3 papers
cs.CV2021
Deployment of Deep Neural Networks for Object Detection on Edge AI Devices with Runtime Optimization
Lukas Stäcker, Juncong Fei, Philipp Heidenreich +4
Deep neural networks have proven increasingly important for automotive scene understanding with new algorithms offering constant improvements of the detection performance. However,…
cs.CV2021
PillarSegNet: Pillar-based Semantic Grid Map Estimation using Sparse LiDAR Data
Juncong Fei, Kunyu Peng, Philipp Heidenreich +2
Semantic understanding of the surrounding environment is essential for automated vehicles. The recent publication of the SemanticKITTI dataset stimulates the research on semantic s…
cs.RO2020
SemanticVoxels: Sequential Fusion for 3D Pedestrian Detection using LiDAR Point Cloud and Semantic Segmentation
Juncong Fei, Wenbo Chen, Philipp Heidenreich +2
3D pedestrian detection is a challenging task in automated driving because pedestrians are relatively small, frequently occluded and easily confused with narrow vertical objects. L…