Anomaly detection, or outlier detection, is a crucial task in various domains to identify instances that significantly deviate from established patterns or the majority of data. In the context of autonomous driving, the identification of anomalies is particularly important to prevent safety-critical incidents, as deep learning models often exhibit overconfidence in anomalous or outlier samples. In this study, we explore different strategies for training an image semantic segmentation model with an anomaly detection module. By introducing modifications to the training stage of the state-of-the-art DenseHybrid model, we achieve significant performance improvements in anomaly detection. Moreover, we propose a simplified detector that achieves comparable results to our modified DenseHybrid approach, while also surpassing the performance of the original DenseHybrid model. These findings demonstrate the efficacy of our proposed strategies for enhancing anomaly detection in the context of autonomous driving.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Synthetic Outlier Generation for Anomaly Detection in Autonomous Driving


    Contributors:


    Publication date :

    2023-09-24


    Size :

    928050 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    PERCEPTION ANOMALY DETECTION FOR AUTONOMOUS DRIVING

    SHA LONG / ZHANG JUNLIANG / GE RUNDONG et al. | European Patent Office | 2025

    Free access

    ADS-Lead: Lifelong Anomaly Detection in Autonomous Driving Systems

    Han, Xingshuo / Zhou, Yuan / Chen, Kangjie et al. | IEEE | 2023


    Perception Datasets for Anomaly Detection in Autonomous Driving: A Survey

    Bogdoll, Daniel / Uhlemeyer, Svenja / Kowol, Kamil et al. | IEEE | 2023


    Traffic flow data anomaly identification method based on fuzzy outlier detection

    WANG XITE / LI SHANZHI / BAI MEI et al. | European Patent Office | 2025

    Free access

    AUTONOMOUS DRIVING DEVICE AND METHOD FOR OPERATING AUTONOMOUS DRIVING DEVICE IN ANOMALY SITUATION

    JEONG SEONG GYUN / LEE SEUNG JAE | European Patent Office | 2021

    Free access