| 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 | 100 | 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 | 38 | 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 | 12 | 2017 |
| 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 | 8 | 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 | 5 | 2020 |
| 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 | 4 | 2019 |
| Learning Object Placements For Relational Instructions by Hallucinating Scene Representations O Mees, A Emek, J Vertens, W Burgard 2020 IEEE International Conference on Robotics and Automation (ICRA), 94-100, 2020 | 3 | 2020 |
| 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 | 1 | 2020 |
| Long-term vehicle localization in urban environments based on pole landmarks extracted from 3-D lidar scans A Schaefer, D Büscher, J Vertens, L Luft, W Burgard Robotics and Autonomous Systems 136, 103709, 2021 | | 2021 |
Wolfram BurgardProfessor of Computer Science, University of FreiburgVerified email at informatik.uni-freiburg.de
