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README.md

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+---
+license: cc-by-nc-4.0
+pipeline_tag: depth-estimation
+tags:
+  - depth-estimation
+  - monocular-depth
+  - metric-depth
+  - epipolar-attention
+library_name: pytorch
+---
+
+# EpiDistill
+
+**Geometric Distillation from Rectified Stereo: Leveraging Epipolar Cues for Monocular Depth**
+
+Jung-Hee Kim, Xiaoming Liu · Michigan State University / UNC Chapel Hill
+
+[Paper](https://arxiv.org/abs/2607.15600) · [Project page](https://jungheekim29.github.io/EpiDistill/) · [Code](https://github.com/jungheekim29/EpiDistill)
+
+EpiDistill turns a frozen depth foundation model into a single-view metric depth
+model. A multi-view teacher learns correspondence through depth-guided epipolar
+attention; at inference the source views are replaced by learnable Rectified
+Stereo Tokens, so the cross-view pathway survives with one image.
+
+## Files
+
+| file | backbone | tensors |
+|---|---|---|
+| `epidistill_unidepthv2.pt` | UniDepthV2 (ViT-L/14) | 401 |
+| `epidistill_depthpro.pt` | DepthPro | 455 |
+
+Each file is a plain PyTorch `state_dict` (no pickled objects beyond tensors, so
+it loads with `weights_only=True`).
+
+## These weights are a correction, not a depth network
+
+They hold only EpiDistill's own parameters. The frozen backbone is **not**
+included and must be obtained separately:
+
+* **UniDepthV2** downloads automatically from `lpiccinelli/unidepth-v2-vitl14`.
+* **DepthPro** needs `depth_pro.pt` from
+  [apple/ml-depth-pro](https://github.com/apple/ml-depth-pro).
+
+## Usage
+
+```python
+from huggingface_hub import hf_hub_download
+from epidistill import EpiDistillConfig, EpiDistillPredictor
+
+path = hf_hub_download("kimjun84/EpiDistill", "epidistill_unidepthv2.pt")
+predictor = EpiDistillPredictor.from_pretrained(
+    path, config=EpiDistillConfig(backbone="unidepthv2")
+)
+depth, K = predictor(rgb)      # depth: (H, W) float32 metres, K: (3, 3)
+```
+
+The model code lives in the
+[EpiDistill repository](https://github.com/jungheekim29/EpiDistill); install it
+first.
+
+## License
+
+**CC BY-NC 4.0** — non-commercial. The UniDepthV2 backbone these weights correct
+is itself CC BY-NC 4.0; DepthPro carries Apple's licence.
+
+## Citation
+
+```bibtex
+@inproceedings{kim2026epidistill,
+  title     = {Geometric Distillation from Rectified Stereo:
+               Leveraging Epipolar Cues for Monocular Depth},
+  author    = {Kim, Jung-Hee and Liu, Xiaoming},
+  booktitle = {ECCV},
+  year      = {2026}
+}
+```