The pursuit of autonomous driving relies on developing perception systems capable of
making accurate, robust, and rapid decisions to interpret the driving environment effectively …

An accurate and robust perception system is key to understanding the driving environment
of autonomous driving and robots. Autonomous driving needs 3-D information about objects …

Abstract 3D point cloud panoptic segmentation is the combined task to (i) assign each point
to a semantic class and (ii) separate the points in each class into object instances. Recently …

With the development of autonomous driving and the emergence of various intelligent traffic
scenarios, object detection technology based on deep learning is more and more widely …

With the continuous advancement of autonomous driving technology, 3D vehicle detection
has become of widespread interest. The traditional aggregate view object detection (AVOD) …

Self-driving vehicles must be controlled by navigation algorithms that ensure safe driving for
passengers, pedestrians and other vehicle drivers. One of the key factors to achieve this …

We introduce a highly efficient method for panoptic segmentation of large 3D point clouds by
redefining this task as a scalable graph clustering problem. This approach can be trained …

The individual identification of pigs is the basis for precision livestock farming (PLF), which
can provide prerequisites for personalized feeding, disease monitoring, growth condition …

A suitable control architecture for connected vehicle platoons may be seen as a promising
solution for today's traffic problems, by improving road safety and traffic flow, reducing …

For autonomous driving, pedestrian and road signs detection are key elements. There is
much existing literature available addressing this issue successfully. However, the …