Flow Matching生成模型详解与代码工具包，助你快速上手
Flow Matching Guide and Code
- 系统梳理流匹配的数学原理与设计选择
- 提供图像、文本生成等完整PyTorch示例
- 适合想入门或深入研究生成模型的研究者
流匹配（Flow Matching, FM）是一种近期的生成建模框架，在图像、视频、音频、语音及生物结构等多个领域均取得了顶尖性能。本指南全面且自包含地回顾了FM的数学基础、设计选择与扩展方法，并提供一个基于PyTorch的工具包，包含图像与文本生成等实例。该工作旨在为初学者与资深研究者提供理解、应用和进一步开发流匹配的实用资源。
原文摘要 · Abstract (English)
Flow Matching (FM) is a recent framework for generative modeling that has achieved state-of-the-art performance across various domains, including image, video, audio, speech, and biological structures. This guide offers a comprehensive and self-contained review of FM, covering its mathematical foundations, design choices, and extensions. By also providing a PyTorch package featuring relevant examples (e.g., image and text generation), this work aims to serve as a resource for both novice and experienced researchers interested in understanding, applying and further developing FM.
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