Search Results for author:
Found 4 papers, 1 papers with code
Deployment of Deep Neural Networks for Object Detection on Edge AI Devices with Runtime Optimization
We therefore perform a case study of the deployment of two representative object detection networks on an edge AI platform.
MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View Understanding
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 progress due to the release of large datasets such as SemanticKITTI and nuScenes-LidarSeg.
PillarSegNet: Pillar-based Semantic Grid Map Estimation using Sparse LiDAR Data
The recent publication of the SemanticKITTI dataset stimulates the research on semantic segmentation of LiDAR point clouds in urban scenarios.
SemanticVoxels: Sequential Fusion for 3D Pedestrian Detection using LiDAR Point Cloud and Semantic Segmentation
Recently, PointPainting has been presented to eliminate this performance drop by effectively fusing the output of a semantic segmentation network instead of the raw image information.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
