Follow
Hanno Ackermann
Hanno Ackermann
Qualcomm AI Research
Verified email at qti.qualcomm.com
Title
Cited by
Cited by
Year
Multilinear pose and body shape estimation of dressed subjects from image sets
N Hasler, H Ackermann, B Rosenhahn, T Thormählen, HP Seidel
2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010
1482010
Clustering with hypergraphs: the case for large hyperedges
P Purkait, TJ Chin, H Ackermann, D Suter
European Conference on Computer Vision (ECCV), 2014
1082014
On support relations and semantic scene graphs
MY Yang, W Liao, H Ackermann, B Rosenhahn
ISPRS journal of photogrammetry and remote sensing 131, 15-25, 2017
572017
3d reconstruction of human motion from monocular image sequences
B Wandt, H Ackermann, B Rosenhahn
IEEE transactions on pattern analysis and machine intelligence 38 (8), 1505-1516, 2016
562016
Deep learning for vanishing point detection using an inverse gnomonic projection
F Kluger, H Ackermann, MY Yang, B Rosenhahn
Pattern Recognition: 39th German Conference, GCPR 2017, Basel, Switzerland …, 2017
472017
Spatial-temporal transformer for dynamic scene graph generation
Y Cong, W Liao, H Ackermann, B Rosenhahn, MY Yang
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
422021
Consac: Robust multi-model fitting by conditional sample consensus
F Kluger, E Brachmann, H Ackermann, C Rother, MY Yang, B Rosenhahn
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
332020
A kinematic chain space for monocular motion capture
B Wandt, H Ackermann, B Rosenhahn
Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018
292018
Learning convolutional neural networks for object detection with very little training data
C Reinders, H Ackermann, MY Yang, B Rosenhahn
Multimodal scene understanding, 65-100, 2019
282019
Uncalibrated factorization using a variable symmetric affine camera
K Kanatani, Y Sugaya, H Ackermann
IEICE transactions on information and systems 90 (5), 851-858, 2007
21*2007
Region-based cycle-consistent data augmentation for object detection
F Kluger, C Reinders, K Raetz, P Schelske, B Wandt, H Ackermann, ...
2018 IEEE International Conference on Big Data (Big Data), 5205-5211, 2018
152018
Nodis: Neural ordinary differential scene understanding
Y Cong, H Ackermann, W Liao, MY Yang, B Rosenhahn
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
142020
Learning disentangled representations via independent subspaces
M Awiszus, H Ackermann, B Rosenhahn
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
122019
Object recognition from very few training examples for enhancing bicycle maps
C Reinders, H Ackermann, MY Yang, B Rosenhahn
2018 IEEE Intelligent Vehicles Symposium (IV), 1-8, 2018
122018
Apathy is the root of all expressions
S Graßhof, H Ackermann, SS Brandt, J Ostermann
2017 12th IEEE International Conference on Automatic Face & Gesture …, 2017
122017
Who With Whom And How? Extracting Large Social Networks Using Search Engines
S Siersdorfer, P Kemkes, H Ackermann, S Zerr
Proceedings of the 24th ACM International on Conference on Information and …, 2015
112015
3D human motion capture from monocular image sequences
B Wandt, H Ackermann, B Rosenhahn
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
112015
Temporally consistent horizon lines
F Kluger, H Ackermann, MY Yang, B Rosenhahn
2020 IEEE International Conference on Robotics and Automation (ICRA), 3161-3167, 2020
102020
Multilinear modelling of faces and expressions
S Grasshof, H Ackermann, SS Brandt, J Ostermann
IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (10), 3540 …, 2020
102020
Robust and Efficient 3-D Reconstruction by Self-Calibration.
H Ackermann, K Kanatani
MVA, 178-181, 2007
92007
The system can't perform the operation now. Try again later.
Articles 1–20