Christian Rupprecht
Christian Rupprecht
VGG, University of Oxford
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα robots.ox.ac.uk - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
Έτος
Deeper Depth Prediction with Fully Convolutional Residual Networks
I Laina, C Rupprecht, V Belagiannis, F Tombari, N Navab
3D Vision (3DV), 2016 Fourth International Conference on, 239-248, 2016
10562016
Robust Optimization for Deep Regression
V Belagiannis, C Rupprecht, G Carneiro, N Navab
Proceedings of the IEEE International Conference on Computer Vision, 2015
1482015
Concurrent segmentation and localization for tracking of surgical instruments
I Laina, N Rieke, C Rupprecht, JP Vizcaíno, A Eslami, F Tombari, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2017
1082017
Automatic segmentation of kidneys using deep learning for total kidney volume quantification in autosomal dominant polycystic kidney disease
K Sharma, C Rupprecht, A Caroli, MC Aparicio, A Remuzzi, M Baust, ...
Scientific reports 7 (1), 1-10, 2017
862017
Self-labelling via simultaneous clustering and representation learning
YM Asano, C Rupprecht, A Vedaldi
arXiv preprint arXiv:1911.05371, 2019
822019
Learning in an uncertain world: Representing ambiguity through multiple hypotheses
C Rupprecht, I Laina, R DiPietro, M Baust, F Tombari, N Navab, GD Hager
International Conference on Computer Vision (ICCV), 2017
752017
A Taxonomy and Library for Visualizing Learned Features in Convolutional Neural Networks
F Grün, C Rupprecht, N Navab, F Tombari
arXiv preprint arXiv:1606.07757, 2016
632016
Deep Active Contours
C Rupprecht, E Huaroc, M Baust, N Navab
arXiv preprint arXiv:1607.05074, 2016
472016
A critical analysis of self-supervision, or what we can learn from a single image
YM Asano, C Rupprecht, A Vedaldi
International Conference on Learning Representations, 2020
46*2020
Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
S Wu, C Rupprecht, A Vedaldi
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
442020
Explaining the ambiguity of object detection and 6d pose from visual data
F Manhardt, DM Arroyo, C Rupprecht, B Busam, T Birdal, N Navab, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
302019
Image segmentation in twenty questions
C Rupprecht, L Peter, N Navab
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
292015
Sensor Substitution for Video-based Action Recognition
C Rupprecht, C Lea, F Tombari, N Navab, GD Hager
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016), 2016
192016
Guide me: Interacting with deep networks
C Rupprecht, I Laina, N Navab, GD Hager, F Tombari
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
142018
Analyzing and Exploiting NARX Recurrent Neural Networks for Long-Term Dependencies
R DiPietro, C Rupprecht, N Navab, GD Hager
arXiv preprint arXiv:1702.07805, 2017
132017
Leukotriene Receptor Blockade as a Life-Saving Treatment in Severe Bronchopulmonary Dysplasia
T Rupprecht, C Rupprecht, D Harms, W Sterlacci, M Vieth, K Seybold
Respiration 88 (4), 285-290, 2014
122014
Classification of polar maps from cardiac perfusion imaging with graph-convolutional neural networks
N Spier, S Nekolla, C Rupprecht, M Mustafa, N Navab, M Baust
Scientific reports 9 (1), 1-8, 2019
102019
Towards unsupervised image captioning with shared multimodal embeddings
I Laina, C Rupprecht, N Navab
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
102019
Dealing with ambiguity in robotic grasping via multiple predictions
G Ghazaei, I Laina, C Rupprecht, F Tombari, N Navab, K Nazarpour
Asian Conference on Computer Vision, 38-55, 2018
92018
Semi-Automatic Segmentation of Autosomal Dominant Polycystic Kidneys using Random Forests
K Sharma, L Peter, C Rupprecht, A Caroli, L Wang, A Remuzzi, M Baust, ...
arXiv preprint arXiv:1510.06915, 2015
92015
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