In the challenging realm of object detection under rainy conditions, visual distortions significantly hinder accuracy. This paper introduces Rain-Adapt Faster RCNN (RAF-RCNN), an innovative end-to-end approach that merges advanced deraining techniques with robust object detection. Our method integrates rain removal and object detection into a single process, using a novel feature transfer learning approach for enhanced robustness. By employing the Extended Area Structural Discrepancy Loss (EASDL), RAF-RCNN enhances feature map evaluation, leading to significant performance improvements. In quantitative testing of the Rainy KITTI dataset, RAF-RCNN achieves a mean Average Precision (mAP) of 51.4% at IOU [0.5, 0.95], exceeding previous methods by at least 5.5%. These results demonstrate RAF-RCNN's potential to significantly enhance perception systems in intelligent transportation, promising substantial improvements in reliability and safety for autonomous vehicles operating in varied weather conditions.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    RAF-RCNN: Adaptive Feature Transfer from Clear to Rainy Conditions for Improved Object Detection


    Beteiligte:
    Wei, Chuheng (Autor:in) / Wu, Guoyuan (Autor:in) / Barth, Matthew J. (Autor:in)


    Erscheinungsdatum :

    24.09.2024


    Format / Umfang :

    7302567 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    OBJECT DETECTION UNDER RAINY CONDITIONS FOR AUTONOMOUS SYSTEMS

    RADHA HAYDER / HNEWA MAZIN / DIEDRICH JON et al. | Europäisches Patentamt | 2022

    Freier Zugriff

    Towards Robust 3D Object Detection In Rainy Conditions

    Piroli, Aldi / Dallabetta, Vinzenz / Kopp, Johannes et al. | IEEE | 2023


    Object detection under rainy conditions for autonomous systems

    RADHA HAYDER / HNEWA MAZIN / DIEDRICH JON et al. | Europäisches Patentamt | 2022

    Freier Zugriff

    Improved Faster RCNN for Traffic Sign Detection*

    Wang, Fei / Li, Yidong / Wei, Yunchao et al. | IEEE | 2020


    Agricultural pest detection algorithm based on improved faster RCNN

    Wang, Zhenghao / Qiao, Lifeng / Wang, Mengke | British Library Conference Proceedings | 2022