2.提供了一种更高效的SD Unet模块,比原生的Unet效果更好,效率更高,同时给出了一种更高效的数据蒸馏方案。 3.使用v-prediction 代替传统的噪声估计 e-prediction,同时在蒸馏的算法流程中,引入了历史算法中都未引入的CFG功能。 4.最后还增加了训练步骤的策略优化,尤其是针对学生-教师网络在端上模型的优化。 模型结...
下面我摘抄两段github上的话,很好地总结了这个阶段的模型的发展:Stable Diffusion v1 refers to a specific configuration of the model architecture that uses a downsampling-factor 8 autoencoder with an 860M UNet and CLIP ViT-L/14 text encoder for the diffusion model. The model was pretrained on 25...
2)更好的收敛性:在某些情况下,v-prediction可能有助于模型更快地收敛到最优解,因为它提供了一种更直接的方式来模拟噪声的去除过程。 使用以上公式 在进行预测的过程中,将原本需要预测的ε,v。 为什么专门提这个?因为在很多比较新的视频及3D生成算法工作中都提到了v-Prediction 替换掉ε-Prediction。 当然详细的公...
During training, the model is trained to inverse the noisy ground truth map, while during testing, the model is inferred to remove noise from its “imperfect” prediction, which drifts away from the underlying corrupted distributions. This drift becomes pronounced with smaller time steps t, owing...
173 (2023-10-31) Adaptive Latent Diffusion Model for 3D Medical Image to Image Translation Multi-modal Magnetic Resonance Imaging Study https://arxiv.org/pdf/2311.00265.pdf 174 (2023-11-6) SEINE Short-to-Long Video Diffusion Model for Generative Transition and Prediction ...
New stable diffusion model (Stable Diffusion 2.0-v) at 768x768 resolution. Same number of parameters in the U-Net as 1.5, but uses OpenCLIP-ViT/H as the text encoder and is trained from scratch. SD 2.0-v is a so-called v-prediction model. The above model is finetuned from SD ...
Diffsound: Discrete Diffusion Model for Text-to-sound Generation Dongchao Yang, Jianwei Yu, Helin Wang, Wen Wang, Chao Weng, Yuexian Zou, Dong Yu arXiv 2022. [Paper] [Project] 20 Jul 2022 Zero-Shot Voice Conditioning for Denoising Diffusion TTS Models Alon Levkovitch, Eliya Nachmani...
样本取自U-Net模型,引导比例为4。Figure 2: Generated images with simple diffusion. Importantly, each image is generated in full image space by a single diffusion model without any cascades (super-resolution) or mixtures of experts. Samples are drawn from the U-Net model with guidance scale 4....
Image generators are, in a sense, prediction machines. The idea is that by providing a trained model with a short history of what just happened plus the user’s input as context, it can generate a pretty usable prediction of what should happen next, and do it quickly enough to be interac...
3. 连续时间的两种diffusion model:diffusion SDE与diffusion ODE 深度生成模型除了可以生成数据以外,还有一类核心任务是估计数据的概率密度(可以用模型计算的数据似然(likelihood)来刻画)。GAN被诟病的一点就是无法计算似然,因为它是隐式生成模型(implicit generative model),这导致GAN无法被用来数据压缩等领域。而VAE只能...