Search Results for author: Christian Laugier

Found 11 papers, 6 papers with code

Vehicle Motion Forecasting using Prior Information and Semantic-assisted Occupancy Grid Maps

no code implementations8 Aug 2023 Rabbia Asghar, Manuel Diaz-Zapata, Lukas Rummelhard, Anne Spalanzani, Christian Laugier

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.

Autonomous Vehicles Motion Forecasting +1

Allo-centric Occupancy Grid Prediction for Urban Traffic Scene Using Video Prediction Networks

no code implementations11 Jan 2023 Rabbia Asghar, Lukas Rummelhard, Anne Spalanzani, Christian Laugier

This allows for the static scene to remain fixed and to represent motion of the ego-vehicle on the grid like other agents'.

Video Prediction

Predicting Future Occupancy Grids in Dynamic Environment with Spatio-Temporal Learning

1 code implementation6 May 2022 Khushdeep Singh Mann, Abhishek Tomy, Anshul Paigwar, Alessandro Renzaglia, Christian Laugier

Reliably predicting future occupancy of highly dynamic urban environments is an important precursor for safe autonomous navigation.

Autonomous Navigation Position

Fusing Event-based and RGB camera for Robust Object Detection in Adverse Conditions

1 code implementation ICRA 2022 Abhishek Tomy, Anshul Paigwar, Khushdeep Singh Mann, Alessandro Renzaglia, Christian Laugier

The ability to detect objects, under image corruptions and different weather conditions is vital for deep learning models especially when applied to real-world applications such as autonomous driving.

Adversarial Attack Autonomous Driving +7

GndNet: Fast Ground Plane Estimation and Point Cloud Segmentation for Autonomous Vehicles

1 code implementation15 Nov 2020 Anshul Paigwar, Özgür Erkent, David Sierra González, Christian Laugier

Ground plane estimation and ground point seg-mentation is a crucial precursor for many applications in robotics and intelligent vehicles like navigable space detection and occupancy grid generation, 3D object detection, point cloud matching for localization and registration for mapping.

3D Object Detection Autonomous Vehicles +4

Attentional PointNet for 3D-Object Detection in Point Clouds

1 code implementation14 Jun 2019 Anshul Paigwar, Özgür Erkent, Christian Wolf, Christian Laugier

In this study, we propose Attentional Point- Net, which is a novel end-to-end trainable deep architecture for object detection in point clouds.

3D Object Detection Autonomous Navigation +2

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