Gaussian correction for Adversarial learning of Boundaries

Chaturvedi, Iti, Chen, Qian, Welsch, Roy E., Thapa, Kishor, and Cambria, Erik (2022) Gaussian correction for Adversarial learning of Boundaries. Signal Processing-Image Communication, 109. 116841.

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Social networking sites often monitor the response to brands, events and activities during personal chats or videos. Here, the facial expression of the speaker can be used for automatic ranking of products. However, manual classification of videos puts the identity of the speaker at risk. There is imminent danger of fake videos circulating that are generated using style transfer. In this paper, we target both these challenges by using an adversarial model that can segment a face from the background scenery and occlusions. The segmentation for a fake video will be of poor quality compared to a real video. Previous segmentation models could only be trained on a few objects and failed on scenic images with occlusions. Here we propose an image translator that learns the boundaries of objects during training using Gaussian correction. To determine the parameters of the Gaussian distribution we make use of a Lyapunov candidate function that converges to a global maximum. We apply the model to segmentation of faces and cars in photos. We also apply it to the task of style transfer to the background without affecting the foreground object. The proposed method outperforms baselines by over 20% on segmentation metrics such as IoU and BFScore.

Item ID: 75922
Item Type: Article (Research - C1)
ISSN: 0923-5965
Keywords: Face expressions; Image segmentation; Discriminator loss; Gaussian correction
Copyright Information: Crown Copyright © 2022 Published by Elsevier B.V. All rights reserved.
Date Deposited: 05 Sep 2022 02:31
FoR Codes: 46 INFORMATION AND COMPUTING SCIENCES > 4603 Computer vision and multimedia computation > 460306 Image processing @ 40%
49 MATHEMATICAL SCIENCES > 4903 Numerical and computational mathematics > 490304 Optimisation @ 30%
49 MATHEMATICAL SCIENCES > 4901 Applied mathematics > 490105 Dynamical systems in applications @ 30%
SEO Codes: 22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220403 Artificial intelligence @ 40%
22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220408 Information systems @ 30%
28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences @ 30%
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