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Event cameras are biologically-inspired sensors that gather the temporal evolution of the scene. They capture pixel-wise brightness variations and output a corresponding stream of asynchronous events. Despite having multiple advantages with…

Computer Vision and Pattern Recognition · Computer Science 2019-12-11 Stefano Pini , Guido Borghi , Roberto Vezzani

Clear imaging under hazy conditions is a critical task. Prior-based and neural methods have improved results. However, they operate on RGB frames, which suffer from limited dynamic range. Therefore, dehazing remains ill-posed and can erase…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Ling Wang , Yunfan Lu , Wenzong Ma , Huizai Yao , Pengteng Li , Hui Xiong

Event cameras are novel sensors that output 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 dynamic range (HDR),…

Computer Vision and Pattern Recognition · Computer Science 2020-04-02 Daniel Gehrig , Mathias Gehrig , Javier Hidalgo-Carrió , Davide Scaramuzza

The bio-inspired event cameras or dynamic vision sensors are capable of asynchronously capturing per-pixel brightness changes (called event-streams) in high temporal resolution and high dynamic range. However, the non-structural…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Qiang Qu , Yiran Shen , Xiaoming Chen , Yuk Ying Chung , Tongliang Liu

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

Traditional RGB-based speech generation faces Temporal Granularity Mismatch since fixed camera exposure times inevitably blur the high-frequency articulatory transients essential for rendering emotional speech. To break this ceiling, we…

Multimedia · Computer Science 2026-05-27 Jingping Fang , Lin Chen , Chenyang Xu , Tong Zhao , Weidong Cai , Xiaoming Chen

Tracking using bio-inspired event cameras has drawn more and more attention in recent years. Existing works either utilize aligned RGB and event data for accurate tracking or directly learn an event-based tracker. The first category needs…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Xiao Wang , Shiao Wang , Chuanming Tang , Lin Zhu , Bo Jiang , Yonghong Tian , Jin Tang

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

Event cameras are activity-driven bio-inspired vision sensors, thereby resulting in advantages such as sparsity,high temporal resolution, low latency, and power consumption. Given the different sensing modality of event camera and high…

Computer Vision and Pattern Recognition · Computer Science 2021-05-11 Lakshmi Annamalai , Vignesh Ramanathan , Chetan Singh Thakur

Event cameras are innovative neuromorphic sensors that asynchronously capture the scene dynamics. Due to the event-triggering mechanism, such cameras record event streams with much shorter response latency and higher intensity sensitivity…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Yunhao Zou , Ying Fu , Tsuyoshi Takatani , Yinqiang Zheng

Event cameras provide a number of benefits over traditional cameras, such as the ability to track incredibly fast motions, high dynamic range, and low power consumption. However, their application into computer vision problems, many of…

Computer Vision and Pattern Recognition · Computer Science 2019-12-20 Alex Zihao Zhu , Ziyun Wang , Kaung Khant , Kostas Daniilidis

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

Existing event stream-based pattern recognition models usually represent the event stream as the point cloud, voxel, image, etc., and design various deep neural networks to learn their features. Although considerable results can be achieved…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Lan Chen , Dong Li , Xiao Wang , Pengpeng Shao , Wei Zhang , Yaowei Wang , Yonghong Tian , Jin Tang

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 advantageous for tasks that require vision sensors with low-latency and sparse output responses. However, the development of deep network algorithms using event cameras has been slow because of the lack of large labelled…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Joachim Ott , Zuowen Wang , Shih-Chii Liu

The advantages of event-sensing over conventional sensors (e.g., higher dynamic range, lower time latency, and lower power consumption) have spurred research into machine learning for event data. Unsurprisingly, deep learning has emerged as…

Machine Learning · Computer Science 2021-06-11 Fuqiang Gu , Weicong Sng , Xuke Hu , Fangwen Yu

Photometric stereo is a technique for estimating surface normals using images captured under varying illumination. However, conventional frame-based photometric stereo methods are limited in real-world applications due to their reliance on…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Hyunwoo Kim , Won-Hoe Kim , Sanghoon Lee , Jianfei Cai , Giljoo Nam , Jae-Sang Hyun

Event cameras are novel vision sensors that sample, in an asynchronous fashion, brightness increments with low latency and high temporal resolution. The resulting streams of events are of high value by themselves, especially for high speed…

Computer Vision and Pattern Recognition · Computer Science 2021-04-13 F. Paredes-Vallés , G. C. H. E. de Croon

Event cameras are novel bio-inspired vision sensors that output pixel-level intensity changes in microsecond accuracy with a high dynamic range and low power consumption. Despite these advantages, event cameras cannot be directly applied to…

Computer Vision and Pattern Recognition · Computer Science 2022-11-02 Jinjin Gu , Jinan Zhou , Ringo Sai Wo Chu , Yan Chen , Jiawei Zhang , Xuanye Cheng , Song Zhang , Jimmy S. Ren

We present a novel method to estimate the surface normal of an object in an ambient light environment using RGB and event cameras. Modern photometric stereo methods rely on an RGB camera, mainly in a dark room, to avoid ambient…

Computer Vision and Pattern Recognition · Computer Science 2023-08-11 Wonjeong Ryoo , Giljoo Nam , Jae-Sang Hyun , Sangpil Kim
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