WIDER FACE

WIDER FACE dataset is a face detection benchmark dataset, of which images are selected from the publicly available WIDER dataset. We choose 32,203 images and label 393,703 faces with a high degree of variability in scale, pose and occlusion as depicted in the sample images. WIDER FACE dataset is organized based on 61 event classes. For each event class, we randomly select 40%/10%/50% data as training, validation and testing sets. We adopt the same evaluation metric employed in the PASCAL VOC dataset. Similar to MALF and Caltech datasets, we do not release bounding box ground truth for the test images. Users are required to submit final prediction files, which we shall proceed to evaluate.

WIDER FACE 数据集是一款人脸检测基准数据集，其图像均取自公开可获取的WIDER数据集。我们从中选取了32203张图像，并为393703张人脸进行了标注，这些人脸的尺度、姿态与遮挡情况均存在高度多样性，正如示例图像中所呈现的那样。WIDER FACE 数据集按照61个事件类别进行划分与组织，针对每个事件类别，我们随机将其数据按40%、10%、50%的比例划分为训练集、验证集与测试集。我们采用了与帕斯卡VOC（PASCAL VOC）数据集一致的评估指标。与MALF数据集和Caltech数据集类似，我们未公开测试集图像的边界框真值（ground truth）。用户需提交最终的预测结果文件，我们将据此开展统一评估。

搜集汇总

背景与挑战

背景概述

WIDER FACE是一个用于人脸检测的基准数据集，选自WIDER数据集，包含32,203张图像和393,703个标注人脸，具有尺度、姿态和遮挡的高度可变性。该数据集基于61个事件类别组织，划分为训练、验证和测试集，采用PASCAL VOC的评估指标，且测试集的真实边界框不公开，用户需提交预测文件以进行评估。