Examples
Pytorch-SVGRender supports a variety of vectorization methods. Including: Image-to-SVG, Text-to-SVG, Text-to-Sketch
LIVE: Towards Layer-wise Image Vectorization
(CVPR 2022)
LIVE to convert raster images to SVGs and simultaneously maintain its image topology.
CLIPasso: Semantically-Aware Object Sketching
(SIGGRAPH 2022)
CLIPasso converts an image of an object to a sketch, allowing for varying levels of abstraction, while preserving its key visual features.
CLIPascene: Scene Sketching with Different Types and Levels of Abstraction
(ICCV 2023)
CLIPascene converts an image of scene image into a sketch using different types and multiple levels of abstraction.
CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoders
(NIPS 2022)
CLIPDraw synthesizes SVGs based on text prompts.
StyleCLIPDraw: Coupling Content and Style in Text-to-Drawing Synthesis
StyleCLIPDraw synthesizes SVG based on a text prompt and a reference image.
CLIPFont: Texture Guided Vector WordArt Generation
(BMVC 2022)
StyleCLIPDraw styles vector fonts according to text prompts.
Input SVG
CLIPFont Rendering Process
Output SVG
VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models
(CVPR 2023)
VectorFusion synthesizes SVGs based on text prompts and supports three primitive styles.
Iconography
SD + LIVE + VectorFusion fine-tuning
Prompt Suffix: "minimal flat 2d vector icon. lineal color. trending on artstation."
Prompt: "A panda rowing a boat in a pond."
Prompt: "A drawing of a cat."
Iconography
train from scratch via VectorFusion.
Prompt Suffix: "minimal flat 2d vector icon. lineal color. trending on artstation."
Prompt: "A panda rowing a boat in a pond."
"A colored mushroom growing on a log."
Pixel Art
train from scratch via VectorFusion.
Prompt Suffix: "pixel art. trending on artstation."
Prompt: "A panda rowing a boat in a pond."
Prompt: "A painting of a starry night sky."
"A cat as 3D rendered in Unreal Engine."
Sketch
train from scratch via VectorFusion.
Prompt Suffix: "minimal 2d line drawing. trending on artstation."
Prompt: "A panda rowing a boat in a pond."
Prompt: "The Eiffel Tower."
Prompt: "A 3D rendering of a temple."
DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models
(NIPS 2023)
DiffSketcher synthesizes vector sketches based on text prompts.
It supports stroke width and color optimization.
And extended additional style input to achieve style transfer.
Sketch
Prompt: "A photo of Sydney opera house."
Sketch + stroke width optimization
Prompt: "A photo of Sydney opera house."
RGBA
Prompt: "A photo of Sydney opera house."
Word-As-Image for Semantic Typography
(SIGGRAPH 2023)
Word-As-Image follows a text prompt to style a letter in a word.
It injects the meaning of a word into its letter.
'Y' in "BUNNY".
'G' in "FROG".
'j' in "jazz".
SVGDreamer: Text Guided SVG Generation with Diffusion Model
(CVPR 2024)
SVGDreamer generates various styles of SVG based on text prompts.
It supports the use of six vector primitives, including
Iconography, Sketch, Pixel Art, Low-Poly, Painting, and Ink and Wash.
Iconography
Prompt: "Sydney opera house. oil painting. by Van Gogh"
Oil Painting
Prompt: "a phoenix coming out of the fire drawing. lineal color. trending on artstation."
Acknowledgements
Thanks to academic research and engineering development in the field of SVG.
- Project Authors
- Ximing Xing and Juncheng Hu
- Author Institution
- Beihang University, School of Software
- Another term
- Contributions to the project are welcome!