https://github.com/cszhilu1998/selfir
공식 코드Self-Supervised Image Restoration with Blurry and Noisy Pairs
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/cszn/DPIR
공식 코드https://github.com/cszn/DPSR
공식 코드Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels
https://github.com/cszn/DnCNN
공식 코드Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/cszn/ircnn
공식 코드https://github.com/ctom2/cider
공식 코드Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image Restoration
https://github.com/ctom2/lucyd-deconvolution
공식 코드LUCYD: A Feature-Driven Richardson-Lucy Deconvolution Network
https://github.com/cucapra/approx-vision
공식 코드https://github.com/cuiziteng/eccv_aeris
공식 코드https://github.com/cxh-research/guidedhybsensuir
공식 코드https://github.com/cynicarlos/retinexrawmamba
공식 코드Retinex-RAWMamba: Bridging Demosaicing and Denoising for Low-Light RAW Image Enhancement
https://github.com/daidaijr/eamamba
공식 코드EAMamba: Efficient All-Around Vision State Space Model for Image Restoration
https://github.com/daiscvprojects/pfadn
공식 코드https://github.com/danaroth83/jodefu
공식 코드https://github.com/daniela997/filmdamagesimulator
공식 코드Simulating analogue film damage to analyse and improve artefact restoration on high-resolution scans
https://github.com/daqians/noisy-character-image-benchmark
공식 코드RCRN: Real-world Character Image Restoration Network via Skeleton Extraction
https://github.com/darshandeshpande/audio-spectral-enhancement
공식 코드https://github.com/dasongli1/learning_degradation
공식 코드https://github.com/davidserra9/abair
공식 코드https://github.com/ddghjikle/out-of-sample-restoration
공식 코드Generalizing to Out-of-Sample Degradations via Model Reprogramming
https://github.com/ddlee-cn/mulut
공식 코드Toward DNN of LUTs: Learning Efficient Image Restoration with Multiple Look-Up Tables
https://github.com/deep-imagelab/hprn
공식 코드HPRN: Holistic Prior-embedded Relation Network for Spectral Super-Resolution
https://github.com/delong-liu-bupt/sen
공식 코드Text-guided Image Restoration and Semantic Enhancement for Text-to-Image Person Retrieval
https://github.com/deng-ai-lab/swformer
공식 코드https://github.com/dengzhuo-AI/Real-Fundus
공식 코드https://github.com/deweihu/oct_ddpm
공식 코드Unsupervised Denoising of Retinal OCT with Diffusion Probabilistic Model
https://github.com/dongqi-fan/irconstyle
공식 코드IRConStyle: Image Restoration Framework Using Contrastive Learning and Style Transfer
https://github.com/dongqi-fan/lir
공식 코드https://github.com/dragonisss/ram
공식 코드Restore Anything with Masks: Leveraging Mask Image Modeling for Blind All-in-One Image Restoration
https://github.com/duanlab123/curvpnp
공식 코드CurvPnP: Plug-and-play Blind Image Restoration with Deep Curvature Denoiser
https://github.com/duanlab123/metaue
공식 코드MetaUE: Model-based Meta-learning for Underwater Image Enhancement
https://github.com/eeic-lab/dreb-net
공식 코드https://github.com/eezkni/ddr
공식 코드DDR: Exploiting Deep Degradation Response as Flexible Image Descriptor
https://github.com/egyptdj/skyb-aim2020-public
공식 코드PyNET-CA: Enhanced PyNET with Channel Attention for End-to-End Mobile Image Signal Processing
https://github.com/ephemeral182/snowformer
공식 코드SnowFormer: Context Interaction Transformer with Scale-awareness for Single Image Desnowing
https://github.com/eth-siplab/rap
공식 코드Restore Anything Pipeline: Segment Anything Meets Image Restoration
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.