This is a model card for the marigold-depth-hr-v1-1 model for monocular depth estimation from a single image.
The model is fine-tuned from the marigold-depth-v1-1 model as
described in our papers:
- CVPR'2024 paper titled "Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation"
- Journal extension titled "Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysis"
Model Details
- Developed by: Bingxin Ke, Kevin Qu, Tianfu Wang, Nando Metzger, Shengyu Huang, Bo Li, Anton Obukhov, Konrad Schindler.
- Model type: Generative latent diffusion-based affine-invariant monocular depth estimation from a single image.
- Language: English.
- License: Apache License License Version 2.0.
- Model Description: This model can be used to generate an estimated depth map of an input image.
- Resolution: The model is designed to support large resolutions up to 4MP.
- Steps and scheduler: This model was designed for usage with the DDIM scheduler and between 10 and 50 denoising steps.
- Outputs:
- Affine-invariant depth map: The predicted values are between 0 and 1, interpolating between the near and far planes of the model's choice.
- Resources for more information: Project Website, Paper, Code.
- Cite as:
@misc{ke2025marigold,
title={Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysis},
author={Bingxin Ke and Kevin Qu and Tianfu Wang and Nando Metzger and Shengyu Huang and Bo Li and Anton Obukhov and Konrad Schindler},
year={2025},
eprint={2505.09358},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@InProceedings{ke2023repurposing,
title={Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation},
author={Bingxin Ke and Anton Obukhov and Shengyu Huang and Nando Metzger and Rodrigo Caye Daudt and Konrad Schindler},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2024}
}