StippleDiffusion is a late-stage denoising ControlNet on an optimal-transport point-set diffusion baseline that produces capacity-constrained stipples from arbitrary density maps, generalizes to unseen point budgets, and matches optimization baselines on Icons-50 while remaining end-to-end trainable
Deep point correlation design , year =
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2representative citing papers
A finite-element method extends 2D odeco integrability to 3D surfaces to generate shear-free quadrilateral meshes with automatic singularity placement and minimized area or stretch distortion under alignment and sizing constraints.
citing papers explorer
-
StippleDiffusion: Capacity-Constrained Stippling using Controlled Diffusion
StippleDiffusion is a late-stage denoising ControlNet on an optimal-transport point-set diffusion baseline that produces capacity-constrained stipples from arbitrary density maps, generalizes to unseen point budgets, and matches optimization baselines on Icons-50 while remaining end-to-end trainable