2.2k citations · 4k across the 15 of their papers we have counts for
15 papers
Improving Structured Text Recognition with Regular Expression Biasing
Baoguang Shi, Wenfeng Cheng, Yijuan Lu +2
We study the problem of recognizing structured text, i.e. text that follows certain formats, and propose to improve the recognition accuracy of structured text by specifying regula…
Progressive and Aligned Pose Attention Transfer for Person Image Generation
Zhen Zhu, Tengteng Huang, Mengde Xu +3
This paper proposes a new generative adversarial network for pose transfer, i.e., transferring the pose of a given person to a target pose. We design a progressive generator which…
ICDAR 2019 Robust Reading Challenge on Reading Chinese Text on Signboard
Xi Liu, Rui Zhang, Yongsheng Zhou +13
Chinese scene text reading is one of the most challenging problems in computer vision and has attracted great interest. Different from English text, Chinese has more than 6000 comm…
Progressive Pose Attention Transfer for Person Image Generation
Zhen Zhu, Tengteng Huang, Baoguang Shi +3
This paper proposes a new generative adversarial network for pose transfer, i.e., transferring the pose of a given person to a target pose. The generator of the network comprises a…
Rotation-Sensitive Regression for Oriented Scene Text Detection
Minghui Liao, Zhen Zhu, Baoguang Shi +2
Text in natural images is of arbitrary orientations, requiring detection in terms of oriented bounding boxes. Normally, a multi-oriented text detector often involves two key tasks:…
TextBoxes++: A Single-Shot Oriented Scene Text Detector
Minghui Liao, Baoguang Shi, Xiang Bai
Scene text detection is an important step of scene text recognition system and also a challenging problem. Different from general object detection, the main challenges of scene tex…
ICDAR2017 Competition on Reading Chinese Text in the Wild (RCTW-17)
Baoguang Shi, Cong Yao, Minghui Liao +6
Chinese is the most widely used language in the world. Algorithms that read Chinese text in natural images facilitate applications of various kinds. Despite the large potential val…
Detecting Oriented Text in Natural Images by Linking Segments
Baoguang Shi, Xiang Bai, Serge Belongie
Most state-of-the-art text detection methods are specific to horizontal Latin text and are not fast enough for real-time applications. We introduce Segment Linking (SegLink), an or…
TextBoxes: A Fast Text Detector with a Single Deep Neural Network
Minghui Liao, Baoguang Shi, Xiang Bai +2
This paper presents an end-to-end trainable fast scene text detector, named TextBoxes, which detects scene text with both high accuracy and efficiency in a single network forward p…
AID: A Benchmark Dataset for Performance Evaluation of Aerial Scene Classification
Gui-Song Xia, Jingwen Hu, Fan Hu +4
Aerial scene classification, which aims to automatically label an aerial image with a specific semantic category, is a fundamental problem for understanding high-resolution remote…
Deep FisherNet for Object Classification
Peng Tang, Xinggang Wang, Baoguang Shi +3
Despite the great success of convolutional neural networks (CNN) for the image classification task on datasets like Cifar and ImageNet, CNN's representation power is still somewhat…
Robust Scene Text Recognition with Automatic Rectification
Baoguang Shi, Xinggang Wang, Pengyuan Lyu +2
Recognizing text in natural images is a challenging task with many unsolved problems. Different from those in documents, words in natural images often possess irregular shapes, whi…
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
Baoguang Shi, Xiang Bai, Cong Yao
Image-based sequence recognition has been a long-standing research topic in computer vision. In this paper, we investigate the problem of scene text recognition, which is among the…
Automatic Script Identification in the Wild
Baoguang Shi, Cong Yao, Chengquan Zhang +3
With the rapid increase of transnational communication and cooperation, people frequently encounter multilingual scenarios in various situations. In this paper, we are concerned wi…
Deep Regression for Face Alignment
Baoguang Shi, Xiang Bai, Wenyu Liu +1
In this paper, we present a deep regression approach for face alignment. The deep architecture consists of a global layer and multi-stage local layers. We apply the back-propagatio…