  Human pose estimation has made significant advancement in recent years.
However, the existing datasets are limited in their coverage of pose variety.
In this paper, we introduce a novel benchmark FollowMeUp Sports that makes an
important advance in terms of specific postures, self-occlusion and class
balance, a contribution that we feel is required for future development in
human body models. This comprehensive dataset was collected using an
established taxonomy of over 200 standard workout activities with three
different shot angles. The collected videos cover a wider variety of specific
workout activities than previous datasets including push-up, squat and body
moving near the ground with severe self-occlusion or occluded by some sport
equipment and outfits. Given these rich images, we perform a detailed analysis
of the leading human pose estimation approaches gaining insights for the
success and failures of these methods.
