| 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 | 749 | 2017 |
| DeepTAM: Deep Tracking and Mapping H Zhou, B Ummenhofer, T Brox Proceedings of the European Conference on Computer Vision (ECCV), 822-838, 2018 | 230 | 2018 |
| Lagrangian fluid simulation with continuous convolutions B Ummenhofer, L Prantl, N Thuerey, V Koltun International Conference on Learning Representations, 2019 | 148 | 2019 |
| CAM-Convs: camera-aware multi-scale convolutions for single-view depth JM Facil, B Ummenhofer, H Zhou, L Montesano, T Brox, J Civera Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 125 | 2019 |
| Global, Dense Multiscale Reconstruction for a Billion Points B Ummenhofer, T Brox International Journal of Computer Vision, 2017 | 83 | 2017 |
| Global, Dense Multiscale Reconstruction for a Billion Points B Ummenhofer, T Brox IEEE International Conference on Computer Vision (ICCV), 2015 | 83 | 2015 |
| Point-based 3d reconstruction of thin objects B Ummenhofer, T Brox Proceedings of the IEEE International Conference on Computer Vision, 969-976, 2013 | 37 | 2013 |
| DeepTAM: Deep tracking and mapping with convolutional neural networks H Zhou, B Ummenhofer, T Brox International Journal of Computer Vision 128 (3), 756-769, 2020 | 28 | 2020 |
| Dense 3d reconstruction with a hand-held camera B Ummenhofer, T Brox Joint DAGM (German Association for Pattern Recognition) and OAGM Symposium …, 2012 | 25 | 2012 |
| Temporally consistent depth estimation in videos with recurrent architectures D Tananaev, H Zhou, B Ummenhofer, T Brox Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 21 | 2018 |
| Adaptive Surface Reconstruction With Multiscale Convolutional Kernels B Ummenhofer, V Koltun Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 18 | 2021 |
| Guaranteed conservation of momentum for learning particle-based fluid dynamics L Prantl, B Ummenhofer, V Koltun, N Thuerey Advances in Neural Information Processing Systems 35, 6901-6913, 2022 | 9 | 2022 |
| Segment-Fusion: Hierarchical Context Fusion for Robust 3D Semantic Segmentation A Thyagharajan, B Ummenhofer, P Laddha, OJ Omer, S Subramoney Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 6 | 2022 |
| Introduction to Dense Reconstruction from Multiple Images B Ummenhofer Albert-Ludwigs-Universität Freiburg im Breisgau, 2018 | 1 | 2018 |
| LEARNING NEURAL REFLECTANCE SHADERS FROM IMAGES B Ummenhofer, S Wang, S Agrawal, Y Lao, K Zhang, S Richter, V Koltun US Patent App. 17/849,055, 2023 | | 2023 |
| Segment fusion based robust semantic segmentation of scenes A Thyagharajan, P Laddha, B Ummenhofer, OJ Omer US Patent App. 17/582,390, 2022 | | 2022 |
| Applying self-confidence in multi-label classification to model training A Thyagharajan, P Laddha, B Ummenhofer, OJ Omer US Patent App. 17/534,558, 2022 | | 2022 |
| Multi-scale convolutional kernels for adaptive grids B Ummenhofer, V Koltun US Patent App. 17/528,829, 2022 | | 2022 |
| Robust 3D Scene Segmentation through Hierarchical and Learnable Part-Fusion A Thyagharajan, B Ummenhofer, P Laddha, OJ Omer, S Subramoney arXiv preprint arXiv:2111.08434, 2021 | | 2021 |
| Large displacement optical flow for volumetric image sequences B Ummenhofer Pattern Recognition: 33rd DAGM Symposium, Frankfurt/Main, Germany, August 31 …, 2011 | | 2011 |
Thomas BroxUniversity of Freiburg and AmazonVerified email at cs.uni-freiburg.de
