Diverse Image Generation via Self-Conditioned GANs

Figure 1: Our proposed self-conditioned GAN model learns to perform clustering and image synthesis simultaneously. The model training requires no manual annotation of object classes. Here, we visualize several discovered clusters for both Places365 (top) and ImageNet (bottom). For each cluster, we show both real images and the generated samples conditioned on the cluster index.