This repository is the official PyTorch implementation of "Integrating Non-local Memory-Augmented Reconstruction and Appearance-Motion Frame Prediction for Video Anomaly Detection"
python==3.6
pytorch==1.5.1
mmcv-full==1.3.1
mmdet==2.11.0
scikit-learn==0.23.2
edflow==0.4.0
PyYAML==5.4.1
tensorboardX==2.4
Please follow the read.me to prepare the dataset.
First, to train the NL_ML_MemAE , run:
$ python nl_ml_memAE_train.py
Then, to train the AMTAE with reconstructed flows, run:
$ python trian.py
Finally, finetune the whole framework as:
$ python finetune.py
To evaluation the trained model, run:
$ python eval.py --model_save_path=[model_save_path]
--cfg_file=[cfg_file]
You can download the pretrained weights of NMR-AFP for Ped2, Avenue and ShanghaiTech datasets from here.
Method | UCSD Ped2 | CUHK Avenue | ShanghaiTech |
---|---|---|---|
NMR-AFP | 99.6% | 91.5% | 77.0% |
This code is heavily borrowed from hf2vad. Thanks LiUzHiAn for their contributions.