Digi2Real

a synthetic face dataset containing images of 20,000 unique synthetic identities

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Description

Digi2Real is a synthetic face dataset containing images of 20,000 unique synthetic identities. We introduce a novel framework for realism transfer, designed to enhance the realism of synthetically generated face images. This framework is applied to a subset of the DigiFace dataset to produce photorealistic images, which are more effective for training face recognition models than the original DigiFace dataset. By combining the controllable features of the graphics pipeline with our realism enhancement technique, we present a new approach for creating attribute-controllable face recognition datasets.

 

License

Digi2Real dataset is published for non-commercial research use only, please check the license agreement.

 

Reference

If you use this dataset, please cite the following publication:

 @article{george2024digi2real,
          title={Digi2Real: Bridging the Realism Gap in Synthetic Data Face Recognition via Foundation Models}, 
          author={Anjith George and Sebastien Marcel},
          year={2024},
          eprint={2411.02188},
          url={https://arxiv.org/abs/2411.02188}, }