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Found 5 papers, 0 papers with code
DeepLocalization: Landmark-based Self-Localization with Deep Neural Networks
The map is generated off-line by extracting landmarks from the vehicle's field of view, while the measurements are collected similarly on the fly.
Long-Term Occupancy Grid Prediction Using Recurrent Neural Networks
We tackle the long-term prediction of scene evolution in a complex downtown scenario for automated driving based on Lidar grid fusion and recurrent neural networks (RNNs).
Offline Object Extraction from Dynamic Occupancy Grid Map Sequences
The evaluation of algorithms for object extraction or the training and validation of learning algorithms rely on labeled ground truth data.
Object Detection on Dynamic Occupancy Grid Maps Using Deep Learning and Automatic Label Generation
We tackle the problem of object detection and pose estimation in a shared space downtown environment.
Dynamic Occupancy Grid Prediction for Urban Autonomous Driving: A Deep Learning Approach with Fully Automatic Labeling
Long-term situation prediction plays a crucial role in the development of intelligent vehicles.
Robotics
