110 citations · 134 across the 10 of their papers we have counts for
10 papers
Cov2Pose: Leveraging Spatial Covariance for Direct Manifold-aware 6-DoF Object Pose Estimation
Nassim Ali Ousalah, Peyman Rostami, Vincent Gaudillière +4
In this paper, we address the problem of 6-DoF object pose estimation from a single RGB image. Indirect methods that typically predict intermediate 2D keypoints, followed by a Pers…
Removing Geometric Bias in One-Class Anomaly Detection with Adaptive Feature Perturbation
Romain Hermary, Vincent Gaudillière, Abd El Rahman Shabayek +1
One-class anomaly detection aims to detect objects that do not belong to a predefined normal class. In practice training data lack those anomalous samples; hence state-of-the-art m…
Hybrid Attention for Robust RGB-T Pedestrian Detection in Real-World Conditions
Arunkumar Rathinam, Leo Pauly, Abd El Rahman Shabayek +4
Multispectral pedestrian detection has gained significant attention in recent years, particularly in autonomous driving applications. To address the challenges posed by adversarial…
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…
A Survey on Deep Learning-Based Monocular Spacecraft Pose Estimation: Current State, Limitations and Prospects
Leo Pauly, Wassim Rharbaoui, Carl Shneider +3
Estimating the pose of an uncooperative spacecraft is an important computer vision problem for enabling the deployment of automatic vision-based systems in orbit, with applications…
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…
Lessons from a Space Lab -- An Image Acquisition Perspective
Leo Pauly, Michele Lynn Jamrozik, Miguel Ortiz Del Castillo +10
The use of Deep Learning (DL) algorithms has improved the performance of vision-based space applications in recent years. However, generating large amounts of annotated data for tr…
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.…
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…