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[ECCV 2024] Official PyTorch implementation of the paper "Scene-aware Human Motion Forecasting via Mutual Distance Prediction"

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MutualDistance

[ECCV 2024] Official PyTorch implementation of the paper "Scene-aware Human Motion Forecasting via Mutual Distance Prediction"

Project Screenshot

Datasets

GTM-IM

For the original dataset please contact the authors of Long-term Human Motion Prediction with Scene Context.

For the motion sequences used in paper are from ContAwareMotionPred.

After downloading the dataset, please update the path of motion sequence, scene sdf and scene points in the code.

We also provide the preprocessed scene sdf file and checkpoints on google drive

After downloading the checkpoints, replace the folder with same name under the GTAIM.

Training on GTA-IM

Please open the corresponding folder and run

python stage1/train_motion.py 
python stage2/train_motion.py 
python finalmodel/train_motion.py --resume_model_s1 xxx/MutualDistance/GTAIM/checkpoints/stage1 --resume_model_s2 xxx/MutualDistance/GTAIM/checkpoints/stage2

xxx is the path on your systerm.

Evaluation on GTA-IM

Please open the corresponding folder and run

python finalmodel/test_motion.py --resume_model xxx/MutualDistance/GTAIM/checkpoints/final

xxx is the path on your systerm.

Datasets

HUMANISE

For the original dataset please contact the authors of HUMANISE: Language-conditioned Human Motion Generation in 3D Scenes.

Please also download the [SMPL-X] (https://smpl-x.is.tue.mpg.de/download.php), here we use the v1.1 version.

After downloading the dataset, please update the path of pure_motion_folder and align_data_folder in the code.

We also provide the preprocessed scene sdf file, mutual distance file and checkpoints on google drive

After downloading, please update the paths in the configuration file.

Training on HUMANISE

Please open the corresponding folder and run

python stage1/train_motion.py 
python stage2/train_motion.py 
python finalmodel/train_motion.py --resume_model_s1 xxx/MutualDistance/HUMANISE/checkpoints/stage1 --resume_model_s2 xxx/MutualDistance/HUMANISE/checkpoints/stage2

xxx is the path on your systerm.

Evaluation on HUMANISE

Please open the corresponding folder and run

python finalmodel/test_motion.py --resume_model xxx/MutualDistance/HUMANISE/checkpoints/final

xxx is the path on your systerm.

Re-training of ContAware and STAG

Please adpot our optimizer to the second stage (Motion Prediction) of ContAware and STAG.

📝 TODO List

  • [Y] Data preparation.
  • [Y] Release training and evaluation codes.
  • [Y] Release checkpoints.
  • [] Release code of visualization.
  • [] Release training code of stage 1&2 on HUMANISE.

Acknowledgments

The overall code framework (dataloading, training, testing etc.) is adapted from DLow ContAwareMotionPred HUMANISE

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[ECCV 2024] Official PyTorch implementation of the paper "Scene-aware Human Motion Forecasting via Mutual Distance Prediction"

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