Awesome
DPSNet
This codebase implements the system described in the paper:
DPSNet: End-to-end Deep Plane Sweep Stereo
Sunghoon Im, Hae-Gon Jeon, Steve Lin, In So Kweon
In ICLR 2019.
See the paper for more details.
Please contact Sunghoon Im (sunghoonim27@gmail.com) if you have any questions.
Requirements
Building and using requires the following libraries and programs
Pytorch 0.4.0 (The codes for (0.3.0 or 1.0) are in the other brach)
CUDA 9.0
python 3.6.4
scipy
argparse
tensorboardX
progressbar2
blessings
path.py
The versions match the configuration we have tested on an ubuntu 16.04 system.
Data Praparation
Training data preparation requires the following libraries and programs
opencv
imageio
joblib
h5py
lz4
- Download DeMoN data (https://github.com/lmb-freiburg/demon)
- Convert data
[Training data]
bash download_traindata.sh
python ./dataset/preparation/preparedata_train.py
[Test data]
bash download_testdata.sh
python ./dataset/preparation/preparedata_test.py
Train
python train.py ./dataset/train/ --mindepth 0.5 --nlabel 64 --log-output
Test
python test.py ./dataset/test/ --sequence-length 2 --output-print --pretrained-dps ./pretrained/dpsnet.pth.tar
Test (ETH3D)
Download full results on ETH3D datasets from https://phuang17.github.io/DeepMVS/index.html and merge it with './dataset/ETH3D_results/' folder, which includes gt_cam
python test_ETH3D.py ./dataset/ETH3D_results/ --sequence-length 3 --output-print --pretrained-dps ./pretrained/dpsnet.pth.tar
Updated result for Table 1
Paper (epoch 4) -> Update (epoch 10)
MVS A.Rel A.diff Sq.Rel RMSE R. log a=1 a=2 a=3
Paper 0.0722 0.2095 0.0798 0.4928 0.1527 0.8930 0.9502 0.9760
Update 0.0813 0.2006 0.0971 0.4419 0.1595 0.8853 0.9454 0.9735
SUN3D A.Rel A.diff Sq.Rel RMSE R. log a=1 a=2 a=3
Paper 0.1470 0.3234 0.1071 0.4269 0.1906 0.7892 0.9317 0.9672
Update 0.1469 0.3355 0.1165 0.4489 0.1956 0.7812 0.9260 0.9728
RGBD A.Rel A.diff Sq.Rel RMSE R. log a=1 a=2 a=3
Paper 0.1538 0.5235 0.2149 0.7226 0.2263 0.7842 0.8959 0.9402
Update 0.1508 0.5312 0.2514 0.6952 0.2421 0.8041 0.8948 0.9268
Scenes A.Rel A.diff Sq.Rel RMSE R. log a=1 a=2 a=3
Paper 0.0558 0.2430 0.1435 0.7136 0.1396 0.9502 0.9726 0.9804
Update 0.0500 0.1515 0.1108 0.4661 0.1164 0.9614 0.9824 0.9880