3D object detection classifies the object category and estimates oriented 3D bounding boxes of physical objects from 3D sensor data.
( Image credit: AVOD )
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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.
Ranked #1 on Object Localization on KITTI Cars Easy
We present a novel and high-performance 3D object detection framework, named PointVoxel-RCNN (PV-RCNN), for accurate 3D object detection from point clouds.
Ranked #1 on 3D Object Detection on KITTI Cyclists Hard
3D object detection from LiDAR point cloud is a challenging problem in 3D scene understanding and has many practical applications.
Current 3D object detection methods are heavily influenced by 2D detectors.
Ranked #3 on 3D Object Detection on SUN-RGBD val
This report presents our method which wins the nuScenes3D Detection Challenge  held in Workshop on Autonomous Driving(WAD, CVPR 2019).
Ranked #2 on 3D Object Detection on nuScenes
We present AVOD, an Aggregate View Object Detection network for autonomous driving scenarios.
However, in this paper we argue that it is not the quality of the data but its representation that accounts for the majority of the difference.