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The advent of deep learning for object detection has led to a wave of new ways for autonomous object labeling techniques for various applications such as autonomous driving and maneuvering, pedestrian/vehicle detection and target identification. Though most previous object detection techniques used RGB-D and 2D detection techniques, the recent increase in LiDar capabilities and point cloud generation has led to an interest in 3D object detection. This research takes a look at current 3D object detection and deep learning networks and conducts a performance comparison with their 2D counterparts.
Theus H Aspiras, K. Asari Vijayan
Primary Advisor's Department
Electrical and Computer Engineering
Stander Symposium poster
"Deep Learning and Object Detection in 3D" (2019). Stander Symposium Posters. 1526.