ST-TR:基于时空变压器网络的骨架活动识别

上传者: 42162978 | 上传时间: 2022-09-13 08:21:24 | 文件大小: 406.42MB | 文件类型: ZIP
时空变压器网络 介绍 该存储库包含以下论文中介绍的模型的实现: 基于骨架的动作识别的时空图卷积网络,Chiara Plizzari,Marco Cannici,Matteo Matteucci, 空间变压器logits的可视化 热图为25 x 25矩阵,其中每一行和每一列代表身体的关节。 位置(i,j)中的元素表示关节i和关节j之间的相关性,这是由于自我注意引起的。 先决条件 Python3 在所有的图书馆requirements.txt 运行方式 python3 main.py 培训:设置在/config/st_gcn/nturgbd/train.yaml : Training :真 测试:在/config/st_gcn/nturgbd/train.yaml设置: Training :错误 资料产生 我们在三个数据集上进行了实验: NTU-RGB + D 60 , NTU-RG

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