Follow
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
7352017
DeepTAM: Deep Tracking and Mapping
H Zhou, B Ummenhofer, T Brox
Proceedings of the European Conference on Computer Vision (ECCV), 822-838, 2018
2222018
Lagrangian fluid simulation with continuous convolutions
B Ummenhofer, L Prantl, N Thuerey, V Koltun
International Conference on Learning Representations, 2019
1372019
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
1162019
Global, Dense Multiscale Reconstruction for a Billion Points
B Ummenhofer, T Brox
International Journal of Computer Vision, 2017
822017
Global, Dense Multiscale Reconstruction for a Billion Points
B Ummenhofer, T Brox
IEEE International Conference on Computer Vision (ICCV), 2015
822015
Point-based 3d reconstruction of thin objects
B Ummenhofer, T Brox
Proceedings of the IEEE International Conference on Computer Vision, 969-976, 2013
372013
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
282020
Dense 3d reconstruction with a hand-held camera
B Ummenhofer, T Brox
Joint DAGM (German Association for Pattern Recognition) and OAGM Symposium†…, 2012
252012
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
202018
Adaptive Surface Reconstruction With Multiscale Convolutional Kernels
B Ummenhofer, V Koltun
Proceedings of the IEEE/CVF International Conference on Computer Vision†…, 2021
182021
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
52022
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
22022
Introduction to Dense Reconstruction from Multiple Images
B Ummenhofer
Albert-Ludwigs-Universitšt Freiburg im Breisgau, 2018
12018
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
SegmentFusion: Hierarchical Context Fusion for Robust 3D Semantic Segmentation (Supplementary Material)
A Thyagharajan, B Ummenhofer, P Laddha, OJ Omer, S Subramoney
The system can't perform the operation now. Try again later.
Articles 1–20