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arXiv · 2506.16421

Structured Semantic 3D Reconstruction (S23DR) Challenge 2025 -- Winning solution

Jan Skvrna·Lukas Neumann
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Abstract

This paper presents the winning solution for the S23DR Challenge 2025, which involves predicting a house's 3D roof wireframe from a sparse point cloud and semantic segmentations. Our method operates directly in 3D, first identifying vertex candidates from the COLMAP point cloud using Gestalt segmentations. We then employ two PointNet-like models: one to refine and classify these candidates by analyzing local cubic patches, and a second to predict edges by processing the cylindrical regions connecting vertex pairs. This two-stage, 3D deep learning approach achieved a winning Hybrid Structure Score (HSS) of 0.43 on the private leaderboard.

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Jan Skvrna, Lukas Neumann. 2025-06-19. Structured Semantic 3D Reconstruction (S23DR) Challenge 2025 -- Winning solution. https://arxiv.org/abs/2506.16421

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