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One of the most successful approaches to modern high quality HDR-video capture is to use camera setups with multiple sensors imaging the scene through a common optical system. However, such systems pose several challenges for HDR…

Computer Vision and Pattern Recognition · Computer Science 2013-08-23 Joel Kronander , Stefan Gustavson , Gerhard Bonnet , Anders Ynnerman , Jonas Unger

Event cameras are novel sensors that output 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 dynamic range (HDR),…

Computer Vision and Pattern Recognition · Computer Science 2020-04-02 Daniel Gehrig , Mathias Gehrig , Javier Hidalgo-Carrió , Davide Scaramuzza

High dynamic range (HDR) image synthesis from multiple low dynamic range (LDR) exposures continues to be actively researched. The extension to HDR video synthesis is a topic of significant current interest due to potential cost benefits.…

Computer Vision and Pattern Recognition · Computer Science 2017-04-05 Yuelong Li , Chul Lee , Vishal Monga

Camera sensors can only capture a limited range of luminance simultaneously, and in order to create high dynamic range (HDR) images a set of different exposures are typically combined. In this paper we address the problem of predicting…

Computer Vision and Pattern Recognition · Computer Science 2017-11-28 Gabriel Eilertsen , Joel Kronander , Gyorgy Denes , Rafał K. Mantiuk , Jonas Unger

High dynamic range (HDR) imaging is of fundamental importance in modern digital photography pipelines and used to produce a high-quality photograph with well exposed regions despite varying illumination across the image. This is typically…

Image and Video Processing · Electrical Eng. & Systems 2024-07-24 Sibi Catley-Chandar , Thomas Tanay , Lucas Vandroux , Aleš Leonardis , Gregory Slabaugh , Eduardo Pérez-Pellitero

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

Event cameras or neuromorphic cameras mimic the human perception system as they measure the per-pixel intensity change rather than the actual intensity level. In contrast to traditional cameras, such cameras capture new information about…

Computer Vision and Pattern Recognition · Computer Science 2016-08-05 Christian Reinbacher , Gottfried Graber , Thomas Pock

High dynamic range (HDR) images capture much more intensity levels than standard ones. Current methods predominantly generate HDR images from 8-bit low dynamic range (LDR) sRGB images that have been degraded by the camera processing…

Image and Video Processing · Electrical Eng. & Systems 2023-09-06 Yunhao Zou , Chenggang Yan , Ying Fu

This paper presents a robust approach for a visual parallel tracking and mapping (PTAM) system that excels in challenging environments. Our proposed method combines the strengths of heterogeneous multi-modal visual sensors, including stereo…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Abanob Soliman , Fabien Bonardi , Désiré Sidibé , Samia Bouchafa

Event cameras triggered a paradigm shift in the computer vision community delineated by their asynchronous nature, low latency, and high dynamic range. Calibration of event cameras is always essential to account for the sensor intrinsic…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Mohammed Salah , Abdulla Ayyad , Muhammad Humais , Daniel Gehrig , Abdelqader Abusafieh , Lakmal Seneviratne , Davide Scaramuzza , Yahya Zweiri

Event cameras sense intensity changes and have many advantages over conventional cameras. To take advantage of event cameras, some methods have been proposed to reconstruct intensity images from event streams. However, the outputs are still…

Computer Vision and Pattern Recognition · Computer Science 2020-03-18 Lin Wang , Tae-Kyun Kim , Kuk-Jin Yoon

Reconstructing an intensity image from the events of a moving event camera is a challenging task that is typically approached with neural networks deployed on graphics processing units. This paper presents a much simpler, FIlter Based…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Bernd Pfrommer

The fusion of sensor data is essential for a robust perception of the environment in autonomous driving. Learning-based fusion approaches mainly use feature-level fusion to achieve high performance, but their complexity and hardware…

Robotics · Computer Science 2025-06-04 Timo Osterburg , Franz Albers , Christopher Diehl , Rajesh Pushparaj , Torsten Bertram

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 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

Long-term inertial navigation is currently limited by the bias drifts of gyroscopes and accelerometers and ultra-stable cold-atom interferometers offer a promising alternative for the next generation of high-end navigation systems. Here, we…

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

Digital imaging aims to replicate realistic scenes, but Low Dynamic Range (LDR) cameras cannot represent the wide dynamic range of real scenes, resulting in under-/overexposed images. This paper presents a deep learning-based approach for…

Computer Vision and Pattern Recognition · Computer Science 2023-07-07 Dwip Dalal , Gautam Vashishtha , Prajwal Singh , Shanmuganathan Raman

Event cameras are novel vision sensors that report per-pixel brightness changes as a stream of asynchronous "events". They offer significant advantages compared to standard cameras due to their high temporal resolution, high dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2021-02-19 Daniel Gehrig , Michelle Rüegg , Mathias Gehrig , Javier Hidalgo Carrio , Davide Scaramuzza

There are shadow and highlight regions in a low dynamic range (LDR) image which is captured from a high dynamic range (HDR) scene. It is an ill-posed problem to restore the saturated regions of the LDR image. In this paper, the saturated…

Computer Vision and Pattern Recognition · Computer Science 2021-11-16 Chaobing Zheng , Zhengguo Li , Shiqian Wu