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/msuimpress/hardmax
공식 코드Learning Binary Color Filter Arrays with Trainable Hard Thresholding
https://github.com/mungomeng/densepred-fullmlp
공식 코드https://github.com/mv-lab/AISP
공식 코드Perceptual Image Enhancement for Smartphone Real-Time Applications
https://github.com/mv-lab/InstructIR
공식 코드InstructIR: High-Quality Image Restoration Following Human Instructions
https://github.com/mv-lab/swin2sr
공식 코드Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration
https://github.com/mzeegers/ADJUST
공식 코드ADJUST: A Dictionary-Based Joint Reconstruction and Unmixing Method for Spectral Tomography
https://github.com/nachifur/rddm
공식 코드https://github.com/nagejacob/tbsn
공식 코드Rethinking Transformer-Based Blind-Spot Network for Self-Supervised Image Denoising
https://github.com/namecantbenull/srudc
공식 코드Under-Display Camera Image Restoration with Scattering Effect
https://github.com/ncherel/inpaint-diff-mat
공식 코드https://github.com/niika/SIDAR
공식 코드https://github.com/nikopj/cdlnet-ojsp
공식 코드CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and Demosaicing
https://github.com/nikopj/groupcdl-tip
공식 코드https://github.com/nithin-gk/at-ddpm
공식 코드https://github.com/nju-pcalab/err
공식 코드https://github.com/nkicsl/resfusion
공식 코드https://github.com/noxsine/gpt_restoration
공식 코드https://github.com/ntuhubin/plair-aw
공식 코드Power Line Aerial Image Restoration under dverse Weather: Datasets and Baselines
https://github.com/nvlabs/i2sb
공식 코드https://github.com/nvlabs/red-diff
공식 코드A Variational Perspective on Solving Inverse Problems with Diffusion Models
https://github.com/ofsoundof/Heterogeneity_Hypothesis
공식 코드The Heterogeneity Hypothesis: Finding Layer-Wise Differentiated Network Architectures
https://github.com/ofsoundof/grl-image-restoration
공식 코드Efficient and Explicit Modelling of Image Hierarchies for Image Restoration
https://github.com/ohayonguy/PMRF
공식 코드Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration
https://github.com/omerb01/puq
공식 코드Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problems
https://github.com/open-mmlab/mmediting
공식 코드GLEAN: Generative Latent Bank for Image Super-Resolution and Beyond
https://github.com/ozgurkara99/ISNAS-DIP
공식 코드ISNAS-DIP: Image-Specific Neural Architecture Search for Deep Image Prior
https://github.com/pashtari/deconver
공식 코드Deconver: A Deconvolutional Network for Medical Image Segmentation
https://github.com/pjlallen/surgical-image-restoration
공식 코드Benchmarking Laparoscopic Surgical Image Restoration and Beyond
https://github.com/pksvision/Deep-WaveNet-Underwater-Image-Restoration
공식 코드Wavelength-based Attributed Deep Neural Network for Underwater Image Restoration
https://github.com/pkuliyi2015/sd-webui-stablesr
공식 코드Exploiting Diffusion Prior for Real-World Image Super-Resolution
https://github.com/pp00704831/banet
공식 코드BANet: Blur-aware Attention Networks for Dynamic Scene Deblurring
https://github.com/princeton-computational-imaging/DirtyPixels
공식 코드Dirty Pixels: Towards End-to-End Image Processing and Perception
https://github.com/pris-cv/pidsr
공식 코드PIDSR: Complementary Polarized Image Demosaicing and Super-Resolution
https://github.com/prismformore/SDSEN
공식 코드Self-Refining Deep Symmetry Enhanced Network for Rain Removal
https://github.com/puppy210/DaLPSR
공식 코드DaLPSR: Leverage Degradation-Aligned Language Prompt for Real-World Image Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.