René Ranftl

Orcid: 0000-0003-4158-2759

Affiliations:

Intel Laboratory, Munich, Germany

According to our database¹, René Ranftl authored at least 48 papers between 2012 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

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In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2023

Monocular Visual-Inertial Depth Estimation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

An Analysis of Super-Net Heuristics in Weight-Sharing NAS.

[BibT_eX]

[DOI]

Kaicheng Yu

René Ranftl

Mathieu Salzmann

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Constrained stochastic optimal control with learned importance sampling: A path integral approach.

[BibT_eX]

[DOI]

Int. J. Robotics Res., 2022

Unsupervised Contrastive Domain Adaptation for Semantic Segmentation.

[BibT_eX]

[DOI]

CoRR, 2022

Language-driven Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Learning high-speed flight in the wild.

[BibT_eX]

[DOI]

Sci. Robotics, 2021

High Speed and High Dynamic Range Video with an Event Camera.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Transferable End-to-end Room Layout Estimation via Implicit Encoding.

[BibT_eX]

[DOI]

CoRR, 2021

Looking Beyond Single Images for Contrastive Semantic Segmentation Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Drone Acrobatics (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Vision Transformers for Dense Prediction.

[BibT_eX]

[DOI]

René Ranftl

Alexey Bochkovskiy

Vladlen Koltun

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search.

[BibT_eX]

[DOI]

Kaicheng Yu

René Ranftl

Mathieu Salzmann

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Deep Drone Racing: From Simulation to Reality With Domain Randomization.

[BibT_eX]

[DOI]

IEEE Trans. Robotics, 2020

Safe Robot Navigation Via Multi-Modal Anomaly Detection.

[BibT_eX]

[DOI]

Lorenz Wellhausen

René Ranftl

Marco Hutter

IEEE Robotics Autom. Lett., 2020

How to Train Your Super-Net: An Analysis of Training Heuristics in Weight-Sharing NAS.

[BibT_eX]

[DOI]

Kaicheng Yu

René Ranftl

Mathieu Salzmann

CoRR, 2020

Deep Drone Acrobatics.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XVI, 2020

High-Dimensional Convolutional Networks for Geometric Pattern Recognition.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Where Should I Walk? Predicting Terrain Properties From Images Via Self-Supervised Learning.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2019

Frequency-Aware Model Predictive Control.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2019

Trajectory Optimization for Legged Robots With Slipping Motions.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2019

Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer.

[BibT_eX]

[DOI]

CoRR, 2019

Feedback MPC for Torque-Controlled Legged Robots.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Robotics and Automation, 2019

Learning to Predict the Wind for Safe Aerial Vehicle Planning.

[BibT_eX]

[DOI]

Florian Achermann

Nicholas R. J. Lawrance

Proceedings of the International Conference on Robotics and Automation, 2019

Deep Layers as Stochastic Solvers.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

What Do Single-View 3D Reconstruction Networks Learn?

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Events-To-Video: Bringing Modern Computer Vision to Event Cameras.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Trajectory Optimization With Implicit Hard Contacts.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2018

Deep Fundamental Matrix Estimation.

[BibT_eX]

[DOI]

René Ranftl

Vladlen Koltun

Proceedings of the Computer Vision - ECCV 2018, 2018

Deep Drone Racing: Learning Agile Flight in Dynamic Environments.

[BibT_eX]

[DOI]

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017

Accurate Optical Flow via Direct Cost Volume Processing.

[BibT_eX]

[DOI]

Jia Xu

René Ranftl

Vladlen Koltun

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Techniques for Gradient-Based Bilevel Optimization with Non-smooth Lower Level Problems.

[BibT_eX]

[DOI]

J. Math. Imaging Vis., 2016

Dense Monocular Depth Estimation in Complex Dynamic Scenes.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Bilevel Optimization with Nonsmooth Lower Level Problems.

[BibT_eX]

[DOI]

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2015

Depth Restoration via Joint Training of a Global Regression Model and CNNs.

[BibT_eX]

[DOI]

Proceedings of the British Machine Vision Conference 2015, 2015

2014

Insights Into Analysis Operator Learning: From Patch-Based Sparse Models to Higher Order MRFs.

[BibT_eX]

[DOI]

Yunjin Chen

René Ranftl

Thomas Pock

IEEE Trans. Image Process., 2014

A Higher-Order MRF Based Variational Model for Multiplicative Noise Reduction.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2014

A bi-level view of inpainting - based image compression.

[BibT_eX]

[DOI]

Yunjin Chen

René Ranftl

Thomas Pock

CoRR, 2014

Non-local Total Generalized Variation for Optical Flow Estimation.

[BibT_eX]

[DOI]

René Ranftl

Kristian Bredies

Thomas Pock

Proceedings of the Computer Vision - ECCV 2014, 2014

A Deep Variational Model for Image Segmentation.

[BibT_eX]

[DOI]

René Ranftl

Thomas Pock

Proceedings of the Pattern Recognition - 36th German Conference, 2014

2013

Minimizing TGV-Based Variational Models with Non-convex Data Terms.

[BibT_eX]

[DOI]

René Ranftl

Thomas Pock

Horst Bischof

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2013

Image Guided Depth Upsampling Using Anisotropic Total Generalized Variation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2013

Multi-modality depth map fusion using primal-dual optimization.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computational Photography, 2013

Variational Shape from Light Field.

[BibT_eX]

[DOI]

Stefan Heber

René Ranftl

Thomas Pock

Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2013

Revisiting Loss-Specific Training of Filter-Based MRFs for Image Restoration.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition - 35th German Conference, 2013

2012

Pushing the limits of stereo using variational stereo estimation.

[BibT_eX]

[DOI]

Proceedings of the 2012 IEEE Intelligent Vehicles Symposium, 2012

Approximate Envelope Minimization for Curvature Regularity.

[BibT_eX]

[DOI]

Stefan Heber

René Ranftl

Thomas Pock

Proceedings of the Computer Vision - ECCV 2012. Workshops and Demonstrations, 2012

René Ranftl

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