原文:One Step Diffusion via Shortcut Models github:GitHub - kvfrans/shortcut-models 摘要 为了缓解目前diffusion架构+flow matching生成速度慢且训练阶段复杂的问题提出了一个叫shortcut model的模型,整个训练过程采用单一网络、单一训练阶段。condition包括当前噪声强
这篇论文提出了快捷模型(shortcut models),用于解决单次生成高质量图像的问题。具体来说, 快捷模型的核心思想:快捷模型通过在给定当前噪声水平和期望步长的情况下,条件化网络,使其能够在生成过程中跳过一些步骤。这种方法类似于在训练时进行自蒸馏,因此不需要单独的蒸馏步骤,并且可以在单次运行中完成训练。训练...
[LG]《One Step Diffusion via Shortcut Models》K Frans, D Hafner, S Levine, P Abbeel [UC Berkeley] (2024) http://t.cn/A6EedLbK #机器学习##人工智能##论文#
作者期待通过蒸馏更先进的模型和引入变化的指导尺度,进一步提升模型性能和灵活性。 图1展现了一下和目前SOTA方法的对比: 基线稳定扩散(Stable Diffusion, SD):生成每张图像需要约250毫秒。扩散匹配蒸馏(Diffusion Matching Distillation, DMD):生成每张图像仅需约90毫秒。强调了DMD技术生成图像的速度比SD快得多,同时还在...
论文介绍 One-step Diffusion with Distribution Matching Distillation 关注微信公众号: DeepGoAI 源码地址: https://tianweiy.github.io/dmd/ 论文地址: https://arxiv.org/abs/2311.18828 这篇论文介绍了一种新的图像生成方法,名为分布匹配蒸馏(DMD),将扩散模型转换为一步生成器,极大地加快了图像生成速度,同时...
网络单步扩散;一次扩散 网络释义
A simplified process of making an insulated gate transistor entails forming the active regions in a single diffusion step. The method includes the steps of implanting and diffusing impurities of a first conductivity type (p for n-channel devices), implanting and diffusing a heavy dose of ...
Combined with a simple regression loss to match the output of the multi-step diffusion model, our method outperforms all published few-step diffusion approaches, reaching 2.62 FID on ImageNet 64x64 and 11.49 FID on zero-shot COCO-30k, comparable to Stable Diffusion but orders of magnitude ...
Diffusion models (DMs) have significantly advanced the development of real-world image super-resolution (Real-ISR), but the computational cost of multi-step diffusion models limits their application. One-step diffusion models generate high-quality images in a one sampling step, greatly reducing ...
Diffusion models (DMs) have significantly advanced the development of real-world image super-resolution (Real-ISR), but the computational cost of multi-step diffusion models limits their application. One-step diffusion models generate high-quality images in a one sampling step, greatly reducing comput...