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PyTorch implementation of E-Motion: Future Motion Simulation via Event Sequence Diffusion

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[NeurIPS 2024] E-Motion: Future Motion Simulation via Event Sequence Diffusion

Arvix: E-Motion: Future Motion Simulation via Event Sequence Diffusion.

๐Ÿ› ๏ธ Requirements and Installation

  • Python >= 3.10
  • Pytorch == 2.0.1
  • CUDA Version >= 11.7
  • Install required packages:
git clone https://github.com/p4r4mount/E-Motion.git
cd E-Motion
conda env create -f environment.yml

๐Ÿ“œ Datasets Preparation

Download the training data from EventVOT, and process the data with following command:

python utils/DataPreprocess.py --dataset_dir /path/to/dataset

๐Ÿš… Training

accelerate launch train.py \ 
	--num_processes num_processes \
	--main_process_port main_process_port \
	--config /path/to/config

๐Ÿ’ก Pre-trained weights

Google Drive: Checkpoint

๐Ÿš€ Inference

Download some samples from Google Drive๏ผŒand run the following command for inference:

python predict.py --model_path /path/to/model/checkpoint \
                  --data_path /path/to/data/file.npy \
                  --output_path /path/to/output/directory

Citation

@article{wu2024motion,
  title={E-Motion: Future Motion Simulation via Event Sequence Diffusion},
  author={Wu, Song and Zhu, Zhiyu and Hou, Junhui and Shi, Guangming and Wu, Jinjian},
  journal={Advances in Neural Information Processing Systems},
  volume={37},
  pages={105552--105582},
  year={2024}
}

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