感知压缩权衡(Perceptual Compression Tradeoffs) LDM生成效果(Image Generation with Latent Diffusion) 效果展示 参考 引言 最近大火的AI作画吸引了很多人的目光,AI作画近期取得如此巨大进展的原因个人认为有很大的功劳归属于Stable Diffusion的开源。Stable diffusion是一个基于Latent Diffusion Models(潜在扩散模型,LDMs)的文...
Based on the observations that the image conditions of I2I models already provide rich information on image structures, and that the time steps with a larger impact tend to be biased, we develop surprisingly simple yet effective approaches for reducing the model size and latency. We validate the...
2,图片感知压缩(Perceptual Image Compression)对应图最左边AutoEncoder部分 3,潜在扩散模型(Latent Diffusion Models)对应图1中间部分 4,条件机制(Conditioning Mechanisms)对应图1右边部分 三 论文贡献 一引言 Diffusion model大获成功,但是它的短板也很明显,需要大量的计算资源,并且推理速度比较慢。如何才能提升...
对于像ImageNet这样的复杂数据集，需要降低压缩率以避免降低质量。总之，LDM-4和-8提供了较高质量的合成结果。Diffusion model与GAN相比的优劣势一、优点Diffusion Model相比于GAN，明显的优点是避免了麻烦的对抗学习。此外，还有几个不太明显的好处：首先，Diffusion Model可以“完美”用latent去表示图片，因为我们可以用...
一、图片感知压缩(Perceptual Image Compression) 感知压缩本质上是一个tradeoff。之前的许多扩散模型没有使用这种技术也可以进行,但是原有的非感知压缩的扩散模型存在一个很大的问题,即在像素空间上训练模型时,如果希望生成高分辨率的图像,则训练空间也是高维的。感知压缩通过使用自编码模型,忽略高频信息,只保留重要的基础...
For a given image, its corresponding text embedding is learned usingthe same optimization process as the text-to-image diffusion model itself, using a learnable textembedding as input after bypassing the original transformer. The optimization is applied together witha learning compression model to ...
Image Compression and Decompression Framework Based on Latent Diffusion Model for Breast Mammography InChan Hwang, MinJae Woo [8th Oct, 2023] [arXiv, 2023] [Paper]InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion Model Jueqi Wang, Jacob Levman, Walter Hugo Lopez Pinaya,...
Compression is an important field of digital image processing where well-engineered methods with high performance exist. Partial differential equations (PDEs), however, have not much been explored in this context so far. In our paper we introduce a novel framework for image compression that makes ...
Learning to Explore Distillability and Sparsability: A Joint Framework for Model Compression InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions Galactica: A Large Language Model for Science DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models...
基于 NNCF 和 Optimum 面向 Intel CPU 对 Stable Diffusion 优化 基于隐空间的扩散模型 (Latent Diffusion Model)，是解决文本到图片生成问题上的颠覆者。Stable Diffusion 是最著名的一例，广泛应用在商业和工业。Stable Diffusion 的想法简单且有效: 从噪声向量开始，多次去噪，以使之在隐空间里逼近图片的表示。但是...