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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 are promising devices for lowlatency tracking and high-dynamic range imaging. In this paper,we propose a novel approach for 6 degree-of-freedom (6-DoF)object motion tracking that combines measurements of eventand frame-based…

Computer Vision and Pattern Recognition · Computer Science 2022-04-11 Haolong Li , Joerg Stueckler

In low-light conditions, capturing videos with frame-based cameras often requires long exposure times, resulting in motion blur and reduced visibility. While frame-based motion deblurring and low-light enhancement have been studied, they…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Taewoo Kim , Jaeseok Jeong , Hoonhee Cho , Yuhwan Jeong , Kuk-Jin Yoon

Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Guillermo Gallego , Jon E. A. Lund , Elias Mueggler , Henri Rebecq , Tobi Delbruck , Davide Scaramuzza

Event cameras are novel vision sensors that sample, in an asynchronous fashion, brightness increments with low latency and high temporal resolution. The resulting streams of events are of high value by themselves, especially for high speed…

Computer Vision and Pattern Recognition · Computer Science 2021-04-13 F. Paredes-Vallés , G. C. H. E. de Croon

Event-based object detection has recently garnered attention in the computer vision community due to the exceptional properties of event cameras, such as high dynamic range and no motion blur. However, feature asynchronism and sparsity…

Computer Vision and Pattern Recognition · Computer Science 2024-09-19 Ting-Kang Yen , Igor Morawski , Shusil Dangi , Kai He , Chung-Yi Lin , Jia-Fong Yeh , Hung-Ting Su , Winston Hsu

Unwanted camera occlusions, such as debris, dust, rain-drops, and snow, can severely degrade the performance of computer-vision systems. Dynamic occlusions are particularly challenging because of the continuously changing pattern. Existing…

Computer Vision and Pattern Recognition · Computer Science 2023-08-02 Rong Zou , Manasi Muglikar , Nico Messikommer , Davide Scaramuzza

Event cameras provide a number of benefits over traditional cameras, such as the ability to track incredibly fast motions, high dynamic range, and low power consumption. However, their application into computer vision problems, many of…

Computer Vision and Pattern Recognition · Computer Science 2019-12-20 Alex Zihao Zhu , Ziyun Wang , Kaung Khant , Kostas Daniilidis

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

Different from visible cameras which record intensity images frame by frame, the biologically inspired event camera produces a stream of asynchronous and sparse events with much lower latency. In practice, visible cameras can better…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Xiao Wang , Jianing Li , Lin Zhu , Zhipeng Zhang , Zhe Chen , Xin Li , Yaowei Wang , Yonghong Tian , Feng Wu

Event-based cameras, inspired by the biological retina, have evolved into cutting-edge sensors distinguished by their minimal power requirements, negligible latency, superior temporal resolution, and expansive dynamic range. At present,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Han Wang , Yuman Nie , Yun Li , Hongjie Liu , Min Liu , Wen Cheng , Yaoxiong Wang

The current event cameras are bio-inspired sensors that respond to brightness changes in the scene asynchronously and independently for every pixel, and transmit these changes as ternary event streams. Event cameras have several benefits…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Eero Lehtonen , Tuomo Komulainen , Ari Paasio , Mika Laiho

We introduce N-ImageNet, a large-scale dataset targeted for robust, fine-grained object recognition with event cameras. The dataset is collected using programmable hardware in which an event camera consistently moves around a monitor…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Junho Kim , Jaehyeok Bae , Gangin Park , Dongsu Zhang , Young Min Kim

Event cameras are novel sensors that report brightness changes in the form of a stream of asynchronous "events" instead of intensity frames. They offer significant advantages with respect to conventional cameras: high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-06-19 Henri Rebecq , René Ranftl , Vladlen Koltun , Davide Scaramuzza

Accurate detection and tracking of objects is vital for effective video understanding. In previous work, the two tasks have been combined in a way that tracking is based heavily on detection, but the detection benefits marginally from the…

Computer Vision and Pattern Recognition · Computer Science 2018-11-28 Zheng Zhang , Dazhi Cheng , Xizhou Zhu , Stephen Lin , Jifeng Dai

Event cameras are biologically-inspired sensors that gather the temporal evolution of the scene. They capture pixel-wise brightness variations and output a corresponding stream of asynchronous events. Despite having multiple advantages with…

Computer Vision and Pattern Recognition · Computer Science 2019-12-11 Stefano Pini , Guido Borghi , Roberto Vezzani

3D object detection is essential for autonomous systems, enabling precise localization and dimension estimation. While LiDAR and RGB cameras are widely used, their fixed frame rates create perception gaps in high-speed scenarios. Event…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Jae-Young Kang , Hoonhee Cho , Kuk-Jin Yoon

Event cameras provide asynchronous, data-driven measurements of local temporal contrast over a large dynamic range with extremely high temporal resolution. Conventional cameras capture low-frequency reference intensity information. These…

Computer Vision and Pattern Recognition · Computer Science 2018-11-02 Cedric Scheerlinck , Nick Barnes , Robert Mahony

This paper presents a long-term object tracking framework with a moving event camera under general tracking conditions. A first of its kind for these revolutionary cameras, the tracking framework uses a discriminative representation for the…

Computer Vision and Pattern Recognition · Computer Science 2020-09-03 Bharath Ramesh , Shihao Zhang , Hong Yang , Andres Ussa , Matthew Ong , Garrick Orchard , Cheng Xiang

Bio-inspired event cameras have recently attracted significant research due to their asynchronous and low-latency capabilities. These features provide a high dynamic range and significantly reduce motion blur. However, because of the…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Aheli Saha , René Schuster , Didier Stricker