Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 5
1554-1561

3D visual understanding oriented towards multimodal interactive fusion and progressive refinement

He Hongtian1
Chen Han1
Liu Yang2
Zhou Liliang3
Zhang Min3
Lei Yinjie1
1. College of Electronics & Information Engineering, Sichuan University, Chengdu 610065, China
2. Key Laboratory of Optical Engineering, Institute of Optics & Electronics, Chinese Academy of Sciences, Chengdu 610209, China
3. CETC Key Laboratory of Avionic Information System Technology, The 10th Research Institute of China Electronics Technology Group Corporation, Chengdu 610036, China
DOI: 10.19734/j.issn.1001-3695.2023.08.0383

Abstract

3D visual understanding aims to intelligently perceive and interpret 3D scenes, achieving a profound understanding and analysis of objects, environment, and dynamic changes. As its core technology, 3D object detection plays an indispensable role. For the problem of low detection accuracy of distant targets and small targets in current 3D detection algorithms, this paper proposed a 3D object detection method called MIFPR, which was oriented towards multimodal interactive fusion and progressive refinement. In the feature extraction stage, this algorithm introduced an adaptive gated information fusion module firstly. Incorporating the geometric features of the point cloud into the image features results in a more discriminative image representation for handling variations in lighting conditions. Subsequently, the proposed voxel centroid-based deformable crossmodal attention module was to drive the fusion of rich semantic features and contextual information from images into the point cloud features. During the proposal refinement stage, this algorithm introduced a progressive attention module. By learning and aggregating features from different stages, it continuously enhanced the model's ability to extract and model fine-grained features, progressively refining bounding boxes. This gradual refinement of the proposal helps improve the detection accuracy of distant and small objects, thereby enhancing the overall capability of visual scene understanding. The proposed method shows significant improvement in the detection accuracy of small objects like pedestrian and cyclist on the KITTI dataset compared to the state-of-the-art baseline. This confirms the effectiveness of the proposed approach.

Foundation Support

国家自然科学基金面上项目(62276176)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.08.0383
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 5
Section: Technology of Graphic & Image
Pages: 1554-1561
Serial Number: 1001-3695(2024)05-039-1554-08

Publish History

[2023-11-01] Accepted Paper
[2024-05-05] Printed Article

Cite This Article

何鸿添, 陈晗, 刘洋, 等. 面向多模态交互式融合与渐进式优化的三维视觉理解 [J]. 计算机应用研究, 2024, 41 (5): 1554-1561. (He Hongtian, Chen Han, Liu Yang, et al. 3D visual understanding oriented towards multimodal interactive fusion and progressive refinement [J]. Application Research of Computers, 2024, 41 (5): 1554-1561. )

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.

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