Mar 17, 2020 · This is the first work that introduces the feedback mechanism into GCNs and action recognition. Compared with conventional GCNs, FGCN has the ...
Nov 24, 2021 · In this paper, we propose a novel network, named Feedback Graph Convolutional Network (FGCN). This is the first work that introduces a feedback ...
Dec 3, 2021 · This is the first work that introduces a feedback mechanism into GCNs for action recognition. Compared with conventional GCNs, FGCN has the ...
Skeleton-based action recognition using a Graph Convolutional Network (GCN) achieved remarkable results by reconstructing a person's skeleton into a graph.
Extensive experiments on three datasets, NTU-RGB+D, NTU-RGB+D120 and Northwestern-UCLA, demonstrate that the proposed FGCN is effective for action recognition.
In this paper, we propose a novel network, named Feedback Graph Convolutional Network (FGCN). This is the first work that introduces the feedback mechanism into ...
Oct 14, 2020 · Abstract:With the advances in capturing 2D or 3D skeleton data, skeleton-based action recognition has received an increasing interest over ...
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People also ask
What are graph convolutional networks used for?
A Graph Convolutional Network, or GCN, is an approach for semi-supervised learning on graph-structured data. It is based on an efficient variant of convolutional neural networks which operate directly on graphs.
What is skeleton-based action recognition?
Skeleton-based Action Recognition is a computer vision task that involves recognizing human actions from a sequence of 3D skeletal joint data captured from sensors such as Microsoft Kinect, Intel RealSense, and wearable devices.
The first attempt to enhance skeleton topologies by graph decomposition. •. The proposed model efficiently refactors out the strong spatiotemporal features.
Nov 17, 2023 · Skeleton-based action recognition methods commonly employ graph neural networks to learn different aspects of skeleton topology information ...
Abstract. Graph convolutional networks (GCNs) have brought considerable improvement to the skeleton-based action recognition task. Existing GCN-based methods ...