很明显,所提出的 BBDM 方法在所有四个任务上都实现了最佳的 FID 性能,并获得了有竞争力的 LPIPS 分数。 Other Translation Tasks 为了进一步验证 BBDM 的泛化性,我们在 VisualGENOME [17] 上进行了修复、着色实验,在 CelebAMaskHQ [18] 上进行了face-to-label实验。图6中的实验结果表明,BBDM可以在各种...
proposed a general framework for image-to-image translation called Pix2Pix [1]. Pix2Pix has shown superior performance on multiple image-to-image translation tasks, and its model structure is simpler than other image-to-image translation models, with stronger training reliability. The original Pix...
While initial solutions to the I2I problem were provided by generative adversarial neural networks (GANs), diffusion models (DMs) currently hold the state-of-the-art status on the I2I translation benchmarks in terms of Frechet inception distance (FID). 什么是I2I问题?I2I问题是指图像到图像(Image-...
Pre title: BBDM: Image-to-Image Translation With Brownian Bridge Diffusion Models source: CVPR 2023 paper: https://arxiv.org/abs/2205.07680 code: http
Image-to-Image Translation.两大挑战:如何处理未配对数据、如何建模多样的转换(translation)。 Vector Quantized Generative Models.生成模型可以粗略地分为两类:隐式和显式的密度估计方法(density estimation methods)。GAN是隐式方法的代表,合成质量高但是训练不稳定,而显式方法易于训练但是输出相对模糊(VAE)或由于自回...
Current image-to-image translation methods formulate the task with conditional generation models, leading to learning only the recolorization or regional changes as being constrained by the rich structural information provided by the conditional contexts. In this work, we propose introducing the vector ...
Zero-shot Image-to-Image Translation 零镜头图像到图像的转换 Large-scale text-to-image generative models have shown their remarkable ability to synthesize diverse and high-quality images. However, it is still challenging to directly apply these models for editing real images for two reasons. First,...
AI models for image translation Image-to-image translation and generative AI in general are touted for being cost-effective, but they're alsocriticized for lacking creativity. It's essential to research thevarious AI modelsthat have been developed to handle image-to-image translation tasks, as ea...
appearance of the back view can be predicted reliably using an image-to-image translation network. While classic methods based on parametric models often fail for single-view images of subjects with challenging clothing, our approach can still produce successful results, which are comparable to those...
Common image-to-image translation methods rely on joint training over data from both source and target domains. The training process requires concurrent access to both datasets, which hinders data separation and privacy protection; and existing models cannot be easily adapted to translation of new dom...