This project explores the capabilities and limitations of Large Reconstruction Models (LRMs) for building reconstruction from street-view imagery. It addresses the unique challenges of field-of-view coverage, occlusions and entanglement in street-view imagery. This is explored through training-free multi-model inference combining large-scale pre-trained foundation models, including instance segmentation, diffusion-based inpainting for handling occlusions, and single-view reconstruction techniques.