Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection

Ozan Unal; Luc Van Gool; Dengxin Dai

doi:10.1109/wacv48630.2021.00299

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Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection

Ozan Unal Luc Van Gool Dengxin Dai

Year: 2021 Pages: 2949-2958

DOI: 10.1109/wacv48630.2021.00299

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Abstract

sponsorship: This work was funded by Toyota Motor Europe via the research project TRACE Zurich. (Toyota Motor Europe via the research project TRACE Zurich)

Keywords:

Computer science Segmentation Point cloud Object detection Artificial intelligence Pipeline (software) Computer vision Convolutional neural network Deep learning Feature (linguistics) Pose Feature extraction Focus (optics) Feature learning Image segmentation Semantics (computer science) Object (grammar) Orientation (vector space) Pattern recognition (psychology)

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Topics

Remote Sensing and LiDAR Applications

Physical Sciences → Environmental Science → Environmental Engineering

Robotics and Sensor-Based Localization

Physical Sciences → Engineering → Aerospace Engineering

3D Surveying and Cultural Heritage

Physical Sciences → Earth and Planetary Sciences → Geology

Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection

Abstract

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