Appearance Harmonization for Single Image Shadow Removal
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Abstract (arXiv)
Shadows often create unwanted artifacts in photographs, and removing them can be very challenging. Previous shadow removal methods often produce de-shadowed regions that are visually inconsistent with the rest of the image. In this work we propose a fully automatic shadow region harmonization approach that improves the appearance compatibility of the de-shadowed region as typically produced by previous methods. It is based on a shadow-guided patch-based image synthesis approach that reconstructs the shadow region using patches sampled from non-shadowed regions. The result is then refined based on the reconstruction confidence to handle unique image patterns. Many shadow removal results and comparisons are show the effectiveness of our improvement. Quantitative evaluation on a benchmark dataset suggests that our automatic shadow harmonization approach effectively improves upon the state-of-the-art.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Mar 2016.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 1.
4 papers.
- 2023Leveraging Inpainting for Single-Image Shadow Removalcited by 24
- 2024Generative Portrait Shadow Removalcited by 10
- 2022CRFormer: A Cross-Region Transformer for Shadow Removalcited by 7
- 2025DeshadowMamba: Deshadowing as 1D Sequential Similaritycited by 1
- 2025DeshadowMamba: Deshadowing as 1D Sequential Similarity28 Oct 2025
- 2024Generative Portrait Shadow Removal7 Oct 2024
- 2023Leveraging Inpainting for Single-Image Shadow Removal10 Feb 2023
- 2022CRFormer: A Cross-Region Transformer for Shadow Removal4 Jul 2022