136 datasets found

Gaussian Shading: Provable Performance-Lossless Image Watermarking for Diffusion Models

The dataset used in this paper is a combined dataset of the TI dataset of 5 concepts, and the dataset from DreamBooth with 20 concepts.

The dataset used for testing the Concept Sliders, consisting of paired image data and text prompts.

The dataset used for training the Concept Sliders, consisting of paired image data and text prompts.

The authors present a photorealistic text-to-image diffusion model with deep language understanding.

ControlVideo is a general framework to utilize T2I diffusion models for one-shot video editing, which incorporates additional conditions such as edge maps, the key frame and...

Semi-autoregressive simplex-based diffusion language model for text generation and modular control

Diffusion models have successfully been applied to generative tasks in various continuous domains. However, applying diffusion to discrete categorical data remains a non-trivial...

Vidu is a high-definition text-to-video generator that demonstrates strong abilities in various aspects, including duration, coherence, and dynamism of the generated videos, on...

The dataset used in the paper for scene text manipulation with diffusion models.

NewEpisode benchmark is a dataset for story character customization, containing refined pretraining data and plenty of data for training and testing story character...

The dataset used in the paper is a text-to-image diffusion model, which is a type of generative model that can generate images from text prompts.

Photoacoustic tomography (PAT) is a rapidly-evolving med-ical imaging modality that combines optical absorption contrast with ultrasound imaging depth. One challenge in PAT is...

The authors propose a method for zero-shot classification that leverages conditional density estimates from text-to-image diffusion models.

Diffusion models have recently emerged as the state-of-the-art of generative modeling, demonstrating remarkable results in image synthesis and across other modalities.

Diffusion Models are popular generative modeling methods in various vision tasks, attracting significant attention. They can be considered a unique instance of self-supervised...

Single Motion Diffusion Model, a model designed to learn the internal motifs of a single motion sequence with arbitrary topology and synthesize motions of arbitrary length that...

The dataset used in the paper for video editing tasks

The dataset used in the paper for video editing tasks

FastDiff is a fast conditional diffusion model for high-quality speech synthesis. It employs a stack of time-aware location-variable convolutions with diverse receptive field...