Funtion/CrowdHuman

CrowdHuman是一个基准数据集，旨在更好地评估在拥挤场景中的检测器。该数据集规模大、标注丰富且多样性高。CrowdHuman包含15000张训练图像、4370张验证图像和5000张测试图像。训练和验证子集共有470K个人类实例，平均每张图像有23人，数据集中包含各种遮挡情况。每个人类实例都标注了头部边界框、人体可见区域边界框和人体全身边界框。我们希望该数据集能作为坚实基础，并促进未来在人类检测任务中的研究。

CrowdHuman is a benchmark dataset to better evaluate detectors in crowd scenarios. The CrowdHuman dataset is large, rich-annotated and contains high diversity. CrowdHuman contains 15000, 4370 and 5000 images for training, validation, and testing, respectively. There are a total of 470K human instances from train and validation subsets and 23 persons per image, with various kinds of occlusions in the dataset. Each human instance is annotated with a head bounding-box, human visible-region bounding-box and human full-body bounding-box. We hope our dataset will serve as a solid baseline and help promote future research in human detection tasks.