StyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation-Reference-Cited by-同舟云学术

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StyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation

Published:2023-10-01 Issue: Volume:27 Page:2184-2194
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
language:
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Author:

Alanov Aibek¹,Titov Vadim¹,Nakhodnov Maksim¹,Vetrov Dmitry²

Affiliation:

1. AIRI

2. HSE University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10376608.pdf?arnumber=10376608

Reference55 articles.

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

2. StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows

3. Neural best-buddies

4. Hyperdomainnet: Universal domain adaptation for generative adversarial networks;Alanov,2022

5. Large scale gan training for high fidelity natural image synthesis;Brock,2018

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Few-shot remote sensing image segmentation based on label propagation and open-set domain adaptation;International Journal of Remote Sensing;2024-08-27

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