This repository is intended to substantiate the results reported in the paper. Additional features including visualization tools will be updated soon!

Environments

Install requirements

conda create -n gsicpslam python==3.9
conda activate gsicpslam
conda install pytorch==2.0.0 torchvision==0.15.0 torchaudio==2.0.0 pytorch-cuda=11.8 -c pytorch -c nvidia
pip install -r requirements.txt

Also, PCL is needed for fast-gicp submodule.

Install submodules

conda activate gsicpslam
pip install submodules/diff-gaussian-rasterization
pip install submodules/simple-knn

cd submodules/fast_gicp
mkdir build
cd build
cmake ..
make
cd ..
python setup.py install --user

Datasets

• Replica

  • Download

    bash download_replica.sh

  • Configure

  Please modify the directory structure to ours.

  The original structure

  Replica
      - room0
          - results (contain rgbd images)
              - frame000000.jpg
              - depth000000.jpg
              ...
          - traj.txt
      ...

  Our structure

  Replica
      - room0
          - images (contain rgb images)
              - frame000000.jpg
              ...
          - depth_images (contain depth images)
              - depth000000.jpg
              ...
          - traj.txt
      ...

• TUM-RGBD

  • Download

    bash download_tum.sh

Run

• Limited to 30 FPS

      # Replica
      bash replica.sh
      # TUM
      bash tum.sh

• Unlimited tracking speed

      # Replica
      bash replica_unlimit.sh
      # TUM
      bash tum_unlimit.sh

Installing SIBR Viewer

cd SIBR_viewers
cmake -Bbuild . -DCMAKE_BUILD_TYPE=Release
cmake --build build -j24 --target install

Real-time demo

Using rerun.io viewer

Rerun viewer shows the means of trackable Gaussians, and rendered image from reconstructed 3dgs map.

python -W ignore gs_icp_slam.py --rerun_viewer

Using SIBR viewer

python -W ignore gs_icp_slam.py --dataset_path dataset/Replica/office0 --verbose

# In other terminal
cd SIBR_viewers
./install/bin/SIBR_remoteGaussian_app --rendering-size 1280 720

Docker

Please see the README.md in the docker_files folder.