SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training?
Hasan Abed Al Kader Hammoud Hani Itani Fabio Pizzati Philip Torr Adel Bibi Bernard Ghanem
We present SynthCLIP, a novel framework for training CLIP models with
entirely synthetic text-image pairs, significantly departing from previous
methods relying on real data. Leveraging recent text-to-image (TTI) generative
networks and large language models (LLM), we are able to generate synthetic
datasets of images and corresponding captions at any scale, with no human
intervention. With training at scale, SynthCLIP achieves performance comparable
to CLIP models trained on real datasets. We also introduce SynthCI-30M, a
purely synthetic dataset comprising 30 million captioned images. Our code,
trained models, and generated data are released at
https://github.com/hammoudhasan/SynthCLIP