Machine learning
CLIP — 对比语言图像预训练
CLIP（对比语言图像预训练）是 OpenAI 于 2021 年由 Radford 等人提出的一个视觉语言模型，它通过在 4 亿个互联网来源的图像-文本对上进行训练，使用对比目标来联合学习对齐的图像和文本表示，从而能够对图像分类任务进行零样本迁移，而无需任何特定任务的微调。
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来源
- Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., & Sutskever, I. (2021). Learning Transferable Visual Models From Natural Language Supervision. Proceedings of the 38th International Conference on Machine Learning, PMLR 139, 8748–8763. link ↗
- Radford, A., et al. (2021). Learning Transferable Visual Models From Natural Language Supervision. arXiv:2103.00020. link ↗
- Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. ISBN: 978-0-262-03561-3
如何引用本页
ScholarGate. (2026, June 3). Contrastive Language-Image Pretraining. ScholarGate. https://scholargate.app/zh/deep-learning/clip
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