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Related papers: Event-Based Motion Magnification

200 papers

Slow-motion replays provide a thrilling perspective on pivotal moments within sports games, offering a fresh and captivating visual experience. However, capturing slow-motion footage typically demands high-tech, expensive cameras and…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Antoine Deckyvere , Anthony Cioppa , Silvio Giancola , Bernard Ghanem , Marc Van Droogenbroeck

This technical report investigates the application of event-based vision sensors in non-invasive qualitative vibration analysis, with a particular focus on frequency measurement and motion magnification. Event cameras, with their high…

Neural and Evolutionary Computing · Computer Science 2024-10-21 Dwijay Bane , Anurag Gupta , Manan Suri

Event cameras are novel bio-inspired sensors that measure per-pixel brightness differences asynchronously. Recovering brightness from events is appealing since the reconstructed images inherit the high dynamic range (HDR) and high-speed…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Zelin Zhang , Anthony Yezzi , Guillermo Gallego

Many important physical phenomena involve subtle signals that are difficult to observe with the unaided eye, yet visualizing them can be very informative. Current motion magnification techniques can reveal these small temporal variations in…

Computer Vision and Pattern Recognition · Computer Science 2018-08-13 Weixuan Chen , Daniel McDuff

Event-based vision sensors, such as the Dynamic Vision Sensor (DVS), are ideally suited for real-time motion analysis. The unique properties encompassed in the readings of such sensors provide high temporal resolution, superior sensitivity…

Computer Vision and Pattern Recognition · Computer Science 2020-01-14 Anton Mitrokhin , Cornelia Fermuller , Chethan Parameshwara , Yiannis Aloimonos

Event cameras excel at high-speed, low-power, and high-dynamic-range scene perception. However, as they fundamentally record only relative intensity changes rather than absolute intensity, the resulting data streams suffer from a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Gang Xu , Zhiyu Zhu , Junhui Hou

Depth completion in dynamic scenes poses significant challenges due to rapid ego-motion and object motion, which can severely degrade the quality of input modalities such as RGB images and LiDAR measurements. Conventional RGB-D sensors…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Zhiqiang Yan , Jianhao Jiao , Zhengxue Wang , Gim Hee Lee

This work introduces and demonstrates the first system capable of imaging fast-moving extended non-rigid objects through strong atmospheric turbulence at high frame rate. Event cameras are a novel sensing architecture capable of estimating…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Yu-Hsiang Huang , Levi Burner , Sachin Shah , Ziyuan Qu , Adithya Pediredla , Christopher A. Metzler

Modeling Neural Radiance Fields for fast-moving deformable objects from visual data alone is a challenging problem. A major issue arises due to the high deformation and low acquisition rates. To address this problem, we propose to use event…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Qi Ma , Danda Pani Paudel , Ajad Chhatkuli , Luc Van Gool

Event cameras offering high dynamic range and low latency have emerged as disruptive technologies in imaging. Despite growing research on leveraging these benefits for different imaging tasks, a comprehensive study of recently advances and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Yunfan Lu , Xiaogang Xu , Pengteng Li , Yusheng Wang , Yi Cui , Huizai Yao , Hui Xiong

Recording fast motion in a high FPS (frame-per-second) requires expensive high-speed cameras. As an alternative, interpolating low-FPS videos from commodity cameras has attracted significant attention. If only low-FPS videos are available,…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Weihua He , Kaichao You , Zhendong Qiao , Xu Jia , Ziyang Zhang , Wenhui Wang , Huchuan Lu , Yaoyuan Wang , Jianxing Liao

Volumetric reconstruction of dynamic scenes is an important problem in computer vision. It is especially challenging in poor lighting and with fast motion. This is partly due to limitations of RGB cameras: To capture frames under low…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Viktor Rudnev , Gereon Fox , Mohamed Elgharib , Christian Theobalt , Vladislav Golyanik

Event cameras are bio-inspired sensors that perform well in challenging illumination conditions and have high temporal resolution. However, their concept is fundamentally different from traditional frame-based cameras. The pixels of an…

Computer Vision and Pattern Recognition · Computer Science 2022-06-13 Xin Peng , Ling Gao , Yifu Wang , Laurent Kneip

Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate downstream image processing, especially for complex tasks such…

Computer Vision and Pattern Recognition · Computer Science 2024-02-13 Darryl Hannan , Ragib Arnab , Gavin Parpart , Garrett T. Kenyon , Edward Kim , Yijing Watkins

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

We present a method that leverages the complementarity of event cameras and standard cameras to track visual features with low-latency. Event cameras are novel sensors that output pixel-level brightness changes, called "events". They offer…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Daniel Gehrig , Henri Rebecq , Guillermo Gallego , Davide Scaramuzza

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

We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional cameras struggle with high-speed motion capture due to bandwidth and dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Ziyun Wang , Friedhelm Hamann , Kenneth Chaney , Wen Jiang , Guillermo Gallego , Kostas Daniilidis

High-quality and challenging event stream datasets play an important role in the design of an efficient event-driven mechanism that mimics the brain. Although event cameras can provide high dynamic range and low-energy event stream data,…

Neural and Evolutionary Computing · Computer Science 2022-05-25 Guobin Shen , Dongcheng Zhao , Yi Zeng

Event cameras are emerging vision sensors whose noise is challenging to characterize. Existing denoising methods for event cameras are often designed in isolation and thus consider other tasks, such as motion estimation, separately (i.e.,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Shintaro Shiba , Yoshimitsu Aoki , Guillermo Gallego