Search Results for author: Shyam Nandan Rai

Found 3 papers, 1 papers with code

The Robust Semantic Segmentation UNCV2023 Challenge Results

no code implementations • 27 Sep 2023 • 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

This paper outlines the winning solutions employed in addressing the MUAD uncertainty quantification challenge held at ICCV 2023.

Autonomous Driving Segmentation +2

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Mask2Anomaly: Mask Transformer for Universal Open-set Segmentation

no code implementations • 8 Sep 2023 • Shyam Nandan Rai, Fabio Cermelli, Barbara Caputo, Carlo Masone

Segmenting unknown or anomalous object instances is a critical task in autonomous driving applications, and it is approached traditionally as a per-pixel classification problem.

Autonomous Driving Classification +3

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Unmasking Anomalies in Road-Scene Segmentation

1 code implementation • ICCV 2023 • Shyam Nandan Rai, Fabio Cermelli, Dario Fontanel, Carlo Masone, Barbara Caputo

We propose a paradigm change by shifting from a per-pixel classification to a mask classification.

Ranked #1 on Scene Segmentation on StreetHazards (using extra training data)

Anomaly Detection Classification +3

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