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.
Flow Matching Guide and Code
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.
- Year
- 2024
- Venue
- arXiv 2024
- Authors
- 10
- Hosting
- Abstract onlyARXIV-DEFAULT
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Attribution
- Abstract & full text
- arxiv.org/abs/2412.06264ARXIV-DEFAULT
- TL;DR
- Semantic Scholar