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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

As neuromorphic sensors, event cameras asynchronously record changes in brightness as streams of sparse events with the advantages of high temporal resolution and high dynamic range. Reconstructing intensity images from events is a highly…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Weilun Li , Lei Sun , Ruixi Gao , Qi Jiang , Yuqin Ma , Kaiwei Wang , Ming-Hsuan Yang , Luc Van Gool , Danda Pani Paudel

Recent learning-based methods for event-based optical flow estimation utilize cost volumes for pixel matching but suffer from redundant computations and limited scalability to higher resolutions for flow refinement. In this work, we take…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Daikun Liu , Lei Cheng , Teng Wang , changyin Sun

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

We present EvDNeRF, a pipeline for generating event data and training an event-based dynamic NeRF, for the purpose of faithfully reconstructing eventstreams on scenes with rigid and non-rigid deformations that may be too fast to capture…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Anish Bhattacharya , Ratnesh Madaan , Fernando Cladera , Sai Vemprala , Rogerio Bonatti , Kostas Daniilidis , Ashish Kapoor , Vijay Kumar , Nikolai Matni , Jayesh K. Gupta

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

Event cameras are bio-inspired sensors that asynchronously report intensity changes in microsecond resolution. DAVIS can capture high dynamics of a scene and simultaneously output high temporal resolution events and low frame-rate intensity…

Computer Vision and Pattern Recognition · Computer Science 2020-04-02 Liyuan Pan , Miaomiao Liu , Richard Hartley

Event cameras are bio-inspired sensors that capture per-pixel asynchronous intensity change rather than the synchronous absolute intensity frames captured by a classical camera sensor. Such cameras are ideal for robotics applications since…

Computer Vision and Pattern Recognition · Computer Science 2022-05-18 Ziwei Wang , Dingran Yuan , Yonhon Ng , Robert Mahony

Event cameras are bio-inspired vision sensors that mimic retinas to asynchronously report per-pixel intensity changes rather than outputting an actual intensity image at regular intervals. This new paradigm of image sensor offers…

Computer Vision and Pattern Recognition · Computer Science 2019-04-02 Yusuke Sekikawa , Kosuke Hara , Hideo Saito

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 capture the per-pixel intensity changes asynchronously and produce event streams encoding the time, pixel position, and polarity (sign) of the intensity changes. Event cameras possess a myriad of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Xu Zheng , Yexin Liu , Yunfan Lu , Tongyan Hua , Tianbo Pan , Weiming Zhang , Dacheng Tao , Lin Wang

Event vision sensors (neuromorphic cameras) output sparse, asynchronous ON/OFF events triggered by log-intensity threshold crossings, enabling microsecond-scale sensing with high dynamic range and low data bandwidth. As a nonlinear system,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Nimrod Kruger , Nicholas Owen Ralph , Gregory Cohen , Paul Hurley

Event cameras are a new type of sensors that are different from traditional cameras. Each pixel is triggered asynchronously by event. The trigger event is the change of the brightness irradiated on the pixel. If the increment or decrement…

Computer Vision and Pattern Recognition · Computer Science 2022-03-24 Kun Xiao , Guohui Wang , Yi Chen , Jinghong Nan , Yongfeng Xie

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

Contrary to conventional frame-based imaging, event-based vision (EBV) or dynamic vision sensing (DVS) asynchronously records binary signals of intensity changes for given pixels with microsecond resolution. The present work explores the…

Fluid Dynamics · Physics 2022-06-22 Christian Willert , Joachim Klinner

Dynamic vision sensors or event cameras provide rich complementary information for video frame interpolation. Existing state-of-the-art methods follow the paradigm of combining both synthesis-based and warping networks. However, few of…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Jiaben Chen , Yichen Zhu , Dongze Lian , Jiaqi Yang , Yifu Wang , Renrui Zhang , Xinhang Liu , Shenhan Qian , Laurent Kneip , Shenghua Gao

Event-based cameras can measure intensity changes (called `{\it events}') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the active pixel sensor (APS), the event camera allows simultaneous output…

Computer Vision and Pattern Recognition · Computer Science 2018-11-28 Liyuan Pan , Cedric Scheerlinck , Xin Yu , Richard Hartley , Miaomiao Liu , Yuchao Dai

Large-scale structures suffer high-frequency deformations due to complex loads. However, harsh lighting conditions and high equipment costs limit measurement methods based on traditional high-speed cameras. This paper proposes a method to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-18 Yifei Bian , Banglei Guan , Zibin Liu , Ang Su , Shiyao Zhu , Yang Shang , Qifeng Yu

Event cameras such as DAVIS can simultaneously output high temporal resolution events and low frame-rate intensity images, which own great potential in capturing scene motion, such as optical flow estimation. Most of the existing optical…

Computer Vision and Pattern Recognition · Computer Science 2022-11-18 Zhexiong Wan , Yuchao Dai , Yuxin Mao

We study the problem of estimating optical flow from event cameras. One important issue is how to build a high-quality event-flow dataset with accurate event values and flow labels. Previous datasets are created by either capturing real…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Xinglong Luo , Kunming Luo , Ao Luo , Zhengning Wang , Ping Tan , Shuaicheng Liu
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