Lozumi/Gym288-skeleton

Gym288-skeleton数据集是一个基于人类骨架的动作识别基准，源自FineGym数据集的Gym288子集。它提供了精确的时序、细粒度的体操动作注释以及从原始视频帧中提取的2D人体姿态序列。该数据集包含288种不同的体操元素，涵盖四个器械：地板练习、平衡木、高低杠和跳马。数据集旨在支持细粒度动作识别、时序损坏或不完整动作建模、基于骨架的表示学习以及物理感知运动理解的研究。

The Gym288-skeleton dataset is a human skeleton-based action recognition benchmark derived from the Gym288 subset of the FineGym dataset. It provides temporally precise, fine-grained annotations of gymnastic actions along with 2D human pose sequences extracted from original video frames. The dataset includes 288 distinct gymnastic elements across four apparatuses: Floor Exercise, Balance Beam, Uneven Bars, and Vault – Women. It is designed to support research in fine-grained action recognition, temporally corrupted or incomplete action modeling, skeleton-based representation learning, and physics-aware motion understanding.