April 9, 2024, 4:44 a.m. | Anqi Wang, Jiahua Dong, Lik-Hang Lee, Jiachuan Shen, Pan Hui

cs.LG updates on arXiv.org arxiv.org

arXiv:2305.00510v3 Announce Type: replace-cross
Abstract: 3D shape generation techniques leveraging deep learning have garnered significant interest from both the computer vision and architectural design communities, promising to enrich the content of the future metaverse. However, research on virtual architectural design remains limited, particularly regarding human-AI collaboration and deep learning-assisted design. We first illuminate the principles, generation techniques, and current literature of virtual architecture, focusing on challenges such as datasets, multimodality, design intuition, and generative frameworks. In our survey, we reviewed …

abstract ai-architecture architecture arxiv communities computer computer vision cs.cv cs.hc cs.lg deep learning design designing future however liberty metaverse research survey the metaverse type virtual vision

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