Johan Vertens
Johan Vertens
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Adapnet: Adaptive semantic segmentation in adverse environmental conditions
A Valada, J Vertens, A Dhall, W Burgard
2017 IEEE International Conference on Robotics and Automation (ICRA), 4644-4651, 2017
Smsnet: Semantic motion segmentation using deep convolutional neural networks
J Vertens, A Valada, W Burgard
2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017
From plants to landmarks: Time-invariant plant localization that uses deep pose regression in agricultural fields
F Kraemer, A Schaefer, A Eitel, J Vertens, W Burgard
arXiv preprint arXiv:1709.04751, 2017
A Maximum Likelihood Approach to Extract Finite Planes from 3-D Laser Scans
A Schaefer, J Vertens, D Büscher, W Burgard
2019 International Conference on Robotics and Automation (ICRA), 72-78, 2019
Perspectives on deep multimodel robot learning
W Burgard, A Valada, N Radwan, T Naseer, J Zhang, J Vertens, O Mees, ...
Robotics Research, 17-24, 2020
Learning Object Placements For Relational Instructions by Hallucinating Scene Representations
O Mees, A Emek, J Vertens, W Burgard
arXiv preprint arXiv:2001.08481, 2020
Long-term urban vehicle localization using pole landmarks extracted from 3-D lidar scans
A Schaefer, D Büscher, J Vertens, L Luft, W Burgard
2019 European Conference on Mobile Robots (ECMR), 1-7, 2019
HeatNet: Bridging the Day-Night Domain Gap in Semantic Segmentation with Thermal Images
J Vertens, J Zürn, W Burgard
arXiv preprint arXiv:2003.04645, 2020
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