DeepVecFont

Fig. 1. Different from most existing font generation methods that aim at synthesizing glyph images, our proposed DeepVecFont is capable of automatically generating high-quality vector fonts. (a) Given a few reference glyphs as input, our method can directly synthesize the whole vector font in the same style. (b) With the fonts synthesized in (a), more vector fonts can be generated by smooth interpolations in the style latent space of our model. The blue points indicate the locations of font style features in our latent space. The interpolated vector fonts are marked by red rectangles.

[1]  Alexei A. Efros,et al.  Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[2]  Jianguo Xiao,et al.  DCFont: an end-to-end deep chinese font generation system , 2017, SIGGRAPH Asia Technical Briefs.

[3]  Trevor Darrell,et al.  Multi-content GAN for Few-Shot Font Style Transfer , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[4]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[5]  Takeo Igarashi,et al.  Example-Based Automatic Font Generation , 2010, Smart Graphics.

[6]  Niloy J. Mitra,et al.  Im2Vec: Synthesizing Vector Graphics without Vector Supervision , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[7]  Louis-Philippe Morency,et al.  Multimodal Machine Learning: A Survey and Taxonomy , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Zhouhui Lian,et al.  Attribute2Font , 2020, ACM Trans. Graph..

[9]  Philip Emery REWRITE , 2013 .

[10]  Zhou Yu,et al.  Multi-modal Factorized Bilinear Pooling with Co-attention Learning for Visual Question Answering , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[11]  Vladimir G. Kim,et al.  Deep Parametric Shape Predictions Using Distance Fields , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Douglas Eck,et al.  A Learned Representation for Scalable Vector Graphics , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[13]  Douglas Eck,et al.  A Neural Representation of Sketch Drawings , 2017, ICLR.

[14]  Jianguo Xiao,et al.  Creating New Chinese Fonts based on Manifold Learning and Adversarial Networks , 2018, Eurographics.

[15]  Jianguo Xiao,et al.  FontRNN: Generating Large‐scale Chinese Fonts via Recurrent Neural Network , 2019, Comput. Graph. Forum.

[16]  Michael I. Jordan,et al.  Advances in Neural Information Processing Systems 30 , 1995 .

[17]  Yoshua Bengio,et al.  Generative Adversarial Nets , 2014, NIPS.

[18]  Thomas Brox,et al.  U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[19]  Alex Graves,et al.  Generating Sequences With Recurrent Neural Networks , 2013, ArXiv.

[20]  Jianguo Xiao,et al.  Artistic glyph image synthesis via one-stage few-shot learning , 2019, ACM Trans. Graph..

[21]  Geoffrey E. Hinton,et al.  Visualizing Data using t-SNE , 2008 .

[22]  Trevor Darrell,et al.  Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding , 2016, EMNLP.

[23]  Yoshua Bengio,et al.  Drawing and Recognizing Chinese Characters with Recurrent Neural Network , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  S. Srihari Mixture Density Networks , 1994 .

[25]  Li Fei-Fei,et al.  Perceptual Losses for Real-Time Style Transfer and Super-Resolution , 2016, ECCV.

[26]  Lukasz Kaiser,et al.  Attention is All you Need , 2017, NIPS.

[27]  Tzu-Mao Li,et al.  Differentiable vector graphics rasterization for editing and learning , 2020, ACM Trans. Graph..

[28]  Jan Kautz,et al.  Learning a manifold of fonts , 2014, ACM Trans. Graph..

[29]  Alexandre Alahi,et al.  DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation , 2020, NeurIPS.

[30]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[31]  Bo Zhao,et al.  EasyFont , 2018, ACM Trans. Graph..

[32]  Yoshua Bengio,et al.  Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.