Explorable tone mapping operators

Chien Chuan Su*, Ren Wang, Hung Jin Lin, Yu Lun Liu, Chia Ping Chen, Yu Lin Chang, Soo Chang Pei*

*此作品的通信作者

研究成果: Conference contribution同行評審

7 引文 斯高帕斯(Scopus)

摘要

Tone-mapping plays an essential role in high dynamic range (HDR) imaging. It aims to preserve visual information of HDR images in a medium with a limited dynamic range. Although many works have been proposed to provide tone-mapped results from HDR images, most of them can only perform tone-mapping in a single pre-designed way. However, the subjectivity of tone-mapping quality varies from person to person, and the preference of tone-mapping style also differs from application to application. In this paper, a learning-based multimodal tone-mapping method is proposed, which not only achieves excellent visual quality but also explores the style diversity. Based on the framework of BicycleGAN [1], the proposed method can provide a variety of expert-level tone-mapped results by manipulating different latent codes. Finally, we show that the proposed method performs favorably against state-of-the-art tone-mapping algorithms both quantitatively and qualitatively.

原文English
主出版物標題Proceedings of ICPR 2020 - 25th International Conference on Pattern Recognition
發行者Institute of Electrical and Electronics Engineers Inc.
頁面10320-10326
頁數7
ISBN(電子)9781728188089
DOIs
出版狀態Published - 2020
事件25th International Conference on Pattern Recognition, ICPR 2020 - Virtual, Milan, Italy
持續時間: 10 1月 202115 1月 2021

出版系列

名字Proceedings - International Conference on Pattern Recognition
ISSN(列印)1051-4651

Conference

Conference25th International Conference on Pattern Recognition, ICPR 2020
國家/地區Italy
城市Virtual, Milan
期間10/01/2115/01/21

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