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Today, state-of-the-art deep neural networks that process event-camera data first convert a temporal window of events into dense, grid-like input representations. As such, they exhibit poor generalizability when deployed at higher inference…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Nikola Zubić , Mathias Gehrig , Davide Scaramuzza

Event cameras are vision sensors that record asynchronous streams of per-pixel brightness changes, referred to as "events". They have appealing advantages over frame-based cameras for computer vision, including high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-21 Daniel Gehrig , Antonio Loquercio , Konstantinos G. Derpanis , Davide Scaramuzza

The Dynamic Vision Sensor (DVS) is an innovative technology that efficiently captures and encodes visual information in an event-driven manner. By combining it with event-driven neuromorphic processing, the sparsity in DVS camera output can…

Computer Vision and Pattern Recognition · Computer Science 2024-02-15 Yiming Bu , Jiayang Liu , Qinru Qiu

Face analysis has been studied from different angles to infer emotion, poses, shapes, and landmarks. Traditionally RGB cameras are used, yet for fine-grained tasks standard sensors might not be up to the task due to their latency, making it…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Luca Cultrera , Federico Becattini , Lorenzo Berlincioni , Claudio Ferrari , Alberto Del Bimbo

Event-based Sensing (EBS) hardware is quickly proliferating while finding foothold in many commercial, industrial, and defense applications. At present, there are a handful of technologically mature systems which produce data streams with…

Image and Video Processing · Electrical Eng. & Systems 2025-11-20 Jonah P. Sengupta , Mohammad Imran Vakil , Thanh M. Dang , Ian Pardee , Paul Coen , Olivia Aul

In a decade, the adaptive quality control of video streaming and the super-resolution (SR) technique have been deeply explored. As edge devices improved to have exceptional processing capability than ever before, streaming users can enhance…

Multimedia · Computer Science 2021-10-13 Minseok Choi , Won Joon Yun , Joongheon Kim

The shift toward IoT-enabled, sensor-driven systems has transformed how operational data is generated, favoring continuous, real-time event streams (ES) over static event logs. This evolution presents new challenges for Streaming Process…

Because of their high temporal resolution, increased resilience to motion blur, and very sparse output, event cameras have been shown to be ideal for low-latency and low-bandwidth feature tracking, even in challenging scenarios. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Nico Messikommer , Carter Fang , Mathias Gehrig , Giovanni Cioffi , Davide Scaramuzza

Emerging event cameras acquire visual information by detecting time domain brightness changes asynchronously at the pixel level and, unlike conventional cameras, are able to provide high temporal resolution, very high dynamic range, low…

Multimedia · Computer Science 2024-11-06 Ahmadreza Sezavar , Catarina Brites , Joao Ascenso

Unlike conventional frame-based sensors, event-based visual sensors output information through spikes at a high temporal resolution. By only encoding changes in pixel intensity, they showcase a low-power consuming, low-latency approach to…

Computer Vision and Pattern Recognition · Computer Science 2019-03-19 Rohan Ghosh , Anupam Gupta , Siyi Tang , Alcimar Soares , Nitish Thakor

In event-based sensing, many sensors independently and asynchronously emit events when there is a change in their input. Event-based sensing can present significant improvements in power efficiency when compared to traditional sampling,…

Image and Video Processing · Electrical Eng. & Systems 2022-01-19 Karen Adam , Adam Scholefield , Martin Vetterli

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

Event-based multimodal large language models (MLLMs) enable robust perception in high-speed and low-light scenarios, addressing key limitations of frame-based MLLMs. However, current event-based MLLMs often rely on dense image-like…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Shaoyu Liu , Jianing Li , Guanghui Zhao , Yunjian Zhang , Wen Jiang , Ming Li , Xiangyang Ji

Attention-based models have been gaining popularity recently for their strong performance demonstrated in fields such as machine translation and automatic speech recognition. One major challenge of attention-based models is the need of…

Computation and Language · Computer Science 2020-11-17 Ching-Feng Yeh , Yongqiang Wang , Yangyang Shi , Chunyang Wu , Frank Zhang , Julian Chan , Michael L. Seltzer

Event cameras output event streams as sparse, asynchronous data with microsecond-level temporal resolution, enabling visual perception with low latency and a high dynamic range. While existing Multimodal Large Language Models (MLLMs) have…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Rui Chen , Xingyu Chen , Shaoan Wang , Shihan Kong , Junzhi Yu

Event-driven sensors, which produce data only when there is a change in the input signal, are increasingly used in applications that require low-latency and low-power real-time sensing, such as robotics and edge devices. To fully achieve…

Signal Processing · Electrical Eng. & Systems 2025-02-04 Hugh Greatorex , Michele Mastella , Ole Richter , Madison Cotteret , Willian Soares Girão , Ella Janotte , Elisabetta Chicca

Event cameras are paradigm-shifting novel sensors that report asynchronous, per-pixel brightness changes called 'events' with unparalleled low latency. This makes them ideal for high speed, high dynamic range scenes where conventional…

Computer Vision and Pattern Recognition · Computer Science 2020-08-25 Timo Stoffregen , Cedric Scheerlinck , Davide Scaramuzza , Tom Drummond , Nick Barnes , Lindsay Kleeman , Robert Mahony

Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Guillermo Gallego , Jon E. A. Lund , Elias Mueggler , Henri Rebecq , Tobi Delbruck , Davide Scaramuzza

In recent decades, visual simultaneous localization and mapping (vSLAM) has gained significant interest in both academia and industry. It estimates camera motion and reconstructs the environment concurrently using visual sensors on a moving…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Kunping Huang , Sen Zhang , Jing Zhang , Dacheng Tao

The rise of new video modalities like virtual reality or autonomous driving has increased the demand for efficient multi-view video compression methods, both in terms of rate-distortion (R-D) performance and in terms of delay and runtime.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Qiqi Hou , Farzad Farhadzadeh , Amir Said , Guillaume Sautiere , Hoang Le
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