三十五、Versatile Diffusion: Text, Images and Variations All in One Diffusion Model 2024.01 三十六、Diffusion Model-Based Image Editing: A Survey 2024.02 三十七、Text-to-Image Diffusion Models are Great Sketch-Photo Matchmakers 2024.03 三十八、It's All About Your Sketch: Democratising Sketch Control in...
The repository is based on our surveyDiffusion Model-Based Image Editing: A Survey. Yi Huang*, Jiancheng Huang*, Yifan Liu*, Mingfu Yan*, Jiaxi Lv*, Jianzhuang Liu*, Wei Xiong, He Zhang, Liangliang Cao, Shifeng Chen Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sci...
常用于image editing任务。在 x_t 上根据prompt去噪,可以保证保留 x_0 的部分内容。无prompt的情况下应该保证reconstruction的效果。详见 确定性加噪,确定性去噪,形式一致(ODE推导的结果)形式一致性 【SDE角度 (参考上面提到的survey,以及DDIM论文中Section 4.3)】上文提到sample的SDE方程有对应的ODE方程描述,而ODE...
We are focusing on how to Control text-to-image diffusion models with Novel Conditions.For more detailed information, please refer to our survey paper: Controllable Generation with Text-to-Image Diffusion Models: A Survey💖 CitationIf you find value in our survey paper or curated collection, ...
013 (2023-11-28) VideoAssembler Identity-Consistent Video Generation with Reference Entities using Diffusion Model https://arxiv.org/pdf/2311.17338.pdf 014 (2023-11-28) Microstructure reconstruction of 2D/3D random materials via diffusion-based deep generative models ...
022 (2023-08-25) Diff-Retinex Rethinking Low-light Image Enhancement with A Generative Diffusion Model https://arxiv.org/pdf/2308.13164.pdf 023 (2023-08-24) A Survey of Diffusion Based Image Generation Models Issues and Their Solutions
The recent wave of AI-generated content (AIGC) has witnessed substantial success in computer vision, with the diffusion model playing a crucial role in this achievement. Due to their impressive generative capabilities, diffusion models are gradually superseding methods based on GANs and auto-regressi...
扩散概率模型(DPMs)在高分辨率图像生成方面显示出显著性能,但由于通常需要大量采样步骤,其采样效率仍有待提高。高阶ODE求解在DPMs中的应用的最新进展使得能够以更少的采样步骤生成高质量图像。然而,大多数采样方法仍使用均匀的时间步长,在使用少量步骤时并不是最优的。
在未来,对扩散模型的研究也可以扩展到学习同时解决多个任务的多用途模型。创建一个扩散模型来生成多种类型的输出,同时基于各种类型的数据,例如文本、类标签或图像,可能会使我们更接近于理解开发人工通用智能(AGI)的必要步骤。 原文:Diffusion Models in Vision: A Survey...
Danielset al. [25]super-resolutionconditioned on imageNCSNCIFAR-10, CelebA Sahariaet al. [18]super-resolutionconditioned on imageDDPM++FFHQ, CelebA-HQ, ImageNet-1K Avrahamiet al. [114]image editingconditioned on image and maskDDPM, ADMImageNet, CUB, LSUN Bedroom, MS-COCO ...