This repository contains a curated list of GAN training datasets.
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Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, consists of 70,000 high-quality PNG images at 1024×1024 resolution and contains considerable variation in terms of age, ethnicity and image background.
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The non-hair-FFHQ dataset is a high-quality image dataset that contains 6,000 non-hair FFHQ portraits, based on stylegan2-ada and ffhq-dataset.
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CelebFaces Attributes Dataset (CelebA) is a large-scale face attributes dataset with more than 200K celebrity images, each with 40 attribute annotations.
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CelebAMask-HQ is a large-scale face image dataset that has 30,000 high-resolution face images selected from the CelebA dataset by following CelebA-HQ. The masks of CelebAMask-HQ were manually-annotated with the size of 512 x 512 and 19 classes including all facial components and accessories such as skin, nose, eyes, eyebrows, ears, mouth, lip, hair, hat, eyeglass, earring, necklace, neck, and cloth.
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MetFaces is an image dataset of human faces extracted from works of art. The dataset consists of 1336 high-quality PNG images at 1024×1024 resolution.
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Artstation-Artistic-face-HQ (AAHQ) is a high-quality image dataset of artistic-face images. The dataset consists of about 25,000 high-quality artistic images collected from the "portraits" channel of Artstation. It offers a lot of variety in terms of painting styles, color tones and face attributes.
