Yingmin Tang

According to our database1, Yingmin Tang authored at least 26 papers between 2010 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2020
DeepStroke: Understanding Glyph Structure with Semantic Segmentation and Tabu Search.
Proceedings of the MultiMedia Modeling - 26th International Conference, 2020

2019
Artistic glyph image synthesis via one-stage few-shot learning.
ACM Trans. Graph., 2019

Boosting scene character recognition by learning canonical forms of glyphs.
Int. J. Document Anal. Recognit., 2019

Irregular scene text detection via attention guided border labeling.
Sci. China Inf. Sci., 2019

FontRNN: Generating Large-scale Chinese Fonts via Recurrent Neural Network.
Comput. Graph. Forum, 2019

Automatic Generation of Chinese Vector Fonts via Deep Layout Inferring.
Proceedings of the SIGGRAPH Asia 2019 Technical Briefs, 2019

DynTypo: Example-Based Dynamic Text Effects Transfer.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

SCFont: Structure-Guided Chinese Font Generation via Deep Stacked Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
As-compact-as-possible vectorization for character images.
Proceedings of the SIGGRAPH Asia 2018 Technical Briefs, Tokyo, Japan, December 04-07, 2018, 2018

Font Recognition in Natural Images via Transfer Learning.
Proceedings of the MultiMedia Modeling - 24th International Conference, 2018

Creating New Chinese Fonts based on Manifold Learning and Adversarial Networks.
Proceedings of the 39th Annual Conference of the European Association for Computer Graphics, 2018

A Common Framework for Interactive Texture Transfer.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017
DCFont: an end-to-end deep chinese font generation system.
Proceedings of the SIGGRAPH Asia 2017 Technical Briefs, Bangkok, Thailand, November 27, 2017

Structure-Aware Image Resizing for Chinese Characters.
Proceedings of the MultiMedia Modeling - 23rd International Conference, 2017

An Automatic Stroke Extraction Method using Manifold Learning.
Proceedings of the 38th Annual Conference of the European Association for Computer Graphics, 2017

2015
Text Detection in Natural Images Using Localized Stroke Width Transform.
Proceedings of the MultiMedia Modeling - 21st International Conference, 2015

Aesthetic Visual Quality Evaluation of Chinese Handwritings.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Content-independent font recognition on a single Chinese character using sparse representation.
Proceedings of the 13th International Conference on Document Analysis and Recognition, 2015

2014
Skeleton-guided vectorization of Chinese calligraphy images.
Proceedings of the IEEE 16th International Workshop on Multimedia Signal Processing, 2014

A Data-Driven Personalized Digital Ink for Chinese Characters.
Proceedings of the MultiMedia Modeling - 20th Anniversary International Conference, 2014

Non-rigid point set registration for Chinese characters using structure-guided coherent point drift.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

FlexiFont: a flexible system to generate personal font libraries.
Proceedings of the ACM Symposium on Document Engineering 2014, 2014

2013
Structure-Based Web Access Method for Ancient Chinese Characters.
Proceedings of the Natural Language Processing and Chinese Computing, 2013

Automatic Correspondence Finding for Chinese Characters Using Graph Matching.
Proceedings of the Seventh International Conference on Image and Graphics, 2013

2011
Metadata Extraction System for Chinese Books.
Proceedings of the 2011 International Conference on Document Analysis and Recognition, 2011

2010
Reversible image watermarking based on a generalized integer transform.
Proceedings of the IEEE International Conference on Acoustics, 2010


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