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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 seizes are available in this repo.
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```bibtex
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@article{he2025distill,
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- vision
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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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