FacadeNet: Conditional Facade Synthesis via Selective Editing

Yiangos Georgiou, Marios Loizou, Tom Kelly, Melinos Averkiou; Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024, pp. 5384-5393

Abstract


We introduce FacadeNet, a deep learning approach for synthesizing building facade images from diverse viewpoints. Our method employs a conditional GAN, taking a single view of a facade along with the desired viewpoint information and generates an image of the facade from the distinct viewpoint. To precisely modify view-dependent elements like windows and doors while preserving the structure of view-independent components such as walls, we introduce a selective editing module. This module leverages image embeddings extracted from a pretrained vision transformer Our experiments demonstrated state-of-the-art performance on building facade generation, surpassing alternative methods.

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[bibtex]
@InProceedings{Georgiou_2024_WACV, author = {Georgiou, Yiangos and Loizou, Marios and Kelly, Tom and Averkiou, Melinos}, title = {FacadeNet: Conditional Facade Synthesis via Selective Editing}, booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}, month = {January}, year = {2024}, pages = {5384-5393} }