Shadow Removal
58 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 |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
ISTD
SRD
Kligler
Jung
Doc3DShade
SD7K
Most implemented papers
Conditional GANs for Multi-Illuminant Color Constancy: Revolution or Yet Another Approach?
Non-uniform and multi-illuminant color constancy are important tasks, the solution of which will allow to discard information about lighting conditions in the image.
Drone Shadow Tracking
In this paper, we incorporate knowledge of the shadow's physical properties, in the form of shadow detection masks, into a correlation-based tracking algorithm.
An Effective Background Estimation Method for Shadows Removal of Document Images
This paper proposes an effective method to remove shadows from the single document images, which contains two stages: shadow detection and shadow removal.
Shadow Removal of Text Document Images by Estimating Local and Global Background Colors
Assuming that the document mainly contains texts, our method estimates the global and local background colors using statistical analysis of the whole image and local neighborhoods.
Shadow Removal by a Lightness-Guided Network with Training on Unpaired Data
In this paper, we present a new Lightness-Guided Shadow Removal Network (LG-ShadowNet) for shadow removal by training on unpaired data.
Unsupervised Shadow Removal Using Target Consistency Generative Adversarial Network
chao-tan/TC-GAN
•
•
Unsupervised shadow removal aims to learn a non-linear function to map the original image from shadow domain to non-shadow domain in the absence of paired shadow and non-shadow data.
Intrinsic Decomposition of Document Images In-the-Wild
However, document shadow or shading removal results still suffer because: (a) prior methods rely on uniformity of local color statistics, which limit their application on real-scenarios with complex document shapes and textures and; (b) synthetic or hybrid datasets with non-realistic, simulated lighting conditions are used to train the models.
Local Water-Filling Algorithm for Shadow Detection and Removal of Document Images
The proposed method can remove the shading artifacts and outperform some state-of-the-art methods, especially for the removal of shadow boundaries.
Learning from Synthetic Shadows for Shadow Detection and Removal
To overcome this challenge, we present SynShadow, a novel large-scale synthetic shadow/shadow-free/matte image triplets dataset and a pipeline to synthesize it.
From Shadow Generation to Shadow Removal
hhqweasd/G2R-ShadowNet
•
•
CVPR 2021
Shadow removal is a computer-vision task that aims to restore the image content in shadow regions.
