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Christian Rupprecht
Christian Rupprecht
Departmental Lecturer, University of Oxford
Bestätigte E-Mail-Adresse bei robots.ox.ac.uk - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
18742016
Self-labelling via simultaneous clustering and representation learning
YM Asano, C Rupprecht, A Vedaldi
arXiv preprint arXiv:1911.05371, 2019
5332019
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
2392020
Robust Optimization for Deep Regression
V Belagiannis, C Rupprecht, G Carneiro, N Navab
Proceedings of the IEEE International Conference on Computer Vision, 2015
1982015
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
1642017
Concurrent segmentation and localization for tracking of surgical instruments
I Laina, N Rieke, C Rupprecht, JP Vizcaíno, A Eslami, F Tombari, ...
Medical Image Computing and Computer-Assisted Intervention− MICCAI 2017 …, 2017
1542017
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), 2049, 2017
1492017
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
1372020
Labelling unlabelled videos from scratch with multi-modal self-supervision
Y Asano, M Patrick, C Rupprecht, A Vedaldi
Advances in Neural Information Processing Systems 33, 2020
1082020
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
962016
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
882019
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
822019
Semantic Image Manipulation Using Scene Graphs
H Dhamo, A Farshad, I Laina, N Navab, GD Hager, F Tombari, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
752020
Deep Active Contours
C Rupprecht, E Huaroc, M Baust, N Navab
arXiv preprint arXiv:1607.05074, 2016
742016
Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and Localization
L Melas-Kyriazi, C Rupprecht, I Laina, A Vedaldi
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
402022
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), 7569, 2019
392019
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
352018
Image segmentation in twenty questions
C Rupprecht, L Peter, N Navab
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
352015
Unsupervised part discovery from contrastive reconstruction
S Choudhury, I Laina, C Rupprecht, A Vedaldi
Advances in Neural Information Processing Systems 34, 28104-28118, 2021
322021
ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
L Karazija, I Laina, C Rupprecht
Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021
322021
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