Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …

In recent decades, visual simultaneous localization and mapping (vSLAM) has gained
significant interest in both academia and industry. It estimates camera motion and …

In this work, we propose a novel framework for unsupervised learning for event cameras that
learns motion information from only the event stream. In particular, we propose an input …

Event cameras are bioinspired vision sensors that output pixel-level brightness changes
instead of standard intensity frames. These cameras do not suffer from motion blur and have …

New vision sensors, such as the dynamic and active-pixel vision sensor (DAVIS),
incorporate a conventional global-shutter camera and an event-based sensor in the same …

Event-based cameras are a new passive sensing modality with a number of benefits over
traditional cameras, including extremely low latency, asynchronous data acquisition, high …

Event-based cameras are bioinspired vision sensors whose pixels work independently from
each other and respond asynchronously to brightness changes, with microsecond …

We present a unifying framework to solve several computer vision problems with event
cameras: motion, depth and optical flow estimation. The main idea of our framework is to find …

Event cameras respond to scene dynamics and offer advantages to estimate motion.
Following recent image-based deep-learning achievements, optical flow estimation methods …

Event-based vision sensors, such as the Dynamic Vision Sensor (DVS), are ideally suited for
real-time motion analysis. The unique properties encompassed in the readings of such …