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metadata
license: other
license_name: stabilityai-ai-non-commercial
license_link: https://huggingface.co/stabilityai/stableviews/blob/main/LICENSE.txt
tags:
  - image-to-video
  - novel-view-synthesis
inference: false
pipeline_tag: image-to-video
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Stable Views

Project Page

Stable Views is a 1.3 billion parameter multi-view diffusion model capable of generating 3D consistent novel views of a scene, given any number o input views and target cameras. For more information, please refer to our paper and webpage.

Model Description

  • Developed by: Stability AI
  • Model type: Transformer image-to-video model
  • Model details: This model was trained to generate 3D consistent novel views of a scene given any number of input views and target cameras. Users can specify the target camera trajectory freely, spanning across a large spatial range. Our model is capable of generating large viewpoint changes and temporally smooth samples. As a result, our samples maintain high consistency without requiring additional NeRF distillation, streamlining the view synthesis pipeline in the wild. Furthermore, we show that our method can generate high-quality videos lasting up to half a minute with seamless loop closure.

License

Model Sources

Usage

For usage instructions, please refer to our GitHub repository.

Intended Uses

Intended uses include the following:

  • Generation of artworks and use in design and other artistic processes.
  • Applications in educational or creative tools.
  • Research on reconstruction models, including understanding the limitations of these models.

All uses of the model should be in accordance with our Acceptable Use Policy.

Out-of-Scope Uses

The model was not trained to be factual or true representations of people or events. As such, using the model to generate such content is out-of-scope of the abilities of this model.

Safety

As part of our safety-by-design and responsible AI deployment approach, we implement safety measures throughout the development of our models, from the time we begin pre-training a model to the ongoing development, fine-tuning, and deployment of each model. We have implemented a number of safety mitigations that are intended to reduce the risk of severe harms. However, it is the responsibility of developers to conduct their own testing and apply additional mitigations based on their specific use cases.
For more about our approach to Safety, please visit our Safety page.

Contact

Please report any issues with the model or contact us: