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--- |
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license: apache-2.0 |
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pipeline_tag: depth-estimation |
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arxiv: <2502.19204> |
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tags: |
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- distill-any-depth |
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- vision |
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--- |
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# Distill Any Depth |
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## Introduction |
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We present Distill-Any-Depth, a new SOTA monocular depth estimation model trained with our proposed knowledge distillation algorithms. It was introduced in the paper [Distill Any Depth: Distillation Creates a Stronger Monocular Depth Estimator](http://arxiv.org/abs/2502.19204). Models with various sizes are available in this repo. |
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## Installation |
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```bash |
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git clone https://huggingface.co/xingyang1/Distill-Any-Depth |
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pip install -r requirements.txt |
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``` |
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## BibTeX entry and citation info |
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If you find this project useful, please consider citing: |
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```bibtex |
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@article{he2025distill, |
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title = {Distill Any Depth: Distillation Creates a Stronger Monocular Depth Estimator}, |
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author = {Xiankang He and Dongyan Guo and Hongji Li and Ruibo Li and Ying Cui and Chi Zhang}, |
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year = {2025}, |
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journal = {arXiv preprint arXiv: 2502.19204} |
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} |
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``` |
