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Aug 31, 2023 · The first attempt to enhance skeleton topologies by graph decomposition. •. The proposed model efficiently refactors out the strong spatiotemporal features.
Jan 27, 2024 · To address this, Yang et al. [128] introduce the Feedback Graph Convolutional Network (FGCN) aimed at incrementally acquiring global spatial-temporal features.
Duration: 35:08
Posted: Nov 11, 2023
Posted: Nov 11, 2023
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Aug 24, 2023 · Finally, we propose Directed Diffusion Graph Convolutional Network (DD-GCN) for action recognition, and the experiments on three public datasets: NTU-RGB+D, NTU ...
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Oct 27, 2023 · Using a Graph convolution network (GCN) for constructing and aggregating node features has been helpful for skeleton-based action recognition.
Dec 1, 2023 · With the development of graph convolutional network (GCN) over the recent years, skeleton-based action recognition has achieved satisfactory results.
Apr 1, 2024 · Abstract. In the field of skeleton-based action recognition, accurately recognizing human actions is crucial for applications such as virtual reality and motion ...
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Duration: 8:25
Posted: Oct 20, 2023
Posted: Oct 20, 2023
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Jun 26, 2024 · In this work, we propose an efficient but strong baseline based on Graph Convolutional Network (GCN), where three main improvements are aggregated, i.e., early ...
Apr 3, 2024 · Graph Convolutional Networks (GCNs) have long set the state-of-the-art in skeleton-based action recognition, leveraging their ability to unravel the complex ...