An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement
CC BY
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Định dạng: | Sách |
Ngôn ngữ: | English |
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Springer
2023
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Truy cập trực tuyến: | https://link.springer.com/article/10.1007/s11263-022-01735-0 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7394 |
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oai:localhost:PNK-73942023-03-31T07:57:47Z An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement Dario, Fuoli Zhiwu, Huang Danda Pani, Paudel Video enhancement spatio-temporal domain CC BY Video enhancement is a challenging problem, more than that of stills, mainly due to high computational cost, larger data volumes and the difficulty of achieving consistency in the spatio-temporal domain. In practice, these challenges are often coupled with the lack of example pairs, which inhibits the application of supervised learning strategies. To address these challenges, we propose an efficient adversarial video enhancement framework that learns directly from unpaired video examples. In particular, our framework introduces new recurrent cells that consist of interleaved local and global modules for implicit integration of spatial and temporal information. 2023-03-31T07:57:47Z 2023-03-31T07:57:47Z 2023 Book https://link.springer.com/article/10.1007/s11263-022-01735-0 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7394 en application/pdf Springer |
institution |
Digital Phenikaa |
collection |
Digital Phenikaa |
language |
English |
topic |
Video enhancement spatio-temporal domain |
spellingShingle |
Video enhancement spatio-temporal domain Dario, Fuoli Zhiwu, Huang Danda Pani, Paudel An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement |
description |
CC BY |
format |
Book |
author |
Dario, Fuoli Zhiwu, Huang Danda Pani, Paudel |
author_facet |
Dario, Fuoli Zhiwu, Huang Danda Pani, Paudel |
author_sort |
Dario, Fuoli |
title |
An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement |
title_short |
An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement |
title_full |
An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement |
title_fullStr |
An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement |
title_full_unstemmed |
An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement |
title_sort |
efficient recurrent adversarial framework for unsupervised real-time video enhancement |
publisher |
Springer |
publishDate |
2023 |
url |
https://link.springer.com/article/10.1007/s11263-022-01735-0 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7394 |
_version_ |
1761912527259697152 |
score |
8.891787 |