Exploring the Potential of World Models for Anomaly Detection in
Autonomous Driving

Exploring the Potential of World Models for Anomaly Detection in Autonomous Driving

10 August 2023

Helen Gremmelmaier

J. Marius Zöllner

Papers citing "Exploring the Potential of World Models for Anomaly Detection in Autonomous Driving"

5 / 5 papers shown

Title
UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving Daniel Bogdoll Noël Ollick Tim Joseph J. Marius Zöllner 37 1 0 10 Jun 2024
Delving into Multi-modal Multi-task Foundation Models for Road Scene Understanding: From Learning Paradigm Perspectives Sheng Luo Wei Chen Wanxin Tian Rui Liu Luanxuan Hou ... Ling Shao Yi Yang Bojun Gao Qun Li Guobin Wu 51 13 0 05 Feb 2024
Applications of Large Scale Foundation Models for Autonomous Driving Yu Huang Yue Chen Zhu Li ELM AI4CE LRM ALM LM&Ro 61 15 0 20 Nov 2023
Model-Based Imitation Learning for Urban Driving Anthony Hu Gianluca Corrado Nicolas Griffiths Zak Murez Corina Gurau Hudson Yeo Alex Kendall R. Cipolla Jamie Shotton 112 135 0 14 Oct 2022
Description of Corner Cases in Automated Driving: Goals and Challenges Daniel Bogdoll Jasmin Breitenstein Florian Heidecker Maarten Bieshaar Bernhard Sick Tim Fingscheidt J. Marius Zöllner 43 55 0 20 Sep 2021