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Related papers: Self-Supervised Event Representations: Towards Acc…

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Event cameras are bio-inspired sensors that capture intensity changes asynchronously with distinct advantages, such as high temporal resolution. Existing methods for event-based object/action recognition predominantly sample and convert…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Jiazhou Zhou , Kanghao Chen , Lei Zhang , Lin Wang

In recent years there has been a growing interest in event cameras, i.e. vision sensors that record changes in illumination independently for each pixel. This type of operation ensures that acquisition is possible in very adverse lighting…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Tomasz Kryjak

Event cameras offer significant advantages over traditional frame-based sensors, including higher temporal resolution, lower latency and dynamic range. However, efficiently converting event streams into formats compatible with standard…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Gabriele Magrini , Federico Becattini , Luca Cultrera , Lorenzo Berlincioni , Pietro Pala , Alberto Del Bimbo

Event cameras are bio-inspired sensors that respond to per-pixel brightness changes in the form of asynchronous and sparse "events". Recently, pattern recognition algorithms, such as learning-based methods, have made significant progress…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Nico Messikommer , Daniel Gehrig , Antonio Loquercio , Davide Scaramuzza

Event cameras are novel vision sensors that report per-pixel brightness changes as a stream of asynchronous "events". They offer significant advantages compared to standard cameras due to their high temporal resolution, high dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2021-02-19 Daniel Gehrig , Michelle Rüegg , Mathias Gehrig , Javier Hidalgo Carrio , Davide Scaramuzza

Event-based sensors offer high temporal resolution and low latency by generating sparse, asynchronous data. However, converting this irregular data into dense tensors for use in standard neural networks diminishes these inherent advantages,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Aayush Atul Verma , Arpitsinh Vaghela , Bharatesh Chakravarthi , Kaustav Chanda , Yezhou Yang

Super-resolution (SR) is a useful technology to generate a high-resolution (HR) visual output from the low-resolution (LR) visual inputs overcoming the physical limitations of the cameras. However, SR has not been applied to enhance the…

Computer Vision and Pattern Recognition · Computer Science 2018-03-19 Hongmin Li , Guoqi Li , Hanchao Liu , Luping Shi

Although synthetic aperture imaging (SAI) can achieve the seeing-through effect by blurring out off-focus foreground occlusions while recovering in-focus occluded scenes from multi-view images, its performance is often deteriorated by dense…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Lei Yu , Xiang Zhang , Wei Liao , Wen Yang , Gui-Song Xia

Event cameras or dynamic vision sensors (DVS) record asynchronous response to brightness changes instead of conventional intensity frames, and feature ultra-high sensitivity at low bandwidth. The new mechanism demonstrates great advantages…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Bo Zhang , Yuqi Han , Jinli Suo , Qionghai Dai

An event camera detects per-pixel intensity difference and produces asynchronous event stream with low latency, high dynamic range, and low power consumption. As a trade-off, the event camera has low spatial resolution. We propose an…

Computer Vision and Pattern Recognition · Computer Science 2020-04-13 S. Mohammad Mostafavi I. , Jonghyun Choi , Kuk-Jin Yoon

Achieving optimal semantic segmentation with frame-based vision sensors poses significant challenges for real-time systems like UAVs and self-driving cars, which require rapid and precise processing. Traditional frame-based methods often…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 D. Hareb , J. Martinet , B. Miramond

Event cameras are novel sensors that output 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 dynamic range (HDR),…

Computer Vision and Pattern Recognition · Computer Science 2020-04-02 Daniel Gehrig , Mathias Gehrig , Javier Hidalgo-Carrió , Davide Scaramuzza

Event cameras are novel bio-inspired vision sensors that output pixel-level intensity changes in microsecond accuracy with a high dynamic range and low power consumption. Despite these advantages, event cameras cannot be directly applied to…

Computer Vision and Pattern Recognition · Computer Science 2022-11-02 Jinjin Gu , Jinan Zhou , Ringo Sai Wo Chu , Yan Chen , Jiawei Zhang , Xuanye Cheng , Song Zhang , Jimmy S. Ren

This paper proposes a self-supervised learned local detector and descriptor, called EventPoint, for event stream/camera tracking and registration. Event-based cameras have grown in popularity because of their biological inspiration and low…

Computer Vision and Pattern Recognition · Computer Science 2022-11-01 Ze Huang , Li Sun , Cheng Zhao , Song Li , Songzhi Su

Long-term temporal information is crucial for event-based perception tasks, as raw events only encode pixel brightness changes. Recent works show that when trained from scratch, recurrent models achieve better results than feedforward…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Mohammad Mohammadi , Ziyi Wu , Igor Gilitschenski

In this paper we have addressed the implementation of the accumulation and projection of high-resolution event data stream (HD -1280 x 720 pixels) onto the image plane in FPGA devices. The results confirm the feasibility of this approach,…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Krzysztof Blachut , Tomasz Kryjak

Event cameras record sparse illumination changes with high temporal resolution and high dynamic range. Thanks to their sparse recording and low consumption, they are increasingly used in applications such as AR/VR and autonomous driving.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-24 Alberto Sabater , Luis Montesano , Ana C. Murillo

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

Event cameras are activity-driven bio-inspired vision sensors, thereby resulting in advantages such as sparsity,high temporal resolution, low latency, and power consumption. Given the different sensing modality of event camera and high…

Computer Vision and Pattern Recognition · Computer Science 2021-05-11 Lakshmi Annamalai , Vignesh Ramanathan , Chetan Singh Thakur

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