Everlyn-Labs/EfficientARV

150

stars

4

commits

Python

primary language

Sep 28, 2024

updated

README

EfficientARV

This project focuses on the development of an efficient autoregressive model for the joint generation of images and videos. The aim is to enhance the generative capabilities of current multimodal large models, ultimately building an interactive world model that integrates both multimodal understanding and generation.

🔆 New Features/Updates

  • Trained the first version on a relatively small dataset

TODO list

  • Implement the training and testing pipeline
  • Test different AR generation schemes
  • Jointly train image and video generation model on a larger dataset with larger resolutions
  • Implement an efficient unstructured image-video tokenizer
  • Integrate generation capabilities into MLLMs
  • Support multiple conditional generation tasks: image animation, image/video inpainting/outpainting, video prediction, video interpolation
  • Support multimodal controllable generation
"time lapse of a cloudy sky""countryside top view""a blue and cloudy sky""aerial view of brown dry landscape"
"waterfalls in between mountain""view of the amazon river""a river waterfall cascading down the plunge basin""flooded landscape with palm trees"
"drone shot of an abandoned coliseum on a snowy mountain top""clouds over mountain""aerial view of road in forest""a peaceful lake"

Training

Coming soon

Inference

Coming soon

Contributors

huge123

4 commits

Everlyn-Labs/EfficientARV

150

stars

4

commits

Python

primary language

Sep 28, 2024

updated

README

EfficientARV

This project focuses on the development of an efficient autoregressive model for the joint generation of images and videos. The aim is to enhance the generative capabilities of current multimodal large models, ultimately building an interactive world model that integrates both multimodal understanding and generation.

🔆 New Features/Updates

  • Trained the first version on a relatively small dataset

TODO list

  • Implement the training and testing pipeline
  • Test different AR generation schemes
  • Jointly train image and video generation model on a larger dataset with larger resolutions
  • Implement an efficient unstructured image-video tokenizer
  • Integrate generation capabilities into MLLMs
  • Support multiple conditional generation tasks: image animation, image/video inpainting/outpainting, video prediction, video interpolation
  • Support multimodal controllable generation
"time lapse of a cloudy sky""countryside top view""a blue and cloudy sky""aerial view of brown dry landscape"
"waterfalls in between mountain""view of the amazon river""a river waterfall cascading down the plunge basin""flooded landscape with palm trees"
"drone shot of an abandoned coliseum on a snowy mountain top""clouds over mountain""aerial view of road in forest""a peaceful lake"

Training

Coming soon

Inference

Coming soon

Contributors

huge123

4 commits

Languages

Python

100.0%