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AnimalFace StyleGAN2-ADA

Progress in GANs has enabled the generation of high-res-olution photorealistic images of astonishing quality. StyleGANs allow for compelling attribute modification on such images via mathematical operations on the latent style vectors in the W/W+ space that effectively modulate the rich hierarchical representations of the generator.

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Cite this as

Tejan Karmali, Rishubh Parihar, Susmit Agrawal, Harsh Rangwani, Varun Jampani, Maneesh Singh, R. Venkatesh Babu (2024). Dataset: AnimalFace StyleGAN2-ADA. https://doi.org/10.57702/ihwjxkp6

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Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Author	Tejan Karmali
More Authors	Rishubh Parihar Susmit Agrawal Harsh Rangwani Varun Jampani Maneesh Singh R. Venkatesh Babu
Homepage	https://github.com/tejan-karmali/AnimalFace-StyleGAN2-ADA