Rethinking the Graph Polynomial Filter via Positive and Negative Coupling Analysis

no code implementations • 16 Apr 2024 • Haodong Wen, Bodong Du, Ruixun Liu, Deyu Meng, Xiangyong Cao

Subsequently, PNCA is used to analyze the mainstream polynomial filters, and a novel simple basis that decouples the positive and negative activation and fully utilizes graph structure information is designed.

Node Classification

Class Similarity Transition: Decoupling Class Similarities and Imbalance from Generalized Few-shot Segmentation

1 code implementation • 8 Apr 2024 • Shihong Wang, Ruixun Liu, Kaiyu Li, Jiawei Jiang, Xiangyong Cao

This paper focuses on the relevance between base and novel classes, and improves GFSS in two aspects: 1) mining the similarity between base and novel classes to promote the learning of novel classes, and 2) mitigating the class imbalance issue caused by the volume difference between the support set and the training set.