alexandre01/deepsvg

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1164 stars · 115 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official PyTorch code for the NeurIPS 2020 paper 'DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation'. It provides a library for deep learning with SVG data, training code, pretrained models, the SVG-Icons8 dataset, and a GUI demo for vector graphics animation.

Use cases

• generate vector graphics with deep learning
• animate SVG icons with a generative model
• convert SVG files into differentiable PyTorch tensors
• train a hierarchical generative network on SVG data
• experiment with SVG autoencoders and VAEs
• use the SVG-Icons8 dataset for sketch or icon modeling

When to choose

• you need a research-grade PyTorch library for SVG deep learning
• you want to reproduce or build on the DeepSVG paper
• you need a dataset of SVG icons for generative modeling
• you want to interpolate or animate between vector graphics

When to avoid

• you need a production-ready SVG rendering or editing tool
• you want a maintained library with active support for new PyTorch versions
• you need general-purpose vector graphics software rather than ML research code

Facets

library · maturity maintenance

machine-learning deep-learning graphics animation data-generation machine-learning deep-learning graphics computer-vision python svg pytorch generative-model autoencoder transformer vector-graphics research-code neurips-2020 dataset

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