Parameter and Data Efficient Spectral Style-DCGAN
Aryan Garg
2024 Poster
in
Affinity Event: Tiny Papers Poster Session 3
in
Affinity Event: Tiny Papers Poster Session 3
Abstract
We present a simple, highly parameter, and data-efficient adversarial network for unconditional face generation. Our method: Spectral Style-DCGAN or SSD utilizes only 6.574 million parameters and 4739 dog faces from the Animal Faces HQ (AFHQ) dataset as training samples while preserving fidelity at low resolutions up to 64x64. Code available at Anonymous-repo.
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