activity
20182022
most citedMSR: Multi-Scale Shape Regression for Scene Text Detection

12 citations · 19 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV20221 cited

Domain Adaptive Scene Text Detection via Subcategorization

Zichen Tian, Chuhui Xue, Jingyi Zhang +1

Most existing scene text detectors require large-scale training data which cannot scale well due to two major factors: 1) scene text images often have domain-specific distributions…

cs.CV2022

Fourier Document Restoration for Robust Document Dewarping and Recognition

Chuhui Xue, Zichen Tian, Fangneng Zhan +2

State-of-the-art document dewarping techniques learn to predict 3-dimensional information of documents which are prone to errors while dealing with documents with irregular distort…

cs.CV20211 cited

Detection and Rectification of Arbitrary Shaped Scene Texts by using Text Keypoints and Links

Chuhui Xue, Shijian Lu, Steven Hoi

Detection and recognition of scene texts of arbitrary shapes remain a grand challenge due to the super-rich text shape variation in text line orientations, lengths, curvatures, etc…

cs.CV20195 cited

GA-DAN: Geometry-Aware Domain Adaptation Network for Scene Text Detection and Recognition

Fangneng Zhan, Chuhui Xue, Shijian Lu

Recent adversarial learning research has achieved very impressive progress for modelling cross-domain data shifts in appearance space but its counterpart in modelling cross-domain…

cs.CV201912 cited

MSR: Multi-Scale Shape Regression for Scene Text Detection

Chuhui Xue, Shijian Lu, Wei Zhang

State-of-the-art scene text detection techniques predict quadrilateral boxes that are prone to localization errors while dealing with straight or curved text lines of different ori…

cs.CV2018

Accurate Scene Text Detection through Border Semantics Awareness and Bootstrapping

Chuhui Xue, Shijian Lu, Fangneng Zhan

This paper presents a scene text detection technique that exploits bootstrapping and text border semantics for accurate localization of texts in scenes. A novel bootstrapping techn…