Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

The design of robots that interact autonomously with the environment and exhibit complex
behaviours is an open challenge that can benefit from understanding what makes living …

Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …

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 …

Event cameras encode visual information with high temporal precision, low data-rate, and
high-dynamic range. Thanks to these characteristics, event cameras are particularly suited …

We propose to incorporate feature correlation and sequential processing into dense optical
flow estimation from event cameras. Modern frame-based optical flow methods heavily rely …

Event cameras are vision sensors that record asynchronous streams of per-pixel brightness
changes, referred to as" events". They have appealing advantages over frame based …

Simultaneous localization and map** (SLAM) consists in the concurrent construction of a
model of the environment (the map), and the estimation of the state of the robot moving …

Event-based cameras have shown great promise in a variety of situations where frame
based cameras suffer, such as high speed motions and high dynamic range scenes …

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