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Efficient Event Stream Super-Resolution with Recursive Multi-Branch Fusion

Official PyTorch Implementation of the IJCAI 2024 Paper:

Efficient Event Stream Super-Resolution with Recursive Multi-Branch Fusion </sub><br><sub>Supp</sub><br>

<p align="left"> <img src="doc/RMFNet.png"/> <br> </p>

Dataset

Please follow the instructions from directory generate_dataset to prepare the synthetic and real-world dataset.

Pretrained model

Some pretrained model are in the pretrain folder.

Training and Inference

Please check the file scripts\train_ours.sh and scripts\infer_ours.sh for training and inference.

Citation

If you find this work helpful, please consider citing our paper.

@article{liangefficient,
  title={Efficient Event Stream Super-Resolution with Recursive Multi-Branch Fusion},
  author={Liang, Quanmin and Huang, Zhilin and Zheng, Xiawu and Yang, Feidiao and Peng, Jun and Huang, Kai and Tian, Yonghong}
}

Contact

If you have any problem about the released code, please contact me with email (liangqm5@mail2.sysu.edu.cn).