Method · Optimization in a generative latent space
Generative Dataset Distillation
Jovan Cicvarić
University of Tübingen 2023 · first public 2023-01
In one paragraph
Master's thesis on generative dataset distillation by optimizing latent codes of pretrained GANs (StyleGAN2 and StyleGAN-XL) instead of pixels directly, evaluated on ImageNet-1K, CIFAR-10/100 and an imitation-learning driving task; the resulting approach placed second and won a best-paper award in the Generative Track of the 2024 Dataset Distillation Challenge.
Where it sits
- Optimization in a generative latent space (Generative priors)
- Setting: Image classification
- Setting: Other data types
BibTeX (generated; prefer the venue's official entry)
@article{cicvari2023generative,
title = {Generative Dataset Distillation},
author = {Jovan Cicvarić},
journal = {University of Tübingen 2023},
year = {2023}
}Nearby in Optimization in a generative latent space
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