Dataset for: Interpretable Performance Modeling in Gymnastics Using Video-Based Pose Estimation

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Authors: Wenjun Hu
Cited by: 0

Abstract

This repository contains the processed datasets and analysis code used in the study “Interpretable performance modeling in gymnastics using video-based pose estimation”.The data include extracted human pose keypoints, derived kinematic features, and scripts for model training and evaluation.Raw video data are not shared due to privacy and ethical considerations.Version noteThis version replaces the previously uploaded raw video files. Raw video data were removed due to privacy and ethical considerations. The updated dataset contains only processed pose keypoints, derived kinematic features, and analysis scripts necessary to reproduce the study findings.

Fields of Study & Subjects

Human Pose and Action Recognition Sports Dynamics and Biomechanics Physical Education and Training Studies

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
9 February 2026
Document type
Dataset