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Related papers: AsynEVO: Asynchronous Event-Driven Visual Odometry…

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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

In event-based sensing, many sensors independently and asynchronously emit events when there is a change in their input. Event-based sensing can present significant improvements in power efficiency when compared to traditional sampling,…

Image and Video Processing · Electrical Eng. & Systems 2022-01-19 Karen Adam , Adam Scholefield , Martin Vetterli

Event-based cameras are raising interest within the computer vision community. These sensors operate with asynchronous pixels, emitting events, or "spikes", when the luminance change at a given pixel since the last event surpasses a certain…

Computer Vision and Pattern Recognition · Computer Science 2023-05-18 Javier Cuadrado , Ulysse Rançon , Benoît Cottereau , Francisco Barranco , Timothée Masquelier

Event cameras produce asynchronous, high-dynamic-range streams well suited for detecting small, fast-moving drones, yet most event-based detectors convert the sparse event stream into dense tensors, discarding the representational…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Mohamad Yazan Sadoun , Sarah Sharif , Yaser Mike Banad

Dense visual odometry (VO), which provides pose estimation and dense 3D reconstruction, serves as the cornerstone for applications ranging from robotics to augmented reality. Recently, feed-forward models have demonstrated remarkable…

Robotics · Computer Science 2026-04-03 Junxiang Pan , Lipu Zhou , Baojie Chen

In this work, we propose a motion robust and high-speed detection pipeline which better leverages the event data. First, we design an event stream representation called temporal active focus (TAF), which efficiently utilizes the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-27 Bingde Liu , Chang Xu , Wen Yang , Huai Yu , Lei Yu

Standard frame-based cameras that sample light intensity frames are heavily impacted by motion blur for high-speed motion and fail to perceive scene accurately when the dynamic range is high. Event-based cameras, on the other hand, overcome…

Computer Vision and Pattern Recognition · Computer Science 2021-03-22 Chankyu Lee , Adarsh Kumar Kosta , Kaushik Roy

Event cameras are neuromorphic sensors that capture asynchronous and sparse event stream when per-pixel brightness changes. The state-of-the-art processing methods for event signals typically aggregate events into a frame or a grid.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Beibei Yang , Weiling Li , Yan Fang

Event cameras are ideally suited to capture High Dynamic Range (HDR) visual information without blur but provide poor imaging capability for static or slowly varying scenes. Conversely, conventional image sensors measure absolute intensity…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Ziwei Wang , Yonhon Ng , Cedric Scheerlinck , Robert Mahony

Dynamic vision sensors or event cameras provide rich complementary information for video frame interpolation. Existing state-of-the-art methods follow the paradigm of combining both synthesis-based and warping networks. However, few of…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Jiaben Chen , Yichen Zhu , Dongze Lian , Jiaqi Yang , Yifu Wang , Renrui Zhang , Xinhang Liu , Shenhan Qian , Laurent Kneip , Shenghua Gao

Event cameras are bio-inspired sensors that capture the per-pixel intensity changes asynchronously and produce event streams encoding the time, pixel position, and polarity (sign) of the intensity changes. Event cameras possess a myriad of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Xu Zheng , Yexin Liu , Yunfan Lu , Tongyan Hua , Tianbo Pan , Weiming Zhang , Dacheng Tao , Lin Wang

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

Event cameras offer significant advantages for low-light video enhancement, primarily due to their high dynamic range. Current research, however, is severely limited by the absence of large-scale, real-world, and spatio-temporally aligned…

Computer Vision and Pattern Recognition · Computer Science 2024-08-30 Kanghao Chen , Guoqiang Liang , Hangyu Li , Yunfan Lu , Lin Wang

Event cameras generate asynchronous signals in response to pixel-level brightness changes, offering a sensing paradigm with theoretically microsecond-scale latency that can significantly enhance the performance of multi-sensor systems.…

Robotics · Computer Science 2025-08-19 Jiayao Mai , Xiuyuan Lu , Kuan Dai , Shaojie Shen , Yi Zhou

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

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

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

Object pose tracking is a fundamental and essential task for robotics to perform tasks in the home and industrial settings. The most commonly used sensors to do so are RGB-D cameras, which can hit limitations in highly dynamic environments…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Zhichao Li , Chiara Bartolozzi , Lorenzo Natale , Arren Glover

Event cameras provide microsecond latency, making them suitable for 6D object pose tracking in fast, dynamic scenes where conventional RGB and depth pipelines suffer from motion blur and large pixel displacements. We introduce EventTrack6D,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Jae-Young Kang , Hoonhee Cho , Taeyeop Lee , Minjun Kang , Bowen Wen , Youngho Kim , Kuk-Jin Yoon

The cameras in modern gaze-tracking systems suffer from fundamental bandwidth and power limitations, constraining data acquisition speed to 300 Hz realistically. This obstructs the use of mobile eye trackers to perform, e.g., low latency…

Computer Vision and Pattern Recognition · Computer Science 2022-08-09 Anastasios N. Angelopoulos , Julien N. P. Martel , Amit P. S. Kohli , Jorg Conradt , Gordon Wetzstein
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