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Use HF papers (#38184)

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Quentin Gallouédec
2025-06-13 13:07:09 +02:00
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docs/source/en/model_doc/depth_pro.md
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## Overview
The DepthPro model was proposed in [Depth Pro: Sharp Monocular Metric Depth in Less Than a Second](https://arxiv.org/abs/2410.02073) by Aleksei Bochkovskii, Amaël Delaunoy, Hugo Germain, Marcel Santos, Yichao Zhou, Stephan R. Richter, Vladlen Koltun.
The DepthPro model was proposed in [Depth Pro: Sharp Monocular Metric Depth in Less Than a Second](https://huggingface.co/papers/2410.02073) by Aleksei Bochkovskii, Amaël Delaunoy, Hugo Germain, Marcel Santos, Yichao Zhou, Stephan R. Richter, Vladlen Koltun.
DepthPro is a foundation model for zero-shot metric monocular depth estimation, designed to generate high-resolution depth maps with remarkable sharpness and fine-grained details. It employs a multi-scale Vision Transformer (ViT)-based architecture, where images are downsampled, divided into patches, and processed using a shared Dinov2 encoder. The extracted patch-level features are merged, upsampled, and refined using a DPT-like fusion stage, enabling precise depth estimation.
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<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/depth_pro_architecture.png"
alt="drawing" width="600"/>
<small> DepthPro architecture. Taken from the <a href="https://arxiv.org/abs/2410.02073" target="_blank">original paper</a>. </small>
<small> DepthPro architecture. Taken from the <a href="https://huggingface.co/papers/2410.02073" target="_blank">original paper</a>. </small>
The `DepthProForDepthEstimation` model uses a `DepthProEncoder`, for encoding the input image and a `FeatureFusionStage` for fusing the output features from encoder.
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A list of official Hugging Face and community (indicated by 🌎) resources to help you get started with DepthPro:
- Research Paper: [Depth Pro: Sharp Monocular Metric Depth in Less Than a Second](https://arxiv.org/pdf/2410.02073)
- Research Paper: [Depth Pro: Sharp Monocular Metric Depth in Less Than a Second](https://huggingface.co/papers/2410.02073)
- Official Implementation: [apple/ml-depth-pro](https://github.com/apple/ml-depth-pro)
- DepthPro Inference Notebook: [DepthPro Inference](https://github.com/qubvel/transformers-notebooks/blob/main/notebooks/DepthPro_inference.ipynb)
- DepthPro for Super Resolution and Image Segmentation