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david-wb / gaze-estimation

A deep learning based gaze estimation framework implemented with PyTorch
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Reference Paper #7

Closed lghasemzadeh closed 3 years ago

lghasemzadeh commented 3 years ago

Hello Davis,

Would you please share the reference paper to this gaze-estimation work? I have these references:

https://ait.ethz.ch/projects/2018/landmarks-gaze/downloads/park2018etra.pdf https://www.cl.cam.ac.uk/research/rainbow/projects/unityeyes/ https://rahimentezari.github.io/GAN/gan-gaze.html https://openaccess.thecvf.com/content_ICCV_2019/papers/He_Photo-Realistic_Monocular_Gaze_Redirection_Using_Generative_Adversarial_Networks_ICCV_2019_paper.pdf https://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_A_Hierarchical_Generative_CVPR_2018_paper.pdf https://www.mdpi.com/1424-8220/20/17/4935/htm

But I need the exact reference to the GAN part.

I actually tested the first link which you mentioned is the base to this work several months ago and the performance was not satisfying and there was lag in the stream and the detection. I want to know exactly what improvement/development/modification made to this work which became this one.

Waiting for your response.

Thx,

david-wb commented 3 years ago

Hi @lghasemzadeh,

This project was completely based on https://ait.ethz.ch/projects/2018/landmarks-gaze/downloads/park2018etra.pdf.

I did not use GANs at all. The training data is generated using UnityEyes.

Hope that helps, David

lghasemzadeh commented 3 years ago

Hi David,

Would you please explain what improvement/development/modification you made to this work: https://ait.ethz.ch/projects/2018/landmarks-gaze/downloads/park2018etra.pdf.

As I mentioned I had tried that algorithm (the reference one) several months ago and its performance is a bit different from what you provided in your repo.

I want to know the differences between the reference one and this work you provided. Are they completely the same in methodology?

Thank you