| Flownet 2.0: Evolution of optical flow estimation with deep networks E Ilg, N Mayer, T Saikia, M Keuper, A Dosovitskiy, T Brox Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 2814 | 2017 |
| A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation N Mayer, E Ilg, P Hausser, P Fischer, D Cremers, A Dosovitskiy, T Brox Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 2149 | 2016 |
| Demon: Depth and motion network for learning monocular stereo B Ummenhofer, H Zhou, J Uhrig, N Mayer, E Ilg, A Dosovitskiy, T Brox Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 656 | 2017 |
| What makes good synthetic training data for learning disparity and optical flow estimation? N Mayer, E Ilg, P Fischer, C Hazirbas, D Cremers, A Dosovitskiy, T Brox International Journal of Computer Vision 126 (9), 942-960, 2018 | 195 | 2018 |
| Automated Boxwood Topiary Trimming with a Robotic Arm and Integrated Stereo Vision* D Kaljaca, N Mayer, B Vroegindeweij, A Mencarelli, E Van Henten, T Brox 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 6 | 2019 |
| Evaluation of a boxwood topiary trimming robot BM van Marrewijk, BA Vroegindeweij, J Gené-Mola, A Mencarelli, ... Biosystems Engineering 214, 11-27, 2022 | 4 | 2022 |
| Diskmask: Focusing Object Features for Accurate Instance Segmentation of Elongated or Overlapping Objects A Böhm, N Mayer, T Brox 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 230-234, 2020 | 3 | 2020 |
| Coupling ICP and Whole Image Alignment for Real-time Camera Tracking N Mayer | 1 | 2014 |
| Evaluation of a boxwood topiary trimming robot BM Marrewijk, BA Vroegindeweij, J Gené Mola, A Mencarelli, J Hemming, ... Biosystems Engineering, 2022, vol. 214 p. 11-27, 2022 | | 2022 |
| Synthetic Training Data for Deep Neural Networks on Visual Correspondence Tasks N Mayer Albert-Ludwigs-Universität Freiburg, 2020 | | 2020 |
Thomas BroxUniversity of Freiburg and AmazonBestätigte E-Mail-Adresse bei cs.uni-freiburg.de
