Shadow Detection
38 papers with code • 1 benchmarks • 3 datasets
SBU
SOBA
Most implemented papers
A+D Net: Training a Shadow Detector with Adversarial Shadow Attenuation
lmhieu612/adnet_demo
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ECCV 2018
The A-Net modifies the original training images constrained by a simplified physical shadow model and is focused on fooling the D-Net's shadow predictions.
Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection
Second, we develop a bidirectional feature pyramid network (BFPN) to aggregate shadow contexts spanned across different CNN layers by deploying two series of RAR modules in the network to iteratively combine and refine context features: one series to refine context features from deep to shallow layers, and another series from shallow to deep layers.
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.
DeepMask: an algorithm for cloud and cloud shadow detection in optical satellite remote sensing images using deep residual network
The average accuracy is 93. 56%, compared with 85. 36% from CFMask.
A Multi-Task Mean Teacher for Semi-Supervised Shadow Detection
To boost the shadow detection performance, this paper presents a multi-task mean teacher model for semi-supervised shadow detection by leveraging unlabeled data and exploring the learning of multiple information of shadows simultaneously.
Ultrasound Confidence Maps of Intensity and Structure Based on Directed Acyclic Graphs and Artifact Models
Ultrasound imaging has been improving, but continues to suffer from inherent artifacts that are challenging to model, such as attenuation, shadowing, diffraction, speckle, etc.
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.
