mlsanityData to 14 Oct 2026

StyleGAN3: Generative Networks for Improving the Equivariance of Translation and Rotation

arXiv 2307.03898 ↗First posted 8 Jul 2023cs.CV eess.IVcited by 3

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Abstract (arXiv)

StyleGAN can use style to affect facial posture and identity features, and noise to affect hair, wrinkles, skin color and other details. Among these, the outcomes of the picture processing will vary slightly between different versions of styleGAN. As a result, the comparison of performance differences between styleGAN2 and the two modified versions of styleGAN3 will be the main focus of this study. We used the FFHQ dataset as the dataset and FID, EQ-T, and EQ-R were used to be the assessment of the model. In the end, we discovered that Stylegan3 version is a better generative network to improve the equivariance. Our findings have a positive impact on the creation of animation and videos.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 11 of its 14 references that are in the map. First posted on arXiv 8 Jul 2023.

Builds on

11 of 14 references.

References · 11

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  2. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
  3. 2014Deep Learning Face Attributes in the Wildcited by 3,693
  4. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,588
  5. 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 2,010
  6. 2021Alias-Free Generative Adversarial Networkscited by 1,184
  7. 2017Generative Adversarial Networks: An Overviewcited by 590
  8. 2020StyleGAN2 Distillation for Feed-forward Image Manipulationcited by 78
  9. 2022Third Time's the Charm? Image and Video Editing with StyleGAN3cited by 54
  10. 2022StyleFaceV: Face Video Generation via Decomposing and Recomposing Pretrained StyleGAN3cited by 11
  11. 2022Texture Representation via Analysis and Synthesis with Generative Adversarial Networkscited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 1.

3 papers.

  1. 2024Synthesizing Iris Images using Generative Adversarial Networks: Survey and Comparative Analysiscited by 5
  2. 2025MFFI: Multi-Dimensional Face Forgery Image Dataset for Real-World Scenarioscited by 3
  3. 2026Unleashing MLLMs on the Edge: A Unified Framework for Cross-Modal ReID via Adaptive SVD Distillationcited by 0