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FacadeNet: Conditional Facade Synthesis via Selective Editing

arXiv 2311.01240 ↗First posted 2 Nov 2023cs.CV cs.AIcited by 0

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Abstract (arXiv)

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 pre-trained vision transformer. Our experiments demonstrated state-of-the-art performance on building facade generation, surpassing alternative methods.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 33 of its 58 references that are in the map. First posted on arXiv 2 Nov 2023.

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References · 33

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21 more
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