We propose a novel inter-object graph representation for activity recognition based on a disentangled graph embedding with direct observation of edge appearance. In contrast to prior efforts, our approach uses explicit appearance for high order relations derived from object-object interaction, formed ...
Spatio-Temporal Inception Graph Convolutional Networks for Skeleton-Based Action Recognition 时空初始图卷积网络用于基于骨骼的动作识别 CVPR2020 STIGCN 邻接矩阵的拓扑是建模输入骨骼相关性的关键因素。先前方法主要集中于图拓扑的设计/学习。但是一旦了解了拓扑,网络的每一层中将仅存在一个单比例特征和一个转换。已经...
Continual spatio-temporal graph convolutional networks. Pattern Recognition , 2023 , 140: 109528 CrossRef Google Scholar [6] YU B X B, LIU Yan, ZHANG Xiang, et al. Mmnet: A model-based multimodal network for human action recognition in RGB-D videos. IEEE Transactions on Pattern Anal...
ARTICLE HISTORY Received 21 October 2022 Accepted 27 May 2023 KEYWORDS Spatiotemporal graph neural network; prediction models; spatiotemporal graph data 1. Introduction Numerous non-Euclidean data emerge in our daily life from transportation networks to social networks, etc. The graph structure, with ...
In skeleton-based action recognition, graph convolutional networks (GCN) have been applied to extract features based on the dynamic of the human body and the method has achieved excellent results recently. However, GCN-based techniques only focus on the
introduction部分的结构是由大到小,首先说3D action识别很火,不同的提取特征和分类器学习的方法有很多,然后列举一大堆,不过确实是按照特征提取和分类器学习这两个方面介绍的。然后缩小范围,提出RNN,先说RNN的小背景,比如大概是个什么东西,成功的应用到什么方面,然后也成功地用到3D action recognition了。RNN用到3D ...
Graph Convolutional Networks (GCNs) have been widely used in skeleton-based action recognition. Though significant performance has been achieved, it is still challenging to effectively model the complex dynamics of skeleton sequences. A novel position-aware spatio-temporal GCN for skeleton-based action...
The intermittent stay of the signals at a given risk class does not give room for immediate action on the CSG well since it is expected to remain in the severe risk category for a couple of days before the failure can occur. To this end, the operators are expected to start taking ...
Spatio-Temporal Backpropagation for Training High-performance Spiking Neural Networks笔记,程序员大本营,技术文章内容聚合第一站。
Spatio-Temporal Attention Based LSTM Networks for 3D Action Recognition and Detection,程序员大本营,技术文章内容聚合第一站。