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Look globally, age locally: Face aging with an attention mechanism

Abstract: 

Face aging is of great importance for cross-age recognition and entertainment-related applications. Recently, conditional generative adversarial networks (cGANs) have achieved impressive results for facial aging. Existing cGANs-based methods usually require a pixel-wise loss to keep the identity and background consistent. However, minimizing the pixel-wise loss between the input and synthesized images likely resulting in a ghosted or blurry face. To address this deficiency, this paper introduces an Attention Conditional GANs (AcGANs) approach for facial aging, which utilizes attention mechanism to \emph{only} alert the regions relevant to face aging. In doing so, the synthesized face can well preserve the background information and personal identity without using the pixel-wise loss, and the ghost artifacts and blurriness can be significantly reduced. Based on the benchmarked dataset Morph, both qualitative and quantitative experiment results demonstrate superior performance over existing algorithms in terms of image quality, personal identity, and age accuracy. Codes are available on \href{https://github.com/JensonZhu14/AcGAN}{https://github.com/JensonZhu14/AcGAN}.

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1 user has voted: Haiping Zhu

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A presentation slice for the paper ``Look globally, age locally: Face aging with an attention mechanism'', which has been published in ICASSP2020.

Paper Details

Authors:
Submitted On:
15 May 2020 - 9:17pm
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Haiping Zhu
Paper Code:
IVMSP-L6.4
Document Year:
2020
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Document Files

slide_paper5430.pdf

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[1] , "Look globally, age locally: Face aging with an attention mechanism", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5362. Accessed: Oct. 26, 2020.
@article{5362-20,
url = {http://sigport.org/5362},
author = { },
publisher = {IEEE SigPort},
title = {Look globally, age locally: Face aging with an attention mechanism},
year = {2020} }
TY - EJOUR
T1 - Look globally, age locally: Face aging with an attention mechanism
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5362
ER -
. (2020). Look globally, age locally: Face aging with an attention mechanism. IEEE SigPort. http://sigport.org/5362
, 2020. Look globally, age locally: Face aging with an attention mechanism. Available at: http://sigport.org/5362.
. (2020). "Look globally, age locally: Face aging with an attention mechanism." Web.
1. . Look globally, age locally: Face aging with an attention mechanism [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5362