Consistent Multi- and Single-View HDR-Image Reconstruction from Single Exposures
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
We propose a CNN-based approach for reconstructing HDR images from just a single exposure. It predicts the saturated areas of LDR images and then blends the linearized input with the predicted outputs. Two loss functions are used: the Mean Absolute Error and the Multi-Scale Structural Similarity Index. The choice of these loss functions allows us to outperform previous algorithms in the reconstructed dynamic range. Once the network trained, we input multi-view images to it to output multi-view coherent images.
Description
@inproceedings{10.2312:egp.20221004,
booktitle = {Eurographics 2022 - Posters},
editor = {Sauvage, Basile and Hasic-Telalovic, Jasminka},
title = {{Consistent Multi- and Single-View HDR-Image Reconstruction from Single Exposures}},
author = {Mohan, Aditya and Zhang, Jing and Cozot, Rémi and Loscos, Celine},
year = {2022},
publisher = {The Eurographics Association},
ISSN = {1017-4656},
ISBN = {978-3-03868-171-7},
DOI = {10.2312/egp.20221004}
}