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We have tested our code on the following setups:

• Ubuntu 20.04 LTS
• Windows 10, 11
• Python >= 3.8
• Pytorch >= 1.11
• conda >= 4.9.2 (optional but recommended)

Follow these commands to create a conda environment:

conda create -n IDMS python=3.8
conda activate IDMS
conda install -c pytorch pytorch=1.11 torchvision cudatoolkit=11.3
pip install -r requirements.txt

For pytorch3D installation refer to https://github.com/facebookresearch/pytorch3d/blob/main/INSTALL.md

Note: If PyOpenGL installed using requirements.txt causes issues in Ubuntu, then install PyOpenGL using:

apt-get update
apt-get install python3-opengl

1. Follow the instructions on the SMPL-X website to download SMPL-X model and keep the downloaded files under the smplx_model folder.

2. Download the GRAB dataset from the GRAB website, and follow the instructions there to extract the files. Save the raw data in ../DATASETS/GRAB.

3. To pre-process the GRAB dataset for our setting, run:

python src/data_loader/dataset_preprocess.py

Download the pretrained weights for the models used in our paper from here and keep it inside save\pretrained_models.

4. To evaluate our pre-trained model, run:

python src/evaluate/eval.py

5. To generate the .npy files with the synthesized motions, run:

python src/test/test_synthesis.py

6. To visualize sample results from our paper, run:

python src/visualize/render_smplx.py