activity
20182022
most citedLearning High-Speed Flight in the Wild

351 citations · 394 across the 4 of their papers we have counts for

collaborators

14 papers

cs.AI20222 cited

Learning Visual Locomotion with Cross-Modal Supervision

Antonio Loquercio, Ashish Kumar, Jitendra Malik

In this work, we show how to learn a visual walking policy that only uses a monocular RGB camera and proprioception. Since simulating RGB is hard, we necessarily have to learn visi…

cs.RO202235 cited

Visual Attention Prediction Improves Performance of Autonomous Drone Racing Agents

Christian Pfeiffer, Simon Wengeler, Antonio Loquercio +1

Humans race drones faster than neural networks trained for end-to-end autonomous flight. This may be related to the ability of human pilots to select task-relevant visual informati…

cs.RO2021351 cited

Learning High-Speed Flight in the Wild

Antonio Loquercio, Elia Kaufmann, René Ranftl +3

Quadrotors are agile. Unlike most other machines, they can traverse extremely complex environments at high speeds. To date, only expert human pilots have been able to fully exploit…

cs.CV2020

Primal-Dual Mesh Convolutional Neural Networks

Francesco Milano, Antonio Loquercio, Antoni Rosinol +2

Recent works in geometric deep learning have introduced neural networks that allow performing inference tasks on three-dimensional geometric data by defining convolution, and somet…

cs.RO2020

Deep Drone Acrobatics

Elia Kaufmann, Antonio Loquercio, René Ranftl +3

Performing acrobatic maneuvers with quadrotors is extremely challenging. Acrobatic flight requires high thrust and extreme angular accelerations that push the platform to its physi…

cs.CV2020

Event-based Asynchronous Sparse Convolutional Networks

Nico Messikommer, Daniel Gehrig, Antonio Loquercio +1

Event cameras are bio-inspired sensors that respond to per-pixel brightness changes in the form of asynchronous and sparse "events". Recently, pattern recognition algorithms, such…