1 Dataset Diffusion 问题设置:目标是生成一个合成数据集,D=(Ii,Si)i=1N,由高保真图像I和像素级语义掩码S组成。这些图像和掩码捕获目标类,,,C=c1,c2,...,cK的语义和位置信息,其中K表示类的数量。构建此数据集的目的是训练一个语义分割器Φ,而不依赖于人工注释。 文章遵循三个步骤的过程。首先,准备包含目标...
几篇论文实现代码:《Dataset Diffusion: Diffusion-based Synthetic Dataset Generation for Pixel-Level Semantic Segmentation》(NeurIPS 2023) GitHub: github.com/VinAIResearch/Dataset-Diffusion 《Intri...
Dataset Diffusion: Diffusion-based Synthetic Data Generation for Pixel-Level Semantic Segmentation (NeurIPS2023) - VinAIResearch/Dataset-Diffusion
本文提出了一种Dataset Diffusion框架生成具有像素级语义分割的合成数据集。通过利用 Stable Diffusion,该框架能够从指定的对象类产生高质量的语义分割和视觉逼真的图像。实验结果表明,Dataset Diffusion在VOC和COCO中具有卓越的mIoU,优于当前的DiffuMask方法。为使用生成模型创建具有精确注释的大规模数据集提供了新的思路。
We propose the Diffusion-Based Synthetic Speech Dataset (DiffSSD), a dataset consisting of about 200 hours of labeled speech, including synthetic speech generated by 8 diffusion-based open-source and 2 commercial generators. We also examine the performance of existing synthetic speech detectors on ...
extensive experiments on the DiFF dataset via a human test and several representative forgery detection methods. The results demonstrate that the binary detection accuracy of both human observers and automated detectors often falls below 30%, shedding light on the challenges in detecting diffusion-...
This dataset contains the diffusion times using in the This is part of the data example to demonstrate modelling NBDA with random effects.
Strong gradient systems can improve the signal-to-noise ratio of diffusion MRI measurements and enable a wider range of acquisition parameters that are beneficial for microstructural imaging. We present a comprehensive diffusion MRI dataset of 26 healthy
Stable-Diffusion热门大模型:recAnimated_v122、majicMIX_realistic_v6、Anything_v45、chilloutmix_NiPrunedFp32Fix、Grapefruit_v41、Guofeng_v33、gameIconInstitute_v30,均可直接解压使用,无需转换。 文件列表 majicMIX_realistic_v6.zip anything_v45.zip Guofeng_v33.zip Grapefruit_v41.zip chilloutmix_NiPrune...
This model uses high-level annotations, including breast types defined by BI-RADS categories, to produce a large, labeled tissue-type breast image dataset. Our prototype model integrates a U-Net with a denoising diffusion probabilistic model to generate tissue-specific 2D sagittal cross-section ...