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Related papers: Event-Based Motion Magnification

200 papers

The dynamic range limitation of conventional RGB cameras reduces global contrast and causes loss of high-frequency details such as textures and edges in complex traffic environments (e.g., nighttime driving, tunnels), hindering…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Zhanwen Liu , Yujing Sun , Yang Wang , Nan Yang , Shengbo Eben Li , Xiangmo Zhao

As the ubiquity of smart mobile devices continues to rise, Optical Camera Communication systems have gained more attention as a solution for efficient and private data streaming. This system utilizes optical cameras to receive data from…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Hang Su , Ling Gao , Tao Liu , Laurent Kneip

The amplification of high-speed micro-motions holds significant promise, with applications spanning fault detection in fast-paced industrial environments to refining precision in medical procedures. However, conventional motion…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Baoyue Zhang , Yajing Zheng , Shiyan Chen , Jiyuan Zhang , Kang Chen , Zhaofei Yu , Tiejun Huang

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

Despite the dynamic development of computer vision algorithms, the implementation of perception and control systems for autonomous vehicles such as drones and self-driving cars still poses many challenges. A video stream captured by…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Piotr Wzorek , Tomasz Kryjak

Event camera is an emerging bio-inspired vision sensors that report per-pixel brightness changes asynchronously. It holds noticeable advantage of high dynamic range, high speed response, and low power budget that enable it to best capture…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Zhanpeng Shao , Wen Zhou , Wuzhen Wang , Jianyu Yang , Youfu Li

Slow shutter speed and long exposure time of frame-based cameras often cause visual blur and loss of inter-frame information, degenerating the overall quality of captured videos. To this end, we present a unified framework of event-based…

Computer Vision and Pattern Recognition · Computer Science 2022-04-15 Xiang Zhang , Lei Yu

Event-based structured light systems have recently been introduced as an exciting alternative to conventional frame-based triangulation systems for the 3D measurements of diffuse surfaces. Important benefits include the fast capture speed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Aniket Dashpute , Jiazhang Wang , James Taylor , Oliver Cossairt , Ashok Veeraraghavan , Florian Willomitzer

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

In this work, we propose a novel framework for unsupervised learning for event cameras that learns motion information from only the event stream. In particular, we propose an input representation of the events in the form of a discretized…

Computer Vision and Pattern Recognition · Computer Science 2018-12-20 Alex Zihao Zhu , Liangzhe Yuan , Kenneth Chaney , Kostas Daniilidis

The event camera, benefiting from its high dynamic range and low latency, provides performance gain for low-light image enhancement. Unlike frame-based cameras, it records intensity changes with extremely high temporal resolution, capturing…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Chunyan She , Fujun Han , Chengyu Fang , Shukai Duan , Lidan Wang

High dynamic range (HDR) imaging is a crucial task in computational photography, which captures details across diverse lighting conditions. Traditional HDR fusion methods face limitations in dynamic scenes with extreme exposure differences,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Shi Guo , Zixuan Chen , Ziran Zhang , Yutian Chen , Gangwei Xu , Tianfan Xue

Continuous video monitoring in surveillance, robotics, and wearable systems faces a fundamental power constraint: conventional RGB cameras consume substantial energy through fixed-rate capture. Event cameras offer sparse, motion-driven…

Computer Vision and Pattern Recognition · Computer Science 2025-12-08 Dmitrii Torbunov , Onur Okuducu , Yi Huang , Odera Dim , Rebecca Coles , Yonggang Cui , Yihui Ren

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 rapidly emerging as powerful vision sensors for 3D reconstruction, uniquely capable of asynchronously capturing per-pixel brightness changes. Compared to traditional frame-based cameras, event cameras produce sparse yet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Chuanzhi Xu , Haoxian Zhou , Langyi Chen , Haodong Chen , Zeke Zexi Hu , Zhicheng Lu , Ying Zhou , Vera Chung , Qiang Qu , Weidong Cai

Most existing RGB-based trackers target low frame rate benchmarks of around 30 frames per second. This setting restricts the tracker's functionality in the real world, especially for fast motion. Event-based cameras as bioinspired sensors…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Jiqing Zhang , Yuanchen Wang , Wenxi Liu , Meng Li , Jinpeng Bai , Baocai Yin , Xin Yang

Visual object tracking under challenging conditions of motion and light can be hindered by the capabilities of conventional cameras, prone to producing images with motion blur. Event cameras are novel sensors suited to robustly perform…

Computer Vision and Pattern Recognition · Computer Science 2022-12-16 Irene Perez-Salesa , Rodrigo Aldana-Lopez , Carlos Sagues

Event cameras rely on motion to obtain information about scene appearance. This means that appearance and motion are inherently linked: either both are present and recorded in the event data, or neither is captured. Previous works treat the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Shuang Guo , Friedhelm Hamann , Guillermo Gallego

Slow motion videos are becoming increasingly popular, but capturing high-resolution videos at extremely high frame rates requires professional high-speed cameras. To mitigate this problem, current techniques increase the frame rate of…

Computer Vision and Pattern Recognition · Computer Science 2020-04-22 Avinash Paliwal , Nima Khademi Kalantari

Event-based motion deblurring has shown promising results by exploiting low-latency events. However, current approaches are limited in their practical usage, as they assume the same spatial resolution of inputs and specific blurriness…

Computer Vision and Pattern Recognition · Computer Science 2023-08-14 Xiang Zhang , Lei Yu , Wen Yang , Jianzhuang Liu , Gui-Song Xia