Lidar imaging systems are one of the hottest topics in the optronics industry. The need to
sense the surroundings of every autonomous vehicle has pushed forward a race dedicated …

Robust and efficient vehicle detection is an important task of environment perception of
intelligent vehicles, which directly affects the behavior decision-making and motion planning …

Earlier work demonstrates the promise of deep-learning-based approaches for point cloud
segmentation; however, these approaches need to be improved to be practically useful. To …

We address semantic segmentation of road-objects from 3D LiDAR point clouds. In
particular, we wish to detect and categorize instances of interest, such as cars, pedestrians …

In this paper, we study the problem of unsupervised object detection from 3D point clouds in
self-driving scenes. We present a simple yet effective method that exploits (i) point clustering …

Convolutional network techniques have recently achieved great success in vision based
detection tasks. This paper introduces the recent development of our research on …

2D fully convolutional network has been recently successfully applied to the object detection
problem on images. In this paper, we extend the fully convolutional network based detection …

The recent activity in the area of autonomous vehicle navigation has initiated a series of
reactions that stirred the automobile industry, pushing for the fast commercialization of this …

Place recognition in 3D data is a challenging task that has been commonly approached by
adapting image-based solutions. Methods based on local features suffer from ambiguity and …

Deep learning has recently gained popularity achieving state-of-the-art performance in tasks
involving text, sound, or image processing. Due to its outstanding performance, there have …