A Survey on Deep Learning Based Segmentation, Detection and Classification for 3D Point Clouds
Prasoon Kumar Vinodkumar, Doğuş Karabulut, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari
University of Tartu Yıldız Technical University
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摘要与影响
The computer vision, graphics, and machine learning research groups have given a significant amount of focus to 3D object recognition (segmentation, detection, and classification). Deep learning approaches have lately emerged as the preferred method for 3D segmentation problems as a result of their outstanding performance in 2D computer vision. As a result, many innovative approaches have been proposed and validated on multiple benchmark datasets. This study offers an in-depth assessment of the latest developments in deep learning-based 3D object recognition. We discuss the most well-known 3D object recognition models, along with evaluations of their distinctive qualities.
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工程3D Shape Modeling and Analysis
Computer Graphics and Visualization Techniques · Robotics and Sensor-Based Localization
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