wanboyang/anomaly_ar_net_icme_2020

This repository is for Weakly Supervised Video Anomaly Detection via Center-Guided Discriminative Learning(ICME 2020). The original paper can be found (https://ieeexplore.ieee.org/document/9102722) or (https://arxiv.org/abs/2104.07268)

anomaly_ar_net_icme_2020's Issues

test

how can i test the model over new videos.

how to train the model over new datasets

TestResult

您好，您的测试数据结果是根据哪次迭代的结果，还是根据最好的那次

About False Alarm Rate (All Video)

Hello,

Firstly, thank you for sharing your source code for the community.

I have a question about the parameters to reproduce the results in the experiment.
I trained your code with the default param values on the code, but the ano_false_alarm_all_video (variable all_ano_false_alarm) is different from the 0.10 reported on the paper. Do I need to use any specific parameters?

why not use ground lable in trainning step？

Thank you for your paper, which has brought me a lot of help，but just i can‘t understand why not use ground lable in trainning step？

other data sets features

Have you experimented on other data sets? Can you provide features, such as UCF, if it is convenient for you.

About the downloaded i3d feature.

I have downloaded the i3d features and extracted the features in a local path. I have also changed the "dataset_path" to my local path. But the i3d features still cannot be found. I notice that there is just one file named "dataset" in the extracted file. Here is the error information:

Traceback (most recent call last):
File "/data1/haoyue/codes/remote/Anomaly-Detection/Anomaly_AR_Net_ICME_2020/main.py", line 29, in
train_dataset = dataset(args=args, train=True)
File "/data1/haoyue/codes/remote/Anomaly-Detection/Anomaly_AR_Net_ICME_2020/video_dataset_anomaly_balance_uni_sample.py", line 38, in init
self.videoname = os.listdir(self.feature_path)
NotADirectoryError: [Errno 20] Not a directory: './dataset/dataset/shanghaitech/features_video/i3d/combine'

what is "AUC_Score_abnormal_video"?

Hello, thank you for the great work!

I got all_auc and far, however, I'm confused about AUC of abnormal video.
Can you explain "AUC_Score_abnormal_video" metric?
I couldn't find it in the paper.

About AUC and FAR

May I ask if the "AUC"and"FAR" in your paper is the "all_auc_score"and"all_ano_false_alarm" in the code？