no code implementations • 28 Mar 2023 • Frederik Hagelskjær
In this paper, we present GP3D, a novel network for generalized pose estimation in 3D point clouds.
no code implementations • 9 Mar 2023 • Rasmus Laurvig Haugaard, Frederik Hagelskjær, Thorbjørn Mosekjær Iversen
Pose estimation is usually approached by seeking the single best estimate of an object's pose, but this approach is ill-suited for tasks involving visual ambiguity.
no code implementations • 19 Dec 2019 • Frederik Hagelskjær, Anders Glent Buch
We present a learning-based method for 6 DoF pose estimation of rigid objects in point cloud data.