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/jeya-maria-jose/TransWeather
공식 코드TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions
https://github.com/jhw2000/jarnet
공식 코드https://github.com/jiahao000/mfm
공식 코드Masked Frequency Modeling for Self-Supervised Visual Pre-Training
https://github.com/jiahong-fu/equivariant-proximal-operator
공식 코드Rotation Equivariant Proximal Operator for Deep Unfolding Methods in Image Restoration
https://github.com/jiahong-fu/kxnet
공식 코드KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution
https://github.com/jianzhangcs/dagl
공식 코드https://github.com/jiaqixuac/WResVLM
공식 코드https://github.com/jiaxi-jiang/fbcnn
공식 코드https://github.com/jimmycv07/DiffIR2VR-Zero
공식 코드DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration Models
https://github.com/jingyunliang/swinir
공식 코드https://github.com/jingyunliang/vrt
공식 코드https://github.com/jinsuyoo/act
공식 코드Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution
https://github.com/jinyeying/DC-ShadowNet-Hard-and-Soft-Shadow-Removal
공식 코드https://github.com/jinyeying/S-Aware-network
공식 코드https://github.com/jinyeying/fogremoval
공식 코드Structure Representation Network and Uncertainty Feedback Learning for Dense Non-Uniform Fog Removal
https://github.com/jinyeying/night-enhancement
공식 코드Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppression
https://github.com/jnjaby/DISCNet
공식 코드Removing Diffraction Image Artifacts in Under-Display Camera via Dynamic Skip Connection Network
https://github.com/jnjaby/alignformer
공식 코드https://github.com/josephtitan/diffloss
공식 코드DiffLoss: unleashing diffusion model as constraint for training image restoration network
https://github.com/joshyZhou/HINT
공식 코드Devil is in the Uniformity: Exploring Diverse Learners within Transformer for Image Restoration
https://github.com/josiahwsmith10/spectral-super-resolution-swin
공식 코드Frequency Estimation Using Complex-Valued Shifted Window Transformer
https://github.com/jp-guo/codiff
공식 코드Compression-Aware One-Step Diffusion Model for JPEG Artifact Removal
https://github.com/jprost76/pnp-hvae
공식 코드Inverse problem regularization with hierarchical variational autoencoders
https://github.com/jun0kim/dkn
공식 코드https://github.com/junaidmalik09/rwdenoise
공식 코드Convolutional versus Self-Organized Operational Neural Networks for Real-World Blind Image Denoising
https://github.com/junfu1995/sgh
공식 코드Scale Guided Hypernetwork for Blind Super-Resolution Image Quality Assessment
https://github.com/junghunoh/sls_cvpr2022
공식 코드Attentive Fine-Grained Structured Sparsity for Image Restoration
https://github.com/justones/irp
공식 코드Exploring and Evaluating Image Restoration Potential in Dynamic Scenes
https://github.com/justones/uir-lora
공식 코드UIR-LoRA: Achieving Universal Image Restoration through Multiple Low-Rank Adaptation
https://github.com/kangliao929/noise-da
공식 코드Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration
https://github.com/kjzju/specular-removal
공식 코드M2-Net: Multi-stages Specular Highlight Detection and Removal in Multi-scenes
https://github.com/kkkls/evssm
공식 코드https://github.com/kkkls/fftformer
공식 코드Efficient Frequency Domain-based Transformers for High-Quality Image Deblurring
https://github.com/kligvasser/xUnit
공식 코드https://github.com/kuis-ai-tekalp-research-group/video-deinterlacing
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.