@inproceedings{43dcb8d56fb34bdcbc286f2e097574df,
title = "MoEnlight: Energy-efficient and self-Adaptive Low-light Video Stream Enhancement on Mobile Devices",
abstract = "Camera-equipped devices and deep learning advancements have driven the development of intelligent mobile video apps. These apps require on-device processing of video streams for real-Time, high-quality services while addressing privacy and robustness. However, their performance is limited by low-light conditions and small-Aperture cameras in mobile platforms. Existing low-light video enhancement solutions are unsuitable due to complex models and lack of energy efficiency. We introduce MoEnlight, an energy-conscious system for enhancing low-light video on mobile devices. MoEnlight achieves real-Time enhancement with competitive quality, adapting to dynamic energy budgets. Our experiments demonstrate MoEnlight's superiority over state-of-The-Art solutions for enhancing low-light videos.",
keywords = "energy awareness, low light video enhancement, mobile devices",
author = "Sicong Liu and Xiaochen Li and Zimu Zhou and Bin Guo and Yuan Xu and Zhiwen Yu",
note = "Publisher Copyright: {\textcopyright} 2023 Owner/Author.; 2023 ACM Turing Award Celebration Conference, CHINA 2023 ; Conference date: 28-07-2023 Through 30-07-2023",
year = "2023",
month = jul,
day = "28",
doi = "10.1145/3603165.3607375",
language = "英语",
series = "Proceedings of ACM Turing Award Celebration Conference, CHINA 2023",
publisher = "Association for Computing Machinery, Inc",
pages = "19--20",
booktitle = "Proceedings of ACM Turing Award Celebration Conference, CHINA 2023",
}
