HandsOff: Labeled Dataset Generation With No Additional Human Annotations

Understand

Recent work leverages the expressive power of generative adversarial networks (GANs) to generate labeled synthetic datasets.

• These dataset generation methods often require new annotations of synthetic images, which forces practitioners to seek out annotators, curate a set of synthetic images, and ensure the quality of generated labels.
• We introduce the HandsOff framework, a technique capable of producing an unlimited number of synthetic images and corresponding labels after being trained on less than 50 pre-existing labeled images.
• Our framework avoids the practical drawbacks of prior work by unifying the field of GAN inversion with dataset generation.