3D Geometric Reconstruction Method of Damaged Cultural Relics Based on Multimodal Data Fusion and Deep Learning

Key Points

• The aim is to develop a method for accurately reconstructing damaged cultural relics in three dimensions using multimodal data sources.
• Utilized deep learning algorithms for feature extraction and fusion.
• Integrated various data modalities to enhance reconstruction accuracy.
• Applied geometric modeling techniques for the visualization of relics.
• Achieved significant improvements in reconstruction fidelity compared to traditional methods.
• Demonstrated the potential for detailed 3D models of cultural relics from incomplete data.