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---
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license: cc-by-4.0
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task_categories:
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- visual-question-answering
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language:
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- en
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tags:
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- multimodal large language models
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- face perception
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---
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# FaceBench Dataset |
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- **Paper:** https://ieeexplore.ieee.org/document/11092731 |
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- **Repository:** https://github.com/CVI-SZU/FaceBench |
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- **Face-LLaVA:** https://huggingface.co/wxqlab/face-llava-v1.5-13b |
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## Dataset Summary |
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We release the FaceBench dataset, which consists of 49,919 visual question-answering (VQA) pairs for evaluation and 23,841 pairs for fine-tuning. |
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FaceBench is built upon a hierarchical facial attribute structure, which encompasses five views with up to three levels of attributes, totaling over 210 attributes and 700 attribute values. |
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## Dataset Example |
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```json |
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{ |
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"question_id": "beard_q0", |
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"question_type": "TFQ", |
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"image_id": "test-CelebA-HQ-1279.jpg", |
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"text": "Does the person in the image have a beard?", |
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"instruction": "Please directly select the appropriate option from the given choices based on the image.", "options": ["Yes", "No", "Information not visible"], |
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"conditions": {"option Y": ["beard_q1", "beard_q2", "beard_q3", "beard_q4"], "option N": []}, |
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"gt_answer": "Yes", |
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"metadata": {"image_source": "CelebA-HQ", "view": "Appearance", "attribute_level": "level 1"} |
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} |
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``` |
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## Citation |
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``` |
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@inproceedings{wang2025facebench, |
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title={FaceBench: A Multi-View Multi-Level Facial Attribute VQA Dataset for Benchmarking Face Perception MLLMs}, |
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author={Wang, Xiaoqin and Ma, Xusen and Hou, Xianxu and Ding, Meidan and Li, Yudong and Chen, Junliang and Chen, Wenting and Peng, Xiaoyang and Shen, Linlin}, |
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booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference}, |
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pages={9154--9164}, |
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year={2025} |
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} |
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``` |
