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 | 852 | 2017 |
DeepTAM: Deep Tracking and Mapping H Zhou, B Ummenhofer, T Brox Proceedings of the European Conference on Computer Vision (ECCV), 822-838, 2018 | 271 | 2018 |
Lagrangian fluid simulation with continuous convolutions B Ummenhofer, L Prantl, N Thuerey, V Koltun International Conference on Learning Representations, 2019 | 209 | 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 | 167 | 2019 |
Global, Dense Multiscale Reconstruction for a Billion Points B Ummenhofer, T Brox International Journal of Computer Vision, 2017 | 84 | 2017 |
Global, Dense Multiscale Reconstruction for a Billion Points B Ummenhofer, T Brox IEEE International Conference on Computer Vision (ICCV), 2015 | 84 | 2015 |
Point-based 3d reconstruction of thin objects B Ummenhofer, T Brox Proceedings of the IEEE International Conference on Computer Vision, 969-976, 2013 | 39 | 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 | 33 | 2020 |
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 | 28 | 2022 |
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 | 25 | 2018 |
Adaptive Surface Reconstruction With Multiscale Convolutional Kernels B Ummenhofer, V Koltun Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 24 | 2021 |
Dense 3d reconstruction with a hand-held camera B Ummenhofer, T Brox Joint DAGM (German Association for Pattern Recognition) and OAGM Symposium …, 2012 | 24 | 2012 |
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 | 10 | 2022 |
Objects With Lighting: A Real-World Dataset for Evaluating Reconstruction and Rendering for Object Relighting B Ummenhofer, S Agrawal, R Sepulveda, Y Lao, K Zhang, T Cheng, ... 2024 International Conference on 3D Vision (3DV), 137-147, 2024 | 3 | 2024 |
Applying self-confidence in multi-label classification to model training A Thyagharajan, P Laddha, B Ummenhofer, OJ Omer US Patent 11,875,555, 2024 | 1 | 2024 |
Introduction to Dense Reconstruction from Multiple Images B Ummenhofer Albert-Ludwigs-Universität Freiburg im Breisgau, 2018 | 1 | 2018 |
Mesh2NeRF: Direct Mesh Supervision for Neural Radiance Field Representation and Generation Y Chen, Y Nie, B Ummenhofer, R Birkl, M Paulitsch, M Müller, M Nießner European Conference on Computer Vision, 173-191, 2025 | | 2025 |
Learning neural reflectance shaders from images B Ummenhofer, S Wang, S Agrawal, Y Lao, K Zhang, S Richter, V Koltun US Patent App. 18/426,740, 2024 | | 2024 |
Learning neural reflectance shaders from images B Ummenhofer, S Wang, S Agrawal, Y Lao, K Zhang, S Richter, V Koltun US Patent 11,972,519, 2024 | | 2024 |
Segment fusion based robust semantic segmentation of scenes A Thyagharajan, P Laddha, B Ummenhofer, OJ Omer US Patent App. 17/582,390, 2022 | | 2022 |