AI RESEARCH

Vector Scaffolding: Inter-Scale Orchestration for Differentiable Image Vectorization

arXiv CS.CV

ArXi:2605.11913v1 Announce Type: new Differentiable vector graphics have enabled powerful gradient-based optimization of vector primitives directly from raster images. However, existing frameworks formulate this as a flat optimization problem, forcing hundreds to thousands of randomly initialized curves to blindly compete for pixel-level error reduction. This disordered optimization leads to topology collapse, where macroscopic structures are distorted by internal high-frequency noise, resulting in a redundant and uneditable "polygon soup" that limits practical editability.