PyTorch implementation of our CVPR 2019 paper:
Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding
Zehao Yu*, Jia Zheng*, Dongze Lian, Zihan Zhou, Shenghua Gao
(* Equal Contribution)
Please download the .tfrecords files for training and testing converted by Chen Liu from here. Then convert the .tfrecords to .npz files as the following:
python data_tools/convert_tfrecords.py --data_type=train --input_tfrecords_file=*train.tfrecords --output_dir=/path/to/save/processd/data
python data_tools/convert_tfrecords.py --data_type=val --input_tfrecords_file=*val.tfrecords --output_dir=/path/to/save/processd/dataRun the following command to train our network.
python main.py train with dataset.root_dir=/path/to/save/processd/dataPlease download our trained network from here.
To evaluate the performance of our method, please run:
python main.py eval with dataset.root_dir=/path/to/save/processd/data resume_dir=pretrained.pt dataset.batch_size=1Run the following command to predict on a single image.
python predict.py eval with resume_dir=pretrained.pt input_image=/path/to/image We thank Chen Liu for his great works and repos.
Please cite our paper for any purpose of usage.
@inproceedings{Yu2019Single,
title={Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding},
author={Zehao Yu and Jia Zheng and Dongze Lian and Zihan Zhou and Shenghua Gao},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
year={2019}
}