Shadow Removal
56 papers with code • 3 benchmarks • 6 datasets
Remove shadow from background
Benchmarks
These leaderboards are used to track progress in Shadow Removal
| Trend | Dataset | Best Model | Paper | Code | Compare |
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ISTD
SRD
Kligler
Jung
Doc3DShade
SD7K
Most implemented papers
Physics-based Shadow Image Decomposition for Shadow Removal
Inspired by physical models of shadow formation, we use a linear illumination transformation to model the shadow effects in the image that allows the shadow image to be expressed as a combination of the shadow-free image, the shadow parameters, and a matte layer.
Auto-Exposure Fusion for Single-Image Shadow Removal
tsingqguo/exposure-fusion-shadow-removal
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CVPR 2021
We conduct extensive experiments on the ISTD, ISTD+, and SRD datasets to validate our method's effectiveness and show better performance in shadow regions and comparable performance in non-shadow regions over the state-of-the-art methods.
Bijective Mapping Network for Shadow Removal
KevinJ-Huang/BMNet
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CVPR 2022
Shadow removal, which aims to restore the background in the shadow regions, is challenging due to the highly ill-posed nature.
Efficient Model-Driven Network for Shadow Removal
zhuyr97/AAAI2022_Unfolding_Network_Shadow_Removal
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AAAI 2022
To address these issues, we first propose a new shadow illumination model for the shadow removal task.
Shadow-Aware Dynamic Convolution for Shadow Removal
xuyimin0926/sadc
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Inspired by the fact that the color mapping of the non-shadow region is easier to learn, our SADC processes the non-shadow region with a lightweight convolution module in a computationally cheap manner and recovers the shadow region with a more complicated convolution module to ensure the quality of image reconstruction.
SpA-Former: Transformer image shadow detection and removal via spatial attention
zhangbaijin/spa-former-shadow-removal
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In this paper, we propose an end-to-end SpA-Former to recover a shadow-free image from a single shaded image.
High-Resolution Document Shadow Removal via A Large-Scale Real-World Dataset and A Frequency-Aware Shadow Erasing Net
CXH-Research/DocShadow-SD7K
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ICCV 2023
We handle high-resolution document shadow removal directly via a larger-scale real-world dataset and a carefully designed frequency-aware network.
Interactive Removal and Ground Truth for Difficult Shadow Scenes
A user-centric method for fast, interactive, robust and high-quality shadow removal is presented.
User-Assisted Shadow Removal
To relight the image, a dense scale field is produced by in-painting the sparse scales.
An Iterative Approach for Shadow Removal in Document Images
Uneven illumination and shadows in document images cause a challenge for digitization applications and automated workflows.
