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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,…

Object detection plays a critical role in autonomous driving, where accurately and efficiently detecting objects in fast-moving scenes is crucial. Traditional frame-based cameras face challenges in balancing latency and bandwidth,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Bingquan Zhou , Jie Jiang

Event cameras provide microsecond latency, making them suitable for 6D object pose tracking in fast, dynamic scenes where conventional RGB and depth pipelines suffer from motion blur and large pixel displacements. We introduce EventTrack6D,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Jae-Young Kang , Hoonhee Cho , Taeyeop Lee , Minjun Kang , Bowen Wen , Youngho Kim , Kuk-Jin Yoon

The cameras in modern gaze-tracking systems suffer from fundamental bandwidth and power limitations, constraining data acquisition speed to 300 Hz realistically. This obstructs the use of mobile eye trackers to perform, e.g., low latency…

Computer Vision and Pattern Recognition · Computer Science 2022-08-09 Anastasios N. Angelopoulos , Julien N. P. Martel , Amit P. S. Kohli , Jorg Conradt , Gordon Wetzstein

Our paper proposes a direct sparse visual odometry method that combines event and RGB-D data to estimate the pose of agile-legged robots during dynamic locomotion and acrobatic behaviors. Event cameras offer high temporal resolution and…

Robotics · Computer Science 2023-05-17 Shifan Zhu , Zhipeng Tang , Michael Yang , Erik Learned-Miller , Donghyun Kim

Event cameras encode visual information with high temporal precision, low data-rate, and high-dynamic range. Thanks to these characteristics, event cameras are particularly suited for scenarios with high motion, challenging lighting…

Computer Vision and Pattern Recognition · Computer Science 2020-12-10 Etienne Perot , Pierre de Tournemire , Davide Nitti , Jonathan Masci , Amos Sironi

Event-based vision sensors, such as the Dynamic Vision Sensor (DVS), are ideally suited for real-time motion analysis. The unique properties encompassed in the readings of such sensors provide high temporal resolution, superior sensitivity…

Computer Vision and Pattern Recognition · Computer Science 2020-01-14 Anton Mitrokhin , Cornelia Fermuller , Chethan Parameshwara , Yiannis Aloimonos

Pose estimation and tracking of objects is a fundamental application in 3D vision. Event cameras possess remarkable attributes such as high dynamic range, low latency, and resilience against motion blur, which enables them to address…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Zibin Liu , Banglei Guan , Yang Shang , Qifeng Yu , Laurent Kneip

Event cameras are emerging imaging technology that offers advantages over conventional frame-based imaging sensors in dynamic range and sensing speed. Complementing the rich texture and color perception of traditional image frames, the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Peiqi Duan , Boyu Li , Yixin Yang , Hanyue Lou , Minggui Teng , Yi Ma , Boxin Shi

Event-based cameras, also called silicon retinas, potentially revolutionize computer vision by detecting and reporting significant changes in intensity asynchronous events, offering extended dynamic range, low latency, and low power…

Image and Video Processing · Electrical Eng. & Systems 2023-11-06 Julian Moosmann , Jakub Mandula , Philipp Mayer , Luca Benini , Michele Magno

Object pose tracking is one of the pivotal technologies in multimedia, attracting ever-growing attention in recent years. Existing methods employing traditional cameras encounter numerous challenges such as motion blur, sensor noise,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Zibin Liu , Banglei Guan , Yang Shang , Shunkun Liang , Zhenbao Yu , Qifeng Yu

Fast neuromorphic event-based vision sensors (Dynamic Vision Sensor, DVS) can be combined with slower conventional frame-based sensors to enable higher-quality inter-frame interpolation than traditional methods relying on fixed motion…

Computer Vision and Pattern Recognition · Computer Science 2021-12-20 Adam Radomski , Andreas Georgiou , Thomas Debrunner , Chenghan Li , Luca Longinotti , Minwon Seo , Moosung Kwak , Chang-Woo Shin , Paul K. J. Park , Hyunsurk Eric Ryu , Kynan Eng

Autonomous driving systems rely heavily on robust sensor fusion to perceive complex envi- ronments. Traditional setups using RGB cameras and LiDAR often struggle in high-dynamic- range scenes or high-speed scenarios due to motion blur and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Mustafa Sakhaia , Kaung Sithua , Min Khant Soe Okea , Maciej Wielgosza

The increasing adoption of human-robot interaction presents opportunities for technology to positively impact lives, particularly those with visual impairments, through applications such as guide-dog-like assistive robotics. We present a…

Robotics · Computer Science 2024-08-27 Adam Scicluna , Cedric Le Gentil , Sheila Sutjipto , Gavin Paul

Event-based bionic camera asynchronously captures dynamic scenes with high temporal resolution and high dynamic range, offering potential for the integration of events and RGB under conditions of illumination degradation and fast motion.…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Pengcheng Shao , Tianyang Xu , Xuefeng Zhu , Xiaojun Wu , Josef Kittler

Event camera sensors are bio-inspired sensors which asynchronously capture per-pixel brightness changes and output a stream of events encoding the polarity, location and time of these changes. These systems are witnessing rapid advancements…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Aupendu Kar , Vishnu Raj , Guan-Ming Su

Inspired by the complementarity between conventional frame-based and bio-inspired event-based cameras, we propose a multi-modal based approach to fuse visual cues from the frame- and event-domain to enhance the single object tracking…

Computer Vision and Pattern Recognition · Computer Science 2021-09-21 Jiqing Zhang , Xin Yang , Yingkai Fu , Xiaopeng Wei , Baocai Yin , Bo Dong

Existing datasets for RGB-DVS tracking are collected with DVS346 camera and their resolution ($346 \times 260$) is low for practical applications. Actually, only visible cameras are deployed in many practical systems, and the newly designed…

Computer Vision and Pattern Recognition · Computer Science 2024-01-08 Yabin Zhu , Xiao Wang , Chenglong Li , Bo Jiang , Lin Zhu , Zhixiang Huang , Yonghong Tian , Jin Tang

We present a method that leverages the complementarity of event cameras and standard cameras to track visual features with low-latency. Event cameras are novel sensors that output pixel-level brightness changes, called "events". They offer…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Daniel Gehrig , Henri Rebecq , Guillermo Gallego , Davide Scaramuzza

Event cameras offer unique advantages such as high temporal resolution, low latency, and high dynamic range, making them more and more popular for vision tasks under challenging light conditions. However, their high cost, limited…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Zijie Ning , Enmin Lin , Sudarshan R. Iyengar , Patrick Vandewalle