activity
20242026
collaborators

6 papers

cs.CV2026

Neural Events: Discrete Asynchronous Autoencoders for Event-Based Vision

Roberto Pellerito, Daniel Gehrig, Shintaro Shiba +1

Event cameras capture dynamic scenes with exceptional temporal fidelity by representing them as a continuous stream of microsecond resolution \textit{events}. Each individual event…

cs.CV2026

Geometric-Photometric Event-based 3D Gaussian Ray Tracing

Kai Kohyama, Yoshimitsu Aoki, Guillermo Gallego +1

Event cameras offer a high temporal resolution over traditional frame-based cameras, which makes them suitable for motion and structure estimation. However, it has been unclear how…

cs.CV2025

Simultaneous Motion And Noise Estimation with Event Cameras

Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego

Event cameras are emerging vision sensors whose noise is challenging to characterize. Existing denoising methods for event cameras are often designed in isolation and thus consider…

cs.CV2025

E-VLC: A Real-World Dataset for Event-based Visible Light Communication And Localization

Shintaro Shiba, Quan Kong, Norimasa Kobori

Optical communication using modulated LEDs (e.g., visible light communication) is an emerging application for event cameras, thanks to their high spatio-temporal resolutions. Event…

cs.CV2025

Iterative Event-based Motion Segmentation by Variational Contrast Maximization

Ryo Yamaki, Shintaro Shiba, Guillermo Gallego +1

Event cameras provide rich signals that are suitable for motion estimation since they respond to changes in the scene. As any visual changes in the scene produce event data, it is…

cs.CV2024

3D Human Scan With A Moving Event Camera

Kai Kohyama, Shintaro Shiba, Yoshimitsu Aoki

Capturing a 3D human body is one of the important tasks in computer vision with a wide range of applications such as virtual reality and sports analysis. However, conventional fram…