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Most novel view synthesis methods -- including Neural Radiance Fields (NeRF) -- struggle to capture the high dynamic range (HDR) radiance required for realistic image-based lighting (IBL). This limitation stems from a reliance on low…

High dynamic range (HDR) imaging enables to immortalize natural scenes similar to the way that they are perceived by human observers. With regular low dynamic range (LDR) capture/display devices, significant details may not be preserved in…

Computer Vision and Pattern Recognition · Computer Science 2021-05-26 Diclehan Karakaya , Oguzhan Ulucan , Mehmet Turkan

Regular cameras and cell phones are able to capture limited luminosity. Thus, in terms of quality, most of the produced images from such devices are not similar to the real world. They are overly dark or too bright, and the details are not…

Computer Vision and Pattern Recognition · Computer Science 2022-12-07 Ali Reza Omrani , Davide Moroni

Capturing images with enough details to solve imaging tasks is a long-standing challenge in imaging, particularly due to the limitations of standard dynamic range (SDR) images which often lose details in underexposed or overexposed regions.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Jingchao Peng , Thomas Bashford-Rogers , Francesco Banterle , Haitao Zhao , Kurt Debattista

Mapping Low Dynamic Range (LDR) images with different exposures to High Dynamic Range (HDR) remains nontrivial and challenging on dynamic scenes due to ghosting caused by object motion or camera jitting. With the success of Deep Neural…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Qingsen Yan , Weiye Chen , Song Zhang , Yu Zhu , Jinqiu Sun , Yanning Zhang

We describe a new method for comparing frame appearance in a frame-to-model 3-D mapping and tracking system using an low dynamic range (LDR) RGB-D camera which is robust to brightness changes caused by auto exposure. It is based on a…

Computer Vision and Pattern Recognition · Computer Science 2016-04-05 Shuda Li , Ankur Handa , Yang Zhang , Andrew Calway

Event cameras provide asynchronous, data-driven measurements of local temporal contrast over a large dynamic range with extremely high temporal resolution. Conventional cameras capture low-frequency reference intensity information. These…

Computer Vision and Pattern Recognition · Computer Science 2018-11-02 Cedric Scheerlinck , Nick Barnes , Robert Mahony

Photographs captured by smartphones and mid-range cameras have limited spatial resolution and dynamic range, with noisy response in underexposed regions and color artefacts in saturated areas. This paper introduces the first approach (to…

Computer Vision and Pattern Recognition · Computer Science 2022-08-01 Bruno Lecouat , Thomas Eboli , Jean Ponce , Julien Mairal

Event cameras asynchronously capture pixel-level intensity changes with extremely low latency. They are increasingly used in conjunction with RGB cameras for a wide range of vision-related applications. However, a major challenge in these…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Pujing Yang , Guangyi Zhang , Yunlong Cai , Lei Yu , Guanding Yu

Outdoor lighting has extremely high dynamic range. This makes the process of capturing outdoor environment maps notoriously challenging since special equipment must be used. In this work, we propose an alternative approach. We first capture…

Computer Vision and Pattern Recognition · Computer Science 2017-11-08 Jinsong Zhang , Jean-François Lalonde

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

Real-time monitoring of high-energy propellant combustion is difficult. Extreme high dynamic range (HDR), microsecond-scale particle motion, and heavy smoke often occur together. These conditions drive saturation, motion blur, and unstable…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Jing Tao , Taihang Lei , Banglei Guan , Ying Qu , Xudong Na , Likun Ma , Yang Shang , Qifeng Yu

High Dynamic Range (HDR) generation remains challenging for generative models, which are largely limited to low dynamic range outputs. Recent diffusionbased approaches approximate HDR by generating multiple exposure-conditioned samples,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Pedram Fekri , WenChen Li , William Chen , Peter Altamirano

Increasing popularity of high-dynamic-range (HDR) image and video content brings the need for metrics that could predict the severity of image impairments as seen on displays of different brightness levels and dynamic range. Such metrics…

Image and Video Processing · Electrical Eng. & Systems 2021-05-12 Aliaksei Mikhailiuk , Maria Perez-Ortiz , Dingcheng Yue , Wilson Suen , Rafal K. Mantiuk

High dynamic range (HDR) imaging involves capturing a series of frames of the same scene, each with different exposure settings, to broaden the dynamic range of light. This can be achieved through burst capturing or using staggered HDR…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Mahmoud Afifi , Zhenhua Hu , Liang Liang

As demand for advanced photographic applications on hand-held devices grows, these electronics require the capture of high quality depth. However, under low-light conditions, most devices still suffer from low imaging quality and inaccurate…

Computer Vision and Pattern Recognition · Computer Science 2018-03-22 Sunghoon Im , Hae-Gon Jeon , In So Kweon

Event cameras output asynchronous events to represent intensity changes with a high temporal resolution, even under extreme lighting conditions. Currently, most of the existing works use a single contrast threshold to estimate the intensity…

Computer Vision and Pattern Recognition · Computer Science 2020-12-18 Ziwei Wang , Yonhon Ng , Pieter van Goor , Robert Mahony

Thanks to High Dynamic Range (HDR) imaging methods, the scope of photography has seen profound changes recently. To be more specific, such methods try to reconstruct the lost luminosity of the real world caused by the limitation of regular…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Ali Reza Omrani , Davide Moroni

High Dynamic Range (HDR) content (i.e., images and videos) has a broad range of applications. However, capturing HDR content from real-world scenes is expensive and time-consuming. Therefore, the challenging task of reconstructing visually…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Hrishav Bakul Barua , Kalin Stefanov , KokSheik Wong , Abhinav Dhall , Ganesh Krishnasamy

This paper describes a physics-based end-to-end software simulation for image systems. We use the software to explore sensors designed to enhance performance in high dynamic range (HDR) environments, such as driving through daytime tunnels…

Computer Vision and Pattern Recognition · Computer Science 2024-08-23 Zhenyi Liu , Devesh Shah , Brian Wandell
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