Machine learningDeep Learning, Generative Models
潜在扩散模型
潜在扩散模型（LDMs）是Rombach等人于2022年提出的一种生成方法，它在压缩的潜在空间而不是像素空间中执行扩散过程，从而能够高效地合成高分辨率图像。通过使用变分自编码器将图像压缩为低维潜在表示，扩散过程在计算上变得可行，同时保持了视觉质量。
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来源
- Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2022). High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 10684-10695). DOI: 10.1109/CVPR52688.2022.01042 ↗
如何引用本页
ScholarGate. (2026, June 3). High-Resolution Image Synthesis with Latent Diffusion Models. ScholarGate. https://scholargate.app/zh/deep-learning/latent-diffusion-models
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