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- Vi Technology (United States)US14 papers
- Tsinghua UniversityCN12 papers
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- University of Electronic Science and Technology of ChinaCN10 papers
- Chinese Academy of SciencesCN9 papers
- Huazhong University of Science and TechnologyCN8 papers
- Hong Kong University of Science and TechnologyHK7 papers
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- University of Science and Technology of ChinaCN5 papers
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- Institute of AutomationCN4 papers
- Tencent (China)CN4 papers
16 papers · 1 filter
Scene Text Detection with Supervised Pyramid Context Network
Enze Xie, Yuhang Zang, Shuai Shao +3
Scene text detection methods based on deep learning have achieved remarkable results over the past years. However, due to the high diversity and complexity of natural scenes, previ…
MGANet: A Robust Model for Quality Enhancement of Compressed Video
Xiandong Meng, Xuan Deng, Shuyuan Zhu +4
In video compression, most of the existing deep learning approaches concentrate on the visual quality of a single frame, while ignoring the useful priors as well as the temporal in…
Scene Text Detection and Recognition: The Deep Learning Era
Shangbang Long, Xin He, Cong Yao
With the rise and development of deep learning, computer vision has been tremendously transformed and reshaped. As an important research area in computer vision, scene text detecti…
Deep Part Induction from Articulated Object Pairs
Li Yi, Haibin Huang, Difan Liu +3
Object functionality is often expressed through part articulation -- as when the two rigid parts of a scissor pivot against each other to perform the cutting function. Such articul…
Scene Text Recognition from Two-Dimensional Perspective
Minghui Liao, Jian Zhang, Zhaoyi Wan +5
Inspired by speech recognition, recent state-of-the-art algorithms mostly consider scene text recognition as a sequence prediction problem. Though achieving excellent performance,…
GridFace: Face Rectification via Learning Local Homography Transformations
Erjin Zhou, Zhimin Cao, Jian Sun
In this paper, we propose a method, called GridFace, to reduce facial geometric variations and improve the recognition performance. Our method rectifies the face by local homograph…