CIFAR10

The classes of CIFAR-10, along with 10 random images from each.

The CIFAR-10 [1] dataset consists of 60,000 colour images from 10 different class categories, with 6,000 images per class. Although the spatial size of each image is small (32x32), it is still complex enough to require a large model to generate quality images. In particular, the current state of the art model in Class-conditional Image Generation on CIFAR-10 is StyleGAN2 [2], which contains more than 20 million trainable parameters. More information about the dataset can be found on the official website.

References

[1] Krizhevsky, Alex, and Geoffrey Hinton. "Learning multiple layers of features from tiny images." (2009): 7.

[2] Kang, Minguk, et al. "Rebooting acgan: Auxiliary classifier gans with stable training." Advances in Neural Information Processing Systems 34 (2021): 23505-23518.