Historical context & research account
BigGAN scales GAN training for class-conditioned ImageNet generation and improves image fidelity. It reinforces an observation that recurs in the foundation-model period: model size, data and computational scale can themselves contribute to generative quality. The historical argument concerns this scaling relationship, not an automatic equation of scale with artistic value.
Dates & version record
Date displayed for this node：2018 · Date recorded in the research master：2018
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Original sources & further reading
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Provenance, translation & verification
Archive node #060 · Historical node
Research masters & supplement references · 1
AI Art Genealogy Research Master · p. 19 · 060
Date as recorded: 2018
BigGAN ↗
BigGAN
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Cite this node
ANTI-AI ARCHIVE. BigGAN. Art-history node #060. https://salondesrefuses.cn/en/art-history/060
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