2 citations · 5 across the 6 of their papers we have counts for
6 papers
Space Debris: Are Deep Learning-based Image Enhancements part of the Solution?
Michele Jamrozik, Vincent Gaudillière, Mohamed Adel Musallam +1
The volume of space debris currently orbiting the Earth is reaching an unsustainable level at an accelerated pace. The detection, tracking, identification, and differentiation betw…
Self-Supervised Learning for Place Representation Generalization across Appearance Changes
Mohamed Adel Musallam, Vincent Gaudillière, Djamila Aouada
Visual place recognition is a key to unlocking spatial navigation for animals, humans and robots. While state-of-the-art approaches are trained in a supervised manner and therefore…
3D-Aware Object Localization using Gaussian Implicit Occupancy Function
Vincent Gaudillière, Leo Pauly, Arunkumar Rathinam +3
To automatically localize a target object in an image is crucial for many computer vision applications. To represent the 2D object, ellipse labels have recently been identified as…
Leveraging Equivariant Features for Absolute Pose Regression
Mohamed Adel Musallam, Vincent Gaudilliere, Miguel Ortiz del Castillo +2
While end-to-end approaches have achieved state-of-the-art performance in many perception tasks, they are not yet able to compete with 3D geometry-based methods in pose estimation.…
SPARK: SPAcecraft Recognition leveraging Knowledge of Space Environment
Mohamed Adel Musallam, Kassem Al Ismaeil, Oyebade Oyedotun +3
This paper proposes the SPARK dataset as a new unique space object multi-modal image dataset. Image-based object recognition is an important component of Space Situational Awarenes…
LSPnet: A 2D Localization-oriented Spacecraft Pose Estimation Neural Network
Albert Garcia, Mohamed Adel Musallam, Vincent Gaudilliere +4
Being capable of estimating the pose of uncooperative objects in space has been proposed as a key asset for enabling safe close-proximity operations such as space rendezvous, in-or…