papers

Publications (6)

cs.RO2026

Efficient Onboard Spacecraft Pose Estimation with Event Cameras and Neuromorphic Hardware

Arunkumar Rathinam, Jules Lecomte, Jost Reelsen +3

Reliable relative pose estimation is a key enabler for autonomous rendezvous and proximity operations, yet space imagery is notoriously challenging due to extreme illumination, hig…

cs.CV2025

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks

Michael Neumeier, Jules Lecomte, Nils Kazinski +3

Recognizing human activities early is crucial for the safety and responsiveness of human-robot and human-machine interfaces. Due to their high temporal resolution and low latency,…

cs.CV2023

Neuromorphic Optical Flow and Real-time Implementation with Event Cameras

Yannick Schnider, Stanislaw Wozniak, Mathias Gehrig +5

Optical flow provides information on relative motion that is an important component in many computer vision pipelines. Neural networks provide high accuracy optical flow, yet their…

cs.NE2025

TONUS: Neuromorphic human pose estimation for artistic sound co-creation

Jules Lecomte, Konrad Zinner, Michael Neumeier +1

Human machine interaction is a huge source of inspiration in today's media art and digital design, as machines and humans merge together more and more. Its place in art reflects it…

cs.NE2025

Scaling Up Resonate-and-Fire Networks for Fast Deep Learning

Thomas E. Huber, Jules Lecomte, Borislav Polovnikov +1

Spiking neural networks (SNNs) present a promising computing paradigm for neuromorphic processing of event-based sensor data. The resonate-and-fire (RF) neuron, in particular, appe…

cs.CV2024

Dynamic Event-based Optical Identification and Communication

Axel von Arnim, Jules Lecomte, Naima Elosegui Borras +2

Optical identification is often done with spatial or temporal visual pattern recognition and localization. Temporal pattern recognition, depending on the technology, involves a tra…