期刊
2018 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2018)
卷 -, 期 -, 页码 1615-1622出版社
IEEE
DOI: 10.1109/WACV.2018.00180
关键词
-
资金
- ERC Starting Grant ARCA [677650]
- European Research Council (ERC) [677650] Funding Source: European Research Council (ERC)
A group of persons can be analyzed at various semantic levels such as individual actions, their interactions, and the activity of the entire group. In this paper, we propose a structural recurrent neural network (SRNN) that uses a series of interconnected RNNs to jointly capture the actions of individuals, their interactions, as well as the group activity. While previous structural recurrent neural networks assumed that the number of nodes and edges is constant, we use a grid pooling layer to address the fact that the number of individuals in a group can vary. We evaluate two variants of the structural recurrent neural network on the Volleyball Dataset.
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