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| title: Marigold-LCM Depth Estimation | |
| emoji: 🏵️ | |
| colorFrom: blue | |
| colorTo: red | |
| sdk: gradio | |
| sdk_version: 4.22.0 | |
| app_file: app.py | |
| pinned: true | |
| license: cc-by-sa-4.0 | |
| models: | |
| - prs-eth/marigold-v1-0 | |
| - prs-eth/marigold-lcm-v1-0 | |
| This is a demo of Marigold-LCM, the state-of-the-art depth estimator for images in the wild. | |
| It combines the power of the original Marigold 10-step estimator and the Latent Consistency Models, delivering high-quality results in as little as one step. | |
| Find out more in our paper titled ["Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation"](https://arxiv.org/abs/2312.02145) | |
| ``` | |
| @misc{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}, | |
| year={2023}, | |
| eprint={2312.02145}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CV} | |
| } | |
| ``` | |