164 citations · 323 across the 19 of their papers we have counts for
7 papers · 1 filter
Pushing the Limits of Asynchronous Graph-based Object Detection with Event Cameras
Daniel Gehrig, Davide Scaramuzza
State-of-the-art machine-learning methods for event cameras treat events as dense representations and process them with conventional deep neural networks. Thus, they fail to mainta…
Multi-Bracket High Dynamic Range Imaging with Event Cameras
Nico Messikommer, Stamatios Georgoulis, Daniel Gehrig +5
Modern high dynamic range (HDR) imaging pipelines align and fuse multiple low dynamic range (LDR) images captured at different exposure times. While these methods work well in stat…
Time Lens++: Event-based Frame Interpolation with Parametric Non-linear Flow and Multi-scale Fusion
Stepan Tulyakov, Alfredo Bochicchio, Daniel Gehrig +3
Recently, video frame interpolation using a combination of frame- and event-based cameras has surpassed traditional image-based methods both in terms of performance and memory effi…
Exploring Event Camera-based Odometry for Planetary Robots
Florian Mahlknecht, Daniel Gehrig, Jeremy Nash +4
Due to their resilience to motion blur and high robustness in low-light and high dynamic range conditions, event cameras are poised to become enabling sensors for vision-based expl…
Are High-Resolution Event Cameras Really Needed?
Daniel Gehrig, Davide Scaramuzza
Due to their outstanding properties in challenging conditions, event cameras have become indispensable in a wide range of applications, ranging from automotive, computational photo…
AEGNN: Asynchronous Event-based Graph Neural Networks
Simon Schaefer, Daniel Gehrig, Davide Scaramuzza
The best performing learning algorithms devised for event cameras work by first converting events into dense representations that are then processed using standard CNNs. However, t…
ESS: Learning Event-based Semantic Segmentation from Still Images
Zhaoning Sun, Nico Messikommer, Daniel Gehrig +1
Retrieving accurate semantic information in challenging high dynamic range (HDR) and high-speed conditions remains an open challenge for image-based algorithms due to severe image…