基于双重注意力时空图卷积网络的行人轨迹预测
向晓倩,陈璟
Pedestrian trajectory prediction based on dual-attention spatial-temporal graph convolutional network
Xiaoqian XIANG,Jing CHEN
表 3
模型参数和推理时间对比表
Tab.3
Comparison of model parameters and inference time
模型
M
/10
3
t
/s
PITF
[
16
]
360.0
0.1145
PECNET
[
15
]
21.0
0.1376
Social-STGCNN
[
7
]
7.6
0.0020
SGCN
[
8
]
25.0
0.1146
SGCN+NPSN
[
11
]
30.4
0.2349
Graph-TERN
[
21
]
48.5
0.0945
TAtt+SAtt
1.1
—
STGCN+6层TXPCNN
7.7
—
Sampling
5.1
—
本研究模型
13.9
0.0879