Caffe implementation of SegStereo and ResNetCorr models.
This code is tested with Caffe, CUDA 8.0 and Ubuntu 16.04.
Our models require rectified stereo pairs. We provide several examples in data
directory
To test or evaluate the disparity model, you can use the script in model/get_disp.py
. We recommend that you put the model under correponding directory.
python get_disp.py --model_weights ./ResNetCorr/ResNetCorr_SRC_pretrain.caffemodel --model_deploy ./ResNetCorr/ResNetCorr_deploy.prototxt --data ../data/KITTI --result ./ResNetCorr/result/kitti --gpu 0 --colorize --evaluate
@inproceedings{yang2018SegStereo,
author = {Yang, Guorun and
Zhao, Hengshuang and
Shi, Jianping and
Deng, Zhidong and
Jia, Jiaya},
title = {SegStereo: Exploiting Semantic Information for Disparity Estimation},
booktitle = ECCV,
year = {2018}
}
@inproceedings{yang2018srcdisp,
author = {Yang, Guorun and
Deng, Zhidong and
Lu, Hongchao and
Li, Zeping},
title = {SRC-Disp: Synthetic-Realistic Collaborative Disparity Learning for Stereo Mathcing},
booktitle = ACCV,
year = {2018}
}
Please contact ygr13@mails.tsinghua.edu.cn