GRB-Sty: Redesign of Generative Residual Block for StyleGAN
We have previously published a paper introducing a novel module, the Generative Residual Block (GRB), which successfully enhances GAN performance. However, the experiments in the earlier paper were conducted on baseline models using spectral normalization, a technique seldom used today. To address t...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-04-01
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| Series: | ICT Express |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405959525000232 |
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| Summary: | We have previously published a paper introducing a novel module, the Generative Residual Block (GRB), which successfully enhances GAN performance. However, the experiments in the earlier paper were conducted on baseline models using spectral normalization, a technique seldom used today. To address this problem, we investigate the effectiveness of GRB on contemporary StyleGAN-based models. This paper introduces an enhanced version of GRB, termed GRB-Sty, which consistently boosts the performance of StyleGAN-based models and demonstrates versatility across various aspects. The significant performance enhancements observed in extensive experiments on multiple benchmark datasets highlight the compatibility of GRB-Sty with state-of-the-art methods. |
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| ISSN: | 2405-9595 |