Rene Ranftl
Rene Ranftl
Intel Labs
Verified email at intel.com
Title
Cited by
Cited by
Year
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
4152013
Pushing the limits of stereo using variational stereo estimation
R Ranftl, S Gehrig, T Pock, H Bischof
2012 IEEE Intelligent Vehicles Symposium, 401-407, 2012
1362012
Accurate optical flow via direct cost volume processing
J Xu, R Ranftl, V Koltun
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
1212017
Dense Monocular Depth Estimation in Complex Dynamic Scenes
R Ranftl, V Vineet, Q Chen, V Koltun
CVPR, 2016
1202016
Non-local total generalized variation for optical flow estimation
R Ranftl, K Bredies, T Pock
European Conference on Computer Vision, 439-454, 2014
1182014
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
932014
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
652018
What do single-view 3d reconstruction networks learn?
M Tatarchenko, SR Richter, R Ranftl, Z Li, V Koltun, T Brox
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
632019
Events-to-video: Bringing modern computer vision to event cameras
H Rebecq, R Ranftl, V Koltun, D Scaramuzza
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
622019
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
602013
Deep fundamental matrix estimation
R Ranftl, V Koltun
Proceedings of the European Conference on Computer Vision (ECCV), 284-299, 2018
572018
Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
R Ranftl, K Lasinger, D Hafner, K Schindler, V Koltun
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
47*2020
Beauty and the beast: Optimal methods meet learning for drone racing
E Kaufmann, M Gehrig, P Foehn, R Ranftl, A Dosovitskiy, V Koltun, ...
2019 International Conference on Robotics and Automation (ICRA), 690-696, 2019
452019
Variational shape from light field
S Heber, R Ranftl, T Pock
International Workshop on Energy Minimization Methods in Computer Vision and …, 2013
452013
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
402015
High speed and high dynamic range video with an event camera
H Rebecq, R Ranftl, V Koltun, D Scaramuzza
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019
382019
A bi-level view of inpainting-based image compression
Y Chen, R Ranftl, T Pock
arXiv preprint arXiv:1401.4112, 2014
322014
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
302013
A Deep Variational Model for Image Segmentation
R Ranftl, T Pock
292014
Deep drone racing: From simulation to reality with domain randomization
A Loquercio, E Kaufmann, R Ranftl, A Dosovitskiy, V Koltun, ...
IEEE Transactions on Robotics 36 (1), 1-14, 2019
282019
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