Summary of Multi-task Learning For Joint Re-identification, Team Affiliation, and Role Classification For Sports Visual Tracking, by Amir M. Mansourian et al.
Multi-task Learning for Joint Re-identification, Team Affiliation, and Role Classification for Sports Visual Tracking
by Amir M. Mansourian, Vladimir Somers, Christophe De Vleeschouwer, Shohreh Kasaei
First submitted to arxiv on: 18 Jan 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Medium Difficulty summary: This paper proposes a novel multi-purpose part-based person representation method called PRTreID for tracking and re-identifying soccer players in videos. The approach simultaneously performs role classification, team affiliation, and re-identification tasks using a single network trained with multi-task supervision. Unlike previous methods, this joint framework is computationally efficient due to shared backbone architecture and generates richer representations through multi-task learning. The method outperforms existing tracking approaches on the SoccerNet dataset when integrated with a state-of-the-art tracking method and part-based post-processing module for long-term tracking. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Low Difficulty summary: Imagine watching soccer videos and being able to track and identify players easily! This paper develops a new way to do just that, using a special kind of computer vision. The approach is very good at recognizing players and telling them apart from each other, even when they’re wearing the same uniform or partially hidden by other players. It’s also really fast and efficient, making it useful for analyzing large amounts of video data. |
Keywords
» Artificial intelligence » Classification » Multi task » Tracking
