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 …

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 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 bio-inspired vision sensors that naturally capture the dynamics of a
scene, filtering out redundant information. This paper presents a deep neural network …

Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

This paper addresses the problem of cross-modal object tracking from RGB videos and
event data. Rather than constructing a complex cross-modal fusion network, we explore the …

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 …

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

The field of neuromorphic computing promises extremely low-power and low-latency
sensing and processing. Challenges in transferring learning algorithms from traditional …

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