DeshadowNet: A multi-context embedding deep network for shadow removal

• Main Authors: QU, Liangqiong, TIAN, Jiandong, HE, Shengfeng, TANG, Yandong, LAU, Rynson W. H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Benchmarking; Computer vision; Deep neural networks; Image segmentation; Semantics; Artificial Intelligence and Robotics; OS and Networks; Systems Architecture
• Online Access: https://ink.library.smu.edu.sg/sis_research/8425; https://ink.library.smu.edu.sg/context/sis_research/article/9428/viewcontent/Qu_DeshadowNet_A_Multi_Context_CVPR_2017_paper.pdf
• Institution: Singapore Management University

Shadow removal is a challenging task as it requires the detection/annotation of shadows as well as semantic understanding of the scene. In this paper, we propose an automatic and end-to-end deep neural network (DeshadowNet) to tackle these problems in a unified manner. DeshadowNet is designed with a...