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Code for "Neural 3D Scene Reconstruction with the Manhattan-world Assumption" CVPR 2022 Oral

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Neural 3D Scene Reconstruction with the Manhattan-world Assumption


introduction

Neural 3D Scene Reconstruction with the Manhattan-world Assumption
Haoyu Guo*, Sida Peng*, Haotong Lin, Qianqian Wang, Guofeng Zhang, Hujun Bao, Xiaowei Zhou
CVPR 2022 (Oral Presentation)


Setup

Installation

conda env create -f environment.yml
conda activate manhattan

Data preparation

Coming soon!

Usage

Training

python train_net.py --cfg_file configs/scannet/0050.yaml gpus 0, exp_name scannet_0050

Mesh Extraction

python run.py --type mesh_extract --output_mesh result.obj --cfg_file configs/scannet/0050.yaml gpus 0, exp_name scannet_0050

Evaluation

python run.py --type evaluate --cfg_file configs/scannet/0050.yaml gpus 0, exp_name scannet_0050

Citation

If you find this code useful for your research, please use the following BibTeX entry.

@inproceedings{guo2022manhattan,
  title={Neural 3D Scene Reconstruction with the Manhattan-world Assumption},
  author={Guo, Haoyu and Peng, Sida and Lin, Haotong and Wang, Qianqian and Zhang, Guofeng and Bao, Hujun and Zhou, Xiaowei},
  booktitle={CVPR},
  year={2022}
}

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Code for "Neural 3D Scene Reconstruction with the Manhattan-world Assumption" CVPR 2022 Oral

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