论文标题
生成扩散模型的调查
A Survey on Generative Diffusion Model
论文作者
论文摘要
深层生成模型已解锁了人类创造力的另一个深刻的领域。通过在数据中捕获和概括模式，我们进入了全面的人工智能（AIGC）的时代。值得注意的是，被认为是最重要的生成模型之一的扩散模型将人类的意念归于各种领域的切实实例，包括图像，文本，语音，生物学和医疗保健。为了提供对扩散的先进和全面的见解，这项调查从三个不同的角度全面阐明了其发展轨迹和未来的方向：扩散，算法增强功能的基本表述以及扩散的流形应用。精心探索每一层，以对其进化有深刻的理解。 https://github.com/chq1155/a-survey-on-generative-diffusion-model中介绍了结构化和汇总方法。
Deep generative models have unlocked another profound realm of human creativity. By capturing and generalizing patterns within data, we have entered the epoch of all-encompassing Artificial Intelligence for General Creativity (AIGC). Notably, diffusion models, recognized as one of the paramount generative models, materialize human ideation into tangible instances across diverse domains, encompassing imagery, text, speech, biology, and healthcare. To provide advanced and comprehensive insights into diffusion, this survey comprehensively elucidates its developmental trajectory and future directions from three distinct angles: the fundamental formulation of diffusion, algorithmic enhancements, and the manifold applications of diffusion. Each layer is meticulously explored to offer a profound comprehension of its evolution. Structured and summarized approaches are presented in https://github.com/chq1155/A-Survey-on-Generative-Diffusion-Model.
