We have just finished a refactorization of our codebase. Now you can use pip install to start using mars instantly! Please contact us without hesitation if you encounter any issues using the latest version. Thanks!

You must have an NVIDIA video card with CUDA installed on the system. This library has been tested with version 11.7 of CUDA. You can find more information about installing CUDA here.

Nerfstudio requires python >= 3.7. We recommend using conda to manage dependencies. Make sure to install Conda before proceeding.

conda create --name mars -y python=3.9
conda activate mars

This section will walk you through the installation process. Our system is dependent on the tiny-cuda-nn project.

pip install mars-nerfstudio
cd /path/to/tiny-cuda-nn/bindings/torch
python setup.py install

The following will train a MARS model.

Our repository provides dataparser for KITTI and vKITTI2 datasets, for your own data, you can write your own dataparser or convert your own dataset to the format of the provided datasets.

The data used in our experiments should contain both the pose parameters of cameras and object tracklets. The camera parameters include the intrinsics and the extrinsics. The object tracklets include the bounding box poses, types, ids, etc. For more information, you can refer to KITTI-MOT or vKITTI2 datasets below.