A versatile HDR video production system

By M. Tocci, C. Kiser, Nora Tocci, Pradeep Sen. ACM Transactions on Graphics, 2011

301 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/ef58787087a634983afdd41e5485cefc51c52e71

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In Computer Vision and Pattern Recognition

Citations in the corpus

Deep high dynamic range imaging of dynamic scenes (2017, methodology): “For example, a few methods use a beam-splitter to split the light to multiple sensors [Tocci et al. 2011; McGuire et al. 2007].”
Robust patch-based hdr reconstruction of dynamic scenes (2012, methodology): “, [Nayar and Mitsunaga 2000; Tocci et al. 2011]), but these devices are typically expensive and are currently unavailable to the general public.”
Deep High Dynamic Range Imaging with Large Foreground Motions (2017, background): “Besides, there are also more expensive solutions that use special devices to capture a higher dynamic range [25, 8, 24] and directly produce HDR images.”
High Dynamic Range Imaging (2015, background): “Following the multi-exposure approach to extending dynamic range, one can capture several exposures per video frame at once using beam splitters, which direct light to multiple sensors [4, 5, 73, 152].”
Deep reverse tone mapping (2017, methodology): “To enable single-shot HDR photography, several devices have been proposed such as cameras with multiple sensors [Kronander et al. 2013; Tocci et al. 2011] and off-the-shelf cameras with coded exposures [Serrano et al. 2016; Zhao et al. 2015].”
HDR image reconstruction from a single exposure using deep CNNs (2017, methodology): “This can be solved by techniques such as multi-sensor imaging [Kronander et al. 2014; Tocci et al. 2011] or by varying the per-pixel exposure [Nayar and Mit-sunaga 2000] or gain [Hajisharif et al. 2015].”