2 citations · 2 across the 5 of their papers we have counts for
6 papers
CAD-Free Learning of Spacecraft Pose Estimators via NeRF-Based Augmentations
Antoine Legrand, Renaud Detry, Christophe De Vleeschouwer
Spacecraft pose estimation networks require tens of thousands of CAD-rendered images to be trained. This reliance on synthetic CAD data (i) limits applicability to targets with rel…
NeRF-based Spacecraft Reconstruction from Monocular Imagery Under Illumination Variability and Pose Uncertainty
Antoine Legrand, Renaud Detry, Christophe De Vleeschouwer
Autonomous rendezvous and proximity operations around uncooperative, unknown spacecraft are critical for active debris removal and on-orbit servicing missions. A key component of s…
NeRF-based Visualization of 3D Cues Supporting Data-Driven Spacecraft Pose Estimation
Antoine Legrand, Renaud Detry, Christophe De Vleeschouwer
On-orbit operations require the estimation of the relative 6D pose, i.e., position and orientation, between a chaser spacecraft and its target. While data-driven spacecraft pose es…
Domain Generalization for 6D Pose Estimation Through NeRF-based Image Synthesis
Antoine Legrand, Renaud Detry, Christophe De Vleeschouwer
This work introduces a novel augmentation method that increases the diversity of a train set to improve the generalization abilities of a 6D pose estimation network. For this purpo…
Leveraging Neural Radiance Fields for Pose Estimation of an Unknown Space Object during Proximity Operations
Antoine Legrand, Renaud Detry, Christophe De Vleeschouwer
We address the estimation of the 6D pose of an unknown target spacecraft relative to a monocular camera, a key step towards the autonomous rendezvous and proximity operations requi…
Domain Generalization for In-Orbit 6D Pose Estimation
Antoine Legrand, Renaud Detry, Christophe De Vleeschouwer
We address the problem of estimating the relative 6D pose, i.e., position and orientation, of a target spacecraft, from a monocular image, a key capability for future autonomous Re…