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René Ranftl
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- affiliation: Intel Laboratory, Munich, Germany
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2020 – today
- 2023
- [c29]Diana Wofk, René Ranftl, Matthias Müller, Vladlen Koltun:
Monocular Visual-Inertial Depth Estimation. ICRA 2023: 6095-6101 - [i26]Diana Wofk, René Ranftl, Matthias Müller, Vladlen Koltun:
Monocular Visual-Inertial Depth Estimation. CoRR abs/2303.12134 (2023) - 2022
- [j14]Jan Carius
, René Ranftl, Farbod Farshidian, Marco Hutter:
Constrained stochastic optimal control with learned importance sampling: A path integral approach. Int. J. Robotics Res. 41(2): 189-209 (2022) - [j13]René Ranftl
, Katrin Lasinger
, David Hafner
, Konrad Schindler
, Vladlen Koltun
:
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer. IEEE Trans. Pattern Anal. Mach. Intell. 44(3): 1623-1637 (2022) - [j12]Kaicheng Yu
, René Ranftl
, Mathieu Salzmann
:
An Analysis of Super-Net Heuristics in Weight-Sharing NAS. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 8110-8124 (2022) - [c28]Boyi Li, Kilian Q. Weinberger, Serge J. Belongie, Vladlen Koltun, René Ranftl:
Language-driven Semantic Segmentation. ICLR 2022 - [i25]Boyi Li, Kilian Q. Weinberger, Serge J. Belongie, Vladlen Koltun, René Ranftl:
Language-driven Semantic Segmentation. CoRR abs/2201.03546 (2022) - [i24]Feihu Zhang, Vladlen Koltun, Philip H. S. Torr, René Ranftl, Stephan R. Richter:
Unsupervised Contrastive Domain Adaptation for Semantic Segmentation. CoRR abs/2204.08399 (2022) - 2021
- [j11]Henri Rebecq
, René Ranftl
, Vladlen Koltun
, Davide Scaramuzza
:
High Speed and High Dynamic Range Video with an Event Camera. IEEE Trans. Pattern Anal. Mach. Intell. 43(6): 1964-1980 (2021) - [j10]Antonio Loquercio
, Elia Kaufmann
, René Ranftl
, Matthias Müller
, Vladlen Koltun
, Davide Scaramuzza
:
Learning high-speed flight in the wild. Sci. Robotics 6(59) (2021) - [c27]Kaicheng Yu, René Ranftl, Mathieu Salzmann:
Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search. CVPR 2021: 13723-13732 - [c26]René Ranftl, Alexey Bochkovskiy
, Vladlen Koltun:
Vision Transformers for Dense Prediction. ICCV 2021: 12159-12168 - [c25]Elia Kaufmann, Antonio Loquercio, René Ranftl, Matthias Müller, Vladlen Koltun, Davide Scaramuzza:
Deep Drone Acrobatics (Extended Abstract). IJCAI 2021: 4780-4783 - [c24]Feihu Zhang, Philip H. S. Torr, René Ranftl, Stephan R. Richter:
Looking Beyond Single Images for Contrastive Semantic Segmentation Learning. NeurIPS 2021: 3285-3297 - [d1]Antonio Loquercio
, Elia Kaufmann
, René Ranftl
, Matthias Mueller, Vladlen Koltun
, Davide Scaramuzza
:
Code and Dataset for the paper "Learning High-Speed Flight in the Wild" (Science Robotics, 2021). Zenodo, 2021 - [i23]René Ranftl, Alexey Bochkovskiy, Vladlen Koltun:
Vision Transformers for Dense Prediction. CoRR abs/2103.13413 (2021) - [i22]Kaicheng Yu, René Ranftl, Mathieu Salzmann:
Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search. CoRR abs/2104.05309 (2021) - [i21]Kaicheng Yu, René Ranftl, Mathieu Salzmann:
An Analysis of Super-Net Heuristics in Weight-Sharing NAS. CoRR abs/2110.01154 (2021) - [i20]Antonio Loquercio, Elia Kaufmann, René Ranftl, Matthias Müller, Vladlen Koltun, Davide Scaramuzza:
Learning High-Speed Flight in the Wild. CoRR abs/2110.05113 (2021) - [i19]Hao Zhao, René Ranftl, Yurong Chen, Hongbin Zha:
Transferable End-to-end Room Layout Estimation via Implicit Encoding. CoRR abs/2112.11340 (2021) - 2020
- [j9]Lorenz Wellhausen
, René Ranftl
, Marco Hutter
:
Safe Robot Navigation Via Multi-Modal Anomaly Detection. IEEE Robotics Autom. Lett. 5(2): 1326-1333 (2020) - [j8]Antonio Loquercio
, Elia Kaufmann
, René Ranftl
, Alexey Dosovitskiy
, Vladlen Koltun
, Davide Scaramuzza
:
Deep Drone Racing: From Simulation to Reality With Domain Randomization. IEEE Trans. Robotics 36(1): 1-14 (2020) - [c23]Christopher B. Choy, Junha Lee, René Ranftl, Jaesik Park
, Vladlen Koltun:
High-Dimensional Convolutional Networks for Geometric Pattern Recognition. CVPR 2020: 11224-11233 - [c22]Elia Kaufmann, Antonio Loquercio, René Ranftl, Matthias Müller, Vladlen Koltun, Davide Scaramuzza
:
Deep Drone Acrobatics. Robotics: Science and Systems 2020 - [i18]Lorenz Wellhausen, René Ranftl, Marco Hutter:
Safe Robot Navigation via Multi-Modal Anomaly Detection. CoRR abs/2001.07934 (2020) - [i17]Kaicheng Yu, René Ranftl, Mathieu Salzmann:
How to Train Your Super-Net: An Analysis of Training Heuristics in Weight-Sharing NAS. CoRR abs/2003.04276 (2020) - [i16]Christopher B. Choy, Junha Lee, René Ranftl, Jaesik Park, Vladlen Koltun:
High-dimensional Convolutional Networks for Geometric Pattern Recognition. CoRR abs/2005.08144 (2020) - [i15]Elia Kaufmann, Antonio Loquercio, René Ranftl, Matthias Müller
, Vladlen Koltun, Davide Scaramuzza:
Deep Drone Acrobatics. CoRR abs/2006.05768 (2020)
2010 – 2019
- 2019
- [j7]Lorenz Wellhausen
, Alexey Dosovitskiy
, René Ranftl
, Krzysztof Walas
, Cesar Cadena
, Marco Hutter
:
Where Should I Walk? Predicting Terrain Properties From Images Via Self-Supervised Learning. IEEE Robotics Autom. Lett. 4(2): 1509-1516 (2019) - [j6]Ruben Grandia
, Farbod Farshidian
, Alexey Dosovitskiy
, René Ranftl
, Marco Hutter
:
Frequency-Aware Model Predictive Control. IEEE Robotics Autom. Lett. 4(2): 1517-1524 (2019) - [j5]Jan Carius
, René Ranftl
, Vladlen Koltun
, Marco Hutter
:
Trajectory Optimization for Legged Robots With Slipping Motions. IEEE Robotics Autom. Lett. 4(3): 3013-3020 (2019) - [c21]Maxim Tatarchenko, Stephan R. Richter, René Ranftl, Zhuwen Li, Vladlen Koltun, Thomas Brox:
What Do Single-View 3D Reconstruction Networks Learn? CVPR 2019: 3405-3414 - [c20]Henri Rebecq, René Ranftl, Vladlen Koltun, Davide Scaramuzza
:
Events-To-Video: Bringing Modern Computer Vision to Event Cameras. CVPR 2019: 3857-3866 - [c19]Adel Bibi, Bernard Ghanem, Vladlen Koltun, René Ranftl:
Deep Layers as Stochastic Solvers. ICLR (Poster) 2019 - [c18]Elia Kaufmann, Mathias Gehrig, Philipp Foehn
, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza
:
Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing. ICRA 2019: 690-696 - [c17]Florian Achermann, Nicholas R. J. Lawrance
, René Ranftl, Alexey Dosovitskiy, Jen Jen Chung
, Roland Siegwart:
Learning to Predict the Wind for Safe Aerial Vehicle Planning. ICRA 2019: 2311-2317 - [c16]Ruben Grandia, Farbod Farshidian, René Ranftl, Marco Hutter:
Feedback MPC for Torque-Controlled Legged Robots. IROS 2019: 4730-4737 - [i14]Henri Rebecq, René Ranftl, Vladlen Koltun, Davide Scaramuzza:
Events-to-Video: Bringing Modern Computer Vision to Event Cameras. CoRR abs/1904.08298 (2019) - [i13]Maxim Tatarchenko, Stephan R. Richter, René Ranftl, Zhuwen Li, Vladlen Koltun, Thomas Brox:
What Do Single-view 3D Reconstruction Networks Learn? CoRR abs/1905.03678 (2019) - [i12]Ruben Grandia, Farbod Farshidian, René Ranftl, Marco Hutter:
Feedback MPC for Torque-Controlled Legged Robots. CoRR abs/1905.06144 (2019) - [i11]Antonio Loquercio, Elia Kaufmann, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Deep Drone Racing: From Simulation to Reality with Domain Randomization. CoRR abs/1905.09727 (2019) - [i10]Henri Rebecq, René Ranftl, Vladlen Koltun, Davide Scaramuzza:
High Speed and High Dynamic Range Video with an Event Camera. CoRR abs/1906.07165 (2019) - [i9]Katrin Lasinger, René Ranftl, Konrad Schindler, Vladlen Koltun:
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer. CoRR abs/1907.01341 (2019) - 2018
- [j4]Jan Carius
, René Ranftl, Vladlen Koltun
, Marco Hutter
:
Trajectory Optimization With Implicit Hard Contacts. IEEE Robotics Autom. Lett. 3(4): 3316-3323 (2018) - [c15]Elia Kaufmann, Antonio Loquercio, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Deep Drone Racing: Learning Agile Flight in Dynamic Environments. CoRL 2018: 133-145 - [c14]René Ranftl, Vladlen Koltun:
Deep Fundamental Matrix Estimation. ECCV (1) 2018: 292-309 - [i8]Elia Kaufmann, Antonio Loquercio, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Deep Drone Racing: Learning Agile Flight in Dynamic Environments. CoRR abs/1806.08548 (2018) - [i7]Ruben Grandia, Farbod Farshidian, Alexey Dosovitskiy, René Ranftl, Marco Hutter:
Frequency-Aware Model Predictive Control. CoRR abs/1809.04539 (2018) - [i6]Elia Kaufmann, Mathias Gehrig, Philipp Foehn, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing. CoRR abs/1810.06224 (2018) - 2017
- [c13]Jia Xu, René Ranftl, Vladlen Koltun:
Accurate Optical Flow via Direct Cost Volume Processing. CVPR 2017: 5807-5815 - [i5]Jia Xu, René Ranftl, Vladlen Koltun:
Accurate Optical Flow via Direct Cost Volume Processing. CoRR abs/1704.07325 (2017) - 2016
- [j3]Peter Ochs, René Ranftl, Thomas Brox, Thomas Pock:
Techniques for Gradient-Based Bilevel Optimization with Non-smooth Lower Level Problems. J. Math. Imaging Vis. 56(2): 175-194 (2016) - [c12]René Ranftl, Vibhav Vineet, Qifeng Chen
, Vladlen Koltun:
Dense Monocular Depth Estimation in Complex Dynamic Scenes. CVPR 2016: 4058-4066 - 2015
- [c11]Gernot Riegler, René Ranftl, Matthias Rüther, Thomas Pock, Horst Bischof:
Depth Restoration via Joint Training of a Global Regression Model and CNNs. BMVC 2015: 58.1-58.12 - [c10]Peter Ochs, René Ranftl, Thomas Brox, Thomas Pock:
Bilevel Optimization with Nonsmooth Lower Level Problems. SSVM 2015: 654-665 - 2014
- [j2]Yunjin Chen, WenSen Feng, René Ranftl, Hong Qiao, Thomas Pock:
A Higher-Order MRF Based Variational Model for Multiplicative Noise Reduction. IEEE Signal Process. Lett. 21(11): 1370-1374 (2014) - [j1]Yunjin Chen, René Ranftl, Thomas Pock:
Insights Into Analysis Operator Learning: From Patch-Based Sparse Models to Higher Order MRFs. IEEE Trans. Image Process. 23(3): 1060-1072 (2014) - [c9]René Ranftl, Thomas Pock:
A Deep Variational Model for Image Segmentation. GCPR 2014: 107-118 - [c8]René Ranftl, Kristian Bredies
, Thomas Pock:
Non-local Total Generalized Variation for Optical Flow Estimation. ECCV (1) 2014: 439-454 - [i4]Yunjin Chen, René Ranftl, Thomas Pock:
Insights into analysis operator learning: From patch-based sparse models to higher-order MRFs. CoRR abs/1401.2804 (2014) - [i3]Yunjin Chen, Thomas Pock, René Ranftl, Horst Bischof:
Revisiting loss-specific training of filter-based MRFs for image restoration. CoRR abs/1401.4107 (2014) - [i2]Yunjin Chen, René Ranftl, Thomas Pock:
A bi-level view of inpainting - based image compression. CoRR abs/1401.4112 (2014) - [i1]Yunjin Chen, WenSen Feng, René Ranftl, Hong Qiao, Thomas Pock:
A higher-order MRF based variational model for multiplicative noise reduction. CoRR abs/1404.5344 (2014) - 2013
- [c7]Yunjin Chen, Thomas Pock, René Ranftl, Horst Bischof
:
Revisiting Loss-Specific Training of Filter-Based MRFs for Image Restoration. GCPR 2013: 271-281 - [c6]Stefan Heber, René Ranftl, Thomas Pock:
Variational Shape from Light Field. EMMCVPR 2013: 66-79 - [c5]David Ferstl, René Ranftl, Matthias Rüther, Horst Bischof
:
Multi-modality depth map fusion using primal-dual optimization. ICCP 2013: 1-8 - [c4]David Ferstl, Christian Reinbacher
, René Ranftl, Matthias Rüther, Horst Bischof:
Image Guided Depth Upsampling Using Anisotropic Total Generalized Variation. ICCV 2013: 993-1000 - [c3]René Ranftl, Thomas Pock, Horst Bischof
:
Minimizing TGV-Based Variational Models with Non-convex Data Terms. SSVM 2013: 282-293 - 2012
- [c2]Stefan Heber, René Ranftl, Thomas Pock:
Approximate Envelope Minimization for Curvature Regularity. ECCV Workshops (3) 2012: 283-292 - [c1]René Ranftl, Stefan Gehrig, Thomas Pock, Horst Bischof
:
Pushing the limits of stereo using variational stereo estimation. Intelligent Vehicles Symposium 2012: 401-407
Coauthor Index
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last updated on 2024-08-20 22:55 CEST by the dblp team
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