24 citations · 28 across the 4 of their papers we have counts for
4 papers
GLAN: A Graph-based Linear Assignment Network
He Liu, Tao Wang, Congyan Lang +3
Differentiable solvers for the linear assignment problem (LAP) have attracted much research attention in recent years, which are usually embedded into learning frameworks as compon…
Deep Probabilistic Graph Matching
He Liu, Tao Wang, Yidong Li +3
Most previous learning-based graph matching algorithms solve the \textit{quadratic assignment problem} (QAP) by dropping one or more of the matching constraints and adopting a rela…
Joint Graph Learning and Matching for Semantic Feature Correspondence
He Liu, Tao Wang, Yidong Li +3
In recent years, powered by the learned discriminative representation via graph neural network (GNN) models, deep graph matching methods have made great progresses in the task of m…
GM-MLIC: Graph Matching based Multi-Label Image Classification
Yanan Wu, He Liu, Songhe Feng +3
Multi-Label Image Classification (MLIC) aims to predict a set of labels that present in an image. The key to deal with such problem is to mine the associations between image conten…