3 papers
cs.CV2019
Analyzing the Cross-Sensor Portability of Neural Network Architectures for LiDAR-based Semantic Labeling
Florian Piewak, Peter Pinggera, Marius Zöllner
State-of-the-art approaches for the semantic labeling of LiDAR point clouds heavily rely on the use of deep Convolutional Neural Networks (CNNs). However, transferring network arch…
cs.CV2018
Improved Semantic Stixels via Multimodal Sensor Fusion
Florian Piewak, Peter Pinggera, Markus Enzweiler +2
This paper presents a compact and accurate representation of 3D scenes that are observed by a LiDAR sensor and a monocular camera. The proposed method is based on the well-establis…
cs.CV2018
Boosting LiDAR-based Semantic Labeling by Cross-Modal Training Data Generation
Florian Piewak, Peter Pinggera, Manuel Schäfer +6
Mobile robots and autonomous vehicles rely on multi-modal sensor setups to perceive and understand their surroundings. Aside from cameras, LiDAR sensors represent a central compone…