A New Conditional Diffusion Consistency Remark 1. 作者这里说在noise prediction上满足self-coinsistency性质的diffusion model,在signal prediction上也同样满足。 这是因为原始的Consistency model是约束的PF ODE轨迹上两个点的去噪图像的一致性,而这里作者用了预测噪声一致性来代替。这里的边界条件也是通过喝consistency...
Enhanced Conditional Diffusion Models for Virtual Try-on Computer Vision Lab, DAMO Academy 1. Abstract Virtual try-on technology aims to improve the shopping experience by enabling customers and businesses to visualize how clothing items look when worn, using only digital images of the garments. Adva...
During the training stage, the gradient of the conditional distribution is approximated by using a conditional diffusion model to predict the noise added to the original urban morphology. In the generation stage, the corresponding conditional distribution is parameterized based on the noise predict...
We call this process a conditional diffusion process. We obtain the generator of the conditional diffusion process. We compare the original generator with that of the conditional diffusion process, and find a relation between these generators. By using this relation, we show some properties of the...
Conditional Diffusion MNIST script.pyis a minimal, self-contained implementation of a conditional diffusion model. It learns to generate MNIST digits, conditioned on a class label. The neural network architecture is a small U-Net (pretrained weights also available in this repo). This code is modi...
In this article, we propose an augmented conditional denoising diffusion probabilistic model with spatial-frequency refinement (SFDiff) for high-fidelity S2O image translation. SFDiff progressively narrows the gap between synthesized and real images in both spatial and frequency perspectives, showcasing ...
In this work, we introduced DiffLinker, a new E(3)-equivariant 3D conditional diffusion model for molecular linker design. Our method showed several desirable and practical features that have the potential to help accelerate the development of prospective drug candidates using FBDD strategies. ...
This paper propose the Patch-based Simplified Conditional Diffusion Model (PSC Diffusion) for low-light image enhancement due to the outstanding performance of diffusion models in image generation. Specifically, recognizing the potential issue of gradient vanishing in extremely low-light images due to ...
与baseline Diffusion Models不同的是,Kaleido 引入了一个Autoregressive Model,以T5的decoder进行初始化。Autoregressive Model的目的是将原始的caption条件,离散化成更加丰富的条件。在训练阶段是和Diffusion一起优化的。Text Encoder的输出以cross attention的形式作用在Autoregressive Model上,迭代预测下一个token。最终训练好...
因此,本文提出了一种离散条件扩散重排序(DCDR,Discrete Conditional Diffusion Reranking)框架,并且为了实现高效、稳健的推理,提出了一系列技术来实现 DCDR 在现实生活中的推荐系统中的部署。 简单介绍一下扩散模型 典型的扩散模型由两部分组成,正向过程和反向过程。