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marigold-iid-lighting-v1-1 model for single-image Intrinsic Image Decomposition (IID).
The model is fine-tuned from the stable-diffusion-2 model as
described in our papers:lighting) is trained to perform HyperSim decomposition into Albedo, Diffuse shading, and Non-diffuse residual.
This decomposition aligns with the intrinsic residual model \(I = A*S+R\), where the image \(I\) is composed of
a three-channel albedo \(A\), a three-channel diffuse shading component \(S\) (representing illumination color),
and an additive three-channel residual term \(R\) capturing non-diffuse effects.
The input is in the sRGB color space, while all outputs are in linear space.
For an alternative model type (appearance) that performs decomposition into Albedo, Roughness, and Metallicity, click
here.1@misc{ke2025marigold,
2 title={Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysis},
3 author={Bingxin Ke and Kevin Qu and Tianfu Wang and Nando Metzger and Shengyu Huang and Bo Li and Anton Obukhov and Konrad Schindler},
4 year={2025},
5 eprint={2505.09358},
6 archivePrefix={arXiv},
7 primaryClass={cs.CV}
8}
9
10@InProceedings{ke2023repurposing,
11 title={Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation},
12 author={Bingxin Ke and Anton Obukhov and Shengyu Huang and Nando Metzger and Rodrigo Caye Daudt and Konrad Schindler},
13 booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
14 year={2024}
15}