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BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations
[article]
2022
Annotating images with pixel-wise labels is a time-consuming and costly process. Recently, DatasetGAN showcased a promising alternative - to synthesize a large labeled dataset via a generative adversarial network (GAN) by exploiting a small set of manually labeled, GAN-generated images. Here, we scale DatasetGAN to ImageNet scale of class diversity. We take image samples from the class-conditional generative model BigGAN trained on ImageNet, and manually annotate 5 images per class, for all 1k
doi:10.48550/arxiv.2201.04684
fatcat:47nypvkkfjgzrifdtvid4zwf5e