> The selfie dataset contains 46,836 selfie images annotated with 36 different attributes. We only use photos of females as training data and test data. The size of the training dataset is 3400,and that of the test dataset is 100, with the image size of 256 x 256. The size of the training dataset is 3400,and that of the test dataset is 100, with the image size of 256 x 256. For the anime dataset, we havefirstly retrieved 69,926 animation character images from Anime-Planet1. Among those images,27,023 face images are extracted by using an anime-face detector2.
These seem tiny, don't NNs need more samples to achieve decent quality?
The CycleGAN datasets [1] all have less than 10k images. The two largest have 10,345 images and 5,129 images, the rest (like the famous horses2zebras) have less than 3k.
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> The selfie dataset contains 46,836 selfie images annotated with 36 different attributes. We only use photos of females as training data and test data. The size of the training dataset is 3400,and that of the test dataset is 100, with the image size of 256 x 256. The size of the training dataset is 3400,and that of the test dataset is 100, with the image size of 256 x 256. For the anime dataset, we havefirstly retrieved 69,926 animation character images from Anime-Planet1. Among those images,27,023 face images are extracted by using an anime-face detector2.
These seem tiny, don't NNs need more samples to achieve decent quality?
The CycleGAN datasets [1] all have less than 10k images. The two largest have 10,345 images and 5,129 images, the rest (like the famous horses2zebras) have less than 3k.
[1] https://github.com/junyanz/CycleGAN#datasets