Researchers have adapted deep learning techniques in a multi-object tracking framework, overcoming short-term occlusion and achieving remarkable performance without sacrificing computational speed.

Abstract: Compared with real-time multi-object tracking (MOT), offline multi-object tracking (OMOT) has the advantages to perform 2D-3D detection fusion, erroneous link correction, and full track ...

NUREMBERG, Germany--(BUSINESS WIRE)--The annual embedded sector’s grand gathering: embedded world 2022 had been carried out from June 21 to 23 2022. Thundercomm, the world-leading IoT product and ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A team of Microsoft and Huazhong University researchers this week ...

Researchers at the University of Toronto Institute for Aerospace Studies (UTIAS) have introduced a pair of high-tech tools that could improve the safety and reliability of autonomous vehicles by ...

Generic object detection and tracking are fundamental and challenging tasks in computer vision. For 2D object detection, IMOU proposes an algorithm framework upon structural re-parameterization and ...

Abstract: Multi-object tracking (MOT) has significant academic value and application potential in scenarios such as video surveillance, autonomous driving, security deployment, and motion behavior ...

Sriharikota (Andhra Pradesh): The Indian space agency is set to test its sophisticated, indigenously-built, multi-object tracking radar (MOTR) on a rocket flight next month while formal commissioning ...