VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

• Published in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition pp. 4490 - 4499
• Main Authors: Zhou, Yin, Tuzel, Oncel
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2018
• Subjects: Encoding; Feature extraction; Laser radar; Proposals; Shape; Three-dimensional displays

Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality. To interface a highly sparse LiDAR point cloud with a region proposal network (RPN), most existing efforts have focused on ha...