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Shadow Removal
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Image Shadow Removal
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/CV-IP/SADC
공식 코드https://github.com/CXH-Research/DocShadow-SD7K
공식 코드https://github.com/CXH-Research/ShadocNet
공식 코드ShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal
https://github.com/CalcuLuUus/RASM
공식 코드https://github.com/GuoLanqing/ShadowDiffusion
공식 코드ShadowDiffusion: When Degradation Prior Meets Diffusion Model for Shadow Removal
https://github.com/IVRL/Drone-Shadow-Tracking
공식 코드https://github.com/Yuki-11/NTIRE2023_ShadowRemoval_IIM_TTI
공식 코드NTIRE 2023 Image Shadow Removal Challenge Technical Report: Team IIM_TTI
https://github.com/acecreamu/angularGAN
공식 코드Conditional GANs for Multi-Illuminant Color Constancy: Revolution or Yet Another Approach?
https://github.com/algolzw/daclip-uir
공식 코드Controlling Vision-Language Models for Multi-Task Image Restoration
https://github.com/algolzw/image-restoration-sde
공식 코드Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models
https://github.com/chao-tan/TC-GAN
공식 코드Unsupervised Shadow Removal Using Target Consistency Generative Adversarial Network
https://github.com/chi-kaichen/S2-ShadowNet
공식 코드Cross-Modal Spherical Aggregation for Weakly Supervised Remote Sensing Shadow Removal
https://github.com/cvlab-stonybrook/DocIIW
공식 코드https://github.com/cvlab-stonybrook/SID
공식 코드https://github.com/deng-ai-lab/swformer
공식 코드https://github.com/dongw22/oath
공식 코드Retinex-guided Histogram Transformer for Mask-free Shadow Removal
https://github.com/fvasluianu97/ifblend
공식 코드https://github.com/guolanqing/awesome-shadow-removal
공식 코드Single-Image Shadow Removal Using Deep Learning: A Comprehensive Survey
https://github.com/guolanqing/shadowformer
공식 코드https://github.com/hhqweasd/G2R-ShadowNet
공식 코드https://github.com/hhqweasd/LG-ShadowNet
공식 코드Shadow Removal by a Lightness-Guided Network with Training on Unpaired Data
https://github.com/jinyeying/DC-ShadowNet-Hard-and-Soft-Shadow-Removal
공식 코드https://github.com/jinyeying/DeS3_Deshadow
공식 코드DeS3: Adaptive Attention-driven Self and Soft Shadow Removal using ViT Similarity
https://github.com/jinyeying/S-Aware-network
공식 코드https://github.com/kilito777/ShaDocFormer
공식 코드https://github.com/lizhh268/shadowmaskformer
공식 코드ShadowMaskFormer: Mask Augmented Patch Embeddings for Shadow Removal
https://github.com/lmhieu612/SID
공식 코드https://github.com/montecarluo/diff-shadow
공식 코드Diff-Shadow: Global-guided Diffusion Model for Shadow Removal
https://github.com/movingforward100/shadow_r
공식 코드ShadowRefiner: Towards Mask-free Shadow Removal via Fast Fourier Transformer
https://github.com/n-kubiak/s3r-net
공식 코드S3R-Net: A Single-Stage Approach to Self-Supervised Shadow Removal
https://github.com/naoto0804/SynShadow
공식 코드Learning from Synthetic Shadows for Shadow Detection and Removal
https://github.com/ngrxmu/lab-net
공식 코드LAB-Net: LAB Color-Space Oriented Lightweight Network for Shadow Removal
https://github.com/niika/SIDAR
공식 코드https://github.com/nkicsl/resfusion
공식 코드https://github.com/sckangz/RGC
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.