model.to(device) model.eval()withtorch.no_grad():#x [b, 1, 28, 28]#x_hat[b, 1, 28, 28]x_hat, _, _ = model(x) n = x.shape[0]#b(4)n1 =int(n**0.5)#2#x_cat = torch.concat((x, x_hat), 3)x_cat = torch.cat((x, x_hat),3)#[b, 1, 28, 56]x_cat = e...
《VQ-VAE》:Stable Diffusion设计的架构源泉 VQ-VAE为图像生成类任务提供了一种新的思路。VQ-VAE的这种建模方法启发了无数的后续工作,包括声名远扬的Stable Diffusion stable diffusion 人工智能 编码器 正态分布 图像编码 原创精选 wx5ecc8c432b706 2月前 ...
DeTiME: Diffusion-Enhanced Topic Modeling using Encoder-decoder based LLM Weijie Xu, Wenxiang Hu, Fanyou Wu, Srinivasan H. Sengamedu 2023 Neural Sinkhorn Topic Model He Zhao, Dinh Q. Phung, Viet Huynh, Trung Le, W. Buntine 2020 CWTM: Leveraging Contextualized Word Embeddings from BERT for ...
The diffusion model is trained to generate intermediate music sequences consisting of codebook indexes, which are then decoded to symbolic music using the VQ-VAE’s decoder. Dataset Transform the MIDI files from the MAESTRO dataset into pianorolls and then use the trained VQ-VAE to encode the ...
This project initially started out as an experiment in usingVQ-VAE+ a diffusion model for speaker conversion. The results are now quite reasonable, but I am still working on improvements. Using this codebase, you can record yourself speaking and change the voice in the recording without changing...
In this paper, many deep learning approaches to attain artist music style transfer were explored with the main focus being approaches related to Vector Quantized Variational AutoEncoder (VQ-VAE) model along with diffusion model using U-Net architecture, primarily on Indian artists and music. ...
2.目前最火的不是Diffusion Model嘛!能不能用扩散模型生成Z? YES!YES!恭喜你,根据这个思路就设计出了Latent-Diffusion! 之后我们会继续讲解这两篇论文! 发布于 2023-09-26 15:08・山东 深度学习(Deep Learning) 计算机视觉 生成式AI 写下你的评论... ...
这也是 Latent Diffusion 和 VQ-Diffusion 的不同之处。 ModelStage-1(latent space learning)Latent SpaceStage-2(prior learning) VQ-VAE VQ-VAE Discrete(after quantization) AutoregressivePixelCNN VQGAN VQGAN(VQ-VAE + GAN + Perceptual Loss) Discrete(after quantization) AutoregressiveGPT-2 (Transformer) ...
至此就将文生图模型最基本的模块DDPM讲完,那文生图模型又是如何引导模型生成图片的呢? 涉及到的两种引导模型,Classifier Guided Diffusion Model和Classifier-Free Guided Diffusion Model,涉及到如下两篇论文。需要继续探索...
之后切开的两个token分别进行RVQ,所以在这个model中的quantizer就变成了两个,最后vq之后的两个token做一个concat就得到了进入Decoder之前的token Z_q 。具体流程如下图所示: Group_RVQ的过程 那么上面有个坑,为什么在多码本的情况下,RVQ的信息都集中在第一个码本呢? 大家可以去看 Encodec 的这个py文件的第...