Machine learningDeep learning / NLP / CV
多模态生成对抗网络
多模态生成对抗网络（Multimodal GAN）是一种以多于一种数据模态（例如，文本描述、图像、音频或结构化数据）为条件或跨多种数据模态联合学习的生成对抗网络。通过融合来自多个来源的信息，生成器可以合成符合跨模态约束的逼真输出，从而实现文本到图像合成、图像到音频生成以及联合模态填充等任务。
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来源
- Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., & Lee, H. (2016). Generative adversarial text to image synthesis. Proceedings of the 33rd International Conference on Machine Learning (ICML), PMLR 48, 1060–1069. link ↗
- Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative adversarial nets. Advances in Neural Information Processing Systems (NeurIPS), 27. link ↗
如何引用本页
ScholarGate. (2026, June 3). Multimodal Generative Adversarial Network. ScholarGate. https://scholargate.app/zh/deep-learning/multimodal-gan
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