new deepfont: font recognition and similarity based on deep … · 2016. 4. 10. · deepfont font...
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© 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.
DeepFont: Font Recognition and Similarity Based on Deep LearningHailin Jin | Principal Scientist | Adobe Research
© 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.
© 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.
Problem definition
Font recognition Font similarity Why does it matter? Use fonts effectively
Design inspiration
Text/image editing
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Challenges
Extremely large scale recognition problem Over 100,000 known fonts
Beyond object recognition Recognize subtle design styles
Extremely difficult to collect real-world training data Have to use synthetic training data
Mismatch between training and test data
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Our approach – DeepFont
Deep Learning – convolutional neural networks Effective at large-scale
Effective at fine-grained recognition
No need to do OCR End-to-end training and data-driven
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DeepFont system overview
Localization Network
Recognition Network
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GPUCPU
DeepFont training
Fonts Font maps
Offline rendering Online
rendering
Words
Images
Data augmentation
CNN training
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Data augmentation
Noise Blur Perspective deformation Shading Variable character spacing Variable aspect ratio
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Effects of data augmentation
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Beyond data augmentation
Cannot enumerate all possible degradation Background, font decoration
May introduce degradation bias in training Leverage abundant unlabeled real-world images
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Network decomposition for domain adaptation
Decompose the network into two parts Train the two parts separately
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Unsupervised cross-domainvariable layers
Supervised domain-specific
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Network decomposition for domain adaptation
Stacked convolutional auto-encoder Synthetic data and unlabeled real data
Unsupervised training Fix the subnetwork Train the rest in a supervised way Labeled synthetic data
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Qualitative evaluation
4383 real-world images collected from font forums
Vary the number of unsupervisedly trained layers
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Model Augmentation Decomposition Top-1 accuracy Top-5 accuracy
LFE (CVPR’04) Y N/A 42.6% 60.3%
DeepFont N N 42.5% 49.2%
DeepFont Y N 66.7% 79.2%
DeepFont Y Y 71.4% 81.8%
0 1 2 3 4 5
Train 91.5% 90.1% 88.8% 87.5% 84.8% 82.1%
Test 79.3% 79.7% 81.8% 81.0% 77.5% 74.0%
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Text localization
Localization model
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Text localization results
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DeepFont for font similarity
Similarity Network
LushScript.ttf
Query Sample
Similar fonts
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Font similarity
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Demo in Photoshop
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Mobile
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Summary
DeepFont Font recognition Font similarity Data augmentation Model decomposition Text localization
Photoshop Mobile Dataset available at http://www.atlaswang.com/deepfont.html References Chen, Yang, Jin, Brandt, Shechtman, Agarwala, and Han. Large-scale Visual Font Recognition. CVPR 2014. Wang, Yang, Jin, Brandt, Shechtman, Agarwala, and Huang. DeepFont: Identify Your Font from An Image. ACM
Multimedia 2015.
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