Annotated Facial Image Dataset for Nigerian Ethnicity Recognition with Baseline Evaluation

This dataset represents 3,000 annotated facial image samples developed to support fine-grained ethnicity recognition research using deep learning techniques. The dataset supports investigations into facial feature representation learning using CNN-based architectures, attention mechanisms, and metric learning approaches. The underlying dataset represents three major Nigerian ethnic groups: Hausa, Igbo, and Yoruba. The public release provides anonymized image identifiers and corresponding ethnicity annotations organized into training, validation, and test splits. The dataset is designed to facilitate research on discriminative facial representation learning, benchmarking, demographic analysis, and fairness-aware computer vision. Each facial sample is associated with an annotated ethnicity class label for supervised machine learning experiments. Metadata and annotation files are provided to support reproducible research and transparent evaluation. Due to the sensitive biometric nature of facial image data, the original facial images are not released under unrestricted public access. Qualified researchers may request controlled access to the facial images for legitimate academic research purposes. Access requests will be evaluated by the corresponding author and may require completion of a Data Use Agreement. Users must comply with ethical research practices and must not attempt to re-identify individuals or use the dataset for surveillance, discrimination, or other harmful applications.本数据集包含3000份带标注的人脸图像样本，旨在支撑基于深度学习技术的细粒度种族识别研究。该数据集可用于探索基于卷积神经网络（Convolutional Neural Network，CNN）架构、注意力机制以及度量学习方法的人脸特征表示学习。 本数据集涵盖尼日利亚三大主要族群：豪萨族（Hausa）、伊博族（Igbo）和约鲁巴族（Yoruba）。本次公开发布的内容包含匿名化图像标识符与对应种族标注，并划分为训练集、验证集与测试集子集。本数据集旨在推动判别式人脸特征表示学习、基准测试、人口统计分析以及公平感知计算机视觉领域的相关研究。 每份人脸样本均附带标注的种族类别标签，可用于监督式机器学习实验。配套提供元数据与标注文件，以支撑可复现研究与透明化评估。 鉴于人脸图像数据属于敏感生物特征信息，原始人脸图像不支持无限制公开获取。合格研究者可申请受控访问权限以开展合法学术研究。访问申请将由通讯作者进行审核，申请人可能需要签署数据使用协议。使用者必须遵守伦理研究规范，不得尝试重新识别个体，亦不得将本数据集用于监视、歧视或其他有害用途。