RANUS: RGB and NIR Urban Scene Dataset for Deep Scene Parsing

In this letter, we present a data-driven method for scene parsing of road scenes to utilize single-channel near-infrared (NIR) images. To overcome the lack of data problem in non-RGB spectrum, we define a new color space and decompose the task of deep scene parsing into two subtasks with two separat...

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Veröffentlicht in:	IEEE robotics and automation letters 2018-07, Vol.3 (3), p.1808-1815
Hauptverfasser:	Gyeongmin Choe, Seong-Heum Kim, Sunghoon Im, Joon-Young Lee, Narasimhan, Srinivasa G., In So Kweon
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Cameras Chromaticity Color Datasets Deep learning in robotics and automation Ground truth Image color analysis Image segmentation Infrared imagery Masks Roads semantic scene understanding Semantics
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