193 datasets found

The data distribution is taken to be a 25-dimensional Gaussian distribution, generated by mixture of gaussians.

The data distribution is taken to be a one-dimensional Gaussian distribution, P0(x0) = N (x0 | 0, v0).

ImageNet [9] and CC-3M [43] datasets

LSUN-{cat, bedroom, church} [48] and FFHQ [25] datasets

MPI3DToy is the most complex dataset containing 1,036,800 images from seven data generative factors captured from real-world robotics experiments.

CelebA and Chairs are the two datasets utilised by Higgins et al. (2016) for qualitative evaluation.

Higgins et al. (2016) use a number of standard image datasets to evaluate both image generation properties of β-VAEs and specially designed datasets for evaluating...

AutoStudio is a multi-agent training-free framework that addresses multi-turn interactive image generation successfully.

The dataset used in this paper is a face-related task with ControlNet. The dataset contains images with different poses and conditions.

The dataset used in this paper is a style-guided generation task with Stable Diffusion. The dataset contains images with different styles and prompts.

The dataset used in the paper for training and testing the Denoising Diffusion Implicit Models.

The dataset used in this paper is a diffusion model for image generation.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used pre-trained DDPMs on ImageNet 64x64, ImageNet 128x128, and LSUN 256x256.

The dataset used in the paper for consistent image generation and video generation.

Text-to-image models, such as DDIM or PLMS.

Language-guided image diffusion models, such as OpenCLIP and LAION-5B.

A dataset used by the authors to test their hypothesis about the white bear phenomenon in large models.

A dataset generated by the authors to test their hypothesis about the white bear phenomenon in large models.

CelebA, FFHQ, and Teapots datasets for image generation.

High-fidelity image generation with fewer labels