Volleyball is a video action recognition dataset. It has 4830 annotated frames that were handpicked from 55 videos with 9 player action labels and 8 team activity labels. It contains group activity annotations as well as individual activity annotations. Source: https://github.com/mostafa-saad/deep-activity-rec#dataset.
This dataset contains 7 challenging volleyball activity classes annotated in 6 videos from professionals in the Austrian Volley League (season 2011/12). A total of 36178 annotations within 18960 frames are provided along with the HD video files (1920x1080 @25fps, DX50 codec). The seven classes consist of 5 volleyball specific classes ('Serve', 'Reception', 'Setting', 'Attack', 'Block') and 2 more general classes ('Stand', 'Defense/Move').
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in volleyball dataset. Thus, to better analyze group activity, a dataset with untrimmed group activity is desired, so that more challenging tasks can be investigated. Our RIT-18 dataset follows Volleyball dataset , but extends it to the settings with large-scale and long duration. In Volleyball dataset , each clip contains a short dura-
This dataset consists of labelled video clips collected from the live broadcast of the game from the broadcasting medium to classify different scoring activities.
Download the dataset to path deep-activity-rec/volleyball; Same directory structure as given deep-activity-rec/volleyball-simple; Whatever steps/changes you did for ibrahim16-cvpr-simple, do it for ibrahim16-cvpr. Run: examples/deep-activity-rec/ibrahim16-cvpr/script.sh; GPU/CPU note: The script.sh has 2 heavy processing phases that needs CPU.
Volleyball is a video action recognition dataset. It has 4830 annotated frames that were handpicked from 55 videos with 9 player action labels and 8 team activity labels. It contains group activity annotations as well as individual activity annotations.
CVPR 2019 Paper - Learning Actor Relation Graphs for Group Activity Recognition - Group-Activity-Recognition/volleyball.py at master · wjchaoGit/Group-Activity ...
Dataset Examples. In C-Sports dataset, there are 11 sports categories and five collective activity categories. Sports categories are American football, basketball, dodgeball, football, handball, hurling, ice hockey, lacrosse, rugby, volleyball and water polo, whereas five collective activities are gathering, dismissal, passing, attack and wandering .
Volleyball Activity Dataset (2014) Activity recognition dataset capturing professionals of the Austrian Volley League, published in Improved sport activity recognition using spatio-temporal context (DVS'14). PRID 450S. Person Re-Identification dataset published in Mahalanobis Distance Learning for Person Re-Identification (Person Re-Identification, Springer 2014). ICG Lab 6