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sunghoonim / Dpsnet

Licence: mit
[ICLR19] DPSNet: End-to-end Deep Plane Sweep Stereo

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python
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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 ([email protected]) 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
  1. Download DeMoN data (https://github.com/lmb-freiburg/demon)
  2. 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
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