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Continuous video monitoring in surveillance, robotics, and wearable systems faces a fundamental power constraint: conventional RGB cameras consume substantial energy through fixed-rate capture. Event cameras offer sparse, motion-driven…

Computer Vision and Pattern Recognition · Computer Science 2025-12-08 Dmitrii Torbunov , Onur Okuducu , Yi Huang , Odera Dim , Rebecca Coles , Yonggang Cui , Yihui Ren

Event cameras, often referred to as dynamic vision sensors, are groundbreaking sensors capable of capturing changes in light intensity asynchronously, offering exceptional temporal resolution and energy efficiency. These attributes make…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Mira Adra , Simone Melcarne , Nelida Mirabet-Herranz , Jean-Luc Dugelay

Event sensors output a stream of asynchronous brightness changes (called ``events'') at a very high temporal rate. Previous works on recovering the lost intensity information from the event sensor data have heavily relied on the event…

Computer Vision and Pattern Recognition · Computer Science 2020-03-18 Prasan A Shedligeri , Kaushik Mitra

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

Event cameras rely on motion to obtain information about scene appearance. This means that appearance and motion are inherently linked: either both are present and recorded in the event data, or neither is captured. Previous works treat the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Shuang Guo , Friedhelm Hamann , Guillermo Gallego

Recording fast motion in a high FPS (frame-per-second) requires expensive high-speed cameras. As an alternative, interpolating low-FPS videos from commodity cameras has attracted significant attention. If only low-FPS videos are available,…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Weihua He , Kaichao You , Zhendong Qiao , Xu Jia , Ziyang Zhang , Wenhui Wang , Huchuan Lu , Yaoyuan Wang , Jianxing Liao

Event cameras offer many advantages over standard cameras due to their distinctive principle of operation: low power, low latency, high temporal resolution and high dynamic range. Nonetheless, the success of many downstream visual…

Computer Vision and Pattern Recognition · Computer Science 2023-09-18 Weng Fei Low , Gim Hee Lee

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

Event-based cameras offer unique advantages such as high temporal resolution, high dynamic range, and low power consumption. However, the massive storage requirements and I/O burdens of existing synthetic data generation pipelines and the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-23 Hanyue Lou , Jinxiu Liang , Minggui Teng , Yi Wang , Boxin Shi

Event cameras provide asynchronous, data-driven measurements of local temporal contrast over a large dynamic range with extremely high temporal resolution. Conventional cameras capture low-frequency reference intensity information. These…

Computer Vision and Pattern Recognition · Computer Science 2018-11-02 Cedric Scheerlinck , Nick Barnes , Robert Mahony

We develop a novel framework for single-scene video anomaly localization that allows for human-understandable reasons for the decisions the system makes. We first learn general representations of objects and their motions (using deep…

Computer Vision and Pattern Recognition · Computer Science 2022-12-16 Ashish Singh , Michael J. Jones , Erik Learned-Miller

Continuous space-time video super-resolution (C-STVSR) endeavors to upscale videos simultaneously at arbitrary spatial and temporal scales, which has recently garnered increasing interest. However, prevailing methods struggle to yield…

Image and Video Processing · Electrical Eng. & Systems 2025-05-09 Shuoyan Wei , Feng Li , Shengeng Tang , Yao Zhao , Huihui Bai

Event cameras offer a considerable alternative to RGB cameras in many scenarios. While there are recent works on event-based novel-view synthesis, dense 3D mesh reconstruction remains scarcely explored and existing event-based techniques…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Shreyas Sachan , Viktor Rudnev , Mohamed Elgharib , Christian Theobalt , Vladislav Golyanik

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

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

Event cameras promise a paradigm shift in vision sensing with their low latency, high dynamic range, and asynchronous nature of events. Unfortunately, the scarcity of high-quality labeled datasets hinders their widespread adoption in deep…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Kaustav Chanda , Aayush Atul Verma , Arpitsinh Vaghela , Yezhou Yang , Bharatesh Chakravarthi

Video Frame Interpolation aims to recover realistic missing frames between observed frames, generating a high-frame-rate video from a low-frame-rate video. However, without additional guidance, the large motion between frames makes this…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Jingxi Chen , Brandon Y. Feng , Haoming Cai , Tianfu Wang , Levi Burner , Dehao Yuan , Cornelia Fermuller , Christopher A. Metzler , Yiannis Aloimonos

Visual reconstruction of fast non-rigid object deformations over time is a challenge for conventional frame-based cameras. In this paper, we propose a novel approach for reconstructing such deformations using measurements from event-based…

Computer Vision and Pattern Recognition · Computer Science 2022-11-15 Yuxuan Xue , Haolong Li , Stefan Leutenegger , Jörg Stückler

Scene reconstruction from casually captured videos has wide applications in real-world scenarios. With recent advancements in differentiable rendering techniques, several methods have attempted to simultaneously optimize scene…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Bohao Liao , Wei Zhai , Zengyu Wan , Zhixin Cheng , Wenfei Yang , Tianzhu Zhang , Yang Cao , Zheng-Jun Zha

In contrast to traditional cameras, whose pixels have a common exposure time, event-based cameras are novel bio-inspired sensors whose pixels work independently and asynchronously output intensity changes (called "events"), with microsecond…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Timo Stoffregen , Guillermo Gallego , Tom Drummond , Lindsay Kleeman , Davide Scaramuzza
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