| SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again W Kehl, F Manhardt, F Tombari, S Ilic, N Navab IEEE International Conference on Computer Vision (ICCV), 1521-1529, 2017 | 662 | 2017 |
| BOP: Benchmark for 6D Object Pose Estimation T Hodan, F Michel, E Brachmann, W Kehl, AG Buch, D Kraft, B Drost, ... Proceedings of the European Conference on Computer Vision (ECCV), 19-34, 2018 | 226 | 2018 |
| Roi-10d: Monocular lifting of 2d detection to 6d pose and metric shape F Manhardt, W Kehl, A Gaidon Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 171 | 2019 |
| Deep Model-Based 6D Pose Refinement in RGB F Manhardt, W Kehl, N Navab, F Tombari IEEE European Conference on Computer Vision (ECCV), 2018 | 114 | 2018 |
| Automotive big data: Applications, workloads and infrastructures A Luckow, K Kennedy, F Manhardt, E Djerekarov, B Vorster, A Apon 2015 IEEE International Conference on Big Data (Big Data), 1201-1210, 2015 | 84 | 2015 |
| Explaining the ambiguity of object detection and 6d pose from visual data F Manhardt, DM Arroyo, C Rupprecht, B Busam, T Birdal, N Navab, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 48 | 2019 |
| Self6d: Self-supervised monocular 6d object pose estimation G Wang, F Manhardt, J Shao, X Ji, N Navab, F Tombari European Conference on Computer Vision, 108-125, 2020 | 47 | 2020 |
| Gdr-net: Geometry-guided direct regression network for monocular 6d object pose estimation G Wang, F Manhardt, F Tombari, X Ji Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 32 | 2021 |
| CPS++: Improving class-level 6D pose and shape estimation from monocular images with self-supervised learning F Manhardt, G Wang, B Busam, M Nickel, S Meier, L Minciullo, X Ji, ... arXiv preprint arXiv:2003.05848, 2020 | 16 | 2020 |
| SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation Y Di, F Manhardt, G Wang, X Ji, N Navab, F Tombari Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 13 | 2021 |
| DB-GAN: Boosting Object Recognition Under Strong Lighting Conditions L Minciullo, F Manhardt, K Yoshikawa, S Meier, F Tombari, N Kobori Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 3 | 2021 |
| DemoGrasp: Few-Shot Learning for Robotic Grasping with Human Demonstration P Wang, F Manhardt, L Minciullo, L Garattoni, S Meier, N Navab, B Busam 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 2 | 2021 |
| Graph-to-3d: End-to-end generation and manipulation of 3d scenes using scene graphs H Dhamo, F Manhardt, N Navab, F Tombari Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 2 | 2021 |
| GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Voting Y Di, R Zhang, Z Lou, F Manhardt, X Ji, N Navab, F Tombari arXiv preprint arXiv:2203.07918, 2022 | 1 | 2022 |
| Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimation G Wang, F Manhardt, X Liu, X Ji, F Tombari IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 1 | 2021 |
| Time-to-Label: Temporal Consistency for Self-Supervised Monocular 3D Object Detection I Mouawad, N Brasch, F Manhardt, F Tombari, F Odone arXiv preprint arXiv:2203.02193, 2022 | | 2022 |
| Object-Aware Monocular Depth Prediction With Instance Convolutions E Simsar, EP Örnek, F Manhardt, H Dhamo, N Navab, F Tombari IEEE Robotics and Automation Letters 7 (2), 5389-5396, 2022 | | 2022 |
| Method and system for processing an image by determining rotation hypotheses S Meier, N Kobori, F Manhardt, DM Arroyo, F Tombari, C Rupprecht US Patent App. 17/274,357, 2022 | | 2022 |
| Method and system for processing an image and determining viewpoints of objects S Meier, N Kobori, W Kehl, F Manhardt, F Tombari US Patent App. 16/757,550, 2021 | | 2021 |
| System and method for lifting 3D representations from monocular images W Kehl, F Manhardt US Patent 11,010,592, 2021 | | 2021 |
Federico TombariGoogle, TU MunichVerified email at in.tum.de
