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Event-based vision sensors, such as the Dynamic Vision Sensor (DVS), are ideally suited for real-time motion analysis. The unique properties encompassed in the readings of such sensors provide high temporal resolution, superior sensitivity…

Computer Vision and Pattern Recognition · Computer Science 2020-01-14 Anton Mitrokhin , Cornelia Fermuller , Chethan Parameshwara , Yiannis Aloimonos

We present Ev-NeRF, a Neural Radiance Field derived from event data. While event cameras can measure subtle brightness changes in high frame rates, the measurements in low lighting or extreme motion suffer from significant domain…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Inwoo Hwang , Junho Kim , Young Min Kim

Event camera is a novel bio-inspired vision sensor that outputs event stream. In this paper, we propose a novel data fusion algorithm called EAS to fuse conventional intensity images with the event stream. The fusion result is applied to…

Computer Vision and Pattern Recognition · Computer Science 2022-07-13 Liren Yang

Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution, offering the potential to handle visual tasks in challenging scenarios. However, due to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Sheng Zhong , Zhongyang Ren , Xiya Zhu , Dehao Yuan , Cornelia Fermuller , Yi Zhou

Leveraging the high temporal resolution and dynamic range, object detection with event cameras can enhance the performance and safety of automotive and robotics applications in real-world scenarios. However, processing sparse event data…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Shenqi Wang , Yingfu Xu , Amirreza Yousefzadeh , Sherif Eissa , Henk Corporaal , Federico Corradi , Guangzhi Tang

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

Compared to frame-based methods, computational neuromorphic imaging using event cameras offers significant advantages, such as minimal motion blur, enhanced temporal resolution, and high dynamic range. The multi-view consistency of Neural…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Chaoran Feng , Wangbo Yu , Xinhua Cheng , Zhenyu Tang , Junwu Zhang , Li Yuan , Yonghong Tian

Event cameras capture changes of illumination in the observed scene rather than accumulating light to create images. Thus, they allow for applications under high-speed motion and complex lighting conditions, where traditional framebased…

Computer Vision and Pattern Recognition · Computer Science 2021-12-21 Vincent Brebion , Julien Moreau , Franck Davoine

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

Event-based vision sensors mimic the operation of biological retina and they represent a major paradigm shift from traditional cameras. Instead of providing frames of intensity measurements synchronously, at artificially chosen rates,…

Computer Vision and Pattern Recognition · Computer Science 2015-10-08 Guillermo Gallego , Christian Forster , Elias Mueggler , Davide Scaramuzza

Event cameras have higher temporal resolution, and require less storage and bandwidth compared to traditional RGB cameras. However, due to relatively lagging performance of event-based approaches, event cameras have not yet replace…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Muhammad Ahmed Ullah Khan , Abdul Hannan Khan , Andreas Dengel

Event cameras are a bio-inspired class of sensors that asynchronously measure per-pixel intensity changes. Under fixed illumination conditions in static or low-motion scenes, rigidly mounted event cameras are unable to generate any events…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Vincenzo Polizzi , Stephen Yang , Quentin Clark , Jonathan Kelly , Igor Gilitschenski , David B. Lindell

We present a widefield fluorescence microscope that integrates an event-based image sensor (EBIS) with a CMOS image sensor (CIS) for ultra-fast microscopy with spectral distinction capabilities. The EBIS achieves temporal resolution of…

Optics · Physics 2024-10-22 Richard G. Baird , Apratim Majumder , Rajesh Menon

Object detection and tracking is an essential perception task for enabling fully autonomous navigation in robotic systems. Edge robot systems such as small drones need to execute complex maneuvers at high-speeds with limited resources,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Adarsh Kumar Kosta , Amogh Joshi , Arjun Roy , Rohan Kumar Manna , Manish Nagaraj , Kaushik Roy

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time,…

Event-based vision revolutionizes traditional image sensing by capturing asynchronous intensity variations rather than static frames, enabling ultrafast temporal resolution, sparse data encoding, and enhanced motion perception. While this…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Joey Mulé , Dhandeep Challagundla , Rachit Saini , Riadul Islam

We present a novel method for measuring the rate of periodic phenomena (e.g., rotation, flicker, and vibration), by an event camera, a device asynchronously reporting brightness changes at independently operating pixels with high temporal…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Jakub Kolář , Radim Špetlík , Jiří Matas

Existing single-modal RGB trackers often face performance bottlenecks in complex dynamic scenes, while the introduction of event sensors offers new potential for enhancing tracking capabilities. However, most current RGB-event fusion…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Jinlin You , Muyu Li , Xudong Zhao

The event camera has appealing properties: high dynamic range, low latency, low power consumption and low memory usage, and thus provides complementariness to conventional frame-based cameras. It only captures the dynamics of a scene and is…

Computer Vision and Pattern Recognition · Computer Science 2020-03-03 Fang Xu , Shijie Lin , Wen Yang , Lei Yu , Dengxin Dai , Gui-song Xia

In frame-based vision, object detection faces substantial performance degradation under challenging conditions due to the limited sensing capability of conventional cameras. Event cameras output sparse and asynchronous events, providing a…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Hu Cao , Zehua Zhang , Yan Xia , Xinyi Li , Jiahao Xia , Guang Chen , Alois Knoll