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Benjamin Ummenhofer
Benjamin Ummenhofer
Research Scientist, Intel Labs
Verified email at intel.com
Title
Cited by
Cited by
Year
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
8522017
DeepTAM: Deep Tracking and Mapping
H Zhou, B Ummenhofer, T Brox
Proceedings of the European Conference on Computer Vision (ECCV), 822-838, 2018
2712018
Lagrangian fluid simulation with continuous convolutions
B Ummenhofer, L Prantl, N Thuerey, V Koltun
International Conference on Learning Representations, 2019
2092019
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
1672019
Global, Dense Multiscale Reconstruction for a Billion Points
B Ummenhofer, T Brox
International Journal of Computer Vision, 2017
842017
Global, Dense Multiscale Reconstruction for a Billion Points
B Ummenhofer, T Brox
IEEE International Conference on Computer Vision (ICCV), 2015
842015
Point-based 3d reconstruction of thin objects
B Ummenhofer, T Brox
Proceedings of the IEEE International Conference on Computer Vision, 969-976, 2013
392013
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
332020
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
282022
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
252018
Adaptive Surface Reconstruction With Multiscale Convolutional Kernels
B Ummenhofer, V Koltun
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
242021
Dense 3d reconstruction with a hand-held camera
B Ummenhofer, T Brox
Joint DAGM (German Association for Pattern Recognition) and OAGM Symposium …, 2012
242012
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
102022
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
32024
Applying self-confidence in multi-label classification to model training
A Thyagharajan, P Laddha, B Ummenhofer, OJ Omer
US Patent 11,875,555, 2024
12024
Introduction to Dense Reconstruction from Multiple Images
B Ummenhofer
Albert-Ludwigs-Universität Freiburg im Breisgau, 2018
12018
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
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