RoIFusion: 3D object detection from LiDAR and vision

Simple item page
dc.contributor.authorChen, Can
dc.contributor.authorZanotti Fragonara, Luca
dc.contributor.authorTsourdos, Antonios
dc.date.accessioned2021-04-14T13:18:22Z
dc.date.available2021-04-14T13:18:22Z
dc.date.issued2021-04-01
dc.description.abstractWhen localizing and detecting 3D objects for autonomous driving scenes, obtaining information from multiple sensors (e.g., camera, LIDAR) is capable of mutually offering useful complementary information to enhance the robustness of 3D detectors. In this paper, a deep neural network architecture, named RoIFusion, is proposed to efficiently fuse the multi-modality features for 3D object detection by leveraging the advantages of LIDAR and camera sensors. In order to achieve this task, instead of densely combining the point-wise feature of the point cloud with the related pixel features, our fusion method novelly aggregates a small set of 3D Region of Interests (RoIs) in the point clouds with the corresponding 2D RoIs in the images, which are beneficial for reducing the computation cost and avoiding the viewpoint misalignment during the feature aggregation from different sensors. Finally, Extensive experiments are performed on the KITTI 3D object detection challenging benchmark to show the effectiveness of our fusion method and demonstrate that our deep fusion approach achieves state-of-the-art performanceen_UK
dc.identifier.citationChen C, Zanotti Fragonara L, Tsourdos A. (2021) RoIFusion: 3D object detection from LiDAR and vision. IEEE Access, Volume 9, 2021, pp. 51710-51721.en_UK
dc.identifier.issn2169-3536
dc.identifier.urihttps://doi.org/10.1109/ACCESS.2021.3070379
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16569
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectpoint clouden_UK
dc.subjectsegmentation networken_UK
dc.subject3D object detectionen_UK
dc.subjectSensors fusionen_UK
dc.titleRoIFusion: 3D object detection from LiDAR and visionen_UK
dc.typeArticleen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
RoIFusion_3D_object_detection_from_LiDAR-2021.pdf
Size:
2.63 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SATM)