Methods › Computer Vision › Generative Models › Vision-aided GAN
Vision-aided GAN
Introduced by Nupur Kumari et al. in Ensembling Off-the-shelf Models for GAN Training
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Vision-aided GAN training involves using pretrained computer vision models in an ensemble of discriminators to improve GAN performance. Linear separability between real and fake samples in pretrained model embeddings is used as a measure to choose the most accurate pretrained models for a dataset.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Ensembling Off-the-shelf Models for GAN Training 16 Dec 2021 · 1 repository · arXiv:2112.09130Syntology ran 9 of 15 samples · 6 unverified
Tasks archive 2025-07-28
1 task the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Image Generation | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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