What's in a Decade? Transforming Faces Through Time

Autor: Chen, Eric Ming, Sun, Jin, Khandelwal, Apoorv, Lischinski, Dani, Snavely, Noah, Averbuch-Elor, Hadar
Rok vydání: 2023
Předmět:
Zdroj: Computer Graphics Forum. 42:281-291
ISSN: 1467-8659
0167-7055
Popis: How can one visually characterize people in a decade? In this work, we assemble the Faces Through Time dataset, which contains over a thousand portrait images from each decade, spanning the 1880s to the present day. Using our new dataset, we present a framework for resynthesizing portrait images across time, imagining how a portrait taken during a particular decade might have looked like, had it been taken in other decades. Our framework optimizes a family of per-decade generators that reveal subtle changes that differentiate decade--such as different hairstyles or makeup--while maintaining the identity of the input portrait. Experiments show that our method is more effective in resynthesizing portraits across time compared to state-of-the-art image-to-image translation methods, as well as attribute-based and language-guided portrait editing models. Our code and data will be available at https://facesthroughtime.github.io
Comment: Project Page: https://facesthroughtime.github.io
Databáze: OpenAIRE
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