Structure‐aware dehazing of sewer inspection images based on monocular depth cues-Reference-Cited by-同舟云学术

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Structure‐aware dehazing of sewer inspection images based on monocular depth cues

Published:2022-08 Issue:6 Volume:38 Page:762-778
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer aided Civil Eng

Author:

Xia Zixia¹,Guo Shuai²,Sun Di³,Lv Yaozhi⁴,Li Honglie⁵,Pan Gang¹

Affiliation:

1. College of Intelligence and Computing Tianjin University Tianjin China

2. Department of Municipal Engineering Hefei University of Technology Anhui China

3. College of Artificial Intelligence Tianjin University of Science and Technology Tianjin China

4. Key laboratory of Infrastructure Durability Tianjin Municipal Engineering Design and Research Institute Tianjin China

5. West‐East Gas Pipeline Company PipeChina Shanghai China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering,Building and Construction

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12900

Reference52 articles.

1. Anvari Z. &Athitsos V.(2020).Dehaze‐GLCGAN: unpaired single image de‐hazing via adversarial training. arXiv preprint arXiv:2008.06632.

2. Non-local Image Dehazing

3. Gated Context Aggregation Network for Image Dehazing and Deraining

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