activity
20172023
most citedLearning High-Speed Flight in the Wild

351 citations · 614 across the 11 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

cs.CV2019

Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer

René Ranftl, Katrin Lasinger, David Hafner +2

The success of monocular depth estimation relies on large and diverse training sets. Due to the challenges associated with acquiring dense ground-truth depth across different envir…

cs.CV2019

High Speed and High Dynamic Range Video with an Event Camera

Henri Rebecq, René Ranftl, Vladlen Koltun +1

Event cameras are novel sensors that report brightness changes in the form of a stream of asynchronous "events" instead of intensity frames. They offer significant advantages with…

cs.CV2019

What Do Single-view 3D Reconstruction Networks Learn?

Maxim Tatarchenko, Stephan R. Richter, René Ranftl +3

Convolutional networks for single-view object reconstruction have shown impressive performance and have become a popular subject of research. All existing techniques are united by…

cs.RO2019

Deep Drone Racing: From Simulation to Reality with Domain Randomization

Antonio Loquercio, Elia Kaufmann, René Ranftl +3

Dynamically changing environments, unreliable state estimation, and operation under severe resource constraints are fundamental challenges that limit the deployment of small autono…

cs.RO2019

Feedback MPC for Torque-Controlled Legged Robots

Ruben Grandia, Farbod Farshidian, René Ranftl +1

The computational power of mobile robots is currently insufficient to achieve torque level whole-body Model Predictive Control (MPC) at the update rates required for complex dynami…

cs.CV2019★ 7 cited

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

Henri Rebecq, René Ranftl, Vladlen Koltun +1

Event cameras are novel sensors that report brightness changes in the form of asynchronous "events" instead of intensity frames. They have significant advantages over conventional…