Restoration of Hand-Drawn Architectural Drawings Using Latent Space Mapping With Degradation Generator

Nakkwan Choi, Seungjae Lee, Yongsik Lee, Seungjoon Yang; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, pp. 14164-14172

Abstract


This work presents the restoration of drawings of wooden built heritage. Hand-drawn drawings contain the most important original information but are often severely degraded over time. A novel restoration method based on the vector quantized variational autoencoders is presented. Latent space representations of drawings and noise are learned, which are used to map noisy drawings to clean drawings for restoration and to generate authentic noisy drawings for data augmentation. The proposed method is applied to the drawings archived in the Cultural Heritage Administration. Restored drawings show significant quality improvement and allow more accurate interpretations of information.

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[bibtex]
@InProceedings{Choi_2023_CVPR, author = {Choi, Nakkwan and Lee, Seungjae and Lee, Yongsik and Yang, Seungjoon}, title = {Restoration of Hand-Drawn Architectural Drawings Using Latent Space Mapping With Degradation Generator}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2023}, pages = {14164-14172} }