题目:DiffMap: Enhancing Map Segmentation with Map Prior Using Diffusion Model 名称:DiffMap:使用扩散模型增强地图先验的地图分割 论文:arxiv.org/abs/2405.0200 代码: 单位:清华、戴姆勒 6.Depth/深度估计 Diffusion4RobustDepth 题目:Diffusion Models for Monocular Depth Estimation: Overcoming Challenging Conditio...
生成模型 首先,目标是通过priorz采样x,使得生成概率最大化: max∑i=1nlogpθ(xi) 概念 首先回顾一下General Latent Variable Model。 Latent variables, as created by factor analytic methods, generally represent “shared” variance, or the degree to which variables “move” together 从数据中提取出来...
实验结果表明,方法仅使用少量时间步长就实现出色的性能,例如在ImageNet 64×64上使用仅四个步骤,FID得分达到了17.86,而使用DDIM则为138.66。 9、DPM-OT: A New Diffusion Probabilistic Model Based on Optimal Transport 从扩散概率模型(DPMs)中进行采样可以看作是一个分段分布转换,通常需要反扩散轨迹的几百或几千...
The SIR model can be regarded as a generalization of the IC model, as the latter appears to be a special case of SIR in which β=1. In practice, the diffusion process may be repeated many times and the mean of the obtained results may be used to estimate the influence of initial ...
8、AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration 扩散模型生成一张图像通常需要大量的时间步骤(推理步骤)。为加速这个繁琐的过程,统一地减少步骤被认为是扩散模型的不争之论的原则。然而,这样的统一假设在实践中并不是最优解;也就是说,对于不...
28、CosmicMan: A Text-to-Image Foundation Model for Humans 提出CosmicMan,一种用于生成高保真人体图像的文本到图像基础模型。与当前困在人体图像质量和文本-图像不对齐困境中的通用基础模型不同,CosmicMan能够生成具有细致外貌、合理结构和精确文本-图像对齐的逼真人体图像,同时还提供详细的密集描述。CosmicMan关键在于...
usp=sharing#scrollTo=zOsoqPdXHuL5 def loss_fn(model, x, marginal_prob_std, eps=1e-5): """Compute the loss function. 参考公式 (5) Args: model: A score model. batch: A mini-batch of training data. Returns: loss: A scalar that represents the average loss value across the mini-...
Generative models allow you to synthesize novel data that is different from the real data but still looks just as realistic. A designer could train a generative model on images of cars and then let the resulting generative AI computationally dream up novel cars with different looks, accelerating ...
We can map data to a noise distribution (the prior) with an SDE and reverse this SDE for generative modeling: Source Denoising diffusion probabilistic models (DDPMs) Denoising diffusion probabilistic models (DDPMs) are a specific type of diffusion model that focuses on probabilistically removing ...
Finally, we highlight open-source diffusion model tools and consider the future applications of diffusion models in bioinformatics. Key points Diffusion models are a generative artificial intelligence technology that can be applied in natural language processing, image synthesis and bioinformatics. Diffusion...