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AVA Video Action Dataset
2D Box
2D Classification
许可协议: Unknown

Overview

The AVA dataset densely annotates 80 atomic visual actions in 57.6k movie clips with actions localized in space and time, resulting in 210k action labels with multiple labels per human occurring frequently. The main differences with existing video datasets are: (1) the definition of atomic visual actions, which avoids collecting data for each and every complex action; (2) precise spatio-temporal annotations with possibly multiple annotations for each human; (3) the use of diverse, realistic video material (movies).

Our goal is to accelerate research on video action recognition. More details about the dataset and initial experiments can be found in our arXiv paper.

数据概要
数据格式
image,
数据量
57.6K
文件大小
--
| 数据量 57.6K | 大小 --
AVA Video Action Dataset
2D Box 2D Classification
许可协议: Unknown

Overview

The AVA dataset densely annotates 80 atomic visual actions in 57.6k movie clips with actions localized in space and time, resulting in 210k action labels with multiple labels per human occurring frequently. The main differences with existing video datasets are: (1) the definition of atomic visual actions, which avoids collecting data for each and every complex action; (2) precise spatio-temporal annotations with possibly multiple annotations for each human; (3) the use of diverse, realistic video material (movies).

Our goal is to accelerate research on video action recognition. More details about the dataset and initial experiments can be found in our arXiv paper.

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