Object pose estimation is a core perception task that enables, for example, object
manipulation and scene understanding. The widely available, inexpensive, and high …

This article concerns the second Satellite Pose Estimation Competition (SPEC2021), an
international competition designed to address the challenging problem of domain gap in …

Abstract Real-time 6 Degree-of-Freedom (DoF) pose estimation is of paramount importance
for various on-orbit tasks. Benefiting from the development of deep learning, Convolutional …

Monocular 6-DoF pose estimation is crucial for spacecrafts to achieve precise navigation
and positioning and it has gained increasing attentions in recent years. However …

The accuracy and reliability of vehicle localization on roads are crucial for applications such
as self-driving cars, toll systems, and digital tachographs. To achieve accurate positioning …

The accurate estimation of spacecraft pose is crucial for missions involving the navigation of
two spacecraft in close proximity. Supervised algorithms are currently the state-of-the-art …

We present a novel technique to estimate the 6D pose of objects from single images where
the 3D geometry of the object is only given approximately and not as a precise 3D model. To …

Deep learning plays a critical role in vision-based satellite pose estimation. However, the
scarcity of real data from the space environment means that deep models need to be trained …

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 purpose, a …

The deep learning (DL) algorithms have emerged as the foremost approach for close-range
navigation of non-cooperative spacecraft. Given the unavailability of in-orbit images DL …