ML Anthology

The Robust Semantic Segmentation UNCV2023 Challenge Results

Xuanlong Yu, Yi Zuo, Zitao Wang, Xiaowen Zhang, Jiaxuan Zhao, Yuting Yang, Licheng Jiao, Rui Peng, Xinyi Wang, Junpei Zhang, Kexin Zhang, Fang Liu, Roberto Alcover-Couso, Juan C. SanMiguel, Marcos Escudero-Viñolo, Hanlin Tian, Kenta Matsui, Tianhao Wang, Fahmy Adan, Zhitong Gao, Xuming He, Quentin Bouniot, Hossein Moghaddam, Shyam Nandan Rai, Fabio Cermelli, Carlo Masone, Andrea Pilzer, Elisa Ricci, Andrei Bursuc, Arno Solin, Martin Trapp, Rui Li, Angela Yao, Wenlong Chen, Ivor Simpson, Neill D. F. Campbell, Gianni Franchi
ICCVW 2023 pp. 4620-4630
doi:10.1109/ICCVW60793.2023.00496 /iccvw/2023/yu2023iccvw-robust/

Abstract

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 of 19 submitted entries, with numerous techniques drawing inspiration from cutting-edge uncertainty quantification methodologies presented at prominent conferences in the fields of computer vision and machine learning and journals over the past few years. Within this document, the challenge is introduced, shedding light on its purpose and objectives, which primarily revolved around enhancing the robustness of semantic segmentation in urban scenes under varying natural adversarial conditions. The report then delves into the top-performing solutions. Moreover, the document aims to provide a comprehensive overview of the diverse solutions deployed by all participants. By doing so, it seeks to offer readers a deeper insight into the array of strategies that can be leveraged to effectively handle the inherent uncertainties associated with autonomous driving and semantic segmentation, especially within urban environments.

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Cite

Text

Yu et al. "The Robust Semantic Segmentation UNCV2023 Challenge Results." IEEE/CVF International Conference on Computer Vision Workshops, 2023. doi:10.1109/ICCVW60793.2023.00496

Markdown

[Yu et al. "The Robust Semantic Segmentation UNCV2023 Challenge Results." IEEE/CVF International Conference on Computer Vision Workshops, 2023.](https://mlanthology.org/iccvw/2023/yu2023iccvw-robust/) doi:10.1109/ICCVW60793.2023.00496

BibTeX

@inproceedings{yu2023iccvw-robust,
  title     = {{The Robust Semantic Segmentation UNCV2023 Challenge Results}},
  author    = {Yu, Xuanlong and Zuo, Yi and Wang, Zitao and Zhang, Xiaowen and Zhao, Jiaxuan and Yang, Yuting and Jiao, Licheng and Peng, Rui and Wang, Xinyi and Zhang, Junpei and Zhang, Kexin and Liu, Fang and Alcover-Couso, Roberto and SanMiguel, Juan C. and Escudero-Viñolo, Marcos and Tian, Hanlin and Matsui, Kenta and Wang, Tianhao and Adan, Fahmy and Gao, Zhitong and He, Xuming and Bouniot, Quentin and Moghaddam, Hossein and Rai, Shyam Nandan and Cermelli, Fabio and Masone, Carlo and Pilzer, Andrea and Ricci, Elisa and Bursuc, Andrei and Solin, Arno and Trapp, Martin and Li, Rui and Yao, Angela and Chen, Wenlong and Simpson, Ivor and Campbell, Neill D. F. and Franchi, Gianni},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2023},
  pages     = {4620-4630},
  doi       = {10.1109/ICCVW60793.2023.00496},
  url       = {https://mlanthology.org/iccvw/2023/yu2023iccvw-robust/}
}