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3D reconstruction methods such as 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) achieve impressive photorealism but fail when input images suffer from severe motion blur. While event cameras provide high-temporal-resolution…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Jun Dai , Renbiao Jin , Bo Xu , Yutian Chen , Linning Xu , Mulin Yu , Tianfan Xue , Shi Guo

High-quality imaging of dynamic scenes in extremely low-light conditions is highly challenging. Photon scarcity induces severe noise and texture loss, causing significant image degradation. Event cameras, featuring a high dynamic range (120…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Haoyue Liu , Jinghan Xu , Luxin Feng , Hanyu Zhou , Haozhi Zhao , Yi Chang , Luxin Yan

Conventional frame-based cameras inevitably produce blurry effects due to motion occurring during the exposure time. Event camera, a bio-inspired sensor offering continuous visual information could enhance the deblurring performance.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Xiaopeng Lin , Hongwei Ren , Yulong Huang , Zunchang Liu , Yue Zhou , Haotian Fu , Biao Pan , Bojun Cheng

Event cameras are vision sensors that record asynchronous streams of per-pixel brightness changes, referred to as "events". They have appealing advantages over frame-based cameras for computer vision, including high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-21 Daniel Gehrig , Antonio Loquercio , Konstantinos G. Derpanis , Davide Scaramuzza

Event cameras are a new type of vision sensor that incorporates asynchronous and independent pixels, offering advantages over traditional frame-based cameras such as high dynamic range and minimal motion blur. However, their output is not…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Burak Ercan , Onur Eker , Aykut Erdem , Erkut Erdem

Event cameras are bio-inspired sensors that mimic the human retina by responding to brightness changes in the scene. They generate asynchronous spike-based outputs at microsecond resolution, providing advantages over traditional cameras…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Suman Ghosh , Guillermo Gallego

Augmented reality devices require multiple sensors to perform various tasks such as localization and tracking. Currently, popular cameras are mostly frame-based (e.g. RGB and Depth) which impose a high data bandwidth and power usage. With…

Computer Vision and Pattern Recognition · Computer Science 2020-08-07 Etienne Dubeau , Mathieu Garon , Benoit Debaque , Raoul de Charette , Jean-François Lalonde

Spike camera, a type of neuromorphic sensor with high-temporal resolution, shows great promise for high-speed visual tasks. Unlike traditional cameras, spike camera continuously accumulates photons and fires asynchronous spike streams. Due…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Liwen Hu , Yang Li , Mianzhi Liu , Yijia Guo , Shenghao Xie , Ziluo Ding , Tiejun Huang , Lei Ma

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

Event cameras have a lot of advantages over traditional cameras, such as low latency, high temporal resolution, and high dynamic range. However, since the outputs of event cameras are the sequences of asynchronous events overtime rather…

Computer Vision and Pattern Recognition · Computer Science 2020-10-13 S. Mohammad Mostafavi I. , Lin Wang , Yo-Sung Ho , Kuk-Jin Yoon

Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate downstream image processing, especially for complex tasks such…

Computer Vision and Pattern Recognition · Computer Science 2024-02-13 Darryl Hannan , Ragib Arnab , Gavin Parpart , Garrett T. Kenyon , Edward Kim , Yijing Watkins

The bio-inspired event cameras or dynamic vision sensors are capable of asynchronously capturing per-pixel brightness changes (called event-streams) in high temporal resolution and high dynamic range. However, the non-structural…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Qiang Qu , Yiran Shen , Xiaoming Chen , Yuk Ying Chung , Tongliang Liu

Event cameras respond to changes in log-brightness at the millisecond level, making them ideal for optical flow estimation. However, existing datasets from event cameras provide only low frame rate ground truth for optical flow, limiting…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Yaozu Ye , Hao Shi , Kailun Yang , Ze Wang , Xiaoting Yin , Lei Sun , Yaonan Wang , Kaiwei Wang

Event cameras are bio-inspired sensors that perform well in challenging illumination conditions and have high temporal resolution. However, their concept is fundamentally different from traditional frame-based cameras. The pixels of an…

Computer Vision and Pattern Recognition · Computer Science 2022-06-13 Xin Peng , Ling Gao , Yifu Wang , Laurent Kneip

Neuromorphic sensors, specifically event cameras, revolutionize visual data acquisition by capturing pixel intensity changes with exceptional dynamic range, minimal latency, and energy efficiency, setting them apart from conventional…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Qi Wang , Zhou Xu , Yuming Lin , Jingtao Ye , Hongsheng Li , Guangming Zhu , Syed Afaq Ali Shah , Mohammed Bennamoun , Liang Zhang

Novel view synthesis via Neural Radiance Fields (NeRFs) or 3D Gaussian Splatting (3DGS) typically necessitates dense observations with hundreds of input images to circumvent artifacts. We introduce Deceptive-NeRF/3DGS to enhance sparse-view…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Xinhang Liu , Jiaben Chen , Shiu-hong Kao , Yu-Wing Tai , Chi-Keung Tang

Event cameras are paradigm-shifting novel sensors that report asynchronous, per-pixel brightness changes called 'events' with unparalleled low latency. This makes them ideal for high speed, high dynamic range scenes where conventional…

Computer Vision and Pattern Recognition · Computer Science 2020-08-25 Timo Stoffregen , Cedric Scheerlinck , Davide Scaramuzza , Tom Drummond , Nick Barnes , Lindsay Kleeman , Robert Mahony

In the realm of high-resolution (HR), fine-grained image segmentation, the primary challenge is balancing broad contextual awareness with the precision required for detailed object delineation, capturing intricate details and the finest…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Qian Yu , Peng-Tao Jiang , Hao Zhang , Jinwei Chen , Bo Li , Lihe Zhang , Huchuan Lu

Event cameras provide an advantage over traditional frame-based cameras when capturing fast-moving objects without a motion blur. They achieve this by recording changes in light intensity (known as events), thus allowing them to operate at…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Wachirawit Ponghiran , Chamika Mihiranga Liyanagedera , Kaushik Roy

Hyperspectral 3D imaging captures both depth maps and hyperspectral images, enabling comprehensive geometric and material analysis. Recent methods achieve high spectral and depth accuracy; however, they require long acquisition times often…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Suhyun Shin , Seungwoo Yoon , Ryota Maeda , Seung-Hwan Baek