Off-TANet:A lightweight neural micro-expression recognizer with optical flow features and integrated attention mechanism

ResearchGate: https://www.researchgate.net/publication/355545710_Off-TANet_A_Lightweight_Neural_Micro-expression_Recognizer_with_Optical_Flow_Features_and_Integrated_Attention_Mechanism?_iepl%5BgeneralViewId%5D=n5Mw0uLS3a9Hzu6kqDKN0QWRouBsQwulh31b&_iepl%5Bcontexts%5D%5B0%5D=searchReact&_iepl%5BviewId%5D=C4Cc0QrPkbdErfXawaM1dZ1tBdzXC6U1iUxh&_iepl%5BsearchType%5D=publication&_iepl%5Bdata%5D%5BcountLessEqual20%5D=1&_iepl%5Bdata%5D%5BinteractedWithPosition1%5D=1&_iepl%5Bdata%5D%5BwithEnrichment%5D=1&_iepl%5Bposition%5D=1&_iepl%5BrgKey%5D=PB%3A355545710&_iepl%5BtargetEntityId%5D=PB%3A355545710&_iepl%5BinteractionType%5D=publicationTitle

Bilibili: https://www.bilibili.com/video/BV1Ab4y1E7y2?spm_id_from=333.999.0.0

How to Run the Code

1.Install packages mentioned in requirements.txt

pip install -r requirements.txt

2.Modify arguments in train_arg.py

3.Get CASME,CASME2 and CASME-2 datasets from the link below,put the cropped pictures under the dataset directory.

The name of the subfolders should be casme1_cropped,casme2_cropped and casme^2_cropped

CASME - http://fu.psych.ac.cn/CASME/casme.php

CASME2 - http://fu.psych.ac.cn/CASME/casme2.php

CASME-2 - http://fu.psych.ac.cn/CASME/cas(me)2.php

4.Run the code

python train.py

The results can be seen in this chart below.

Model	UAR	UF1	Total Params	Total Flops	Total MemR+W
Off-ApexNet	0.5832	0.5650	2.66M	3.87M	10.35MB
STSTNet	0.5584	0.5399	162,051	526.98K	0.78MB
Dual-Inception	0.6167	0.5814	6.45M	12.64M	26.27MB
MACNN	0.6835	0.6660	70.57M	793.67M	297.86MB
Micro-Attention	0.7086	0.7021	53.38M	1.0G	237.97MB
Off-TANet	0.7315	0.7242	59,403	30.08M	5.64MB

The required Python packages are in requirements.txt, and other environments of ours are as follows:

Operating system: Ubuntu 16.04.6 LTS

CPU: Intel(R) Xeon(R) Gold 5118 CPU@ 2.30GHz

GPU: Tesla K80 (10G video RAM)

CUDA Version: 9.0