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 数据集系一项面部检测基准数据集，其图像选自于公开可得的 WIDER 数据集。本数据集精选了 32,203 张图像，并对 393,703 张面部进行了标注，这些标注在尺度、姿态和遮挡方面展现出高度的可变性，如样本图像所示。WIDER FACE 数据集按照 61 个事件类别进行组织。对于每个事件类别，我们随机选取 40%、10% 和 50% 的数据作为训练集、验证集和测试集。我们采用了与 PASCAL VOC 数据集相同的评估指标。与 MALF 和 Caltech 数据集类似，我们不对测试图像发布边界框的 ground truth。用户需提交最终的预测文件，我们将据此进行评估。