https://arxiv.org/abs/2205.13996

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Computer Science > Computer Vision and Pattern Recognition

arXiv:2205.13996 (cs)
[Submitted on 27 May 2022]

Title:Video2StyleGAN: Disentangling Local and Global Variations in a
Video

Authors:Rameen Abdal, Peihao Zhu, Niloy J. Mitra, Peter Wonka
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    Abstract: Image editing using a pretrained StyleGAN generator has
    emerged as a powerful paradigm for facial editing, providing
    disentangled controls over age, expression, illumination, etc.
    However, the approach cannot be directly adopted for video
    manipulations. We hypothesize that the main missing ingredient is
    the lack of fine-grained and disentangled control over face
    location, face pose, and local facial expressions. In this work,
    we demonstrate that such a fine-grained control is indeed
    achievable using pretrained StyleGAN by working across multiple
    (latent) spaces (namely, the positional space, the W+ space, and
    the S space) and combining the optimization results across the
    multiple spaces. Building on this enabling component, we
    introduce Video2StyleGAN that takes a target image and driving
    video(s) to reenact the local and global locations and
    expressions from the driving video in the identity of the target
    image. We evaluate the effectiveness of our method over multiple
    challenging scenarios and demonstrate clear improvements over
    alternative approaches.

Comments: Video : this https URL
Subjects: Computer Vision and Pattern Recognition (cs.CV); Graphics
          (cs.GR)
Cite as:  arXiv:2205.13996 [cs.CV]
          (or arXiv:2205.13996v1 [cs.CV] for this version)
          https://doi.org/10.48550/arXiv.2205.13996
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Rameen Abdal [view email]
[v1] Fri, 27 May 2022 14:18:19 UTC (22,670 KB)
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