Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

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-based cameras are the emerging bioinspired technology in vision sensing. Different
from the traditional standard cameras, the event-based cameras asynchronously record the …

Event-based cameras have recently drawn the attention of the Computer Vision community
thanks to their advantages in terms of high temporal resolution, low power consumption and …

Neuromorphic vision sensing (NVS) devices represent visual information as sequences of
asynchronous discrete events (aka," spikes'") in response to changes in scene reflectance …

We present EKLT, a feature tracking method that leverages the complementarity of event
cameras and standard cameras to track visual features with high temporal resolution. Event …

Spiking neural networks (SNNs) are potentially highly efficient models for inference on fully
parallel neuromorphic hardware, but existing training methods that convert conventional …

We present a method that leverages the complementarity of event cameras and standard
cameras to track visual features with low-latency. Event cameras are novel sensors that …

Neuromorphic vision sensing (NVS) devices represent visual information as sequences of
asynchronous discrete events (aka,“spikes”) in response to changes in scene reflectance …

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