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Open Access

Dynamic Scene Graph Generation of Point Clouds with Structural Representation Learning

School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China
Standard and Metrology Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China
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Abstract

Scene graphs of point clouds help to understand object-level relationships in the 3D space. Most graph generation methods work on 2D structured data, which cannot be used for the 3D unstructured point cloud data. Existing point-cloud-based methods generate the scene graph with an additional graph structure that needs labor-intensive manual annotation. To address these problems, we explore a method to convert the point clouds into structured data and generate graphs without given structures. Specifically, we cluster points with similar augmented features into groups and establish their relationships, resulting in an initial structural representation of the point cloud. Besides, we propose a Dynamic Graph Generation Network (DGGN) to judge the semantic labels of targets of different granularity. It dynamically splits and merges point groups, resulting in a scene graph with high precision. Experiments show that our methods outperform other baseline methods. They output reliable graphs describing the object-level relationships without additional manual labeled data.

Keywords

scene graph generationstructural representationpoint cloud

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Tsinghua Science and Technology
Volume 29 Issue 1,
February 2024
Pages 232-243
DOI: 10.26599/TST.2023.9010002
Cite this article:
Qi C, Yin J, Zhang Z, et al. Dynamic Scene Graph Generation of Point Clouds with Structural Representation Learning. Tsinghua Science and Technology, 2024, 29(1): 232-243. https://doi.org/10.26599/TST.2023.9010002

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Received: 25 August 2022
Revised: 09 November 2022
Accepted: 06 January 2023
Published: 21 August 2023
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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