Pose and Facial Expression Transfer by using StyleGAN

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Hauptverfasser: Jahoda, Petr, Cech, Jan
Format: Preprint
Veröffentlicht: 2025
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author Jahoda, Petr
Cech, Jan
author_facet Jahoda, Petr
Cech, Jan
contents We propose a method to transfer pose and expression between face images. Given a source and target face portrait, the model produces an output image in which the pose and expression of the source face image are transferred onto the target identity. The architecture consists of two encoders and a mapping network that projects the two inputs into the latent space of StyleGAN2, which finally generates the output. The training is self-supervised from video sequences of many individuals. Manual labeling is not required. Our model enables the synthesis of random identities with controllable pose and expression. Close-to-real-time performance is achieved.
format Preprint
id arxiv_https___arxiv_org_abs_2504_13021
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Pose and Facial Expression Transfer by using StyleGAN
Jahoda, Petr
Cech, Jan
Computer Vision and Pattern Recognition
Artificial Intelligence
We propose a method to transfer pose and expression between face images. Given a source and target face portrait, the model produces an output image in which the pose and expression of the source face image are transferred onto the target identity. The architecture consists of two encoders and a mapping network that projects the two inputs into the latent space of StyleGAN2, which finally generates the output. The training is self-supervised from video sequences of many individuals. Manual labeling is not required. Our model enables the synthesis of random identities with controllable pose and expression. Close-to-real-time performance is achieved.
title Pose and Facial Expression Transfer by using StyleGAN
topic Computer Vision and Pattern Recognition
Artificial Intelligence
url https://arxiv.org/abs/2504.13021