과제정보
이 논문은 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2021R1F1A1047492)
참고문헌
- Cao, Y., Jia, L., Chen, Y., Lin, N., Yang, C., Zhang, B., Liu, Z., Li, X., Dai, H. (2019). Recent Advances of Generative Adversarial Networks in Computer Vision, IEEE Access, 7, pp. 14985-15006. https://doi.org/10.1109/access.2018.2886814
- Choi, Y., Choi, M., Kim, M., Ha, J. W., Kim, S., Choo, J. (2018). Stargan: Unified generative adversarial networks for multi-domain image-to-image translation, In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 8789-8797.
- Chung, M. Y., Lee, H. S. (2019). Classification of emotional adjective for the hospital indoor image based on deep learning, Journal of the Korean institute of interior design, 28(6), pp. 75-85. https://doi.org/10.14774/jkiid.2019.28.6.075
- Han, S. K., Shin, D. Y. (2021). A study on architectural image generation using artificial intelligence algorithm: A fundamental study on the generation of due diligence images based on architectural sketch, Journal of KIBIM, 11(2), pp. 54-59. https://doi.org/10.13161/KIBIM.2021.11.2.054
- Han, S. W., Lee, K. S. (2002). Modeling for estimation of improving indoor environment using interior plants, Journal of the Korean institute of interior landscape architecture, 4(2), pp. 79-89.
- Johnson, J., Alahi, A., Fei-Fei, L. (2016). Perceptual losses for real-time style transfer and super-resolution, In European conference on computer vision, pp. 694-711.
- Kim, J. S., Lee, J. K. (2020). Implementation and application of interior design style training model using deep learning, Journal of the Korean institute of interior design, 29(5), pp. 96-104. https://doi.org/10.14774/JKIID.2020.29.5.096
- Kim, S. K. (2018). A study on the development plan of domestic home furnishing industry, Journal of the Korean furniture society, 29(4), pp. 228-244.
- Kim, S. W., Park, K. H. (2018). U-net and Residual-based Cycle-GAN for improving object transfiguration performance, The Journal of Korea Robotics Society, 13(1), pp. 1-7. https://doi.org/10.7746/jkros.2018.13.1.001
- Lee, D. J., Ko, E. H. (2011). A study on the relationship between personality and interior style preference, Journal of the architectural institute of Korea planning & design, 27(2), pp. 99-106.
- Liu, Y. (2021). Improved generative adversarial network and its application in image oil painting style transfer, Image and Vision Computing, 105, 104087. https://doi.org/10.1016/j.imavis.2020.104087
- Min, J. H., Choi, G. S. (2014). Study on color & texture image of finishing material by interior component: centered on interior desing style type, Journal of Korea society of color studies, 28(4), pp. 75-87. https://doi.org/10.17289/jkscs.28.4.201411.75
- Sun, T., Jung, C., Fu, Q., Han, Q. (2019). Nir to rgb domain translation using asymmetric cycle generative adversarial networks, IEEE Access, 7, pp. 112459-112469. https://doi.org/10.1109/access.2019.2933671
- Ye, X., Du, J., Ye, Y. (2021). MasterplanGAN: Facilitating the sma rt rende r ing of u rban maste r p lans v ia generative adversarial networks, Environment and Planning B: Urban Analytics and City Science, doi: 10.1177/23998083211023516
- Zhan, F., Huang, J., Lu, S. (2019). Adaptive composition gan towards realistic image synthesis, arXiv preprint arXiv:1905.04693v1
- Zhu, J. Y., Park, T., Isola, P., Efros, A. A. (2017). Unpaired image-to-image translation using cycle-consistent adversarial networks, In Proceedings of the IEEE international conference on computer vision, pp. 2223-2232.