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A Survey on Monocular 3D Object Detection Algorithms Based on Deep Learning

Junhui Wu, Dong Yin, Jie Chen, Y. Wu, Huiping Si, Kaiyan Lin

Year
2020
Citations
20

Abstract

Abstract An accurate and effective perception of environment is important for autonomous vehicle and robot. The perception system needs to obtain the 3D information of objects, which includes objects’ space location and pose. Camera is widely equipped on autonomous vehicle because of its price advantage. However, the monocular camera cannot provide depth information which is necessary for 3D object detection. Many algorithms based on monocular 3D object detection have been developed in recent years. Deep learning is popular for perception system which transforms image data from camera into semantic information. This paper presents an overview of monocular 3D object detection algorithms based on deep Learning and summarize the contributions and limitations of these algorithms. We also compare the performance of different algorithms on different datasets.

Keywords

MonocularArtificial intelligenceComputer scienceComputer visionObject detectionObject (grammar)Monocular visionPerceptionDeep learningRobot

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