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Tracking using bio-inspired event cameras has drawn more and more attention in recent years. Existing works either utilize aligned RGB and event data for accurate tracking or directly learn an event-based tracker. The first category needs…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Xiao Wang , Shiao Wang , Chuanming Tang , Lin Zhu , Bo Jiang , Yonghong Tian , Jin Tang

Because of their high temporal resolution, increased resilience to motion blur, and very sparse output, event cameras have been shown to be ideal for low-latency and low-bandwidth feature tracking, even in challenging scenarios. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Nico Messikommer , Carter Fang , Mathias Gehrig , Giovanni Cioffi , Davide Scaramuzza

Visual object tracking under challenging conditions of motion and light can be hindered by the capabilities of conventional cameras, prone to producing images with motion blur. Event cameras are novel sensors suited to robustly perform…

Computer Vision and Pattern Recognition · Computer Science 2022-12-16 Irene Perez-Salesa , Rodrigo Aldana-Lopez , Carlos Sagues

Existing tracking algorithms typically rely on low-frame-rate RGB cameras coupled with computationally intensive deep neural network architectures to achieve effective tracking. However, such frame-based methods inherently face challenges…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Shiao Wang , Xiao Wang , Liye Jin , Bo Jiang , Lin Zhu , Lan Chen , Yonghong Tian , Bin Luo

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

Most existing RGB-based trackers target low frame rate benchmarks of around 30 frames per second. This setting restricts the tracker's functionality in the real world, especially for fast motion. Event-based cameras as bioinspired sensors…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Jiqing Zhang , Yuanchen Wang , Wenxi Liu , Meng Li , Jinpeng Bai , Baocai Yin , Xin Yang

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

We then introduce a novel hierarchical knowledge distillation strategy that incorporates the similarity matrix, feature representation, and response map-based distillation to guide the learning of the student Transformer network. We also…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Shiao Wang , Xiao Wang , Chao Wang , Liye Jin , Lin Zhu , Bo Jiang , Yonghong Tian , Jin Tang

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

Event-based cameras are bio-inspired vision sensors whose pixels work independently from each other and respond asynchronously to brightness changes, with microsecond resolution. Their advantages make it possible to tackle challenging…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Yi Zhou , Guillermo Gallego , Shaojie Shen

Event-based cameras are biologically inspired sensors that output events, i.e., asynchronous pixel-wise brightness changes in the scene. Their high dynamic range and temporal resolution of a microsecond makes them more reliable than…

Robotics · Computer Science 2021-07-13 Antea Hadviger , Igor Cvišić , Ivan Marković , Sacha Vražić , Ivan Petrović

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,…

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

Event cameras offer the exciting possibility of tracking the camera's pose during high-speed motion and in adverse lighting conditions. Despite this promise, existing event-based monocular visual odometry (VO) approaches demonstrate limited…

Computer Vision and Pattern Recognition · Computer Science 2023-12-18 Simon Klenk , Marvin Motzet , Lukas Koestler , Daniel Cremers

Event cameras continue to attract interest due to desirable characteristics such as high dynamic range, low latency, virtually no motion blur, and high energy efficiency. One of the potential applications that would benefit from these…

Computer Vision and Pattern Recognition · Computer Science 2022-10-17 Tobias Fischer , Michael Milford

In Intelligent Transportation Systems (ITS), multi-object tracking is primarily based on frame-based cameras. However, these cameras tend to perform poorly under dim lighting and high-speed motion conditions. Event cameras, characterized by…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Mengyu Li , Xingcheng Zhou , Guang Chen , Alois Knoll , Hu Cao

Event cameras offer unparalleled advantages for real-time perception in dynamic environments, thanks to the microsecond-level temporal resolution and asynchronous operation. Existing event detectors, however, are limited by fixed-frequency…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Dongyue Lu , Lingdong Kong , Gim Hee Lee , Camille Simon Chane , Wei Tsang Ooi

Today, people can easily record memorable moments, ranging from concerts, sports events, lectures, family gatherings, and birthday parties with multiple consumer cameras. However, synchronizing these cross-camera streams remains…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Shaowei Liu , David Yifan Yao , Saurabh Gupta , Shenlong Wang

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

Despite significant progress, RGB-based trackers remain vulnerable to challenging imaging conditions, such as low illumination and fast motion. Event cameras offer a promising alternative by asynchronously capturing pixel-wise brightness…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Shiao Wang , Xiao Wang , Duoqing Yang , Wenhao Zhang , Bo Jiang , Lin Zhu , Yonghong Tian , Bin Luo
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