| Learning to generate chairs, tables, and cars with convolutional networks A Dosovitskly, JT Springenberg, M Tatarchenko, T Brox IEEE Transactions on Pattern Analysis and Machine Intelligence 39 (4), 692-705, 2017 | 1044* | 2017 |
| Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs M Tatarchenko, A Dosovitskiy, T Brox Proceedings of the IEEE international conference on computer vision, 2088-2096, 2017 | 869 | 2017 |
| Tangent convolutions for dense prediction in 3d M Tatarchenko, J Park, V Koltun, QY Zhou Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 654 | 2018 |
| Multi-view 3d models from single images with a convolutional network M Tatarchenko, A Dosovitskiy, T Brox Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 523* | 2016 |
| What do single-view 3d reconstruction networks learn? M Tatarchenko, SR Richter, R Ranftl, Z Li, V Koltun, T Brox Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 448 | 2019 |
| Semi-supervised semantic segmentation with high-and low-level consistency S Mittal, M Tatarchenko, T Brox IEEE transactions on pattern analysis and machine intelligence 43 (4), 1369-1379, 2019 | 400 | 2019 |
| Parting with illusions about deep active learning S Mittal, M Tatarchenko, Ö Çiçek, T Brox arXiv preprint arXiv:1912.05361, 2019 | 55 | 2019 |
| Self-supervised 3d shape and viewpoint estimation from single images for robotics O Mees, M Tatarchenko, T Brox, W Burgard 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 21 | 2019 |
| Fostering generalization in single-view 3d reconstruction by learning a hierarchy of local and global shape priors J Bechtold, M Tatarchenko, V Fischer, T Brox Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 18 | 2021 |
| ISOOV2 DL - Semantic Instance Segmentation of Touching and Overlapping Objects A Böhm, M Tatarchenko, T Falk 2019 IEEE 16th International symposium on biomedical imaging (ISBI 2019 …, 2019 | 8 | 2019 |
| 3D-reconstruction of indoor environments from human activity B Frank, M Ruhnke, M Tatarchenko, W Burgard 2015 IEEE International Conference on Robotics and Automation (ICRA), 4644-4649, 2015 | 2 | 2015 |
| Histogram-based Deep Learning for Automotive Radar M Tatarchenko, K Rambach 2023 IEEE Radar Conference (RadarConf23), 1-6, 2023 | 1 | 2023 |
| Image semantic segmentation of indoor scenes: A survey R Velastegui, M Tatarchenko, S Karaoglu, T Gevers Computer Vision and Image Understanding 248, 104102, 2024 | | 2024 |
| RealDiff: Real-world 3D Shape Completion using Self-Supervised Diffusion Models BM Öcal, M Tatarchenko, S Karaoglu, T Gevers arXiv preprint arXiv:2409.10180, 2024 | | 2024 |
| SceneTeller: Language-to-3D Scene Generation BM Öcal, M Tatarchenko, S Karaoglu, T Gevers arXiv preprint arXiv:2407.20727, 2024 | | 2024 |
| Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory J Kälble, S Wirges, M Tatarchenko, E Ilg Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
| Scalable 3D Deep Learning: Methods and Applications M Tatarchenko PhD Thesis, 2020 | | 2020 |
| SceneTeller: Language-to-3D Scene Generation–Supplementary Material– BM Öcal, M Tatarchenko, S Karaoğlu, T Gevers | | |
Thomas BroxUniversity of FreiburgVerified email at cs.uni-freiburg.de
