Lin, C., Tian, D., Duan, X., Zhou, J., Zhao, D. and Cao, D. (2023) 3D-DFM: anchor-free multimodal 3-D object detection with dynamic fusion module for autonomous driving. IEEE Transactions on Neural Networks and Learning Systems, 34(12), pp. 10812-10822. (doi: 10.1109/TNNLS.2022.3171553) (PMID:35560081)
Text
271132.pdf - Accepted Version 29MB |
Abstract
Recent advances in cross-modal 3D object detection rely heavily on anchor-based methods, and however, intractable anchor parameter tuning and computationally expensive postprocessing severely impede an embedded system application, such as autonomous driving. In this work, we develop an anchor-free architecture for efficient camera-light detection and ranging (LiDAR) 3D object detection. To highlight the effect of foreground information from different modalities, we propose a dynamic fusion module (DFM) to adaptively interact images with point features via learnable filters. In addition, the 3D distance intersection-over-union (3D-DIoU) loss is explicitly formulated as a supervision signal for 3D-oriented box regression and optimization. We integrate these components into an end-to-end multimodal 3D detector termed 3D-DFM. Comprehensive experimental results on the widely used KITTI dataset demonstrate the superiority and universality of 3D-DFM architecture, with competitive detection accuracy and real-time inference speed. To the best of our knowledge, this is the first work that incorporates an anchor-free pipeline with multimodal 3D object detection.
Item Type: | Articles |
---|---|
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Zhao, Dr Dezong |
Authors: | Lin, C., Tian, D., Duan, X., Zhou, J., Zhao, D., and Cao, D. |
College/School: | College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity |
Journal Name: | IEEE Transactions on Neural Networks and Learning Systems |
Publisher: | IEEE |
ISSN: | 2162-237X |
ISSN (Online): | 2162-2388 |
Published Online: | 13 May 2022 |
Copyright Holders: | Copyright © 2022 IEEE |
First Published: | First published in IEEE Transactions on Neural Networks and Learning Systems 34(12):10812 - 10822 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
University Staff: Request a correction | Enlighten Editors: Update this record