MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for
multiple uncertainty types and tasks

v1v2 (latest)

MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks

2 March 2022

Rémi Kazmierczak

Séverine Dubuisson

ArXiv (abs)PDF HTML

Papers citing "MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks"

6 / 6 papers shown

Title
OpenAD: Open-World Autonomous Driving Benchmark for 3D Object Detection Zhongyu Xia Jishuo Li Zhiwei Lin Xinhao Wang Yansen Wang Ming-Hsuan Yang VLM 173 3 0 26 Nov 2024
Generalize or Detect? Towards Robust Semantic Segmentation Under Multiple Distribution Shifts Zhitong Gao Bingnan Li Mathieu Salzmann Xuming He OOD VLM 176 1 0 06 Nov 2024
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving Daniel Bogdoll Iramm Hamdard Lukas Namgyu Rößler Felix Geisler Muhammed Bayram ... Miguel de Campos Anushervon Tabarov Yitian Yang Hanno Gottschalk J. Marius Zöllner 74 5 0 13 May 2024
The Robust Semantic Segmentation UNCV2023 Challenge Results Xuanlong Yu Yi Zuo Zitao Wang Xiaowen Zhang Jiaxuan Zhao ... Angela Yao Wenlong Chen Ivor J. A. Simpson Neill D. F. Campbell Gianni Franchi UQCV 85 5 0 27 Sep 2023
Perception Datasets for Anomaly Detection in Autonomous Driving: A Survey Daniel Bogdoll Svenja Uhlemeyer K. Kowol J. Marius Zöllner 88 19 0 06 Feb 2023
Latent Discriminant deterministic Uncertainty Gianni Franchi Xuanlong Yu Andrei Bursuc Emanuel Aldea Séverine Dubuisson David Filliat UQCV 69 18 0 20 Jul 2022