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Related papers: Inter-event Interval Microscopy for Event Cameras

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The paper addresses the shortcoming of current event-based vision (EBV) sensors in the context of particle imaging. Latency is introduced both on the pixel level as well as during read-out from the array and results in systemic timing…

Fluid Dynamics · Physics 2023-05-24 Christian E. Willert

Bio-inspired neuromorphic cameras asynchronously record pixel brightness changes and generate sparse event streams. They can capture dynamic scenes with little motion blur and more details in extreme illumination conditions. Due to the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Pei Zhang , Chutian Wang , Edmund Y. Lam

By combining complementary benefits of short- and long-exposure images, Dual-Exposure Imaging (DEI) enhances image quality in low-light scenarios. However, existing DEI approaches inevitably suffer from producing artifacts due to spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Mingyuan Lin , Hongyi Liu , Chu He , Wen Yang , Gui-Song Xia , Lei Yu

Most existing video anomaly detectors rely solely on RGB frames, which lack the temporal resolution needed to capture abrupt or transient motion cues, key indicators of anomalous events. To address this limitation, we propose Image-Event…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Sungheon Jeong , Jihong Park , Mohsen Imani

Identifying independently moving objects is an essential task for dynamic scene understanding. However, traditional cameras used in dynamic scenes may suffer from motion blur or exposure artifacts due to their sampling principle. By…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Yi Zhou , Guillermo Gallego , Xiuyuan Lu , Siqi Liu , Shaojie Shen

Event cameras offer unique advantages such as high temporal resolution, low latency, and high dynamic range, making them more and more popular for vision tasks under challenging light conditions. However, their high cost, limited…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Zijie Ning , Enmin Lin , Sudarshan R. Iyengar , Patrick Vandewalle

Dynamic vision sensors (DVS) are bio-inspired devices that capture visual information in the form of asynchronous events, which encode changes in pixel intensity with high temporal resolution and low latency. These events provide rich…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Jingkai Sun , Qiang Zhang , Jiaxu Wang , Jiahang Cao , Renjing Xu

Event cameras, inspired by biological vision systems, provide a natural and data efficient representation of visual information. Visual information is acquired in the form of events that are triggered by local brightness changes. Each pixel…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Cheng Gu , Erik Learned-Miller , Daniel Sheldon , Guillermo Gallego , Pia Bideau

Event cameras excel in capturing high-contrast scenes and dynamic objects, offering a significant advantage over traditional frame-based cameras. Despite active research into leveraging event cameras for semantic segmentation, generating…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Hoonhee Cho , Sung-Hoon Yoon , Hyeokjun Kweon , Kuk-Jin Yoon

Fast neuromorphic event-based vision sensors (Dynamic Vision Sensor, DVS) can be combined with slower conventional frame-based sensors to enable higher-quality inter-frame interpolation than traditional methods relying on fixed motion…

Computer Vision and Pattern Recognition · Computer Science 2021-12-20 Adam Radomski , Andreas Georgiou , Thomas Debrunner , Chenghan Li , Luca Longinotti , Minwon Seo , Moosung Kwak , Chang-Woo Shin , Paul K. J. Park , Hyunsurk Eric Ryu , Kynan Eng

Dynamic Vision Sensor (DVS) can asynchronously output the events reflecting apparent motion of objects with microsecond resolution, and shows great application potential in monitoring and other fields. However, the output event stream of…

Computer Vision and Pattern Recognition · Computer Science 2022-03-23 Jinze Chen , Yang Wang , Yang Cao , Feng Wu , Zheng-Jun Zha

Event-based visual odometry is a specific branch of visual Simultaneous Localization and Mapping (SLAM) techniques, which aims at solving tracking and mapping subproblems (typically in parallel), by exploiting the special working principles…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Junkai Niu , Sheng Zhong , Xiuyuan Lu , Shaojie Shen , Guillermo Gallego , Yi Zhou

Event cameras offer superior sensitivity to high-speed motion and extreme lighting, making event-based monocular depth estimation a promising approach for robust 3D perception in challenging conditions. However, progress is severely…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yinrui Ren , Jinjing Zhu , Kanghao Chen , Zhuoxiao Li , Jing Ou , Zidong Cao , Tongyan Hua , Peilun Shi , Yingchun Fu , Wufan Zhao , Hui Xiong

State-of-the-art solutions for Shape-from-Polarization (SfP) suffer from a speed-resolution tradeoff: they either sacrifice the number of polarization angles measured or necessitate lengthy acquisition times due to framerate constraints,…

Computer Vision and Pattern Recognition · Computer Science 2023-04-12 Manasi Muglikar , Leonard Bauersfeld , Diederik Paul Moeys , Davide Scaramuzza

Event cameras output event streams as sparse, asynchronous data with microsecond-level temporal resolution, enabling visual perception with low latency and a high dynamic range. While existing Multimodal Large Language Models (MLLMs) have…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Rui Chen , Xingyu Chen , Shaoan Wang , Shihan Kong , Junzhi Yu

Event cameras capture sparse, asynchronous brightness changes which offer high temporal resolution, high dynamic range, low power consumption, and sparse data output. These advantages make them ideal for Space Situational Awareness,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Sami Arja , Alexandre Marcireau , Nicholas Owen Ralph , Saeed Afshar , Gregory Cohen

A new event camera dataset, EVIMO2, is introduced that improves on the popular EVIMO dataset by providing more data, from better cameras, in more complex scenarios. As with its predecessor, EVIMO2 provides labels in the form of per-pixel…

Computer Vision and Pattern Recognition · Computer Science 2022-05-10 Levi Burner , Anton Mitrokhin , Cornelia Fermüller , Yiannis Aloimonos

Event cameras are bio-inspired sensors that output asynchronous and sparse event streams, instead of fixed frames. Benefiting from their distinct advantages, such as high dynamic range and high temporal resolution, event cameras have been…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Zixin Zhang , Kanghao Chen , Lin Wang

Direct methods for event-based visual odometry solve the mapping and camera pose tracking sub-problems by establishing implicit data association in a way that the generative model of events is exploited. The main bottlenecks faced by…

Robotics · Computer Science 2024-05-08 Junkai Niu , Sheng Zhong , Yi Zhou

In this paper, we consider the intensity-based inversion method (IIM) for quantitative material parameter estimation in quasi-static elastography. In particular, we consider the problem of estimating the material parameters of a given…

Numerical Analysis · Mathematics 2026-01-19 Ekaterina Sherina , Simon Hubmer
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