House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects

Nelson Nauata, Sepidehsadat Hosseini, Kai-Hung Chang, Hang Chu, Chin-Yi Cheng, Yasutaka Furukawa. House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19-25, 2021. pages 13632-13641, Computer Vision Foundation / IEEE, 2021. [doi]

@inproceedings{NauataHCCCF21,
  title = {House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects},
  author = {Nelson Nauata and Sepidehsadat Hosseini and Kai-Hung Chang and Hang Chu and Chin-Yi Cheng and Yasutaka Furukawa},
  year = {2021},
  url = {https://openaccess.thecvf.com/content/CVPR2021/html/Nauata_House-GAN_Generative_Adversarial_Layout_Refinement_Network_towards_Intelligent_Computational_Agent_CVPR_2021_paper.html},
  researchr = {https://researchr.org/publication/NauataHCCCF21},
  cites = {0},
  citedby = {0},
  pages = {13632-13641},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19-25, 2021},
  publisher = {Computer Vision Foundation / IEEE},
}