KA-GCN: Kernel-Attentive Graph Convolutional Network for 3D face analysis
Graph Structure Learning (GSL) methods address the limitations of real-world graphs by refining their structure and representation. This allows Graph Neural Networks (GNNs) to be applied to broader unstructured domains such as 3D face analysis. GSL can be considered as the dynamic learning of connec...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | Array |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590005625000190 |
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