54 citations · 114 across the 9 of their papers we have counts for
13 papers
Event Spectroscopy: Event-based Multispectral and Depth Sensing using Structured Light
Christian Geckeler, Niklas Neugebauer, Manasi Muglikar +2
Uncrewed aerial vehicles (UAVs) are increasingly deployed in forest environments for tasks such as environmental monitoring and search and rescue, which require safe navigation thr…
Event-Based De-Snowing for Autonomous Driving
Manasi Muglikar, Nico Messikommer, Marco Cannici +1
Adverse weather conditions, particularly heavy snowfall, pose significant challenges to both human drivers and autonomous vehicles. Traditional image-based de-snowing methods often…
Event Cameras Meet SPADs for High-Speed, Low-Bandwidth Imaging
Manasi Muglikar, Siddharth Somasundaram, Akshat Dave +3
Traditional cameras face a trade-off between low-light performance and high-speed imaging: longer exposure times to capture sufficient light results in motion blur, whereas shorter…
Seeing Behind Dynamic Occlusions with Event Cameras
Rong Zou, Manasi Muglikar, Nico Messikommer +1
Unwanted camera occlusions, such as debris, dust, rain-drops, and snow, can severely degrade the performance of computer-vision systems. Dynamic occlusions are particularly challen…
Event-based Shape from Polarization
Manasi Muglikar, Leonard Bauersfeld, Diederik Paul Moeys +1
State-of-the-art solutions for Shape-from-Polarization (SfP) suffer from a speed-resolution tradeoff: they either sacrifice the number of polarization angles measured or necessitat…
Cracking Double-Blind Review: Authorship Attribution with Deep Learning
Leonard Bauersfeld, Angel Romero, Manasi Muglikar +1
Double-blind peer review is considered a pillar of academic research because it is perceived to ensure a fair, unbiased, and fact-centered scientific discussion. Yet, experienced r…
Dense Continuous-Time Optical Flow from Events and Frames
Mathias Gehrig, Manasi Muglikar, Davide Scaramuzza
We present a method for estimating dense continuous-time optical flow from event data. Traditional dense optical flow methods compute the pixel displacement between two images. Due…
ESL: Event-based Structured Light
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. We propose a no…
Event Guided Depth Sensing
Manasi Muglikar, Diederik Paul Moeys, Davide Scaramuzza
Active depth sensors like structured light, lidar, and time-of-flight systems sample the depth of the entire scene uniformly at a fixed scan rate. This leads to limited spatio-temp…
How to Calibrate Your Event Camera
Manasi Muglikar, Mathias Gehrig, Daniel Gehrig +1
We propose a generic event camera calibration framework using image reconstruction. Instead of relying on blinking LED patterns or external screens, we show that neural-network-bas…
AlphaPilot: Autonomous Drone Racing
Philipp Foehn, Dario Brescianini, Elia Kaufmann +4
This paper presents a novel system for autonomous, vision-based drone racing combining learned data abstraction, nonlinear filtering, and time-optimal trajectory planning. The syst…
Voxel Map for Visual SLAM
Manasi Muglikar, Zichao Zhang, Davide Scaramuzza
In modern visual SLAM systems, it is a standard practice to retrieve potential candidate map points from overlapping keyframes for further feature matching or direct tracking. In t…
Redesigning SLAM for Arbitrary Multi-Camera Systems
Juichung Kuo, Manasi Muglikar, Zichao Zhang +1
Adding more cameras to SLAM systems improves robustness and accuracy but complicates the design of the visual front-end significantly. Thus, most systems in the literature are tail…