137 datasets found

The dataset used in the paper is a collection of images synthesized using the proposed metasurface-based architecture.

The dataset used for training the generative adversarial network (GAN) model.

This dataset is used for fine-grained sketch-based image retrieval (FG-SBIR) and sketch style transfer. It contains 50,025 shoe photos.

The dataset is used to train the GlyphDraw model for visual text generation. It contains 792k images with 3.3M characters in images and more than 4.8k common unique Chinese...

Conditional Adversarial Generative Flow for Controllable Image Synthesis

Cap3D: A dataset of 3D models with corresponding images.

CADS: Unleash the diversity of diffusion models through condition-annealed sampling.

High-resolution image synthesis with latent diffusion models.

The dataset used in the paper is Dsprites and 3DShapes, which are popular disentanglement evaluation datasets.

The LLVIP dataset contains registered images in two domains of visible light and infrared light.

The Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix dataset contains 4870 registered image pairs, covering a variety of HER2 expression levels.

LSUN Conference Rooms

A dataset of 121 video sequences of common household objects, captured by GoPro Hero9 action cameras at 30 FPS and 1920 × 1080 resolution.

The dataset used in the paper is a new dataset for zero-shot performance comparison of spatial conditions.

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

The dataset used in the Discriminator Rejection Sampling (DRS) algorithm, consisting of a mixture of 25 2D-Gaussian distributions.

The dataset used in the paper is LSUN bedroom and church-outdoor datasets (64×64).

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the Stable Diffusion Model (SDM) v1.5.

SynArtifact-1K is a comprehensive dataset of synthetic images with artifact annotations, constructed to fine-tune Vision-Language Model (VLM) as artifact classifier.

The dataset is used for training and testing the proposed VTGAN model for fundus-to-angiogram synthesis and disease prediction.