activity
20192022
most citedFC2RN: A Fully Convolutional Corner Refinement Network for Accurate Multi-Oriented Scene Text Detection

6 citations · 11 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2022

UNITS: Unsupervised Intermediate Training Stage for Scene Text Detection

Youhui Guo, Yu Zhou, Xugong Qin +2

Recent scene text detection methods are almost based on deep learning and data-driven. Synthetic data is commonly adopted for pre-training due to expensive annotation cost. However…

cs.CV20211 cited

Which and Where to Focus: A Simple yet Accurate Framework for Arbitrary-Shaped Nearby Text Detection in Scene Images

Youhui Guo, Yu Zhou, Xugong Qin +1

Scene text detection has drawn the close attention of researchers. Though many methods have been proposed for horizontal and oriented texts, previous methods may not perform well w…

cs.CV20214 cited

Mask is All You Need: Rethinking Mask R-CNN for Dense and Arbitrary-Shaped Scene Text Detection

Xugong Qin, Yu Zhou, Youhui Guo +5

Due to the large success in object detection and instance segmentation, Mask R-CNN attracts great attention and is widely adopted as a strong baseline for arbitrary-shaped scene te…

cs.CV2020

Gaussian Constrained Attention Network for Scene Text Recognition

Zhi Qiao, Xugong Qin, Yu Zhou +2

Scene text recognition has been a hot topic in computer vision. Recent methods adopt the attention mechanism for sequence prediction which achieve convincing results. However, we a…

cs.CV20206 cited

FC2RN: A Fully Convolutional Corner Refinement Network for Accurate Multi-Oriented Scene Text Detection

Xugong Qin, Yu Zhou, Dayan Wu +2

Recent scene text detection works mainly focus on curve text detection. However, in real applications, the curve texts are more scarce than the multi-oriented ones. Accurate detect…

cs.CV2019

Curved Text Detection in Natural Scene Images with Semi- and Weakly-Supervised Learning

Xugong Qin, Yu Zhou, Dongbao Yang +1

Detecting curved text in the wild is very challenging. Recently, most state-of-the-art methods are segmentation based and require pixel-level annotations. We propose a novel scheme…