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CART: Caltech Aerial RGB-Thermal Dataset in the Wild
March 15, 2024, 4:45 a.m. | Connor Lee, Matthew Anderson, Nikhil Raganathan, Xingxing Zuo, Kevin Do, Georgia Gkioxari, Soon-Jo Chung
cs.CV updates on arXiv.org arxiv.org
Abstract: We present the first publicly available RGB-thermal dataset designed for aerial robotics operating in natural environments. Our dataset captures a variety of terrains across the continental United States, including rivers, lakes, coastlines, deserts, and forests, and consists of synchronized RGB, long-wave thermal, global positioning, and inertial data. Furthermore, we provide semantic segmentation annotations for 10 classes commonly encountered in natural settings in order to facilitate the development of perception algorithms robust to adverse weather and …
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