In this work, we introduce APEIRON, a rich multimodal aerial dataset that simultaneously collects perception data from a stereocamera and an event based camera sensor, along with measurements of wireless network links obtained using an LTE module. The assembled dataset consists of both perception and network data, making it suitable for typical perception or communication applications.
This paper introduces Helios, the first extremely low-power, real-time, event-based hand gesture recognition system designed for all-day on smart eyewear. Helios can recognize seven classes of gestures, including subtle microgestures like swipes and pinches, with 91% accuracy. We also demonstrate real-time performance across 20 users at a remarkably low latency of 60ms.
In this paper, we present SEVD, a first-of-its-kind multi-view ego, and fixed perception synthetic event-based dataset using multiple dynamic vision sensors within the CARLA simulator. We evaluate the dataset using state-of-the-art event-based (RED, RVT) and frame-based (YOLOv8) methods for traffic participant detection tasks and provide baseline benchmarks for assessment.
Prophesee et Bpifrance investissent 15 millions d’euros pour le développement d’une nouvelle génération de capteurs neuromorphique, fabriqués en France, destinés à l’IA embarquée dans 1,3 milliard de smartphones.
In this work, we present our exploration of optimizing event-based neural network inference on SENECA, a scalable and flexible neuromorphic architecture. Our optimizations for event-based neural networks can be potentially generalized to a wide range of event-based neuromorphic processors.