Unlocking Potential of 3D-aware GAN for More Expressive Face Generation-Reference-Cited by-同舟云学术

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Unlocking Potential of 3D-aware GAN for More Expressive Face Generation

Published:2023-06-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 ACM International Conference on Multimedia Retrieval
language:
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Author:

Hwang Juheon¹^ORCID,Kang Jiwoo²^ORCID,Lee Kyoungoh³^ORCID,Lee Sanghoon¹^ORCID

Affiliation:

1. Department of Electrical and Electronic Engineering, Yonsei University, Republic of Korea

2. Division of Artificial Intelligence Engineering, Sookmyung Women's University, Republic of Korea

3. AI Application Section, Electronics and Telecommunications Research Institute, Republic of Korea

Funder

National Research Foundation of Korea (NRF)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3591106.3592273

Reference55 articles.

1. Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?

2. Image2StyleGAN++: How to Edit the Embedded Images?

3. ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement

4. HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing

5. A morphable model for the synthesis of 3D faces

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