Hanno Ackermann
Hanno Ackermann
Vahvistettu sähköpostiosoite verkkotunnuksessa tnt.uni-hannover.de - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
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
1362010
Clustering with hypergraphs: the case for large hyperedges
P Purkait, TJ Chin, H Ackermann, D Suter
European Conference on Computer Vision (ECCV), 2014
912014
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
512016
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
472017
Deep learning for vanishing point detection using an inverse gnomonic projection
F Kluger, H Ackermann, MY Yang, B Rosenhahn
German Conference on Pattern Recognition, 17-28, 2017
382017
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
202020
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
202007
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
152018
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
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
92019
Robust and Efficient 3-D Reconstruction by Self-Calibration.
H Ackermann, K Kanatani
MVA, 178-181, 2007
92007
Learning disentangled representations via independent subspaces
M Awiszus, H Ackermann, B Rosenhahn
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
82019
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
82017
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
72018
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
72018
Iterative low complexity factorization for projective reconstruction
H Ackermann, K Kanatani
International Workshop on Robot Vision, 153-164, 2008
72008
Fast projective reconstruction: Toward ultimate efficiency
H Ackermann, K Kanatani
Information and Media Technologies 3 (2), 432-442, 2008
72008
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
62020
Projective structure from facial motion
S Graßhof, H Ackermann, F Kuhnke, J Ostermann, SS Brandt
2017 Fifteenth IAPR International Conference on Machine Vision Applications …, 2017
62017
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Artikkelit 1–20