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Event cameras offer high temporal resolution and low latency, making them ideal sensors for high-speed robotic applications where conventional cameras suffer from image degradations such as motion blur. In addition, their low power…

Event-based keypoint detection and matching holds significant potential, enabling the integration of event sensors into highly optimized Visual SLAM systems developed for frame cameras over decades of research. Unfortunately, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Yannick Burkhardt , Simon Schaefer , Stefan Leutenegger

Event cameras have recently shown promising capabilities in instantaneous motion estimation due to their robustness to low light and fast motions. However, computing wide-baseline correspondence between two arbitrary views remains a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-22 Ruijun Zhang , Hang Su , Kostas Daniilidis , Ziyun Wang

Video frame interpolation (VFI) that leverages the bio-inspired event cameras as guidance has recently shown better performance and memory efficiency than the frame-based methods, thanks to the event cameras' advantages, such as high…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Haoyue Liu , Jinghan Xu , Yi Chang , Hanyu Zhou , Haozhi Zhao , Lin Wang , Luxin Yan

High-speed vision sensing is essential for real-time perception in applications such as robotics, autonomous vehicles, and industrial automation. Traditional frame-based vision systems suffer from motion blur, high latency, and redundant…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Riadul Islam , Joey Mulé , Dhandeep Challagundla , Shahmir Rizvi , Sean Carson

Keypoint detection and tracking in traditional image frames are often compromised by image quality issues such as motion blur and extreme lighting conditions. Event cameras offer potential solutions to these challenges by virtue of their…

Robotics · Computer Science 2024-03-19 Xiangyuan Wang , Kuangyi Chen , Wen Yang , Lei Yu , Yannan Xing , Huai Yu

Event cameras are a bio-inspired class of sensors that asynchronously measure per-pixel intensity changes. Under fixed illumination conditions in static or low-motion scenes, rigidly mounted event cameras are unable to generate any events…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Vincenzo Polizzi , Stephen Yang , Quentin Clark , Jonathan Kelly , Igor Gilitschenski , David B. Lindell

Event cameras capture the motion of intensity gradients (edges) in the image plane in the form of rapid asynchronous events. When accumulated in 2D histograms, these events depict overlays of the edges in motion, consequently obscuring the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Pritam P. Karmokar , Quan H. Nguyen , William J. Beksi

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 work on packets of events trade off speed for accuracy,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Shintaro Shiba , Yoshimitsu Aoki , Guillermo Gallego

Conventional visual simultaneous localization and mapping (SLAM) algorithms often fail under rapid motion, low illumination, or abrupt lighting transitions due to motion blur and limited dynamic range. Event cameras mitigate these issues…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Şebnem Sarıözkan , Hürkan Şahin , Olaya Álvarez-Tuñón , Erdal Kayacan

The neuromorphic event cameras, which capture the optical changes of a scene, have drawn increasing attention due to their high speed and low power consumption. However, the event data are noisy, sparse, and nonuniform in the…

Computer Vision and Pattern Recognition · Computer Science 2021-03-23 Chang Liu , Xiaojuan Qi , Edmund Lam , Ngai Wong

Event vision sensors (neuromorphic cameras) output sparse, asynchronous ON/OFF events triggered by log-intensity threshold crossings, enabling microsecond-scale sensing with high dynamic range and low data bandwidth. As a nonlinear system,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Nimrod Kruger , Nicholas Owen Ralph , Gregory Cohen , Paul Hurley

Event-based motion field estimation is an important task. However, current optical flow methods face challenges: learning-based approaches, often frame-based and relying on CNNs, lack cross-domain transferability, while model-based methods,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Dehao Yuan , Levi Burner , Jiayi Wu , Minghui Liu , Jingxi Chen , Yiannis Aloimonos , Cornelia Fermüller

Reliable self-localization is a foundational skill for many intelligent mobile platforms. This paper explores the use of event cameras for motion tracking thereby providing a solution with inherent robustness under difficult dynamics and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Tao Liu , Runze Yuan , Yi'ang Ju , Xun Xu , Jiaqi Yang , Xiangting Meng , Xavier Lagorce , Laurent Kneip

Event cameras are bio-inspired sensors that offer several advantages, such as low latency, high-speed and high dynamic range, to tackle challenging scenarios in computer vision. This paper presents a solution to the problem of 3D…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Yi Zhou , Guillermo Gallego , Henri Rebecq , Laurent Kneip , Hongdong Li , Davide Scaramuzza

Event cameras are emerging vision sensors and their advantages are suitable for various applications such as autonomous robots. Contrast maximization (CMax), which provides state-of-the-art accuracy on motion estimation using events, may…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Shintaro Shiba , Yoshimitsu Aoki , Guillermo Gallego

In sports, such as alpine skiing, coaches would like to know the speed and various biomechanical variables of their athletes and competitors. Existing methods use either body-worn sensors, which are cumbersome to setup, or manual image…

Computer Vision and Pattern Recognition · Computer Science 2019-09-02 Roman Bachmann , Jörg Spörri , Pascal Fua , Helge Rhodin

Event cameras are bio-inspired, motion-activated sensors that demonstrate substantial potential in handling challenging situations, such as motion blur and high-dynamic range. In this paper, we proposed EVI-SAM to tackle the problem of 6…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Weipeng Guan , Peiyu Chen , Huibin Zhao , Yu Wang , Peng Lu

For robust visual-inertial SLAM in perceptually-challenging indoor environments,recent studies exploit line features to extract descriptive information about scene structure to deal with the degeneracy of point features. But existing…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Wanting Li , Shuo Wang , Yongcai Wang , Yu Shao , Xuewei Bai , Deying Li

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time,…