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.
Current 3D object detection methods are heavily influenced by 2D detectors.
SOTA for 3D Object Detection on ScanNetV2
This report presents our method which wins the nuScenes3D Detection Challenge  held in Workshop on Autonomous Driving(WAD, CVPR 2019).
SOTA for 3D Object Detection on nuScenes
Our method, called Stereo R-CNN, extends Faster R-CNN for stereo inputs to simultaneously detect and associate object in left and right images.
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.
#2 best model for 3D object detection from stereo images on KITTI Cars Moderate
We introduce a novel method for 3D object detection and pose estimation from color images only.
#10 best model for 6D Pose Estimation using RGB on LineMOD