370 citations · 452 across the 9 of their papers we have counts for
10 papers
Context-Aware Selective Label Smoothing for Calibrating Sequence Recognition Model
Shuangping Huang, Yu Luo, Zhenzhou Zhuang +3
Despite the success of deep neural network (DNN) on sequential data (i.e., scene text and speech) recognition, it suffers from the over-confidence problem mainly due to overfitting…
Decoupling Visual-Semantic Feature Learning for Robust Scene Text Recognition
Changxu Cheng, Bohan Li, Qi Zheng +2
Semantic information has been proved effective in scene text recognition. Most existing methods tend to couple both visual and semantic information in an attention-based decoder. A…
SentiPrompt: Sentiment Knowledge Enhanced Prompt-Tuning for Aspect-Based Sentiment Analysis
Chengxi Li, Feiyu Gao, Jiajun Bu +8
Aspect-based sentiment analysis (ABSA) is an emerging fine-grained sentiment analysis task that aims to extract aspects, classify corresponding sentiment polarities and find opinio…
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…
Implicit Feature Alignment: Learn to Convert Text Recognizer to Text Spotter
Tianwei Wang, Yuanzhi Zhu, Lianwen Jin +5
Text recognition is a popular research subject with many associated challenges. Despite the considerable progress made in recent years, the text recognition task itself is still co…
MOST: A Multi-Oriented Scene Text Detector with Localization Refinement
Minghang He, Minghui Liao, Zhibo Yang +6
Over the past few years, the field of scene text detection has progressed rapidly that modern text detectors are able to hunt text in various challenging scenarios. However, they m…
Joint Layout Analysis, Character Detection and Recognition for Historical Document Digitization
Weihong Ma, Hesuo Zhang, Lianwen Jin +3
In this paper, we propose an end-to-end trainable framework for restoring historical documents content that follows the correct reading order. In this framework, two branches named…
Learn to Augment: Joint Data Augmentation and Network Optimization for Text Recognition
Canjie Luo, Yuanzhi Zhu, Lianwen Jin +1
Handwritten text and scene text suffer from various shapes and distorted patterns. Thus training a robust recognition model requires a large amount of data to cover diversity as mu…
All You Need Is Boundary: Toward Arbitrary-Shaped Text Spotting
Hao Wang, Pu Lu, Hui Zhang +6
Recently, end-to-end text spotting that aims to detect and recognize text from cluttered images simultaneously has received particularly growing interest in computer vision. Differ…
TextField: Learning A Deep Direction Field for Irregular Scene Text Detection
Yongchao Xu, Yukang Wang, Wei Zhou +3
Scene text detection is an important step of scene text reading system. The main challenges lie on significantly varied sizes and aspect ratios, arbitrary orientations and shapes.…