2 citations · 2 across the 4 of their papers we have counts for
4 papers
LiDAS: Lighting-driven Dynamic Active Sensing for Nighttime Perception
Simon de Moreau, Andrei Bursuc, Hafid El-Idrissi +1
Nighttime environments pose significant challenges for camera-based perception, as existing methods passively rely on the scene lighting. We introduce Lighting-driven Dynamic Activ…
DOC-Depth: A novel approach for dense depth ground truth generation
Simon de Moreau, Mathias Corsia, Hassan Bouchiba +4
Accurate depth information is essential for many computer vision applications. Yet, no available dataset recording method allows for fully dense accurate depth estimation in a larg…
LED: Light Enhanced Depth Estimation at Night
Simon de Moreau, Yasser Almehio, Andrei Bursuc +3
Nighttime camera-based depth estimation is a highly challenging task, especially for autonomous driving applications, where accurate depth perception is essential for ensuring safe…
Improving Predictive Performance and Calibration by Weight Fusion in Semantic Segmentation
Timo Sämann, Ahmed Mostafa Hammam, Andrei Bursuc +2
Averaging predictions of a deep ensemble of networks is apopular and effective method to improve predictive performance andcalibration in various benchmarks and Kaggle competitions…