97 citations · 210 across the 11 of their papers we have counts for
12 papers
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…
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…
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…
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…
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…
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…
Event-based Background-Oriented Schlieren
Shintaro Shiba, Friedhelm Hamann, Yoshimitsu Aoki +1
Schlieren imaging is an optical technique to observe the flow of transparent media, such as air or water, without any particle seeding. However, conventional frame-based techniques…
Fast Event-based Optical Flow Estimation by Triplet Matching
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Event cameras are novel bio-inspired sensors that offer advantages over traditional cameras (low latency, high dynamic range, low power, etc.). Optical flow estimation methods that…
A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Event cameras are emerging vision sensors and their advantages are suitable for various applications such as autonomous robots. Contrast maximization (CMax), which provides state-o…
Secrets of Event-Based Optical Flow
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Event cameras respond to scene dynamics and offer advantages to estimate motion. Following recent image-based deep-learning achievements, optical flow estimation methods for event…
Event Collapse in Contrast Maximization Frameworks
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Contrast maximization (CMax) is a framework that provides state-of-the-art results on several event-based computer vision tasks, such as ego-motion or optical flow estimation. Howe…
Exploration of Reinforcement Learning for Event Camera using Car-like Robots
Riku Arakawa, Shintaro Shiba
We demonstrate the first reinforcement-learning application for robots equipped with an event camera. Because of the considerably lower latency of the event camera, it is possible…