Autonomous vehicles require object detection systems to navigate traffic and avoid obstacles on the road. However, current detection methods often suffer from diminished detection capabilities due ...

Three-dimensional object detection is crucial for autonomous vehicles. It utilizes point cloud data generated by LiDAR to help autonomous vehicles identify surrounding objects. This technology is ...

Shadows analyzed to model 3D scenes including objects blocked from view. Researchers from MIT and Meta have developed a computer vision technique that could enable an autonomous vehicle to perceive ...

A specialised algorithm could help autonomous vehicles track hidden objects, such as a pedestrian, a bicycle or another vehicle concealed behind a parked car ...

And sometimes a little bit farther in front of us, there’s a lot of uncertainty because we’re occluded from other objects in the environment.” In such cases, the vehicle’s ability to rapidly process ...

Autonomous vehicles keep crashing into things, even though ADAS technology promises to make driving safer because machines can think and react faster than human drivers. Humans rely on seeing and ...

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.

Computer science and electrical engineering researchers at UC Irvine and Japan’s Keio University demonstrated that they could fool the sensing systems that enable autonomous vehicles to navigate ...

Discover how TuSimple Holdings Inc's patented method for autonomous vehicles optimizes resources by classifying and prioritizing objects. Learn about the recently granted patent and system that ...