10 citations · 14 across the 2 of their papers we have counts for
7 papers
LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization
Lukas von Stumberg, Patrick Wenzel, Nan Yang +1
We present LM-Reloc -- a novel approach for visual relocalization based on direct image alignment. In contrast to prior works that tackle the problem with a feature-based formulati…
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…
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…
Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light
Eunah Jung, Nan Yang, Daniel Cremers
We propose the concept of a multi-frame GAN (MFGAN) and demonstrate its potential as an image sequence enhancement for stereo visual odometry in low light conditions. We base our m…
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…
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry
Nan Yang, Rui Wang, Jörg Stückler +1
Monocular visual odometry approaches that purely rely on geometric cues are prone to scale drift and require sufficient motion parallax in successive frames for motion estimation a…