Accuracy: 96.2
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Group Activity Recognition
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.
<span class="description-source">Source: A Multi-Stream Convolutional Neural Network Framework for Group Activity Recognition </span>
개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.
벤치마크
Papers with Code 아카이브의 데이터셋별 기록 예시입니다. 평가 조건과 지표 방향이 검증되지 않아 순위를 의미하지 않습니다.
Dataset기록된 모델 예시MetricPaperCode
데이터셋
2개논문
Accuracy: 96.5
Accuracy: 89.61
Accuracy: 93.49
Group Activity Recognition Using Joint Learning of Individual Action Recognition and People Grouping
Accuracy: 93.3
Accuracy: 83.75
Accuracy: 91
Accuracy: 93.2
Accuracy: 93.6
Accuracy: 81.2
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