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 ...

A Smart IoT Enabled End-to-End 3D Object Detection System for Autonomous Vehicles. IEEE Transactions on Intelligent Transportation Systems , 2022; 1 DOI: 10.1109/TITS.2022.3210490 Cite This Page : ...

Ritsumeikan University researchers introduce DPPFA−Net, a groundbreaking 3D object detection network melding LiDAR and image data to improve accuracy for robots and self-driving cars. Addressing ...

Self-driving cars need to implement efficient, effective, and accurate detection systems to provide a safe and reliable experience to its users. To this end, an international research team has now ...

3D object detection (3DOD) is central to real-world vision systems and a critical component in the development of perception capabilities for autonomous vehicles (AVs) and mobile autonomous robots.

"We devised a detection model based on YOLOv3, a well-known identification algorithm. The model was first used for 2D object detection and then modified for 3D objects," he elaborates.

Researchers have unveiled a novel 3D method to track fast-moving objects at speeds previously unattainable. The new tracking approach is real-time and leverages single-pixel imaging technology ...

Stereo vision is vital to the next-generation technology of autonomous driving and other modern functions like last-mile delivery, as well as future use in robots and robotaxis.

3D object detection (3DOD) is central to real-world vision systems and a critical component in the development of perception capabilities for autonomous vehicles (AVs) and mobile autonomous robots.