2 citations · 2 across the 3 of their papers we have counts for
5 papers
BEVal: A Cross-dataset Evaluation Study of BEV Segmentation Models for Autonomous Driving
Manuel Alejandro Diaz-Zapata, Wenqian Liu, Robin Baruffa +1
Current research in semantic bird's-eye view segmentation for autonomous driving focuses solely on optimizing neural network models using a single dataset, typically nuScenes. This…
TLCFuse: Temporal Multi-Modality Fusion Towards Occlusion-Aware Semantic Segmentation-Aided Motion Planning
Gustavo Salazar-Gomez, Wenqian Liu, Manuel Diaz-Zapata +2
In autonomous driving, addressing occlusion scenarios is crucial yet challenging. Robust surrounding perception is essential for handling occlusions and aiding motion planning. Sta…
Vehicle Motion Forecasting using Prior Information and Semantic-assisted Occupancy Grid Maps
Rabbia Asghar, Manuel Diaz-Zapata, Lukas Rummelhard +2
Motion prediction is a challenging task for autonomous vehicles due to uncertainty in the sensor data, the non-deterministic nature of future, and complex behavior of agents. In th…
LAPTNet-FPN: Multi-scale LiDAR-aided Projective Transform Network for Real Time Semantic Grid Prediction
Manuel Alejandro Diaz-Zapata, David Sierra González, Özgür Erkent +2
Semantic grids can be useful representations of the scene around an autonomous system. By having information about the layout of the space around itself, a robot can leverage this…
LAPTNet: LiDAR-Aided Perspective Transform Network
Manuel Alejandro Diaz-Zapata, Özgür Erkent, Christian Laugier +2
Semantic grids are a useful representation of the environment around a robot. They can be used in autonomous vehicles to concisely represent the scene around the car, capturing vit…