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. The study, published in Cyborg and Bionic Systems, introduces the Merge-and-Split Graph Convolutional Network (MS-GCN), a novel approach specifically designed to address the complexities of skeleton-based interaction recognition.