The MultiID-Bench dataset is a benchmark introduced in the paper WithAnyone: Towards Controllable and ID Consistent Image Generation. It is specifically tailored for multi-person scenarios in text-to-image research, providing diverse references for each identity. This dataset aims to quantify "copy-paste" artifacts and evaluate the trade-off between identity fidelity and variation, enabling models like WithAnyone to achieve controllable and… See the full description on the dataset page:
https://huggingface.co/datasets/WithAnyone/MultiID-Bench.
