198 citations · 219 across the 7 of their papers we have counts for
7 papers
PBFormer: Capturing Complex Scene Text Shape with Polynomial Band Transformer
Ruijin Liu, Ning Lu, Dapeng Chen +3
We present PBFormer, an efficient yet powerful scene text detector that unifies the transformer with a novel text shape representation Polynomial Band (PB). The representation has…
Self-distillation Regularized Connectionist Temporal Classification Loss for Text Recognition: A Simple Yet Effective Approach
Ziyin Zhang, Ning Lu, Minghui Liao +4
Text recognition methods are gaining rapid development. Some advanced techniques, e.g., powerful modules, language models, and un- and semi-supervised learning schemes, consecutive…
ICDAR 2023 Competition on Reading the Seal Title
Wenwen Yu, Mingyu Liu, Mingrui Chen +5
Reading seal title text is a challenging task due to the variable shapes of seals, curved text, background noise, and overlapped text. However, this important element is commonly f…
Improving Table Structure Recognition with Visual-Alignment Sequential Coordinate Modeling
Yongshuai Huang, Ning Lu, Dapeng Chen +5
Table structure recognition aims to extract the logical and physical structure of unstructured table images into a machine-readable format. The latest end-to-end image-to-text appr…
Synthetic-to-Real Unsupervised Domain Adaptation for Scene Text Detection in the Wild
Weijia Wu, Ning Lu, Enze Xie
Deep learning-based scene text detection can achieve preferable performance, powered with sufficient labeled training data. However, manual labeling is time consuming and laborious…
PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks
Wenwen Yu, Ning Lu, Xianbiao Qi +2
Computer vision with state-of-the-art deep learning models has achieved huge success in the field of Optical Character Recognition (OCR) including text detection and recognition ta…