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- W2625286981 abstract "Despite significant progress in the development of human action detection datasets and algorithms, no current dataset is representative of real-world aerial view scenarios. We present Okutama-Action, a new video dataset for aerial view concurrent human action detection. It consists of 43 minute-long fully-annotated sequences with 12 action classes. Okutama-Action features many challenges missing in current datasets, including dynamic transition of actions, significant changes in scale and aspect ratio, abrupt camera movement, as well as multi-labeled actors. As a result, our dataset is more challenging than existing ones, and will help push the field forward to enable real-world applications." @default.
- W2625286981 created "2017-06-23" @default.
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- W2625286981 date "2017-07-01" @default.
- W2625286981 modified "2023-10-15" @default.
- W2625286981 title "Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection" @default.
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- W2625286981 doi "https://doi.org/10.1109/cvprw.2017.267" @default.
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