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EricGuo5513 authored Jul 18, 2022
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# TM2T: Stochastical and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Texts (ECCV 2022)
## [[Project Page]](https://ericguo5513.github.io/TM2T) [[Paper]]https://arxiv.org/abs/2207.01696.pdf)
## [[Project Page]](https://ericguo5513.github.io/TM2T) [[Paper]](https://arxiv.org/abs/2207.01696.pdf)

![teaser_image](https://github.com/EricGuo5513/TM2T/blob/main/docs/teaser_image.png)

Given a textual description for example, *"the figure rises from a lying position and walks in a counterclockwise circle, and then lays back down the ground"*, our approach generates a diverse set of 3d human motions that are faithful to the provided text.

## Python Virtual Environment

Anaconda is recommended to create this virtual environment.

```sh
conda create -f environment.yaml
conda activate text2motion_pub
conda activate tm2t
```

If you cannot successfully create the environment, here is a list of required libraries:
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tqdm
ffmpeg = 4.3.1 # Other version may also work but are not tested.
matplotlib = 3.3.1
[nlpeval](https://github.com/Maluuba/nlg-eval)
```

After all, if you want to generate 3D motions from customized raw texts, you still need to install the language model for spacy.
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