45 citations · 54 across the 4 of their papers we have counts for
10 papers · 1 filter
Tight Integration of Feature-based Relocalization in Monocular Direct Visual Odometry
Mariia Gladkova, Rui Wang, Niclas Zeller +1
In this paper we propose a framework for integrating map-based relocalization into online direct visual odometry. To achieve map-based relocalization for direct methods, we integra…
SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition
Yan Xia, Yusheng Xu, Shuang Li +4
We tackle the problem of place recognition from point cloud data and introduce a self-attention and orientation encoding network (SOE-Net) that fully explores the relationship betw…
Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels
L. Koestler, N. Yang, R. Wang +1
The training of deep-learning-based 3D object detectors requires large datasets with 3D bounding box labels for supervision that have to be generated by hand-labeling. We propose a…
DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization
Juan Du, Rui Wang, Daniel Cremers
For relocalization in large-scale point clouds, we propose the first approach that unifies global place recognition and local 6DoF pose refinement. To this end, we design a Siamese…
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry
Nan Yang, Lukas von Stumberg, Rui Wang +1
We propose D3VO as a novel framework for monocular visual odometry that exploits deep networks on three levels -- deep depth, pose and uncertainty estimation. We first propose a no…
DirectShape: Direct Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation
Rui Wang, Nan Yang, Joerg Stueckler +1
Scene understanding from images is a challenging problem encountered in autonomous driving. On the object level, while 2D methods have gradually evolved from computing simple bound…