ArcGAN: Generative Adversarial Networks for 3D Architectural Image Generation
- Title
- ArcGAN: Generative Adversarial Networks for 3D Architectural Image Generation
- Creator
- Ranpara D.; Raghul V.; Devan A.M.; Shukla S.
- Description
- Due to advancements in infrastructural modulations, architectural design is one of the most peculiar and tedious processes. As the technology evolves to the next phase, using some latest techniques like generative adversarial networks, creating a hybrid architectural design from old and new models is possible with maximum accuracy. Training the model with appropriate samples makes it evident that the designing phase will be simple for even a layman by including proper parameters such as material description, structural engineering, etc. This research paper suggests a hybrid model for an architectural design using generative adversarial networks. For example, merging Romes architectural style with Italys will accurately and precisely recover the pixel-level structure of 3D forms without needing a 2D viewpoint or 3D annotations from a real 2D-generated image. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
- Source
- Lecture Notes in Electrical Engineering, Vol-1189 LNEE, pp. 75-85.
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Albedo; BiGAN; Conditional image generation; FineGAN; GAN inversion; Generative adversarial networks; MixNMatch; StyleGAN; Unsupervised 3D shape reconstruction
- Coverage
- Ranpara D., Christ (Deemed to Be University), Karnataka, Bangalore, India; Raghul V., Christ (Deemed to Be University), Karnataka, Bangalore, India; Devan A.M., Christ (Deemed to Be University), Karnataka, Bangalore, India; Shukla S., Christ (Deemed to Be University), Karnataka, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISSN: 18761100; ISBN: 978-981972450-5
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Ranpara D.; Raghul V.; Devan A.M.; Shukla S., “ArcGAN: Generative Adversarial Networks for 3D Architectural Image Generation,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19265.