143 citations · 167 across the 8 of their papers we have counts for
9 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…
MSO: Multi-Feature Space Joint Optimization Network for RGB-Infrared Person Re-Identification
Yajun Gao, Tengfei Liang, Yi Jin +4
The RGB-infrared cross-modality person re-identification (ReID) task aims to recognize the images of the same identity between the visible modality and the infrared modality. Exist…
A Universal Model for Cross Modality Mapping by Relational Reasoning
Zun Li, Congyan Lang, Liqian Liang +4
With the aim of matching a pair of instances from two different modalities, cross modality mapping has attracted growing attention in the computer vision community. Existing method…
EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising
Tengfei Liang, Yi Jin, Yidong Li +3
In the past few decades, to reduce the risk of X-ray in computed tomography (CT), low-dose CT image denoising has attracted extensive attention from researchers, which has become a…
HERA: Partial Label Learning by Combining Heterogeneous Loss with Sparse and Low-Rank Regularization
Gengyu Lyu, Songhe Feng, Yi Jin +3
Partial Label Learning (PLL) aims to learn from the data where each training instance is associated with a set of candidate labels, among which only one is correct. Most existing m…