MohamedLotfy989/Group_Activity_Recognition_Volleyball
An implementation of seminal CVPR 2016 paper: "A Hierarchical Deep Temporal Model for Group Activity Recognition."
This tool analyzes volleyball video footage to automatically identify and classify group activities like 'Right set' or 'Left spike,' as well as individual player actions such as 'Blocking' or 'Setting'. It takes raw video or image frames as input and outputs precise labels for what's happening on the court. Sports analysts, coaches, and performance strategists can use this to review game footage without manual tagging.
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Use this if you need to automatically categorize complex team plays and individual actions within volleyball matches from video footage for performance analysis or scouting.
Not ideal if your primary need is general object tracking or activity recognition outside the specific domain of volleyball.
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Language
Python
License
BSD-3-Clause
Category
Last pushed
Feb 15, 2025
Commits (30d)
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