Papers with Code 아카이브
Unified Image Restoration
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 5
- 보존된 평가 기록
- 5
Using a single model to restore inputs with different degradation types.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/aitical/cplir
공식 코드Beyond Degradation Redundancy: Contrastive Prompt Learning for All-in-One Image Restoration
https://github.com/aitical/sipl
공식 코드Boosting All-in-One Image Restoration via Self-Improved Privilege Learning
https://github.com/algolzw/daclip-uir
공식 코드Controlling Vision-Language Models for Multi-Task Image Restoration
https://github.com/amap-ml/ld-rps
공식 코드LD-RPS: Zero-Shot Unified Image Restoration via Latent Diffusion Recurrent Posterior Sampling
https://github.com/c-yn/adair
공식 코드AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation
https://github.com/calvinyang0/crnet
공식 코드CRNet: A Detail-Preserving Network for Unified Image Restoration and Enhancement Task
https://github.com/davidserra9/abair
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/hejh8/cyclerdm
공식 코드https://github.com/justones/uir-lora
공식 코드UIR-LoRA: Achieving Universal Image Restoration through Multiple Low-Rank Adaptation
https://github.com/leonmakise/prores
공식 코드ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration
https://github.com/mdyao/NDR-Restore
공식 코드Neural Degradation Representation Learning for All-In-One Image Restoration
https://github.com/toummHus/HAIR
공식 코드https://github.com/va1shn9v/promptir
공식 코드https://github.com/xl-tang3/DA-RCOT
공식 코드Degradation-Aware Residual-Conditioned Optimal Transport for Unified Image Restoration
https://github.com/xuyimin0926/u-wadn
공식 코드Unified-Width Adaptive Dynamic Network for All-In-One Image Restoration
https://github.com/JingHao99/IDR-Ingredients-oriented-Degradation-Reformulation
https://github.com/algolzw/image-restoration-sde
Photo-Realistic Image Restoration in the Wild with Controlled Vision-Language Models
https://github.com/xl-tang3/RCOT
Degradation-Aware Residual-Conditioned Optimal Transport for Unified Image Restoration
https://github.com/xlearning-scu/2022-cvpr-airnet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.