Three Branches: Detecting Actions With Richer Features

08/13/2019

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by   Jin Xia, et al.

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We present our three branch solutions for International Challenge on Activity Recognition at CVPR2019. This model seeks to fuse richer information of global video clip, short human attention and long-term human activity into a unified model. We have participated in two tasks: Task A, the Kinetics challenge and Task B, spatio-temporal action localization challenge. For Kinetics, we achieve 21.59 the test sets, which outperforms all submissions to the AVA challenge at CVPR 2018 for more than 10 activity knowledge, which is a new dataset including key information of human activity.