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
Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data
xw-hu/Mask-ShadowGAN
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ICCV 2019
This paper presents a new method for shadow removal using unpaired data, enabling us to avoid tedious annotations and obtain more diverse training samples.
Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN
vinthony/ghost-free-shadow-removal
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With the help of novel masks or scenes, we enhance the current datasets using synthesized shadow images.
Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal
IsHYuhi/ST-CGAN_Stacked_Conditional_Generative_Adversarial_Networks
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CVPR 2018
Specifically, a shadow image is fed into the first generator which produces a shadow detection mask.
DeshadowNet: A Multi-Context Embedding Deep Network for Shadow Removal
Two levels of features are derived from the global network and transferred to two parallel networks.
Shadow Removal via Shadow Image Decomposition
Training our model on this new augmented ISTD dataset further lowers the RMSE on the shadow area to 7. 4.
RIS-GAN: Explore Residual and Illumination with Generative Adversarial Networks for Shadow Removal
To our best knowledge, we are the first one to explore residual and illumination for shadow removal.
Direction-aware Spatial Context Features for Shadow Detection and Removal
xw-hu/DSC
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This paper presents a novel deep neural network design for shadow detection and removal by analyzing the spatial image context in a direction-aware manner.
Robust Graph Learning from Noisy Data
The proposed model is able to boost the performance of data clustering, semisupervised classification, and data recovery significantly, primarily due to two key factors: 1) enhanced low-rank recovery by exploiting the graph smoothness assumption, 2) improved graph construction by exploiting clean data recovered by robust PCA.
Water-Filling: An Efficient Algorithm for Digitized Document Shadow Removal
In this paper, we propose a novel algorithm to rectify illumination of the digitized documents by eliminating shading artifacts.
BEDSR-Net: A Deep Shadow Removal Network From a Single Document Image
IsHYuhi/BEDSR-Net_A_Deep_Shadow_Removal_Network_from_a_Single_Document_Image
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CVPR 2020
For taking advantage of specific properties of document images, a background estimation module is designed for extracting the global background color of the document.
