Show-1

Text-to-video generator

Generates videos from text prompts using a combination of pixel and latent diffusion models

[IJCV] Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generation

GitHub

1k stars
39 watching
62 forks
Language: Python
last commit: 9 days ago

Related projects:

Repository Description Stars
showlab/vlog Transforms video content into a long document containing visual and audio information that can be used for chat or other applications. 538
antoine77340/howto100m Provides code and tools for learning joint text-video embeddings using the HowTo100M dataset 252
pku-yuangroup/magictime Tools and models for generating time-lapse videos from text prompts 1,303
damo-nlp-sg/videollama2 An audio-visual language model designed to understand and generate video content 871
taoxugit/attngan Reproduces text-to-image generation with attentional generative adversarial networks. 1,339
openmotionlab/motiongpt Develops a unified model to generate high-quality motions and text descriptions from human motion data 1,505
pixart-alpha/pixart-sigma Develops a PyTorch model for 4K text-to-image generation using diffusion transformer 1,681
eps696/aphantasia A text-to-image tool using CLIP and FFT/DWT parameters to generate detailed images from user-provided text prompts. 776
dmulyalin/n2g A Python library to generate diagrams in various formats from structured data 157
thereforegames/txt2mask Automatically generates masks for image inpainting using natural language input 518
transitive-bullshit/ffmpeg-generate-video-preview Generates image strips or GIFs from video files 152
aspiers/ly2video Converts music represented by a GNU LilyPond file into a video containing a horizontally scrolling music staff synchronized with audio rendering. 158
mingyuan-zhang/motiondiffuse Generates human motion from text input using a diffusion model 860
tsinghuaai/cpm-1-generate Provides tools and scripts for generating text using a pre-trained Chinese language model 1,588
labforcomputationalvision/texturesynth Generates synthetic digital images of visual textures based on mathematical models 34