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arXiv Computer Vision By Bryan G. Pantoja-Rosero

AstraLOD3: Zero-shot multimodal agentic reconstruction of LOD3 building models

Read the original on arXiv Computer Vision →

AstraLOD3 is a zero‑shot multimodal agentic system that reconstructs LOD3 building models using multi‑view images, calibrated cameras, a filtered sparse SfM point cloud, and a natural‑language specification. The Astra agent selects and executes computational steps in Python and Blender, achieving a mean FRDS of 0.9647 across 35 runs, including 24 benchmark buildings, with geometric agreement comparable to purpose‑built methods. Ablation studies show the impact of reconstruction guidance, evidence modalities, model configuration, and run‑to‑run variability, demonstrating that LOD3 reconstruction can be framed as a constrained agentic process rather than a fixed pipeline.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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