论文题目:Skeleton-based action recognitionwithmulti-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, 29...
论文题目: Skeleton-based action recognition via spatial and temporal transformer networks 作者:Plizzari C, Cannici M, Matteucci M. , 期刊:Computer Vision and Image Understanding 影响因子:IF4.5 中科院分区:三区 年份、卷号、刊号、页码:2021, 208: 103219. 研究目标: 近年来,基于骨骼的人体活动识别引起...
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...
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 ...
Action action的动作由FDNet输出 action的定义比较简单: 帧向左移动 帧向右移动 帧保持不动 现在,我们打开看一下FDNet网络的结构 Selection_078.png 上图的执行流程如下 S_b经过一个全连接层得到一段向量 S_a经过3层卷积后,在经过一层全连接层得到另一段向量 ...
Ref: OpenMMTalk #1| Skeleton based action recognition _PoseC3D Ref: 行为识别(action recognition)目前的难点在哪? 行为识别综述 Ref: https://zhuanlan.zhihu.com/p/88945361 2. 行为识别方法 2.1 时空关键点(space-time interest points) 2.2 密集轨迹(dense-trajectories) 2.3 表观和光流并举(two-stream...
The invention relates to a human body skeleton-based action recognition method. The method is characterized by comprising the following basic steps that: step 1, a continuous skeleton data frame sequence of a person who is executing target actions is obtained from a somatosensory device; step 2,...
Current state-of-the-art approaches to skeleton-based action recognition are mostly based on recurrent neural networks (RNN). In this paper, we propose a novel convolutional neural networks (CNN) based framework for both action classification and detection. Raw skeleton coordinates as well as skelet...
In the field of skeleton-based action recognition, ST-GCN has gained popularity because of its strong capability to model graph data and its effective use of prior knowledge regarding human joint connections. However, it faces certain challenges and limitations, such as difficulties in transferring ...
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...