1 citations · 1 across the 4 of their papers we have counts for
4 papers
Lunar-G2R: Geometry-to-Reflectance Learning for High-Fidelity Lunar BRDF Estimation
Clementine Grethen, Nicolas Menga, Roland Brochard +4
We address the problem of estimating realistic, spatially varying reflectance for complex planetary surfaces such as the lunar regolith, which is critical for high-fidelity renderi…
Adapting Stereo Vision From Objects To 3D Lunar Surface Reconstruction with the StereoLunar Dataset
Clementine Grethen, Simone Gasparini, Geraldine Morin +3
Accurate 3D reconstruction of lunar surfaces is essential for space exploration. However, existing stereo vision reconstruction methods struggle in this context due to the Moon's l…
High performance Lunar landing simulations
Jérémy Lebreton, Roland Brochard, Nicolas Ollagnier +6
Autonomous precision navigation to land onto the Moon relies on vision sensors. Computer vision algorithms are designed, trained and tested using synthetic simulations. High qualit…
Training Datasets Generation for Machine Learning: Application to Vision Based Navigation
Jérémy Lebreton, Ingo Ahrns, Roland Brochard +8
Vision Based Navigation consists in utilizing cameras as precision sensors for GNC after extracting information from images. To enable the adoption of machine learning for space ap…