degradation Redundancy: Contrastive Prompt Learning for All-in-One Image Restoration
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/aitical/dswinir
공식 코드https://github.com/aitical/sipl
공식 코드Boosting All-in-One Image Restoration via Self-Improved Privilege Learning
https://github.com/akshaydudhane16/bipnet
공식 코드https://github.com/akshaydudhane16/burstormer
공식 코드Burstormer: Burst Image Restoration and Enhancement Transformer
https://github.com/akshaydudhane16/dynet
공식 코드Dynamic Pre-training: Towards Efficient and Scalable All-in-One Image Restoration
https://github.com/alexhe101/fourierisp
공식 코드Enhancing RAW-to-sRGB with Decoupled Style Structure in Fourier Domain
https://github.com/alexzou14/vqcnir
공식 코드VQCNIR: Clearer Night Image Restoration with Vector-Quantized Codebook
https://github.com/alfaiate/DeconvolutionIncompleteObs
공식 코드A Framework for Fast Image Deconvolution with Incomplete Observations
https://github.com/algolzw/daclip-uir
공식 코드Controlling Vision-Language Models for Multi-Task Image Restoration
https://github.com/algolzw/image-restoration-sde
공식 코드Image Restoration with Mean-Reverting Stochastic Differential Equations
https://github.com/alik033/lit-net
공식 코드Harnessing Multi-resolution and Multi-scale Attention for Underwater Image Restoration
https://github.com/alphacatplus/vmambair
공식 코드https://github.com/amap-ml/ld-rps
공식 코드LD-RPS: Zero-Shot Unified Image Restoration via Latent Diffusion Recurrent Posterior Sampling
https://github.com/amazingren/semanir
공식 코드Sharing Key Semantics in Transformer Makes Efficient Image Restoration
https://github.com/andreasfloros/trustworthy-super-resolution
공식 코드Trustworthy Image Super-Resolution via Generative Pseudoinverse
https://github.com/andrew0613/x-restormer
공식 코드A Comparative Study of Image Restoration Networks for General Backbone Network Design
https://github.com/anguswlx/nnspectrum
공식 코드Reconstructing spectral functions via automatic differentiation
https://github.com/anima-lab/diffstategrad
공식 코드Diffusion State-Guided Projected Gradient for Inverse Problems
https://github.com/anisamziane/rawtexture
공식 코드Learning deep illumination-robust features from multispectral filter array images
https://github.com/annegnx/PnP-Flow
공식 코드PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
https://github.com/anonsubdip/subspace_dip
공식 코드https://github.com/anonymous-ai-for-earth/satellite-to-satellite-translation
공식 코드https://github.com/arcananana/dssr
공식 코드Learning Detail-Structure Alternative Optimization for Blind Super-Resolution
https://github.com/arpitbansal297/cold-diffusion-models
공식 코드Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise
https://github.com/avisekiit/TCSVT-LightWeight-CNNs
공식 코드Lightweight Modules for Efficient Deep Learning based Image Restoration
https://github.com/avra98/optimal-eye-surgeon
공식 코드Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at Initialization
https://github.com/badr-moufad/dcps
공식 코드Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors
https://github.com/bahjat-kawar/ddrm
공식 코드https://github.com/bahjat-kawar/ddrm-jpeg
공식 코드JPEG Artifact Correction using Denoising Diffusion Restoration Models
https://github.com/bemc22/GeneralizedR2R
공식 코드Generalized Recorrupted-to-Recorrupted: Self-Supervised Learning Beyond Gaussian Noise
https://github.com/berumotto-vermouth/S2R
공식 코드S2R: Exploring a Double-Win Transformer-Based Framework for Ideal and Blind Super-Resolution
https://github.com/bit-vision/rsir
공식 코드Recurrent Spike-based Image Restoration under General Illumination
https://github.com/bruno-31/groupsc
공식 코드Fully Trainable and Interpretable Non-Local Sparse Models for Image Restoration
https://github.com/burchim/iqa-conformer-bns
공식 코드Conformer and Blind Noisy Students for Improved Image Quality Assessment
https://github.com/c-yn/adair
공식 코드AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.