SDRNet integrates shadow detection and shadow removal into one network, which makes it possible for shadow detection and shadow removal to share features, greatly reducing the number of calculations and improving the efficiency of the model.
SDRNet can complete the shadow detection and removal tasks in a unified network. SDRNet highly shares features and have no additional computational complexity.
Oct 21, 2024 · Highlights•SDRNet can complete the shadow detection and removal tasks in a unified network.•SDRNet highly shares features and have no ...
A DL based approach is introduced for image pixel-level shadow detection using a CNN-based approach, pattern conserver convolutional neural network ...
SDRNet: An end-to-end shadow detection and removal network
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Image shadow detection and removal can effectively recover image information lost in the image due to the existence of shadows, which helps improve the ...
Bibliographic details on SDRNet: An end-to-end shadow detection and removal network.
Image shadow detection and removal can effectively recover image information lost in the image due to the existence of shadows, which helps improve the ...
SDRNet: An end-to-end shadow detection and removal network, SP:IC(84), 2020, pp. 115832. Elsevier DOI 2004. Shadow detection, Shadow removal, Multi-scale ...
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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.
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Based on the above two methods, an end-to-end shadow detection and removal network SDRNet is proposed. SDRNet completes the task of sharing two feature ...