MS-RNN: A Flexible Multi-Scale Framework for Spatiotemporal Predictive Learning
PrecipLSTM: A Meteorological Spatiotemporal LSTM for Precipitation Nowcasting
MS-LSTM: Exploring Spatiotemporal Multiscale Representations in Video Prediction Domain
| ConvRNNs | MS-RNNs |
|---|---|
| ConvLSTM | MS-ConvLSTM |
| TrajGRU | MS-TrajGRU |
| PredRNN | MS-PredRNN |
| PredRNN++ | MS-PredRNN++ |
| MIM | MS-MIM |
| MotionRNN | MS-MotionRNN |
| PredRNN-V2 | MS-PredRNN-V2 |
| PrecipLSTM | MS-PrecipLSTM |
| CMS-LSTM | MS-CMS-LSTM |
| MoDeRNN | MS-MoDeRNN |
| MK-LSTM | MS-LSTM |
pip3 install -r requirements.txtHigher versions of CUDA are not supported, and CUDA 11.1 is recommended. https://blog.csdn.net/qq_40947610/article/details/114757551
cd img_local_att
python setup.py installhttps://github.com/zzd1992/Image-Local-Attention
See connfig.py
python -m torch.distributed.launch --nproc_per_node=4 main.py@article{ma2022ms,
title={MS-RNN: A flexible multi-scale framework for spatiotemporal predictive learning},
author={Ma, Zhifeng and Zhang, Hao and Liu, Jie},
journal={arXiv preprint arXiv:2206.03010},
year={2022}
}
@article{ma2022preciplstm,
title={PrecipLSTM: A Meteorological Spatiotemporal LSTM for Precipitation Nowcasting},
author={Ma, Zhifeng and Zhang, Hao and Liu, Jie},
journal={IEEE Transactions on Geoscience and Remote Sensing},
volume={60},
pages={1--8},
year={2022},
publisher={IEEE}
}
@article{ma2023ms,
title={MS-LSTM: Exploring Spatiotemporal Multiscale Representations in Video Prediction Domain},
author={Ma, Zhifeng and Zhang, Hao and Liu, Jie},
journal={arXiv preprint arXiv:2304.07724},
year={2023}
}
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