Author:
Zhang Jiangning,Xu Chao,Liu Liang,Wang Mengmeng,Wu Xia,Liu Yong,Jiang Yunliang
Publisher
Springer International Publishing
Reference35 articles.
1. Aigner, S., Körner, M.: FutureGAN: anticipating the future frames of video sequences using spatio-temporal 3D convolutions in progressively growing GANs. arXiv preprint arXiv:1810.01325 (2018)
2. Cai, H., Bai, C., Tai, Y.W., Tang, C.K.: Deep video generation, prediction and completion of human action sequences. In: ECCV, pp. 366–382 (2018)
3. Dosovitskiy, A., et al.: FlowNet: learning optical flow with convolutional networks. In: ICCV, pp. 2758–2766 (2015)
4. Goodfellow, I., et al.: Generative adversarial nets. In: NeurIPS, pp. 2672–2680 (2014)
5. Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., Courville, A.C.: Improved training of Wasserstein GANs. In: NeurIPS, pp. 5767–5777 (2017)
Cited by
17 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. A single 3D shape wavelet-based generative model;Computers & Graphics;2024-04
2. Single to Diverse Video Generation Using Conditional Diffusion Probabilistic Model;2024 1st International Conference on Cognitive, Green and Ubiquitous Computing (IC-CGU);2024-03-01
3. A Benchmark for Controllable Text -Image-to-Video Generation;IEEE Transactions on Multimedia;2024
4. Aesthetics-Driven Virtual Time-Lapse Photography Generation;Proceedings of the 31st ACM International Conference on Multimedia;2023-10-26
5. Animated lightning bolt generation using machine learning;2023 Twelfth International Conference on Image Processing Theory, Tools and Applications (IPTA);2023-10-16