每一个 ST-Conv Block 是由两个 Gated Temporal Convolution layer 夹着一个 Graph Convolution layer 组成。之所以,TGC 的 channel number 是 64,SGC 的是 16,是因为原作者认为这种「三明治」结构既可以achieve fast spatial-state propagation from graph convolution through temporal convolutions,又可以helps the ...
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting 论文笔记---GCN在交通领域的应用(二) 一、论文翻译: 1、摘要: 及时准确地交通预测对于城市交通控制和指导具有至关重要的意义。由于交通流量的非线性和复杂性,传统的方法不能满足中长期预测任务的需求,并且往往会忽略时...
Eachindicates a frame of current traffic status at time stept, which is recorded in a graph-structured data matrix. Network Structure Fig. 2 Architecture of spatio-temporal graph convolutional networks. The framework STGCN consists of two spatio-temporal convolutional blocks (ST-Conv blocks) and ...
本文详细解析了Spatio-Temporal Graph Convolutional Networks（STGCN）模型，特别是其在交通流量预测领域的应用。首先澄清了STGCN与ST-GCN的区别，指出前者主要针对交通流量预测，而后者则应用于人体骨骼动作识别。模型的核心在于结合Graph Convolution和Gated Causal Convolution，无需依赖于LSTM或GRU进行预测。STG...
Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting总结,程序员大本营,技术文章内容聚合第一站。
最近,graph convolutional networks(GCNs),将 CNN 拓展到了 任意结构的 graphs 上来,已经得到了很大的关注,并且得到了广泛的应用,如:image classification, document classification, and semi-supervised learning. 但是,这些方法都是基于一种 fixed graph 作为输入。将 GCNs 在大型数据集上来建模 dynamic graphs,如:...
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition回到顶部 摘要动态人体骨架模型带有进行动作识别的重要信息,传统的方法通常使用手工特征或者遍历规则对骨架进行建模,从而限制了表达能力并且很难去泛化。作者提出了一个新颖的动态骨架模型ST-GCN,它可以从数据中自动地学习空间和时间的pattern...
Graph attention temporal convolutional network for traffic speed forecasting on road networksTraffic predictiondeep learninggraph attention networktemporal convolutional networkTraffic speed forecasting plays an increasingly essential role in successful intelligent transportation systems. However, this still remains a...
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting Introduction We propose a novel deep learning framework,STGCN, to tackle time series prediction problem in traffic domain. Instead of applying regular convolutional and recurrent units, we formulate the problem...
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition AAAI2018 基于skeleton动作识别的时空图卷积网络 一、主要内容: 动态骨骼形态可以自然地表示为人体关节位置的时间序列,以二维或三维坐标的形式表示。图神经网络(GCNs)将卷积神经网络(CNNs)推广到任意结构的图。本文...G...