release

Author: rayeeli

.gitignore

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+
+.idea/*
+*.pyc
+cmake-build-*
+*.egg-info/
+*.so
+*/build/
+/exp/
+/data/
+

LICENSE

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+<p align="center">
+  <h1 align="center">3D Neural Edge Reconstruction</h1>
+  <p align="center">
+    <a href="https://github.com/rayeeli/"><strong>Lei Li</strong></a>
+    ·
+    <a href="https://pengsongyou.github.io/"><strong>Songyou Peng</strong></a>
+    ·
+    <a href="https://niujinshuchong.github.io/"><strong>Zehao Yu</strong></a>
+    ·
+    <a href="http://b1ueber2y.me/"><strong>Shaohui Liu</strong></a>
+    ·
+    <a href="https://rpautrat.github.io/"><strong>Rémi Pautrat</strong></a>
+    <br>
+    <a href=""><strong>Xiaochuan Yin</strong></a>
+    ·
+    <a href="https://people.inf.ethz.ch/pomarc/"><strong>Marc Pollefeys</strong></a>
+  </p>
+  <h2 align="center">CVPR 2024</h2>
+  <h3 align="center"><a href="https://arxiv.org/pdf/2405.19295">Paper</a> | <a href="https://youtu.be/ONXfu2b4Nug">Video</a> | <a href="https://neural-edge-map.github.io/">Project Page</a></h3>
+</p>
+
+<p align="center" style="display: flex; justify-content: center;">
+  <img src="./media/replica.gif" style="width: 80%;" />
+</p>
+
+<p align="center">
+EMAP enables 3D edge reconstruction from multi-view 2D edge maps.  
+</p>
+<br>
+
+## Installation
+
+```
+git clone https://github.com/cvg/EMAP.git
+cd EMAP
+
+conda create -n emap python=3.8
+conda activate emap
+
+conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=12.1 -c pytorch -c nvidia
+pip install -r requirements.txt
+```
+
+## Datasets
+Download datasets from [huggingface](https://huggingface.co/datasets/rayeeli/EMAP):
+```
+python scripts/download_data.py 
+```
+The data is organized as follows:
+
+```
+<scan_id>
+|-- meta_data.json      # camera parameters
+|-- color               # images for each view
+    |-- 0_colors.png
+    |-- 1_colors.png
+    ...
+|-- edge_DexiNed        # edge maps extracted from DexiNed
+    |-- 0_colors.png
+    |-- 1_colors.png
+    ...
+|-- edge_PidiNet        # edge maps extracted from PidiNet
+    |-- 0_colors.png
+    |-- 1_colors.png
+    ...
+```
+
+## Training and Evaluation
+To train and extract edges on different datasets, use the following commands:
+
+#### ABC-NEF_Edge Dataset
+```
+bash scripts/run_ABC.bash
+```
+
+#### Replica_Edge Dataset
+```
+bash scripts/run_Replica.bash
+```
+
+#### DTU_Edge Dataset
+```
+bash scripts/run_DTU.bash
+```
+
+## Code Release Status
+- [x] Training Code
+- [x] Inference Code
+- [x] Evaluation Code
+- [ ] Custom Dataset Support
+
+## License
+
+Shield: [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
+The majority of EMAP is licensed under a [MIT License](LICENSE).
+
+## <a name="CitingEMAP"></a>Citing EMAP
+
+If you find the code useful, please consider the following BibTeX entry.
+
+```BibTeX
+@InProceedings{li2024neural,
+  title={3D Neural Edge Reconstruction},
+  author={Li, Lei and Peng, Songyou and Yu, Zehao and Liu, Shaohui and Pautrat, R{\'e}mi and Yin, Xiaochuan and Pollefeys, Marc},
+  booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  year={2024},
+}
+```
+
+## Contact
+If you encounter any issues, you can also contact Lei through lllei.li0386@gmail.com.
+
+## Acknowledgement
+
+This project is built upon [NeuralUDF](https://github.com/xxlong0/NeuralUDF), [NeuS](https://github.com/Totoro97/NeuS) and [MeshUDF](https://github.com/cvlab-epfl/MeshUDF). We use pretrained [DexiNed](https://github.com/xavysp/DexiNed) and [PidiNet](https://github.com/hellozhuo/pidinet) for edge map extraction. We thank all the authors for their great work and repos.