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marigold-depth-v1-0 model for monocular depth estimation from a single image.
The model is fine-tuned from the stable-diffusion-2 model as
described in our papers:"timestep_spacing": "trailing" setting
in the scheduler configuration file or by adding pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
after the pipeline is loaded in the code before the first usage. For compatibility reasons we kept this v1-0 model identical to the paper setting and provided a
newer v1-1 model with optimal settings for all possible step configurations.1@InProceedings{ke2023repurposing,
2 title={Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation},
3 author={Bingxin Ke and Anton Obukhov and Shengyu Huang and Nando Metzger and Rodrigo Caye Daudt and Konrad Schindler},
4 booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
5 year={2024}
6}
7
8@misc{ke2025marigold,
9 title={Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysis},
10 author={Bingxin Ke and Kevin Qu and Tianfu Wang and Nando Metzger and Shengyu Huang and Bo Li and Anton Obukhov and Konrad Schindler},
11 year={2025},
12 eprint={2505.09358},
13 archivePrefix={arXiv},
14 primaryClass={cs.CV}
15}