The Robust Semantic Segmentation UNCV2023 Challenge Results

This paper outlines the winning solutions employed in addressing the MUAD uncertainty quantification challenge held at ICCV 2023. The challenge was centered around semantic segmentation in urban environments, with a particular focus on natural adversarial scenarios. The report presents the results o...

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Veröffentlicht in:	arXiv.org 2023-09
Hauptverfasser:	Yu, Xuanlong, Zuo, Yi, Wang, Zitao, Zhang, Xiaowen, Zhao, Jiaxuan, Yang, Yuting, Jiao, Licheng, Peng, Rui, Wang, Xinyi, Zhang, Junpei, Zhang, Kexin, Liu, Fang, Alcover-Couso, Roberto, SanMiguel, Juan C, Escudero-Viñolo, Marcos, Hanlin Tian, Matsui, Kenta, Wang, Tianhao, Fahmy Adan, Gao, Zhitong, He, Xuming, Bouniot, Quentin, Moghaddam, Hossein, Shyam Nandan Rai, Cermelli, Fabio, Masone, Carlo, Pilzer, Andrea, Ricci, Elisa, Bursuc, Andrei, Solin, Arno, Trapp, Martin, Li, Rui, Yao, Angela, Chen, Wenlong, Simpson, Ivor, Campbell, Neill D F, Franchi, Gianni
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer vision Documents Machine learning Semantic segmentation Semantics Uncertainty Urban environments
Online-Zugang:	Volltext
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