태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Provided with the timestamp of a boundary inside a video, the machine is required to generate sentences describing the status change at the boundary.
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
The Kinetics dataset is a large-scale, high-quality dataset for human action recognition in videos. The dataset consists of around 500,000 video clips covering 600 human action classes with at least 600 video clips for each action class. Each video clip lasts around 10 seconds and is labeled with a single action class. The videos are collected from YouTube. Source: Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey
Kinetics-GEB+ (Generic Event Boundary Captioning, Grounding and Retrieval) is a dataset that consists of over 170k boundaries associated with captions describing status changes in the generic events in 12K videos.
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.