119 citations · 156 across the 24 of their papers we have counts for
3 papers · 1 filter
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…
A Statistical Update of Grid Representations from Range Sensors
Luis Roldão, Raoul De Charette, Anne Verroust-Blondet
In a wide range of robotic applications, being able to create a 3D model of the surrounding environment is a key feature for autonomous tasks. In this research report, we present a…