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Event cameras do not produce images, but rather a continuous flow of events, which encode changes of illumination for each pixel independently and asynchronously. While they output temporally rich information, they lack any depth…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Vincent Brebion , Julien Moreau , Franck Davoine

Event cameras are novel sensors that report brightness changes in the form of a stream of asynchronous "events" instead of intensity frames. They offer significant advantages with respect to conventional cameras: high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-06-19 Henri Rebecq , René Ranftl , Vladlen Koltun , Davide Scaramuzza

Sign Language Translation (SLT) is a core task in the field of AI-assisted disability. Traditional SLT methods are typically based on visible light videos, which are easily affected by factors such as lighting variations, rapid hand…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Shiao Wang , Xiao Wang , Duoqing Yang , Yao Rong , Fuling Wang , Jianing Li , Lin Zhu , Bo Jiang

Different from visible cameras which record intensity images frame by frame, the biologically inspired event camera produces a stream of asynchronous and sparse events with much lower latency. In practice, visible cameras can better…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Xiao Wang , Jianing Li , Lin Zhu , Zhipeng Zhang , Zhe Chen , Xin Li , Yaowei Wang , Yonghong Tian , Feng Wu

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-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 high-speed maneuvering scenarios.…

Self-supervised learning is the key to unlocking generic computer vision systems. By eliminating the reliance on ground-truth annotations, it allows scaling to much larger data quantities. Unfortunately, self-supervised monocular depth…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Jaime Spencer , Chris Russell , Simon Hadfield , Richard Bowden

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 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

Event cameras are neuromorphic vision sensors that record a scene as sparse and asynchronous event streams. Most event-based methods project events into dense frames and process them using conventional vision models, resulting in high…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Bochen Xie , Yongjian Deng , Zhanpeng Shao , Qingsong Xu , Youfu Li

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

Event cameras are novel sensors that report brightness changes in the form of asynchronous "events" instead of intensity frames. They have significant advantages over conventional cameras: high temporal resolution, high dynamic range, and…

Computer Vision and Pattern Recognition · Computer Science 2019-04-18 Henri Rebecq , René Ranftl , Vladlen Koltun , Davide Scaramuzza

Event-based cameras can overpass frame-based cameras limitations for important tasks such as high-speed motion detection during self-driving cars navigation in low illumination conditions. The event cameras' high temporal resolution and…

Computer Vision and Pattern Recognition · Computer Science 2022-01-31 Haixin Sun , Minh-Quan Dao , Vincent Fremont

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

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 record sparse illumination changes with high temporal resolution and high dynamic range. Thanks to their sparse recording and low consumption, they are increasingly used in applications such as AR/VR and autonomous driving.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-24 Alberto Sabater , Luis Montesano , Ana C. Murillo

Event cameras sense intensity changes and have many advantages over conventional cameras. To take advantage of event cameras, some methods have been proposed to reconstruct intensity images from event streams. However, the outputs are still…

Computer Vision and Pattern Recognition · Computer Science 2020-03-18 Lin Wang , Tae-Kyun Kim , Kuk-Jin Yoon

Egocentric gesture recognition is a pivotal technology for enhancing natural human-computer interaction, yet traditional RGB-based solutions suffer from motion blur and illumination variations in dynamic scenarios. While event cameras show…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Luming Wang , Hao Shi , Xiaoting Yin , Kailun Yang , Kaiwei Wang , Jian Bai

Event camera has recently received much attention for low-light image enhancement (LIE) thanks to their distinct advantages, such as high dynamic range. However, current research is prohibitively restricted by the lack of large-scale,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Guoqiang Liang , Kanghao Chen , Hangyu Li , Yunfan Lu , Lin Wang

Event cameras offer a promising avenue for multi-view stereo depth estimation and Simultaneous Localization And Mapping (SLAM) due to their ability to detect blur-free 3D edges at high-speed and over broad illumination conditions. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Diego Hitzges , Suman Ghosh , Guillermo Gallego