Identity-preserving face recovery from portraits
Recovering the latent photorealistic faces from their artistic portraits aids human perception and facial analysis. However, a recovery process that can preserve identity is challenging because the fine details of real faces can be distorted or lost in stylized images. In this paper, we present a new Identity-preserving Face Recovery from Portraits (IFRP) to recover latent photorealistic faces from unaligned stylized portraits. Our IFRP method consists of two components: Style Removal Network...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision, WACV 2018|
|01_Shiri_Identity-preserving_face_2018.pdf||776.42 kB||Adobe PDF||Request a copy|
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