71 datasets found

A novel Context-RNN-GAN model for diagrammatic abstract reasoning and image generation

We present a novel approach for generating minority samples that live on low-density regions of a data manifold.

Diffusion models are widely used in image generation because they can generate high-quality and realistic samples.

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.

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.

The dataset used in the paper is a set of true images and simulated images produced by a custom simulation technique. The true images are experimental data images, and the...

The dataset used in the paper is a set of true images and simulated images produced by a custom simulation technique. The true images are experimental data images, and the...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a large-scale text-to-image model to generate images with multiple subjects.

MARS is an innovative auto-regressive framework that not only retains the capabilities of pre-trained Large Language Models (LLMs) but also incorporates top-tier text-to-image...

The dataset used in the paper is DPM-Solver++

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a pre-trained model to generate images.

Image generation from scene graphs is a task in computer vision that requires generating images from graph-structured inputs, such as scene graphs.

Generating images from graph-structured inputs, such as scene graphs, is uniquely challenging due to the difficulty of aligning nodes and connections in graphs with objects and...

A text-to-image diffusion model trained on a recaptioned dataset to improve image generation quality and semantic alignment.

Relational CLEVR is a synthetic dataset of rendered 3D objects of various colours, shapes, sizes and textures.

Positional CLEVR is a synthetic dataset of rendered 3D objects of various colours, shapes, sizes and textures.