MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulation

MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulation

<jats:p>Recent advances in generative adversarial networks (GANs) have led to remarkable achievements in face image synthesis. While methods that use style-based GANs can generate strikingly photorealistic face images, it is often difficult to control the characteristics of the generated faces...

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Bibliographic Details
Main Authors: Medin, Safa C, Egger, Bernhard, Cherian, Anoop, Wang, Ye, Tenenbaum, Joshua B, Liu, Xiaoming, Marks, Tim K
Other Authors: Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Format: Article
Language:English
Published: Association for the Advancement of Artificial Intelligence (AAAI) 2023
Online Access:https://hdl.handle.net/1721.1/150402

Internet

https://hdl.handle.net/1721.1/150402

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