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GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks

Facial landmarks constitute the most compressed representation of faces and are known to preserve information such as pose, gender and facial structure present in the faces.

Data and Resources

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Cite this as

Xing Di, Vishwanath A. Sindagi, Vishal M. Patel (2024). Dataset: GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks. https://doi.org/10.57702/dccaxfik

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It is available for use in manuscripts, and will be published when the Dataset is made public.

Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Author	Xing Di
More Authors	Vishwanath A. Sindagi Vishal M. Patel
Homepage	https://github.com/DetionDX/GP-GAN-Gender-Preserving-GAN-for-Synthesizing-Faces-from-Landmarks