Robots and autonomous vehicles can use 3D point clouds from LiDAR sensors and camera images to perform 3D object detection. However, current techniques that combine both types of data struggle to ...

Now, a team of researchers has developed a novel Internet-of-Things-enabled deep learning-based end-to-end 3D object detection system with improved detection capabilities even under unfavorable ...

Multi-modal methods based on camera and LiDAR sensors have garnered significant attention in the field of 3D detection. However, many prevalent works focus on single or partial stage fusion, leading ...

Arxiv – Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. Abstract 3D object detection is an essential task in autonomous driving. Recent ...

Traditional 3D object detectors, whether fully-, semi-, or weakly-supervised, rely heavily on extensive human annotations. In contrast, this paper introduces an unsupervised 3D object detector that ...

GlobalData uncovers the leading innovators in LiDAR for 3D object detection for the automotive industry.

Thanks to the progress of more advanced algorithms and higher computing power, the results of the 3D object detection task from nuScenes were greatly improved in 2022.

Github, everyone's favorite nerdery, added STL object file support - basically a system for uploading and rendering 3D models - in April. Now, however, they've improved their service with a system ...