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In this paper, we explore the problem of event-based meshflow estimation, a novel task that involves predicting a spatially smooth sparse motion field from event cameras. To start, we review the state-of-the-art in event-based flow…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Xinglong Luo , Ao Luo , Kunming Luo , Zhengning Wang , Ping Tan , Bing Zeng , Shuaicheng Liu

Event-based cameras have shown great promise in a variety of situations where frame based cameras suffer, such as high speed motions and high dynamic range scenes. However, developing algorithms for event measurements requires a new class…

Computer Vision and Pattern Recognition · Computer Science 2018-08-14 Alex Zihao Zhu , Liangzhe Yuan , Kenneth Chaney , Kostas Daniilidis

Most of the artificial lights fluctuate in response to the grid's alternating current and exhibit subtle variations in terms of both intensity and spectrum, providing the potential to estimate the Electric Network Frequency (ENF) from…

Image and Video Processing · Electrical Eng. & Systems 2023-05-05 Lexuan Xu , Guang Hua , Haijian Zhang , Lei Yu , Ning Qiao

Event camera sensors are bio-inspired sensors which asynchronously capture per-pixel brightness changes and output a stream of events encoding the polarity, location and time of these changes. These systems are witnessing rapid advancements…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Aupendu Kar , Vishnu Raj , Guan-Ming Su

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 bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Guillermo Gallego , Jon E. A. Lund , Elias Mueggler , Henri Rebecq , Tobi Delbruck , Davide Scaramuzza

We present a method for estimating dense continuous-time optical flow from event data. Traditional dense optical flow methods compute the pixel displacement between two images. Due to missing information, these approaches cannot recover the…

Computer Vision and Pattern Recognition · Computer Science 2024-02-13 Mathias Gehrig , Manasi Muglikar , Davide Scaramuzza

We propose to incorporate feature correlation and sequential processing into dense optical flow estimation from event cameras. Modern frame-based optical flow methods heavily rely on matching costs computed from feature correlation. In…

Computer Vision and Pattern Recognition · Computer Science 2021-10-22 Mathias Gehrig , Mario Millhäusler , Daniel Gehrig , Davide Scaramuzza

Underwater imaging is fundamentally challenging due to wavelength-dependent light attenuation, strong scattering from suspended particles, turbidity-induced blur, and non-uniform illumination. These effects impair standard cameras and make…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Nick Truong , Pritam P. Karmokar , William J. Beksi

Event cameras are sensors of great interest for many applications that run in low-resource and challenging environments. They log sparse illumination changes with high temporal resolution and high dynamic range, while they present minimal…

Computer Vision and Pattern Recognition · Computer Science 2022-04-19 Alberto Sabater , Luis Montesano , Ana C. Murillo

Good temporal representations are crucial for video understanding, and the state-of-the-art video recognition framework is based on two-stream networks. In such framework, besides the regular ConvNets responsible for RGB frame inputs, a…

Computer Vision and Pattern Recognition · Computer Science 2018-05-22 Wanjia Liu , Huaijin Chen , Rishab Goel , Yuzhong Huang , Ashok Veeraraghavan , Ankit Patel

The stark contrast in the design philosophy of an event camera makes it particularly ideal for operating under high-speed, high dynamic range and low-light conditions, where standard cameras underperform. Nonetheless, event cameras still…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Weng Fei Low , Gim Hee Lee

Event-based vision sensors offer asynchronous, high-temporal-resolution measurements that are attractive for low-latency robotic perception, but many event-based motion estimation methods are computationally intensive and difficult to map…

Robotics · Computer Science 2026-05-28 Arianna Alonso Bizzi , Fernando Cladera , C. J. Taylor

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

Event cameras are dynamic vision sensors inspired by the biological retina, characterized by their high dynamic range, high temporal resolution, and low power consumption. These features make them capable of perceiving 3D environments even…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Hoonhee Cho , Jae-Young Kang , Kuk-Jin Yoon

The broad scope of obstacle avoidance has led to many kinds of computer vision-based approaches. Despite its popularity, it is not a solved problem. Traditional computer vision techniques using cameras and depth sensors often focus on…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Celyn Walters , Simon Hadfield

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,…

The current event cameras are bio-inspired sensors that respond to brightness changes in the scene asynchronously and independently for every pixel, and transmit these changes as ternary event streams. Event cameras have several benefits…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Eero Lehtonen , Tuomo Komulainen , Ari Paasio , Mika Laiho

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 the potential to revolutionize vision systems with their high temporal resolution and dynamic range, yet they remain susceptible to lens flare, a fundamental optical artifact that causes severe degradation. In event…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Haiqian Han , Lingdong Kong , Jianing Li , Ao Liang , Chengtao Zhu , Jiacheng Lyu , Lai Xing Ng , Xiangyang Ji , Wei Tsang Ooi , Benoit R. Cottereau