系统梳理扩散模型的噪声调度设计及其对生成质量的影响
A Comprehensive Review on Noise Control of Diffusion Model
- 分析不同噪声调度策略的设计原理与差异
- 揭示噪声调度对采样和训练质量的关键影响
- 适合研究生成模型或优化扩散过程的读者
扩散模型近年来成为生成高质量图像的强大框架。其核心组件之一是噪声调度，它控制扩散过程中噪声注入的速率。由于噪声调度显著影响采样质量和训练效果，理解其设计与影响至关重要。本文探讨了多种噪声调度方法，突出它们的特点与性能表现。
原文摘要 · Abstract (English)
Diffusion models have recently emerged as powerful generative frameworks for producing high-quality images. A pivotal component of these models is the noise schedule, which governs the rate of noise injection during the diffusion process. Since the noise schedule substantially influences sampling quality and training quality, understanding its design and implications is crucial. In this discussion, various noise schedules are examined, and their distinguishing features and performance characteristics are highlighted.
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