Text2Video-Zero Model Card - ControlNet Canny GTA-5 Style

Text2Video-Zero is a zero-shot text to video generator. It can perform zero-shot text-to-video generation, Video Instruct Pix2Pix (instruction-guided video editing), text and pose conditional video generation, text and canny-edge conditional video generation, and text, canny-edge and dreambooth conditional video generation. For more information about this work, please have a look at our paper and our demo:

Our code works with any StableDiffusion base model.

Weights for Text2Video-Zero

Model Details

• Developed by: Levon Khachatryan, Andranik Movsisyan, Vahram Tadevosyan, Roberto Henschel, Zhangyang Wang, Shant Navasardyan and Humphrey Shi
• Model type: Dreambooth text-to-image and text-to-video generation model with edge control for text2video zero
• Language(s): English
• License: The CreativeML OpenRAIL M license.
• Model Description: This is a model for text2video zero with edge guidance and gta-5 style. It can be used also with ControlNet in a text-to-image setup with edge guidance.
• DreamBoth Keyword: gtav style
• Resources for more information: GitHub, Paper, CIVITAI.
• Cite as:

  @article{text2video-zero,
    title={Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators},
    author={Khachatryan, Levon and Movsisyan, Andranik and Tadevosyan, Vahram and Henschel, Roberto and Wang, Zhangyang and Navasardyan, Shant and Shi, Humphrey},
    journal={arXiv preprint arXiv:2303.13439},
    year={2023}
  }

Original Weights

Model Details

• Developed by: Quiet_Joker (Username listed on CIVITAI)
• Model type: Dreambooth text-to-image generation model
• Language(s): English
• License: The CreativeML OpenRAIL M license.
• Model Description: This is a model that was created using DreamBooth to generate images with GTA-5 style, based on text prompts.
• DreamBoth Keyword: gtav style
• Resources for more information: CIVITAI.

Biases content acknowledgement:

Citation

  @article{text2video-zero,
    title={Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators},
    author={Khachatryan, Levon and Movsisyan, Andranik and Tadevosyan, Vahram and Henschel, Roberto and Wang, Zhangyang and Navasardyan, Shant and Shi, Humphrey},
    journal={arXiv preprint arXiv:2303.13439},
    year={2023}
  }