44 citations · 84 across the 8 of their papers we have counts for
13 papers
StrucTexT: Structured Text Understanding with Multi-Modal Transformers
Yulin Li, Yuxi Qian, Yuchen Yu +7
Structured text understanding on Visually Rich Documents (VRDs) is a crucial part of Document Intelligence. Due to the complexity of content and layout in VRDs, structured text und…
PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network
Pengfei Wang, Chengquan Zhang, Fei Qi +7
The reading of arbitrarily-shaped text has received increasing research attention. However, existing text spotters are mostly built on two-stage frameworks or character-based metho…
Learning Global Structure Consistency for Robust Object Tracking
Bi Li, Chengquan Zhang, Zhibin Hong +5
Fast appearance variations and the distractions of similar objects are two of the most challenging problems in visual object tracking. Unlike many existing trackers that focus on m…
Towards Accurate Scene Text Recognition with Semantic Reasoning Networks
Deli Yu, Xuan Li, Chengquan Zhang +3
Scene text image contains two levels of contents: visual texture and semantic information. Although the previous scene text recognition methods have made great progress over the pa…
An End-to-end Video Text Detector with Online Tracking
Hongyuan Yu, Chengquan Zhang, Xuan Li +3
Video text detection is considered as one of the most difficult tasks in document analysis due to the following two challenges: 1) the difficulties caused by video scenes, i.e., mo…
A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning
Pengfei Wang, Chengquan Zhang, Fei Qi +6
Detecting scene text of arbitrary shapes has been a challenging task over the past years. In this paper, we propose a novel segmentation-based text detector, namely SAST, which emp…