Learn-to-Predict-How-Humans-Manipulate-Large-Sized-Objects-From-Interactive-Motions-objects

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Learn-to-Predict-How-Humans-Manipulate-Large-Sized-Objects-From-Interactive-Motions-objects

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This is the repo for the paper "Learn to Predict How Humans Manipulate Large-Sized Objects From Interactive Motions"

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// repository documentation

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# Learn to Predict Human Manipulation of Large-Sized Objects Through Interactive Motions

Hello, welcome to our project repository!

## Dataset Access

To access our dataset, please visit this [Google Drive link](https://drive.google.com/drive/folders/174k-o7UFuIZg8BsZRbDGcAbVskKsF36r?usp=sharing).

## Visualizing Dataset Samples

To view samples from our dataset, use the following command:

python visData.py

## Obtaining SMPL Parameters

To extract SMPL parameters of human skeleton motion:

Download the dataset and place it in the `./data/` directory.
Follow the configuration settings in `render_mesh.py`.
Run the following command to utilize SMPLify ([SMPLify website](https://smplify.is.tue.mpg.de)) for extracting SMPL parameters. 
(This process may be time-consuming)

python render_mesh.py

The SMPL meshes and parameters will be saved in `./data/SAMPLE_NAME/SMPL_result/`.
To view the SMPL joint motions, use:

python visData.py --smpl_joint True

## Simulation Tool

Included in this repository is a basic simulator for testing the physical properties of various object layouts. Run it using:

python Simulator/Simulate_Demo.py

## Future Updates

Stay tuned for more materials and updates to this project.

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