32 datasets found

Generating videos with content and motion variations is a challenging task in computer vision. The proposed model is trained in an end-to-end manner, without the need to utilize...

Video Diffusion Models have been developed for video generation, usually integrating text and image conditioning to enhance control over the generated content.

A video dataset for training a generalist video generation model.

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

Customized generation using diffusion models has made impressive progress in image generation, but remains un-satisfactory in the challenging video generation task, as it...

A dataset of 30M videos along with their text captions.

Diffusion models have achieved great success in image generation. However, when leveraging this idea for video generation, we face significant challenges in maintaining the...

The dataset used in the paper is MSR-VTT and UCF-101, two public datasets for video-text generation. MSR-VTT contains 4,900 videos with 20 manually annotated captions for each...

The MultiStudioBench dataset contains 25 subjects, including objects, animals, etc., and there are few images for each subject. Images in the dataset are from previous works or...

The Fashion dataset is used for human image animation task. It contains videos of humans performing different actions.

Webvid is a large-scale video dataset that contains internet videos.

Video In-Context Learning (Vid-ICL) is a novel framework that extends in-context learning to video data.

CogVideo is a large-scale pretrained transformer for text-to-video generation. It is trained on a dataset of 5.4 million captioned videos with a spatial resolution of 160×160.

The dataset used for video generation and evaluation of the proposed iVGAN model.

The dataset used for video generation and evaluation of the proposed iVGAN model.

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 this paper for text-to-video generation, consisting of short video clips.

The dataset used in this paper for text-to-video generation, consisting of short video clips.

The dataset used in this paper for text-to-video generation, consisting of short video clips.

A dataset of MUG facial expression, consisting of videos of 52 actors performing 6 different facial expressions.