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• W4383899745 startingPage "18856" @default.
• W4383899745 abstract "In the development of autonomous driving technologies, 3-D car detection based on light detection and ranging (LiDAR) has been recognized as a key research topic. However, the performance of LiDAR-based methods is limited by the incomplete point cloud problem caused by signal missing and object occlusion. To this end, we introduce a novel early fusion method called key supplement to tackle this challenge. Specifically, we supplement the key area, where there is a high probability of incomplete point cloud problem, by using the pseudo point cloud generated by images. In addition, we propose a method that takes full advantage of multimodality to reconstruct incomplete point cloud. The experiment results show that the performances of the examined state-of-the-art LiDAR-based methods are improved by incorporating our proposed key supplement method." @default.
• W4383899745 created "2023-07-12" @default.
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• W4383899745 date "2023-08-15" @default.
• W4383899745 modified "2023-10-14" @default.
• W4383899745 title "Key Supplement: Improving 3-D Car Detection With Pseudo Point Cloud" @default.
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• W4383899745 doi "https://doi.org/10.1109/jsen.2023.3292137" @default.
• W4383899745 hasPublicationYear "2023" @default.
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