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September 5, 2025Athens Journal of SciencesOpen Access

Exploring Architectural Design 3D Reconstruction Approaches through Deep Learning Methods: A Comprehensive Survey

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This comprehensive survey categorizes deep learning techniques for 3D reconstruction in architecture, highlighting their implications for design.

Deep learning techniques streamline architectural design processes, enhancing 3D reconstruction capabilities.
Advances in computer vision, driven by deep learning, have transformed applications like object detection and semantic segmentation.
Malleable architectural designs require efficient adaptations, underscoring the need for flexible 3D reconstruction methods.
The focus on learning-based generative design could significantly improve the efficiency of architectural modifications.

Gorjian et al. (2025) studied this question.

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This comprehensive survey categorizes deep learning techniques for 3D reconstruction in architecture, highlighting their implications for design.