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Neuromorphic "event" cameras, designed to mimic the human vision system with asynchronous sensing, unlock a new realm of high-speed and high dynamic range applications. However, researchers often either revert to a framed representation of…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Andrew C. Freeman , Montek Singh , Ketan Mayer-Patel

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

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 are bio-inspired sensors providing significant advantages over standard cameras such as low latency, high temporal resolution, and high dynamic range. We propose a novel structured-light system using an event camera to tackle…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Manasi Muglikar , Guillermo Gallego , Davide Scaramuzza

Event cameras are bio-inspired sensors with some notable features, including high dynamic range and low latency, which makes them exceptionally suitable for perception in challenging scenarios such as high-speed motion and extreme lighting…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Kuangyi Chen , Jun Zhang , Friedrich Fraundorfer

Event camera, a novel neuromorphic vision sensor, records data with high temporal resolution and wide dynamic range, offering new possibilities for accurate visual representation in challenging scenarios. However, event data is inherently…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Lin Zhu , Ruonan Liu , Xiao Wang , Lizhi Wang , Hua Huang

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

Pose estimation and tracking of objects is a fundamental application in 3D vision. Event cameras possess remarkable attributes such as high dynamic range, low latency, and resilience against motion blur, which enables them to address…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Zibin Liu , Banglei Guan , Yang Shang , Qifeng Yu , Laurent Kneip

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-based cameras (EBCs) have emerged as a bio-inspired alternative to traditional cameras, offering advantages in power efficiency, temporal resolution, and high dynamic range. However, the development of image analysis methods for EBCs…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Dmitrii Torbunov , Yihui Ren , Animesh Ghose , Odera Dim , Yonggang Cui

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

This paper presents a novel fusion of low-level approaches for dimensionality reduction into an effective approach for high-level objects in neuromorphic camera data called Inceptive Event Time-Surfaces (IETS). IETSs overcome several…

Neural and Evolutionary Computing · Computer Science 2020-02-28 R Wes Baldwin , Mohammed Almatrafi , Jason R Kaufman , Vijayan Asari , Keigo Hirakawa

Event cameras respond to brightness changes in the scene asynchronously and independently for every pixel. Due to the properties, these cameras have distinct features: high dynamic range (HDR), high temporal resolution, and low power…

Computer Vision and Pattern Recognition · Computer Science 2022-10-17 Jongwan Kim , DongJin Lee , Byunggook Na , Seongsik Park , Jeonghee Jo , Sungroh Yoon

Line segment extraction is effective for capturing geometric features of human-made environments. Event-based cameras, which asynchronously respond to contrast changes along edges, enable efficient extraction by reducing redundant data.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Mikihiro Ikura , Arren Glover , Masayoshi Mizuno , Chiara Bartolozzi

Event cameras, which feature pixels that independently respond to changes in brightness, are becoming increasingly popular in high-speed applications due to their lower latency, reduced bandwidth requirements, and enhanced dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ziyuan Qu , Zihao Zou , Vivek Boominathan , Praneeth Chakravarthula , Adithya Pediredla

State-of-the-art frame interpolation methods generate intermediate frames by inferring object motions in the image from consecutive key-frames. In the absence of additional information, first-order approximations, i.e. optical flow, must be…

Computer Vision and Pattern Recognition · Computer Science 2021-06-15 Stepan Tulyakov , Daniel Gehrig , Stamatios Georgoulis , Julius Erbach , Mathias Gehrig , Yuanyou Li , Davide Scaramuzza

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

We present Recurrent Vision Transformers (RVTs), a novel backbone for object detection with event cameras. Event cameras provide visual information with sub-millisecond latency at a high-dynamic range and with strong robustness against…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Mathias Gehrig , Davide Scaramuzza

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time,…

Identifying independently moving objects is an essential task for dynamic scene understanding. However, traditional cameras used in dynamic scenes may suffer from motion blur or exposure artifacts due to their sampling principle. By…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Yi Zhou , Guillermo Gallego , Xiuyuan Lu , Siqi Liu , Shaojie Shen