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cs.CV2020

Reducing the Sim-to-Real Gap for Event Cameras

Timo Stoffregen, Cedric Scheerlinck, Davide Scaramuzza +4

Event cameras are paradigm-shifting novel sensors that report asynchronous, per-pixel brightness changes called 'events' with unparalleled low latency. This makes them ideal for hi…

cs.CV2019

CED: Color Event Camera Dataset

Cedric Scheerlinck, Henri Rebecq, Timo Stoffregen +3

Event cameras are novel, bio-inspired visual sensors, whose pixels output asynchronous and independent timestamped spikes at local intensity changes, called 'events'. Event cameras…

cs.CV2019

High Frame Rate Video Reconstruction based on an Event Camera

Liyuan Pan, Richard Hartley, Cedric Scheerlinck +3

Event-based cameras measure intensity changes (called `events') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the `active pixel sensor…

cs.CV2018

Asynchronous Spatial Image Convolutions for Event Cameras

Cedric Scheerlinck, Nick Barnes, Robert Mahony

Spatial convolution is arguably the most fundamental of 2D image processing operations. Conventional spatial image convolution can only be applied to a conventional image, that is,…

cs.CV2018

Bringing a Blurry Frame Alive at High Frame-Rate with an Event Camera

Liyuan Pan, Cedric Scheerlinck, Xin Yu +3

Event-based cameras can measure intensity changes (called `{\it events}') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the active pix…

cs.CV2018

Continuous-time Intensity Estimation Using Event Cameras

Cedric Scheerlinck, Nick Barnes, Robert Mahony

Event cameras provide asynchronous, data-driven measurements of local temporal contrast over a large dynamic range with extremely high temporal resolution. Conventional cameras cap…