3 accepted papers
Spatio-temporal graph convolutional networks (STGCN) have become popular recently because they can handle structured data with dynamic temporal variations. However, the lack of interpretability limits the potential application of STGCNs. Gradient-based class activation maps (Grad-CAM) are a popular…
Understanding complex hand actions, such as assembly tasks or kitchen activities, from hand skeleton data is an important yet challenging task. In this paper, we analyze hand skeleton-based complex activities by modeling dynamic hand skeletons through a spatiotemporal graph convolutional neural netw…
Analysis of hand skeleton data can be used to understand patterns in manipulation and assembly tasks. This paper introduces a graph-based representation of hand skeleton data and proposes a method to perform unsupervised temporal segmentation of a sequence of sub-tasks in order to evaluate the effic…