Throwing4: Phase-Aware Pose Modeling for Throw-Distance Prediction in Elite Athletics
Elite athletics throwing provides a structured biomechanical action sequence together with an objective continuous outcome, namely throw distance, making it a suitable setting for performance-oriented sports analytics. In this work, we investigate whether explicit phase alignment of pose dynamics improves throw-distance prediction under realistic broadcast conditions. To support this study, we curate Throwing4, a dataset of 500 elite throwing clips spanning javelin, discus, hammer, and shot put, with corresponding two-dimensional pose sequences, frame-level phase annotations, and official distance labels. We formulate throw-distance prediction from broadcast-derived pose as a regression p...
| Authors | Bikash Kumar Badatya, Kartike Tiwari, Jyotirmoy Amin et al. |
|---|---|
| Primary category | cs.CV |
| Published | 12 October 2026 |
| Last updated at source | 12 October 2026 |
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