41 citations · 45 across the 3 of their papers we have counts for
4 papers
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,…
MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View Understanding
Kunyu Peng, Juncong Fei, Kailun Yang +6
At the heart of all automated driving systems is the ability to sense the surroundings, e.g., through semantic segmentation of LiDAR sequences, which experienced a remarkable progr…
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…
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…