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 ...
PoseConv3D Revisiting Skeleton-based Action Recognition(2022年CVPR)论文地址:arxiv.org/abs/2104.1358一种3D CNN的方式:将关节转化为伪图像,多一个维度,进而进行3D-CNN卷积。基于GCN的方法在以下方面有局限性:(1)鲁棒性(Robustness)。GCN直接使用人体关节坐标,它的识别能力受到坐标分布偏移的显著影响,在使用不同的...
论文题目:Skeleton-based action recognition with multi-stream adaptive graph convolutional networks 作者&团队:Shi L, Zhang Y, Cheng J, et al. 1.中国科学院自动化研究所 2.中国科学院大学人工智能学院 发表期刊/会议:IEEE Transactions on Image Processing 中科院分区:SCI1区 年份、卷号、刊号、页码:2020, ...
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 ...
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...
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...
Skeleton-based action recognition has made great progress recently, but many problems still remain unsolved. For example, the representations of skeleton sequences captured by most of the previous methods lack spatial structure information and detailed temporal dynamics features. In this paper, we propos...
提升了10个点 也可以算是一种对于骨架信息的表示吧 【2017】Skeleton-basedActionRecognitionwithConvolutionalNeuralNetworks...首先,以后可以工作可以考虑一下基于图卷及的行为识别今年很多,且在数据集上性能领先。 如下图所示: 应用场景: 【2019】Skeleton-basedActionRecognitionof ...
Skeleton-Based Action Recognition with Directed Graph Neural Network回到顶部 摘要因为骨架信息可以鲁棒地适应动态环境和复杂的背景,所以经常被广泛应用在动作识别任务上,现有的方法已经证实骨架中的关键点和骨头信息对动作识别任务非常有用。然而如何将两种类型的数据最大化地利用还没有被很好地解决。作者...
skeleton-based action recognition The Skeleton-based Action Recognition Network (SARN) is a deep learning system that uses the body skeleton information of the subject to recognize different human activities. The system uses a Convolutional NeuralNetwork (CNN) to extract spatial and temporal feature ...