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/zhangjc-2k/dpu
https://github.com/zhangjc-2k/ssr
https://github.com/zhangximing213/denoise
CycleISP: Real Image Restoration via Improved Data Synthesis
https://github.com/zhaozixiang1228/gdsr-dctnet
https://github.com/zhenngbolun/Learnbale_Bandpass_Filter
https://github.com/zhusiling/EDSR
Enhanced Deep Residual Networks for Single Image Super-Resolution
https://github.com/ziyangwang007/mamba-unet
https://github.com/zsyOAOA/VDNet
https://github.com/zxr931120/-
Deep Residual Network for Joint Demosaicing and Super-Resolution
https://github.com/zzskyy0301/ML_PROJECT
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.