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A Multi-Stream Convolutional Neural Network Framework for Group Activity Recognition
[article]
2018
arXiv
pre-print
In this work, we present a framework based on multi-stream convolutional neural networks (CNNs) for group activity recognition. Streams of CNNs are separately trained on different modalities and their predictions are fused at the end. Each stream has two branches to predict the group activity based on person and scene level representations. A new modality based on the human pose estimation is presented to add extra information to the model. We evaluate our method on the Volleyball and
arXiv:1812.10328v1
fatcat:5yulxfy5tzew5bwvyrnina3d3u