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View Code? Open in Web Editor NEW[AAAI 2020] Pytorch codes for Regularized Fine-grained Meta Face Anti-spoofing
Home Page: https://arxiv.org/pdf/1911.10771.pdf
[AAAI 2020] Pytorch codes for Regularized Fine-grained Meta Face Anti-spoofing
Home Page: https://arxiv.org/pdf/1911.10771.pdf
Hi, a great job. But when I reuse your code to trian model by myself, I encounter the following problems:
I find the model is too large, and when training, the results are very shocking. For example, when I use the epoch100 trained_model to test, the ACC in testing-set is 80%, but when I use the epoch101 trained_model to test, the ACC in testing-set is below 60%. Do you know why?
I cannot reproduce the results of the C&I&M to O scenario in your paper. The best AUC results that I achieved by using your code is 82%, which has a large gap compared to the results published in your paper 91.16%. How do you test your model on Oulu dataset? Do you use the all data (training and testing) or just the testing data? Why I cannot reproduce the results?
Thank you very much!!
It's a good job, but it doesn't mention aim-fas. Aim-fas is similar to this article.
Wait for the pre-trained model?
Hi,
thanks for sharing the code.
I have some questions about your project that I would like to confirm.
1.What did your meta learner mainly learn?(FeatExtractor Weight or some hyperparameters?)
2.When testing, is it not necessary to generate a face depth map? because it is only used to auxiliary supervision, like an image label?
3.we need to generate a depth map through PRNet and add it to the input ? or your code contains this generate function?
4.Is it possible to achieve real-time detection?
Thanks.
您可以提供一下fake_depth.jpg吗,所有假脸的深度是不是都假设为0了,那么您在训练的过程中用的fake_depth.jpg是什么样的呢,可以描述一下吗
这是数据集自带的吗
I have some questions about the code In datasets/DatasetLoader.py :
if getreal:
filename = 'image_list_real.txt'
else:
filename = 'image_list_fake.txt'
What's the content in image_list_real.txt about and how do you get these files?
I cannot get these files after I download the datasets so I am curious about it.
I have some problem about how to process the origin dataset.
Thanks for your great work and hope for relpy!
您好,我按照您的要求送入网络rgb人脸图片,但是不管是real还是fake的样本,分数都在0.5左右,没有大的变化。请问您遇到过这种问题吗? @ @rshaojimmy
Is the depth map label range 0-255 or 0-1? If it is the latter, what is the normalization method?
if getreal and name=='idiap':
depth_dir = os.path.join('depth', dirlist[0], dirlist[1], dirlist[2], imgname + '_depth.jpg')
elif getreal and name=='CASIA':
depth_dir = os.path.join('depth', dirlist[0], dirlist[1], dirlist[2], imgname + '_depth.jpg')
elif getreal and name=='MSU':
depth_dir = os.path.join('depth', dirlist[0], dirlist[1], imgname + '_depth.jpg')
elif getreal and name=='OULU':
depth_dir = os.path.join('depth', dirlist[0], imgname + '_depth.jpg')
else:
==> depth_dir = os.path.join('depth', 'fake_depth.jpg')
Why you let all name of fake_depth_image are 'fake_depth.jpg' ?
Did you not use them?
i see the hsv image also as the input in your code, and don't mark it in your paper . can you tell me what information dose hsv image can provide?
Hello, I'm Minha Kim researching anti-spoofing in korea.
Firstly, I appreciate you sharing this method with the public.
I have one question, how did you get ~_depth images?
As I know, all datasets don't contain depth images.
So, I wonder how did you make or get the dataset as a depth type of image.
Thank you :)
With best regards,
Minha Kim.
I am sorry for the inconveninent I have caused. I would like to ask, do you reproduce the code of MetaReg?
Hi,
Thanks for sharing your code.
I have installed and setup the prerequisite software.
However when I run the Testing mode using this command "python main.py --training_type Test", I encountered the following error. The program main.py seems to be asking for the command line argument parameter tstfile.
Appreciate your advice. Thanks
File "main.py", line 175, in
main(parser.parse_args())
File "main.py", line 22, in main
savefilename = osp.join(args.tstfile, args.tstdataset+'to'+args.dataset_target+args.snapshotnum)
AttributeError: 'Namespace' object has no attribute 'tstfile'
Best Regards,
Benjamin
I am confused about the path processing of the data txt file. Can you share the specific path format of the txt file? Thank you!
I am trying to run the Test method but keep running into errors, can you please mention what are all the required files and settings that I would need to be able to run it.
I don't know the content of the txts, such as image_list_all.txt. Hope you can share them, thanks a lot
I want to compare the ROC curves of some methods for domain generalization.
Could you please provide optimal training model? Thank you.
My Email address:[email protected]
Nice job! I do not have enough data, but I want to test the performance of this model.
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