prs-eth / PaGeR-depth-indoor

📟 PaGeR(Panoramic Geometry Estimation) Depth Estimation Model Card

This is a model card for the PaGeR-depth-indoor model for monocular depth estimation from a single panoramic ERP image. The model is fine-tuned from our original depth checkpoint on the combination of Scannet and Structured3D datasets, specialized for indoor depth prediction, as described in our paper:

• [Paper](paper link) titled "Panorama Geometry Estimation using Single-Step Diffusion Models"

This model excels in depth estimation for indoor environments, for a more general model, check out the original model . You can also check out other depth and normals models in our collection , or test models in our demo .

Model Details

• Developed by: Vukasin Bozic , Isidora Slavkovic , Dominik Narnhofer , Nando Metzger , Denis Rozumny , Konrad Schindler , Nikolai Kalischek .
• Model type: Generative latent diffusion-based one-step scale-invariant monocular panoramic depth estimation from a single ERP image.
• License: CreativeML OpenRAIL License .
• Model Description: This model can be used to generate an estimated depth map of a panoramic input image.
  • Resolution : The model is designed to support large resolutions up to 3K.
  • Dataset : Scannet++ , Structured3D
  • Steps and scheduler : This model works in a swift, one-step regime.
  • Outputs :
    • Scale-invariant depth map : The predicted values represent a depth map, interpolating between the near and far planes of the model's choice.
• Resources for more information: [Project Website](insert link), [Paper](insert link), Code .
• Cite as:

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