huguesva / face-anti-spoofing-neural-network Goto Github PK
View Code? Open in Web Editor NEWImplementation of "Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision" in PyTorch.
Implementation of "Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision" in PyTorch.
I am obtaining the offset values between '85 to 115' for live and fake images. What possibly could be the reason behind it? Also, why have we selected 850 as our offset value?
Hi there
I wonder if you can share the pretrained network with me @huguesva ?
I need to validate my results with benchmarks provided in this paper.
I've required the OULU dataset for over a month without any reply. Could you please share your OULU dataset? Thank you very much.
My email : [email protected]
I haven't found gen_anchor()
function in this file utils.paf
(https://github.com/cleardusk/3DDFA/blob/master/utils/paf.py). @huguesva Can you please help me?
@huguesva Can you update READMEand upload models and dataset if possible ? Also provide info on accuracy
Hello,
I would like to ask you about the depth images.
At the first glance, I've tested the depth images which is generated from this repo. https://github.com/cleardusk/3DDFA.
It's obvious that the model performs can generate the depth map for every case including genuine/spoof images.
Do we need do apply further post-processing to obtain the 3D-shape images for real and non 3D-shape images for spoof?
Thank you in advanced.
Thank you for sharing your work.But the parameter 'net' (in Project_Spoofing ) isn't defined.Could you please help me with this?
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