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Enhancing interaction recognition: The power of merge-and-split graph convolutional networks

In an advancement for robotics and artificial intelligence, researchers at Chongqing University of Technology, along with their international collaborators, have developed a cutting-edge method for enhancing interaction recognition. .

Shaoqiang wangGraph convolutional network for skeletonSchool of artificial intelligenceUniversity of technologyGraph convolutional networkChongqing universityArtificial intelligenceBionic systemsMerge and split graph convolutional networkMerge and split graph convolutionHierarchical guided attentionShort term dependenceSkeleton based interaction recognition

Revamping Interaction Recognition via Merge-Split Graph Networks

Revamping Interaction Recognition via Merge-Split Graph Networks
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University of technologyGraph convolutional network for skeletonGraph convolutional networkChongqing universityBionic systemsMerge and split graph convolutional networkMerge and split graph convolutionHierarchical guided attentionShort term dependenceSplit graph structureGuided attentionDependence moduleSplit graph convolutional networkSkeleton based interaction recognition