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Vector graphics are widely used to represent fonts, logos, digital artworks, and graphic designs.
Bidirectional recurrent neural networks
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Learning to infer graphics programs from hand-drawn images. corr abs/1707.09627 (2017)
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A neural representation of sketch drawings
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Csgnet: Neural shape parser for constructive solid geometry. corr abs/1712.08290 (2017)
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Synthesizing programs for images using reinforced adversarial learning
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A papier-mâché approach to learning 3d surface generation
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Perception-driven semi-structured boundary vectorization
Neural painters: A learned differentiable constraint for generating brushstroke paintings
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Calibrating the adaptive learning rate to improve convergence of adam
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S. Hoshyari, E. Alberto Dominici, A. Sheffer, N. Carr, D. Ceylan, Z. Wang, and I.-C. Shen · 2018
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Strokenet: A neural painting environment
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Vectorization of line drawings via polyvector fields
M. Bessmeltsev and J. Solomon · 2019
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Deepspline: Data-driven reconstruction of parametric curves and surfaces
J. Gao, C. Tang, V. Ganapathi-Subramanian, J. Huang, H. Su, and L. J. Guibas · 2019
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Artistic glyph image synthesis via one-stage few-shot learning
Y. Gao, Y. Guo, Z. Lian, Y. Tang, and J. Xiao · 2019
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Deep line drawing vectorization via line subdivision and topology reconstruction
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Learning to paint with model-based deep reinforcement learning
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Deepsvg: A hierarchical generative network for vector graphics animation, 2020
A. Carlier, M. Danelljan, A. Alahi, and R. Timofte · 2020
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Deep vectorization of technical drawings
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Uv-net: Learning from curve-networks and solids
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Differentiable vector graphics rasterization for editing and learning
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Discovering pattern structure using differentiable compositing
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Sketchformer: Transformer-based representation for sketched structure
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Deep parametric shape predictions using distance fields
D. Smirnov, M. Fisher, V. G. Kim, R. Zhang, and J. Solomon · 2020
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