Rene Ranftl
Rene Ranftl
Intel Labs
Bestätigte E-Mail-Adresse bei intel.com
TitelZitiert vonJahr
Image guided depth upsampling using anisotropic total generalized variation
D Ferstl, C Reinbacher, R Ranftl, M Rüther, H Bischof
Proceedings of the IEEE International Conference on Computer Vision, 993-1000, 2013
2752013
Pushing the limits of stereo using variational stereo estimation
R Ranftl, S Gehrig, T Pock, H Bischof
Intelligent Vehicles Symposium (IV), 2012 IEEE, 401-407, 2012
1102012
Non-local total generalized variation for optical flow estimation
R Ranftl, K Bredies, T Pock
European Conference on Computer Vision, 439-454, 2014
852014
Insights into analysis operator learning: From patch-based sparse models to higher order MRFs
Y Chen, R Ranftl, T Pock
IEEE Transactions on Image Processing 23 (3), 1060-1072, 2014
662014
Revisiting loss-specific training of filter-based MRFs for image restoration
Y Chen, T Pock, R Ranftl, H Bischof
German Conference on Pattern Recognition, 271-281, 2013
472013
Accurate optical flow via direct cost volume processing
J Xu, R Ranftl, V Koltun
arXiv preprint arXiv:1704.07325, 2017
372017
Dense Monocular Depth Estimation in Complex Dynamic Scenes
R Ranftl, V Vineet, Q Chen, V Koltun
CVPR, 2016
372016
Variational shape from light field
S Heber, R Ranftl, T Pock
International Workshop on Energy Minimization Methods in Computer Vision and …, 2013
372013
Bilevel optimization with nonsmooth lower level problems
P Ochs, R Ranftl, T Brox, T Pock
International Conference on Scale Space and Variational Methods in Computer …, 2015
272015
A bi-level view of inpainting-based image compression
Y Chen, R Ranftl, T Pock
arXiv preprint arXiv:1401.4112, 2014
252014
A Deep Variational Model for Image Segmentation
R Ranftl, T Pock
232014
Minimizing TGV-based variational models with non-convex data terms
R Ranftl, T Pock, H Bischof
International Conference on Scale Space and Variational Methods in Computer …, 2013
212013
A higher-order MRF based variational model for multiplicative noise reduction
Y Chen, W Feng, R Ranftl, H Qiao, T Pock
IEEE signal processing letters 21 (11), 1370-1374, 2014
162014
Techniques for gradient-based bilevel optimization with non-smooth lower level problems
P Ochs, R Ranftl, T Brox, T Pock
Journal of Mathematical Imaging and Vision 56 (2), 175-194, 2016
92016
Insights into analysis operator learning: A view from higher-order filter-based mrf model
Y Chen, R Ranftl, T Pock
IEEE Trans. Image Process 23 (3), 1060-1072, 2014
92014
Multi-modality depth map fusion using primal-dual optimization
D Ferstl, R Ranftl, M Rüther, H Bischof
Computational Photography (ICCP), 2013 IEEE International Conference on, 1-8, 2013
62013
Approximate Envelope Minimization for Curvature Regularity
S Heber, R Ranftl, T Pock
Workshop on Higher-Order Models and Global Constraints in Computer Vision …, 2012
62012
Depth Restoration via Joint Training of a Global Regression Model and CNNs
G Riegler, R Ranftl, M Rüther, T Pock, H Bischof
British Machine Vision Conference, 2015
52015
Deep drone racing: Learning agile flight in dynamic environments
E Kaufmann, A Loquercio, R Ranftl, A Dosovitskiy, V Koltun, ...
arXiv preprint arXiv:1806.08548, 2018
42018
Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing
E Kaufmann, M Gehrig, P Foehn, R Ranftl, A Dosovitskiy, V Koltun, ...
arXiv preprint arXiv:1810.06224, 2018
12018
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