Publisher
Springer Nature Switzerland
Reference84 articles.
1. Achlioptas P, Diamanti O, Mitliagkas I, Guibas L (2018) Learning representations and generative models for 3D point clouds. In: Dy J, Krause A (eds) Proceedings of the 35th international conference on machine learning. PMLR, pp 40–49
2. Aldausari N, Sowmya A, Marcus N, Mohammadi G (2022) Video generative adversarial networks: a review. ACM Comput Surv 55. https://doi.org/10.1145/3487891
3. Antipov G, Baccouche M, Dugelay J-L (2017) Face aging with conditional generative adversarial networks. In: 2017 IEEE international conference on image processing (ICIP). IEEE Press, pp 2089–2093
4. Arjovsky M, Chintala S, Bottou L (2017) Wasserstein generative adversarial networks. In: Precup D, Teh YW (eds) Proceedings of the 34th international conference on machine learning. PMLR, pp 214–223
5. Azadi S, Pathak D, Ebrahimi S, Darrell T (2020) Compositional GAN: learning image-conditional binary composition. Int J Comput Vis 128:2570–2585. https://doi.org/10.1007/s11263-020-01336-9
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. An Innovation of Exploiting Generative Adversarial Networks to Augment Virtual Reality Experiences;2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC);2024-01-29
2. The Possibilities of AI and Augmented Reality in Education;2024 IEEE International Conference on Consumer Electronics (ICCE);2024-01-06