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Volume: 32 | Article ID: art00007
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VisibilityNet: Camera visibility detection and image restoration for autonomous driving
  DOI :  10.2352/ISSN.2470-1173.2020.16.AVM-079  Published OnlineJanuary 2020
Abstract

Cameras sensors are crucial for autonomous driving as they are the only sensing modality that provide measured color information of the surrounding scene. Cameras are directly exposed to external weather conditions where visibility is dramatically affected due to various reasons such as rain, ice, fog, soil, ..etc. Hence, it is crucial to detect and remove the visibility degradation caused by the harsh weather conditions. In this paper, we focus mainly on soiling degradation. We provide methods for classification of the soiled parts as well as methods for estimating the scene behind the soiled parts. A new dataset is created providing manually annotated soiled masks knows as WoodScape dataset to encourage research in that area.

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Michal Uřičář, Hazem Rashed, Adithya Ranga, Ashok Dahal, Senthil Yogamani, "VisibilityNet: Camera visibility detection and image restoration for autonomous drivingin Proc. IS&T Int’l. Symp. on Electronic Imaging: Autonomous Vehicles and Machines,  2020,  pp 79-1 - 79-8,  https://doi.org/10.2352/ISSN.2470-1173.2020.16.AVM-079

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