Author(s): Wang, YF (Wang, Yangfan); Wang, C (Wang, Chen); Long, P (Long, Peng); Gu, YZ (Gu, Yuzong); Li, WF (Li, Wenfa)

Source: DISPLAYS Volume: 70 Article Number: 102077 DOI: 10.1016/j.displa.2021.102077 Published: DEC 2021

Abstract: 3D object detection is a critical part of environmental perception systems and one of the most fundamental tasks in understanding the 3D visual world, which benefit a series of downstream real-world applications. RGB-D images include object texture and semantic information, as well as depth information describing spatial geometry. Recently, numerous 3D object detection models for RGB-D images have been proposed with excellent performance, but summaries in this area are still absent. To stimulate future research, this paper provides a detailed analysis of current developments in 3D object detection methods for RGB-D images to motivate future research. It covers three major parts, including background on 3D object detection, RGB-D data details, and comparative results of state-of-the-art methods on several publicly available datasets, with an emphasis on contributions, design ideas, and limitations, as well as insightful observations and inspiring future research directions.

Accession Number: WOS:000703884000001

ISSN: 0141-9382

eISSN: 1872-7387

Full Text: https://www.sciencedirect.com/science/article/pii/S0141938221000846?via%3Dihub