UniPoly: Unified End-to-End pipeline for Raster2Vector Tasks

Spatial vectorization provides structured representations for urban modeling, digital twins, indoor navigation, and Geographic Information Systems (GIS). Existing methods often rely on task-specific architectures or multi-stage pipelines, while evaluation protocols remain fragmented across spatial domains. We propose UniPoly, a unified end-to-end framework for raster-to-vector (R2V) spatial reconstruction that represents diverse spatial objects as polygons. UniPoly adopts a shared polygon-based reconstruction paradigm with configurable components and introduces Poly Relational Attention (PRA) to model interactions within and across polygons. We further establish a unified evaluation protocol for both multi-stage and end-to-end methods, assessing region accuracy, geometric complexity, boundary fidelity, and vector fidelity. Extensive experiments on four indoor and outdoor benchmarks for floorplan, building, farmland, and road reconstruction show that UniPoly achieves the best or second-best performance on 31 of 32 evaluated metrics, with eight metrics per benchmark, while maintaining competitive inference efficiency. These results demonstrate the effectiveness of UniPoly across diverse spatial domains. Code will be released upon acceptance.