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Zero
title: Marigold-LCM Depth Estimation | |
emoji: 🏵️ | |
colorFrom: blue | |
colorTo: red | |
sdk: gradio | |
sdk_version: 4.21.0 | |
app_file: app.py | |
pinned: true | |
license: cc-by-sa-4.0 | |
models: | |
- prs-eth/marigold-lcm-v1-0 | |
hf_oauth: true | |
hf_oauth_expiration_minutes: 43200 | |
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 CVPR 2024 paper titled ["Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation"](https://arxiv.org/abs/2312.02145) | |
``` | |
@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} | |
} | |
``` | |