CalTennis is a large-scale video benchmark designed for evaluating monocular-to-3D human pose estimation in the wild.
The dataset comprises over 11 million frames (51 hours) of tennis practice and match play from 40 players, captured with 2–6 synchronized cameras at 60Hz. It is 10x larger than existing in-the-wild human motion video datasets and offers the first large-scale benchmark for synchronized multi-view recordings of expert… See the full description on the dataset page:
https://huggingface.co/datasets/demalenk/caltennis.
