mlsanityData to 14 Oct 2026

SAM-helps-Shadow:When Segment Anything Model meet shadow removal

arXiv 2306.06113 ↗First posted 1 Jun 2023cs.CVcited by 6

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Abstract (arXiv)

The challenges surrounding the application of image shadow removal to real-world images and not just constrained datasets like ISTD/SRD have highlighted an urgent need for zero-shot learning in this field. In this study, we innovatively adapted the SAM (Segment anything model) for shadow removal by introducing SAM-helps-Shadow, effectively integrating shadow detection and removal into a single stage. Our approach utilized the model's detection results as a potent prior for facilitating shadow detection, followed by shadow removal using a second-order deep unfolding network. The source code of SAM-helps-Shadow can be obtained from https://github.com/zhangbaijin/SAM-helps-Shadow.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 27 of its 47 references that are in the map. First posted on arXiv 1 Jun 2023.

Builds on

27 of 47 references.

References · 27

  1. 2023Segment Anythingcited by 8,234
  2. 2023Customized Segment Anything Model for Medical Image Segmentationcited by 280
  3. 2023Inpaint Anything: Segment Anything Meets Image Inpaintingcited by 233
  4. 2017Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removalcited by 161
  5. 2019Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GANcited by 103
  6. 2019Shadow Removal via Shadow Image Decompositioncited by 98
  7. 2019Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Datacited by 92
  8. 2021Auto-Exposure Fusion for Single-Image Shadow Removalcited by 79
  9. 2022DC-ShadowNet: Single-Image Hard and Soft Shadow Removal Using Unsupervised Domain-Classifier Guided Networkcited by 69
  10. 2020From Shadow Segmentation to Shadow Removalcited by 59
  11. 2018Direction-aware Spatial Context Features for Shadow Detection and Removalcited by 58
  12. 2021From Shadow Generation to Shadow Removalcited by 55
15 more
  1. 2021CANet: A Context-Aware Network for Shadow Removalcited by 47
  2. 2020Shadow Removal by a Lightness-Guided Network with Training on Unpaired Datacited by 38
  3. 2023SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Modelcited by 38
  4. 2019RIS-GAN: Explore Residual and Illumination with Generative Adversarial Networks for Shadow Removalcited by 35
  5. 2020Cloud Removal for Remote Sensing Imagery via Spatial Attention Generative Adversarial Networkcited by 29
  6. 2020SiENet: Siamese Expansion Network for Image Extrapolationcited by 18
  7. 2021Unsupervised Portrait Shadow Removal via Generative Priorscited by 16
  8. 2023Segment Anything in Non-Euclidean Domains: Challenges and Opportunitiescited by 16
  9. 2022Shadow-Aware Dynamic Convolution for Shadow Removalcited by 11
  10. 2022CRFormer: A Cross-Region Transformer for Shadow Removalcited by 8
  11. 2023From Saliency to DINO: Saliency-guided Vision Transformer for Few-shot Keypoint Detectioncited by 8
  12. 2022SpA-Former: Transformer image shadow detection and removal via spatial attentioncited by 7
  13. 2020Unsupervised Shadow Removal Using Target Consistency Generative Adversarial Networkcited by 5
  14. 2020Self-Supervised Shadow Removalcited by 5
  15. 2022CNSNet: A Cleanness-Navigated-Shadow Network for Shadow Removalcited by 5

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 5.

6 papers.

  1. 2024Moving Object Segmentation: All You Need Is SAM (and Flow)cited by 30
  2. 2024Extending Segment Anything Model into Auditory and Temporal Dimensions for Audio-Visual Segmentationcited by 5
  3. 2023Industrial Segment Anything -- a Case Study in Aircraft Manufacturing, Intralogistics, Maintenance, Repair, and Overhaulcited by 4
  4. 2024SAVE: Segment Audio-Visual Easy way using Segment Anything Modelcited by 4
  5. 2024SoftShadow: Leveraging Soft Masks for Penumbra-Aware Shadow Removalcited by 4
  6. 2024SinkSAM-Net: Knowledge-Driven Self-Supervised Sinkhole Segmentation Using Topographic Priors and Segment Anything Modelcited by 0