Event cameras are bio-inspired sensors that capture the per-pixel intensity changes
asynchronously and produce event streams encoding the time, pixel position, and polarity …

Drone deployment has become crucial in a variety of applications, including solutions to
traffic issues in metropolitan areas and highways. On the other hand, data collected via …

Abstract We present Recurrent Vision Transformers (RVTs), a novel backbone for object
detection with event cameras. Event cameras provide visual information with sub …

The best performing learning algorithms devised for event cameras work by first converting
events into dense representations that are then processed using standard CNNs. However …

Once an academic venture, autonomous driving has received unparalleled corporate
funding in the last decade. Still, operating conditions of current autonomous cars are mostly …

Event cameras are a type of novel neuromorphic sen-sor that has been gaining increasing
attention. Existing event-based backbones mainly rely on image-based designs to extract …

To help meet the increasing need for dynamic vision sensor (DVS) event camera data, this
paper proposes the v2e toolbox that generates realistic synthetic DVS events from intensity …

Automotive embedded algorithms have very high constraints in terms of latency, accuracy
and power consumption. In this work, we propose to train spiking neural networks (SNNs) …

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 …

Retrieving accurate semantic information in challenging high dynamic range (HDR) and
high-speed conditions remains an open challenge for image-based algorithms due to …