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Pengyuan Lyu
Researcher at Huazhong University of Science and Technology
Publications - 31
Citations - 3036
Pengyuan Lyu is an academic researcher from Huazhong University of Science and Technology. The author has contributed to research in topics: Computer science & Convolutional neural network. The author has an hindex of 15, co-authored 26 publications receiving 2109 citations. Previous affiliations of Pengyuan Lyu include Baidu & Tencent.
Papers
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Proceedings ArticleDOI
Robust Scene Text Recognition with Automatic Rectification
TL;DR: This article proposed a robust text recognizer with automatic rectification (RARE), which consists of a Spatial Transformer Network (STN) and a Sequence Recognition Network (SRN).
Journal ArticleDOI
ASTER: An Attentional Scene Text Recognizer with Flexible Rectification
TL;DR: This work introduces ASTER, an end-to-end neural network model that comprises a rectification network and a recognition network that predicts a character sequence directly from the rectified image.
Proceedings ArticleDOI
Multi-oriented Scene Text Detection via Corner Localization and Region Segmentation
TL;DR: This paper proposes to detect scene text by localizing corner points of text bounding boxes and segmenting text regions in relative positions and achieves better or comparable results in both accuracy and efficiency.
Posted Content
Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes
TL;DR: This paper investigates the problem of scene text spotting, which aims at simultaneous text detection and recognition in natural images, and proposes an end-to-end trainable neural network model, named as Mask TextSpotter, which is inspired by the newly published work Mask R-CNN.
Book ChapterDOI
Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes
TL;DR: Wang et al. as discussed by the authors proposed Mask TextSpotter, an end-to-end trainable neural network model for scene text detection and recognition, which achieved state-of-the-art results in text detection.