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Eye tracking is crucial for human-computer interaction in different domains. Conventional cameras encounter challenges such as power consumption and image quality during different eye movements, prompting the need for advanced solutions…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Xiaopeng Lin , Hongwei Ren , Bojun Cheng

Event cameras are bio-inspired sensors that respond to local changes in light intensity and feature low latency, high energy efficiency, and high dynamic range. Meanwhile, Spiking Neural Networks (SNNs) have gained significant attention due…

Computer Vision and Pattern Recognition · Computer Science 2024-01-24 Hongwei Ren , Yue Zhou , Yulong Huang , Haotian Fu , Xiaopeng Lin , Jie Song , Bojun Cheng

We present a robust and real-time monocular six degree of freedom relocalization system. Our system trains a convolutional neural network to regress the 6-DOF camera pose from a single RGB image in an end-to-end manner with no need of…

Computer Vision and Pattern Recognition · Computer Science 2016-02-19 Alex Kendall , Matthew Grimes , Roberto Cipolla

Accurate 6-DoF pose estimation of objects is critical for robots to perform precise manipulation tasks. However, for dynamic object pose estimation, conventional camera-based approaches face several major challenges, such as motion blur,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Zhe Wang , Qijin Song , Zihao Li , Jingyu Xiao , Weibang Bai

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

We present a new method to relocalize the 6DOF pose of an event camera solely based on the event stream. Our method first creates the event image from a list of events that occurs in a very short time interval, then a Stacked Spatial LSTM…

Computer Vision and Pattern Recognition · Computer Science 2019-07-10 Anh Nguyen , Thanh-Toan Do , Darwin G. Caldwell , Nikos G. Tsagarakis

Event cameras have emerged as a promising vision sensor in recent years due to their unparalleled temporal resolution and dynamic range. While registration of 2D RGB images to 3D point clouds is a long-standing problem in computer vision,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Xiuhong Lin , Changjie Qiu , Zhipeng Cai , Siqi Shen , Yu Zang , Weiquan Liu , Xuesheng Bian , Matthias Müller , Cheng Wang

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 have gained popularity in computer vision due to their data sparsity, high dynamic range, and low latency. As a bio-inspired sensor, event cameras generate sparse and asynchronous data, which is inherently incompatible with…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Hongwei Ren , Yue Zhou , Haotian Fu , Yulong Huang , Renjing Xu , Bojun Cheng

Event camera is an emerging bio-inspired vision sensors that report per-pixel brightness changes asynchronously. It holds noticeable advantage of high dynamic range, high speed response, and low power budget that enable it to best capture…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Zhanpeng Shao , Wen Zhou , Wuzhen Wang , Jianyu Yang , Youfu Li

Human pose estimation focuses on predicting body keypoints to analyze human motion. Currently, most pose estimation tasks rely on conventional RGB cameras. In contrast, event cameras provide high temporal resolution and low latency,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Haoxian Zhou , Chuanzhi Xu , Langyi Chen , Pengfei Ye , Haodong Chen , Yuk Ying Chung , Qiang Qu

Traditional visual place recognition (VPR), usually using standard cameras, is easy to fail due to glare or high-speed motion. By contrast, event cameras have the advantages of low latency, high temporal resolution, and high dynamic range,…

Computer Vision and Pattern Recognition · Computer Science 2022-11-24 Kuanxu Hou , Delei Kong , Junjie Jiang , Hao Zhuang , Xinjie Huang , Zheng Fang

Compared to conventional cameras, event cameras provide a high dynamic range and low latency, offering greater robustness to rapid motion and challenging lighting conditions. Although the potential of event cameras for visual place…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Therese Joseph , Tobias Fischer , Michael Milford

Convolutional neural networks (CNNs) and transfer learning have recently been used for 6 degrees of freedom (6-DoF) camera pose estimation. While they do not reach the same accuracy as visual SLAM-based approaches and are restricted to a…

Computer Vision and Pattern Recognition · Computer Science 2019-12-02 Soroush Seifi , Tinne Tuytelaars

Aerial imagery has been increasingly adopted in mission-critical tasks, such as traffic surveillance, smart cities, and disaster assistance. However, identifying objects from aerial images faces the following challenges: 1) objects of…

Computer Vision and Pattern Recognition · Computer Science 2020-01-24 Ziyang Tang , Xiang Liu , Guangyu Shen , Baijian Yang

Event cameras are novel sensors that report brightness changes in the form of asynchronous "events" instead of intensity frames. They have significant advantages over conventional cameras: high temporal resolution, high dynamic range, and…

Computer Vision and Pattern Recognition · Computer Science 2019-04-18 Henri Rebecq , René Ranftl , Vladlen Koltun , Davide Scaramuzza

Event cameras draw inspiration from biological systems, boasting low latency and high dynamic range while consuming minimal power. The most current approach to processing Event Cloud often involves converting it into frame-based…

Computer Vision and Pattern Recognition · Computer Science 2025-03-31 Hongwei Ren , Yue Zhou , Jiadong Zhu , Haotian Fu , Yulong Huang , Xiaopeng Lin , Yuetong Fang , Fei Ma , Hao Yu , Bojun Cheng

Event-based cameras can overpass frame-based cameras limitations for important tasks such as high-speed motion detection during self-driving cars navigation in low illumination conditions. The event cameras' high temporal resolution and…

Computer Vision and Pattern Recognition · Computer Science 2022-01-31 Haixin Sun , Minh-Quan Dao , Vincent Fremont

Compared to regular cameras, Dynamic Vision Sensors or Event Cameras can output compact visual data based on a change in the intensity in each pixel location asynchronously. In this paper, we study the application of current image-based…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Masoud Dayani Najafabadi , Mohammad Reza Ahmadzadeh

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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