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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

Event cameras can capture pixel-level illumination changes with very high temporal resolution and dynamic range. They have received increasing research interest due to their robustness to lighting conditions and motion blur. Two main…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Raul Tapia , Augusto Gómez Eguíluz , José Ramiro Martínez-de Dios , Anibal Ollero

Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events". The innovative way they acquire data presents several advantages over standard devices, especially in poor…

Computer Vision and Pattern Recognition · Computer Science 2021-11-01 Mirco Planamente , Chiara Plizzari , Marco Cannici , Marco Ciccone , Francesco Strada , Andrea Bottino , Matteo Matteucci , Barbara Caputo

Visual reconstruction of fast non-rigid object deformations over time is a challenge for conventional frame-based cameras. In this paper, we propose a novel approach for reconstructing such deformations using measurements from event-based…

Computer Vision and Pattern Recognition · Computer Science 2022-11-15 Yuxuan Xue , Haolong Li , Stefan Leutenegger , Jörg Stückler

Conventional frame camera is the mainstream sensor of the autonomous driving scene perception, while it is limited in adverse conditions, such as low light. Event camera with high dynamic range has been applied in assisting frame camera for…

Computer Vision and Pattern Recognition · Computer Science 2024-08-19 Shihan Peng , Hanyu Zhou , Hao Dong , Zhiwei Shi , Haoyue Liu , Yuxing Duan , Yi Chang , Luxin Yan

Line segment extraction is effective for capturing geometric features of human-made environments. Event-based cameras, which asynchronously respond to contrast changes along edges, enable efficient extraction by reducing redundant data.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Mikihiro Ikura , Arren Glover , Masayoshi Mizuno , Chiara Bartolozzi

Current optical flow methods exploit the stable appearance of frame (or RGB) data to establish robust correspondences across time. Event cameras, on the other hand, provide high-temporal-resolution motion cues and excel in challenging…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Qianang Zhou , Junhui Hou , Meiyi Yang , Yongjian Deng , Youfu Li , Junlin Xiong

In this paper, an event-based tracker is presented. Inspired by recent advances in asynchronous processing of individual events, we develop a direct matching scheme that aligns spatial distributions of events at different times. More…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Maria Zafeiri , Georgios Evangelidis , Emmanouil Psarakis

Event cameras are rapidly emerging as powerful vision sensors for 3D reconstruction, uniquely capable of asynchronously capturing per-pixel brightness changes. Compared to traditional frame-based cameras, event cameras produce sparse yet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Chuanzhi Xu , Haoxian Zhou , Langyi Chen , Haodong Chen , Zeke Zexi Hu , Zhicheng Lu , Ying Zhou , Vera Chung , Qiang Qu , Weidong Cai

We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional cameras struggle with high-speed motion capture due to bandwidth and dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Ziyun Wang , Friedhelm Hamann , Kenneth Chaney , Wen Jiang , Guillermo Gallego , Kostas Daniilidis

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 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

Event-based sensors have recently drawn increasing interest in robotic perception due to their lower latency, higher dynamic range, and lower bandwidth requirements compared to standard CMOS-based imagers. These properties make them ideal…

Event cameras or neuromorphic cameras mimic the human perception system as they measure the per-pixel intensity change rather than the actual intensity level. In contrast to traditional cameras, such cameras capture new information about…

Computer Vision and Pattern Recognition · Computer Science 2016-08-05 Christian Reinbacher , Gottfried Graber , Thomas Pock

Active depth sensors like structured light, lidar, and time-of-flight systems sample the depth of the entire scene uniformly at a fixed scan rate. This leads to limited spatio-temporal resolution where redundant static information is…

Computer Vision and Pattern Recognition · Computer Science 2021-12-21 Manasi Muglikar , Diederik Paul Moeys , Davide Scaramuzza

Scene reconstruction from casually captured videos has wide applications in real-world scenarios. With recent advancements in differentiable rendering techniques, several methods have attempted to simultaneously optimize scene…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Bohao Liao , Wei Zhai , Zengyu Wan , Zhixin Cheng , Wenfei Yang , Tianzhu Zhang , Yang Cao , Zheng-Jun Zha

Event cameras also known as neuromorphic sensors are relatively a new technology with some privilege over the RGB cameras. The most important one is their difference in capturing the light changes in the environment, each pixel changes…

Computer Vision and Pattern Recognition · Computer Science 2022-10-26 Mehdi Sefidgar Dilmaghani , Waseem Shariff , Cian Ryan , Joe Lemley , Peter Corcoran

Event-based cameras provide accurate and high temporal resolution measurements for performing computer vision tasks in challenging scenarios, such as high-dynamic range environments and fast-motion maneuvers. Despite their advantages,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Mohammad Rostami , Dayuan Jian , Ruitong Sun

Event-based camera has emerged as a promising paradigm for robot perception, offering advantages with high temporal resolution, high dynamic range, and robustness to motion blur. However, existing deep learning-based event processing…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Shenqi Wang , Guangzhi Tang

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
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