Dataset · Hugging Face

WithAnyone/MultiID-Bench

Name: MultiID-Bench
Creator: WithAnyone
License: other
Keywords: task_categories:text-to-image, language:en, license:other, size_categories:n<1K, format:parquet, modality:image, modality:text, library:datasets, library:pandas, library:polars, library:mlcroissant, arxiv:2510.14975, region:us, face-generation, identity-consistent

MultiID-Bench in WithAnyone 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.

View on Hugging FaceReport an issue

Author / organization	WithAnyone
License (as declared)	other
Downloads	284 (as reported by Hugging Face)
Likes	8
Created	13 October 2025
Last updated at source	4 February 2026

face-generationidentity-consistentmulti-personbenchmark

Embed this entry

<iframe src="https://silytics.si/embed/item/ada80d6b-5e67-442b-bf68-b0a0951a458b" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.