태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Group Activity Recognition is a subset of human activity recognition problem which focuses on the collective behavior of a group of people, resulted from the individual actions of the persons and their interactions. Collective activity recognition is a basic task for automatic human behavior analysis in many areas like surveillance or sports videos.
Source: A Multi-Stream Convolutional Neural Network Framework for Group Activity Recognition
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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 Image Source: https://github.com/mostafa-saad/deep-activity-rec#dataset
The Collective Activity Dataset contains 5 different collective activities: crossing, walking, waiting, talking, and queueing and 44 short video sequences some of which were recorded by consumer hand-held digital camera with varying view point. Source: http://vhosts.eecs.umich.edu/vision//activity-dataset.html Image Source: http://vhosts.eecs.umich.edu/vision//activity-dataset.html
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.