面向群体活动识别的行动者关系图互学习网络

Zhu Ya Lou, L. Fan, Kuang Ping, Feng Dong
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引用次数: 0

摘要

行动者关系图(ARG)是一种有效的群体行为检测方法,但在某些领域仍有待改进。在本文中,我们提出使用绝对差和(SAD)来计算字符外观的相似性,引入深度相互学习来支持网络的训练,并添加可视化模型。通过对扩展数据集的训练,结果表明改进后的网络可以达到预期的较好的群体活动预测精度。
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Mutual Learning Networks Of Actor Relation Graph For Group Activity Recognition
The Actor Relation Graph (ARG) is an effective method for detecting group behaviour but still needs improvement in some areas. In this paper, we propose using the sum of absolute differences (SAD) to compute the similarity of characters' appearance, introduce deep mutual learning to support the network's training, and add a visualization model. By training with the extended dataset, the results show that our improved network can achieve the expected better prediction accuracy of group activities.
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