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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 2
634-640

AF-Center: multi-modal 3D object detection method with adaptive voxel-painting fusion and Gaussian center sample assignment

Qin Jianwei
Wang Chuanxu
Fu Xiaoshan
School of Information Science & Technology, Qingdao University of Science & Technology, Qingdao Shandong 266000, China
DOI: 10.19734/j.issn.1001-3695.2022.05.0271

Abstract

Camera images and LiDAR point clouds can provide complementary information for 3D object detection, but how to perform effective fusion remains a challenge. To address the alignment bias problem caused by the undifferentiated fusion in traditional methods, this paper proposed an adaptive fusion network. Firstly, it constructed the attention affinity matrix between the point cloud voxels and the corresponding multiple image pixels, and then achieved the importance differentiation fusion from multiple pixels to single voxels based on the affinity matrix. In addition, for the problem that it was difficult to enumerate all directions in the traditional anchor-based detection method, this paper represented the target as key points and first performs center localization, and then regressioned to other attributes such as 3D size and orientation. At the same time, to address the problem that the sample size of the center was too small for key point detection, this paper used an elliptical Gaussian heat map for the redistribution of center samples. This algorithm improves 2.3%, 5.9%, and 4.0% level2 mAPH over the baseline PointPillar, CenterPoint, and 3D-MAN, respectively, on the Waymo dataset.

Foundation Support

国家自然科学基金资助项目(61672305)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.05.0271
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 2
Section: Technology of Graphic & Image
Pages: 634-640
Serial Number: 1001-3695(2023)02-054-0634-07

Publish History

[2022-08-11] Accepted Paper
[2023-02-05] Printed Article

Cite This Article

秦建伟, 王传旭, 付小珊. AF-Center：基于自适应体素绘画融合和高斯中心样本分配的多模态三维目标检测 [J]. 计算机应用研究, 2023, 40 (2): 634-640. (Qin Jianwei, Wang Chuanxu, Fu Xiaoshan. AF-Center: multi-modal 3D object detection method with adaptive voxel-painting fusion and Gaussian center sample assignment [J]. Application Research of Computers, 2023, 40 (2): 634-640. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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