LRA&LDRA: Rethinking Residual Predictions for Efficient Shadow Detection and Removal-Reference-Cited by-同舟云学术

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LRA&LDRA: Rethinking Residual Predictions for Efficient Shadow Detection and Removal

Published:2023-01 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
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Author:

Kerim Yucel Mehmet¹,Dimaridou Valia²,Manganelli Bruno¹,Ozay Mete¹,Drosou Anastasios²,Saa-Garriga Albert¹

Affiliation:

1. Samsung Research UK

2. CERTH ITI,Greece

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10030081/10030084/10030463.pdf?arnumber=10030463

Reference83 articles.

1. Entropy Minimization for Shadow Removal

2. Shadow optimization from structured deep edge detection;shen;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2015

3. ARGAN: Attentive Recurrent Generative Adversarial Network for Shadow Detection and Removal

4. MobileNetV2: Inverted Residuals and Linear Bottlenecks

5. On the removal of shadows from images

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Shadow detection using a cross-attentional dual-decoder network with self-supervised image reconstruction features;Image and Vision Computing;2024-03

2. Airborne-Shadow: Towards Fine-Grained Shadow Detection in Aerial Imagery;Lecture Notes in Computer Science;2024

3. No-reference shadow detection quality assessment via reference learning and multi-mode exploring;Computers & Graphics;2023-11

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