AGORA is a synthetic human dataset with high realism and accurate ground truth. It consists of around 14K training and 3K test images by rendering between 5 and 15 people per image using either image-based lighting or rendered 3D environments, taking care to make the images physically plausible and photoreal. In total, AGORA contains 173K individual person crops. AGORA provides (1) SMPL/SMPL-X parameters and (2) segmentation masks for each subject in images.
Relative Human (RH) contains multi-person in-the-wild RGB images with rich human annotations, including: Depth layers: relative depth relationship/ordering between all people in the image. Age group classfication: adults, teenagers, kids, babies. Others: Genders, Bounding box, 2D pose.