In this work, we propose a novel model with hierarchical spatial reasoning and temporal stack learning network (HSR-TSL) to explore the discriminative spatial and temporal features for human action recognition, which consists of a hierarchical spatial reasoning network (HSRN) and a temporal stack ...
The primary challenge in skeleton-based action recognition lies in the effective capture of spatio-temporal correlations among skeleton joints. However, when the human body interacts with other objects in the background, these spatio-temporal correlations may become less apparent. To tackle this ...
做skeleton based action recognition会用到人体关节的邻接矩阵,之前做skeleton based action recognition基本都是有骨骼相连的关节对才会在邻接矩阵的相应位置标记一个1,没有连接的位置就标记为0,但本文不同,本文考虑到不相连的关节之间的相互关系也是很重要的,比如两只手不是直接相连的,但是两只手的相互位置关系在识别...
读书笔记:Dynamic GCN: Context-enriched Topology Learning for Skeleton-based Action Recognition,程序员大本营,技术文章内容聚合第一站。
论文题目:Multi-scale sampling attention graph convolutional networks for skeleton-based action recognition 作者&团队:Tian H, Zhang Y, Wu H, et al. 1.山东大学机器人控制科学与工程学院中心 2.加利福尼亚大学洛杉矶分校电气与计算机工程系 发表期刊/会议:Neurocomputing ...
A OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis. deep-learningpytorchaction-recognitiongraph-convolutional-networkskeleton-based-action-recognition UpdatedNov 25, 2022 Python Walter0807/MotionBERT ...
论文题目:Spatiotemporal progressive inward-outward aggregation network for skeleton-based action recognition 作者&团队:Yin X, Zhong J, Lian D, et al. 1.广东多媒体信息服务工程技术研究中心,深圳大学 发表期刊/会议:Pattern Recognition 中科院分区:SCI 2区 ...
In the field of skeleton-based action recognition, accurately recognizing human actions is crucial for applications such as virtual reality and motion analysis. However, this task faces challenges such intraindividual action differences and long-term temporal dependencies. To address these challenges, we...
GCN for skeleton-based action recognition 图卷积网络广泛应用于基于骨架的动作识别中,它将人类骨骼序列建模为时空图。ST-GCN是基于GCN的方法的著名baseline,它结合了空间图卷积和交错时间卷积,用于时空建模。在baseline上,adjacency powering用于多尺度建模,而自我注意机制提高了建模能力。尽管GCN在基于骨架的动作识别方面...
MS-AAGCN:Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks,程序员大本营,技术文章内容聚合第一站。