60 datasets found

StyleGAN-V for video generation

DIGAN for video generation

MoCoGAN-HD for video generation

Video Implicit Diffusion Models for video generation

The dataset used for training the video model consists of Webvid-10M, a large-scale dataset of short videos with textual descriptions.

UCF-101, Sky Time-lapse, and Taichi datasets are used for video generation tasks.

Diffusion models have recently achieved remarkable results for video generation. Despite the encouraging performances, the generated videos are typically constrained to a small...

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.

A dataset for video generation and video-based tasks.

Video prediction is a challenging task. The quality of video frames from current state-of-the-art (SOTA) generative models tends to be poor and generalization beyond the...

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.

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.

A dataset of sprite, consisting of sequences of 8 frames of size 64x64.

A sequential variational autoencoder for sequential data, including videos and audios, with self-supervision and regularization.