VariGAN: Enhancing Image Style Transfer via UNet Generator, Depthwise Discriminator, and LPIPS Loss in Adversarial Learning Framework

Image style transfer is a challenging task that has gained significant attention in recent years due to its growing complexity. Training is typically performed using paradigms offered by GAN-based image style transfer networks. Cycle-based training methods provide an approach for handling unpaired d...

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書誌詳細

出版年:	Sensors
主要な著者:	Dawei Guan, Xinping Lin, Haoyi Zhang, Hang Zhou
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2025-04-01
主題:	style transfer GAN LPIPS UNet ResNet image segmentation
オンライン･アクセス:	https://www.mdpi.com/1424-8220/25/9/2671