SVGDreamer introduces semantic-driven image vectorization (SIVE) and vectorized particle-based score distillation (VPSD) to produce editable, high-quality, diverse SVGs from text.
Styleclipdraw: Coupling content and style in text-to-drawing synthesis
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2years
2023 2verdicts
UNVERDICTED 2representative citing papers
DiffSketcher synthesizes vector sketches from natural language by optimizing Bezier curves with diffusion model guidance via extended SDS loss.
citing papers explorer
-
SVGDreamer: Text Guided SVG Generation with Diffusion Model
SVGDreamer introduces semantic-driven image vectorization (SIVE) and vectorized particle-based score distillation (VPSD) to produce editable, high-quality, diverse SVGs from text.
-
DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models
DiffSketcher synthesizes vector sketches from natural language by optimizing Bezier curves with diffusion model guidance via extended SDS loss.