Learning Non-volumetric Depth Fusion using Successive Reprojections

This is the github page for the paper

Learning Non-volumetric Depth Fusion using Successive Reprojections
Simon Donné, Andreas Geiger
CVPR 2019

Code will be published here by the time the manuscript is published. For the datasets, videos, and so on, please visit https://avg.is.tuebingen.mpg.de/research_projects/defusr.

Requirements / Setting up

Creating a working conda environment

Unfortunately, PyTorch changed their C++ bindings halfway through this project. The current version of this code only supports PyTorch 0.4.1.

conda create -n defusr python=3.7
conda activate defusr
conda install pytorch=0.4.1 torchvision cuda92 -c pytorch
conda install -c conda-forge opencv
pip install pycuda
pip install Cython
conda install termcolor
conda install matplotlib
conda install gitpython
conda install tqdm

Compiling the MYTH library

MYTH (My Torch Helpers) is an included library of auxiliary functions required for the network execution. It can be compiled by

conda activate defusr
cd code/MYTH
chmod +x build.sh
./build.sh

Running the evaluation

For running the evaluation, download the pretrained networks here, as well as the DTU dataset. Fix the relevant paths in the scripts in the evaluations/ folder, and run the scripts.