activity
20182021
most citedLearning Regional Attraction for Line Segment Detection

39 citations · 41 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2021

Deep Graph Matching under Quadratic Constraint

Quankai Gao, Fudong Wang, Nan Xue +2

Recently, deep learning based methods have demonstrated promising results on the graph matching problem, by relying on the descriptive capability of deep features extracted on grap…

cs.CV2020

Zero-Assignment Constraint for Graph Matching with Outliers

Fudong Wang, Nan Xue, Jin-Gang Yu +1

Graph matching (GM), as a longstanding problem in computer vision and pattern recognition, still suffers from numerous cluttered outliers in practical applications. To address this…

cs.CV20201 cited

Holistically-Attracted Wireframe Parsing

Nan Xue, Tianfu Wu, Song Bai +4

This paper presents a fast and parsimonious parsing method to accurately and robustly detect a vectorized wireframe in an input image with a single forward pass. The proposed metho…

cs.CV201939 cited

Learning Regional Attraction for Line Segment Detection

Nan Xue, Song Bai, Fu-Dong Wang +4

This paper presents regional attraction of line segment maps, and hereby poses the problem of line segment detection (LSD) as a problem of region coloring. Given a line segment map…

cs.CV20191 cited

A Functional Representation for Graph Matching

Fu-Dong Wang, Gui-Song Xia, Nan Xue +2

Graph matching is an important and persistent problem in computer vision and pattern recognition for finding node-to-node correspondence between graph-structured data. However, as…

cs.CV2018

Learning Attraction Field Representation for Robust Line Segment Detection

Nan Xue, Song Bai, Fudong Wang +3

This paper presents a region-partition based attraction field dual representation for line segment maps, and thus poses the problem of line segment detection (LSD) as the region co…