no code implementations • 28 Jul 2023 • Rong Zou, Manasi Muglikar, Nico Messikommer, Davide Scaramuzza
We present the first large-scale dataset consisting of synchronized images and event sequences to evaluate our approach.
no code implementations • CVPR 2023 • Manasi Muglikar, Leonard Bauersfeld, Diederik Paul Moeys, Davide Scaramuzza
Our method uses the continuous event stream caused by the rotation to reconstruct relative intensities at multiple polarizer angles.
1 code implementation • 14 Nov 2022 • Leonard Bauersfeld, Angel Romero, Manasi Muglikar, Davide Scaramuzza
In this work, we present a transformer-based, neural-network architecture that only uses the text content and the author names in the bibliography to attribute an anonymous manuscript to an author.
1 code implementation • 25 Mar 2022 • Mathias Gehrig, Manasi Muglikar, Davide Scaramuzza
To the best of our knowledge, our model is the first method that can regress dense pixel trajectories from event data.
no code implementations • 30 Nov 2021 • Manasi Muglikar, Guillermo Gallego, Davide Scaramuzza
Event cameras are bio-inspired sensors providing significant advantages over standard cameras such as low latency, high temporal resolution, and high dynamic range.
no code implementations • 20 Oct 2021 • Manasi Muglikar, Diederik Paul Moeys, Davide Scaramuzza
The depth estimation is achieved by an event-based structured light system consisting of a laser point projector coupled with a second event-based sensor tuned to detect the reflection of the laser from the scene.
1 code implementation • 26 May 2021 • Manasi Muglikar, Mathias Gehrig, Daniel Gehrig, Davide Scaramuzza
We propose a generic event camera calibration framework using image reconstruction.
no code implementations • 26 May 2020 • Philipp Foehn, Dario Brescianini, Elia Kaufmann, Titus Cieslewski, Mathias Gehrig, Manasi Muglikar, Davide Scaramuzza
This paper presents a novel system for autonomous, vision-based drone racing combining learned data abstraction, nonlinear filtering, and time-optimal trajectory planning.
no code implementations • 4 Mar 2020 • Manasi Muglikar, Zichao Zhang, Davide Scaramuzza
We propose a voxel-map representation to efficiently retrieve map points for visual SLAM.
no code implementations • 4 Mar 2020 • Juichung Kuo, Manasi Muglikar, Zichao Zhang, Davide Scaramuzza
We adapt a state-of-the-art visual-inertial odometry with these modifications, and experimental results show that the modified pipeline can adapt to a wide range of camera setups (e. g., 2 to 6 cameras in one experiment) without the need of sensor-specific modifications or tuning.