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20212024
most citedModeling Entities as Semantic Points for Visual Information Extraction in the Wild

2 citations · 5 across the 5 of their papers we have counts for

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cs.CV2024

HIP: Hierarchical Point Modeling and Pre-training for Visual Information Extraction

Rujiao Long, Pengfei Wang, Zhibo Yang +1

End-to-end visual information extraction (VIE) aims at integrating the hierarchical subtasks of VIE, including text spotting, word grouping, and entity labeling, into a unified fra…

cs.CV2024

LORE++: Logical Location Regression Network for Table Structure Recognition with Pre-training

Rujiao Long, Hangdi Xing, Zhibo Yang +4

Table structure recognition (TSR) aims at extracting tables in images into machine-understandable formats. Recent methods solve this problem by predicting the adjacency relations o…

cs.CV2023★ 2 cited

Modeling Entities as Semantic Points for Visual Information Extraction in the Wild

Zhibo Yang, Rujiao Long, Pengfei Wang +5

Recently, Visual Information Extraction (VIE) has been becoming increasingly important in both the academia and industry, due to the wide range of real-world applications. Previous…

cs.CV2023★ 2 cited

LORE: Logical Location Regression Network for Table Structure Recognition

Hangdi Xing, Feiyu Gao, Rujiao Long +5

Table structure recognition (TSR) aims at extracting tables in images into machine-understandable formats. Recent methods solve this problem by predicting the adjacency relations o…

cs.CV2021

Parsing Table Structures in the Wild

Rujiao Long, Wen Wang, Nan Xue +4

This paper tackles the problem of table structure parsing (TSP) from images in the wild. In contrast to existing studies that mainly focus on parsing well-aligned tabular images wi…