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Related papers: EventNet: Asynchronous Recursive Event Processing

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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

Facial Expression Recognition (FER) is an active research domain that has shown great progress recently, notably thanks to the use of large deep learning models. However, such approaches are particularly energy intensive, which makes their…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Sami Barchid , Benjamin Allaert , Amel Aissaoui , José Mennesson , Chaabane Djéraba

Event-based vision sensors encode local pixel-wise brightness changes in streams of events rather than image frames and yield sparse, energy-efficient encodings of scenes, in addition to low latency, high dynamic range, and lack of motion…

Computer Vision and Pattern Recognition · Computer Science 2022-02-09 Alexander Kugele , Thomas Pfeil , Michael Pfeiffer , Elisabetta Chicca

Event cameras, often referred to as dynamic vision sensors, are groundbreaking sensors capable of capturing changes in light intensity asynchronously, offering exceptional temporal resolution and energy efficiency. These attributes make…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Mira Adra , Simone Melcarne , Nelida Mirabet-Herranz , Jean-Luc Dugelay

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

Event cameras offer a considerable alternative to RGB cameras in many scenarios. While there are recent works on event-based novel-view synthesis, dense 3D mesh reconstruction remains scarcely explored and existing event-based techniques…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Shreyas Sachan , Viktor Rudnev , Mohamed Elgharib , Christian Theobalt , Vladislav Golyanik

Event-based cameras are becoming increasingly popular for their ability to capture high-speed motion with low latency and high dynamic range. However, generating videos from events remains challenging due to the highly sparse and varying…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Burak Ercan , Onur Eker , Canberk Saglam , Aykut Erdem , Erkut Erdem

Event-specific concepts are the semantic concepts designed for the events of interest, which can be used as a mid-level representation of complex events in videos. Existing methods only focus on defining event-specific concepts for a small…

Computer Vision and Pattern Recognition · Computer Science 2015-08-18 Guangnan Ye , Yitong Li , Hongliang Xu , Dong Liu , Shih-Fu Chang

Event cameras, with their high dynamic range and temporal resolution, are ideally suited for object detection, especially under scenarios with motion blur and challenging lighting conditions. However, while most existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Ziming Wang , Ziling Wang , Huaning Li , Lang Qin , Runhao Jiang , De Ma , Huajin Tang

Leveraging the high temporal resolution and dynamic range, object detection with event cameras can enhance the performance and safety of automotive and robotics applications in real-world scenarios. However, processing sparse event data…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Shenqi Wang , Yingfu Xu , Amirreza Yousefzadeh , Sherif Eissa , Henk Corporaal , Federico Corradi , Guangzhi Tang

Event cameras generate asynchronous and sparse event streams capturing changes in light intensity. They offer significant advantages over conventional frame-based cameras, such as a higher dynamic range and an extremely faster data rate,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-09 Yi Tian , Juan Andrade-Cetto

Event cameras like Dynamic Vision Sensors (DVS) report micro-timed brightness changes instead of full frames, offering low latency, high dynamic range, and motion robustness. DVS-PedX (Dynamic Vision Sensor Pedestrian eXploration) is a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Mustafa Sakhai , Kaung Sithu , Min Khant Soe Oke , Maciej Wielgosz

Event-based cameras capture visual information as asynchronous streams of per-pixel brightness changes, generating sparse, temporally precise data. Compared to conventional frame-based sensors, they offer significant advantages in capturing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Biswadeep Sen , Benoit R. Cottereau , Nicolas Cuperlier , Terence Sim

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 have recently gained significant traction since they open up new avenues for low-latency and low-power solutions to complex computer vision problems. To unlock these solutions, it is necessary to develop algorithms that can…

Computer Vision and Pattern Recognition · Computer Science 2023-09-28 Federico Paredes-Vallés , Kirk Y. W. Scheper , Christophe De Wagter , Guido C. H. E. de Croon

Event-based cameras are biologically inspired sensors that output asynchronous pixel-wise brightness changes in the scene called events. They have a high dynamic range and temporal resolution of a microsecond, opposed to standard cameras…

Robotics · Computer Science 2019-07-18 Antea Hadviger , Ivan Marković , Ivan Petrović

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

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 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

In this work, we present optical space imaging using an unconventional yet promising class of imaging devices known as neuromorphic event-based sensors. These devices, which are modeled on the human retina, do not operate with frames, but…

Computer Vision and Pattern Recognition · Computer Science 2019-11-21 Saeed Afshar , Andrew P Nicholson , Andre van Schaik , Gregory Cohen
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