SAVMap extracts semantic structure points from panoramic video, tracks them across rectified views, and recovers 3D wireframe maps via Manhattan-constrained SfM, reporting 4.8 cm aggregate MAE over 5000 shelf elements in a 46-row warehouse.
Structured semantic 3D reconstruction (S23DR) challenge 2025 – winning solution,
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Transformer model predicts 3D wireframe edges from semantically subsampled SfM points and frozen autoencoder features, achieving 0.6476 HSS on HoHo 22k dataset for second place in S23DR Challenge 2026.
citing papers explorer
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SAVMap: Structure-Aided Visual Mapping of Large-Scale 2.5D Manhattan Wireframes from Panoramic Video
SAVMap extracts semantic structure points from panoramic video, tracks them across rectified views, and recovers 3D wireframe maps via Manhattan-constrained SfM, reporting 4.8 cm aggregate MAE over 5000 shelf elements in a 46-row warehouse.
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Edge Prediction for Roof Wireframe Reconstruction with Transformers
Transformer model predicts 3D wireframe edges from semantically subsampled SfM points and frozen autoencoder features, achieving 0.6476 HSS on HoHo 22k dataset for second place in S23DR Challenge 2026.