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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

Event vision sensors (neuromorphic cameras) output sparse, asynchronous ON/OFF events triggered by log-intensity threshold crossings, enabling microsecond-scale sensing with high dynamic range and low data bandwidth. As a nonlinear system,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Nimrod Kruger , Nicholas Owen Ralph , Gregory Cohen , Paul Hurley

Reconstruction of high-quality HDR images is at the core of modern computational photography. Significant progress has been made with multi-frame HDR reconstruction methods, producing high-resolution, rich and accurate color reconstructions…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Richard Shaw , Sibi Catley-Chandar , Ales Leonardis , Eduardo Perez-Pellitero

Optical flow computation with frame-based cameras provides high accuracy but the speed is limited either by the model size of the algorithm or by the frame rate of the camera. This makes it inadequate for high-speed applications. Event…

Computer Vision and Pattern Recognition · Computer Science 2022-07-25 Ashwin Sanjay Lele , Arijit Raychowdhury

Radiance of real-world scenes typically spans a much wider dynamic range than what standard cameras can capture. While conventional HDR methods merge alternating-exposure frames, these approaches are inherently constrained to 2D pixel-level…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Shin Dong-Yeon , Kim Jun-Seong , Kwon Byung-Ki , Tae-Hyun Oh

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

The strong temporal consistency of surveillance video enables compelling compression performance with traditional methods, but downstream vision applications operate on decoded image frames with a high data rate. Since it is not…

Multimedia · Computer Science 2024-02-09 Andrew C. Freeman , Ketan Mayer-Patel , Montek Singh

Event camera sensors are bio-inspired sensors which asynchronously capture per-pixel brightness changes and output a stream of events encoding the polarity, location and time of these changes. These systems are witnessing rapid advancements…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Aupendu Kar , Vishnu Raj , Guan-Ming Su

Standard frame-based cameras that sample light intensity frames are heavily impacted by motion blur for high-speed motion and fail to perceive scene accurately when the dynamic range is high. Event-based cameras, on the other hand, overcome…

Computer Vision and Pattern Recognition · Computer Science 2021-03-22 Chankyu Lee , Adarsh Kumar Kosta , Kaushik Roy

High-speed vision sensing is essential for real-time perception in applications such as robotics, autonomous vehicles, and industrial automation. Traditional frame-based vision systems suffer from motion blur, high latency, and redundant…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Riadul Islam , Joey Mulé , Dhandeep Challagundla , Shahmir Rizvi , Sean Carson

High Dynamic Range (HDR) video acquisition using the alternating exposure (AE) paradigm has garnered significant attention due to its cost-effectiveness with a single consumer camera. However, despite progress driven by deep neural…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Qianyu Zhang , Bolun Zheng , Lingyu Zhu , Hangjia Pan , Zunjie Zhu , Zongpeng Li , Shiqi Wang

This paper proposes the first non-flow-based deep framework for high dynamic range (HDR) imaging of dynamic scenes with large-scale foreground motions. In state-of-the-art deep HDR imaging, input images are first aligned using optical flows…

Computer Vision and Pattern Recognition · Computer Science 2018-07-25 Shangzhe Wu , Jiarui Xu , Yu-Wing Tai , Chi-Keung Tang

High dynamic range (HDR) imaging is an important task in image processing that aims to generate well-exposed images in scenes with varying illumination. Although existing multi-exposure fusion methods have achieved impressive results,…

Computer Vision and Pattern Recognition · Computer Science 2023-05-30 Jun Xiao , Qian Ye , Tianshan Liu , Cong Zhang , Kin-Man Lam

It is difficult to recover the motion field from a real-world footage given a mixture of camera shake and other photometric effects. In this paper we propose a hybrid framework by interleaving a Convolutional Neural Network (CNN) and a…

Computer Vision and Pattern Recognition · Computer Science 2017-04-20 Wenbin Li , Da Chen , Zhihan Lv , Yan Yan , Darren Cosker

Event cameras are bio-inspired sensors that respond to per-pixel brightness changes in the form of asynchronous and sparse "events". Recently, pattern recognition algorithms, such as learning-based methods, have made significant progress…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Nico Messikommer , Daniel Gehrig , Antonio Loquercio , Davide Scaramuzza

Event cameras are novel sensors that report 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 temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-06-19 Henri Rebecq , René Ranftl , Vladlen Koltun , Davide Scaramuzza

High dynamic range (HDR) imaging combines multiple images with different exposure times into a single high-quality image. The image signal processing pipeline (ISP) is a core component in digital cameras to perform these operations. It…

Image and Video Processing · Electrical Eng. & Systems 2021-10-05 Prashant Chaudhari , Franziska Schirrmacher , Andreas Maier , Christian Riess , Thomas Köhler

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

Light field cameras have been proved to be powerful tools for 3D reconstruction and virtual reality applications. However, the limited resolution of light field images brings a lot of difficulties for further information display and…

Image and Video Processing · Electrical Eng. & Systems 2020-08-27 Qingyan Sun , Shuo Zhang , Song Chang , Lixi Zhu , Youfang Lin

Event-based cameras are vision devices that transmit only brightness changes with low latency and ultra-low power consumption. Such characteristics make event-based cameras attractive in the field of localization and object tracking in…

Computer Vision and Pattern Recognition · Computer Science 2020-10-30 Sherif A. S. Mohamed , Jawad N. Yasin , Mohammad-hashem Haghbayan , Antonio Miele , Jukka Heikkonen , Hannu Tenhunen , Juha Plosila