16 citations · 17 across the 10 of their papers we have counts for
5 papers · 1 filter
Hierarchical Attention and Graph Neural Networks: Toward Drift-Free Pose Estimation
Kathia Melbouci, Fawzi Nashashibi
The most commonly used method for addressing 3D geometric registration is the iterative closet-point algorithm, this approach is incremental and prone to drift over multiple consec…
Trajectory Prediction for Autonomous Driving based on Multi-Head Attention with Joint Agent-Map Representation
Kaouther Messaoud, Nachiket Deo, Mohan M. Trivedi +1
Predicting the trajectories of surrounding agents is an essential ability for autonomous vehicles navigating through complex traffic scenes. The future trajectories of agents can b…
Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation
Maximilian Jaritz, Raoul de Charette, Emilie Wirbel +2
Convolutional neural networks are designed for dense data, but vision data is often sparse (stereo depth, point clouds, pen stroke, etc.). We present a method to handle sparse dept…
End-to-End Race Driving with Deep Reinforcement Learning
Maximilian Jaritz, Raoul de Charette, Marin Toromanoff +2
We present research using the latest reinforcement learning algorithm for end-to-end driving without any mediated perception (object recognition, scene understanding). The newly pr…
Joint interpretation of on-board vision and static GPS cartography for determination of correct speed limit
Alexandre Bargeton, Fabien Moutarde, Fawzi Nashashibi +1
We present here a first prototype of a "Speed Limit Support" Advance Driving Assistance System (ADAS) producing permanent reliable information on the current speed limit applicable…