Comments (1)
@BeierZhu Hi, it is not a mistype, I actually followed an ECCV 2018 paper: A Deeply-initialized Coarse-to-fine Ensemble of
Regression Trees for Face Alignment(Please refer to table 3) to use inter-pupil distance as the normalization factor.
I also noticed some metrics listed on my table are actually inter-ocular normalized, such as Disentangling 3D Pose in A Dendritic CNN
for Unconstrained 2D Face Alignment, I will correct those ones and provide my inter-ocular normalized NME as well on arXiv.
Please note that using inter-ocular distance as the normalization factor will actually result in a smaller NME, so the inter-pupil normalized NMEs will always larger than the inter-ocular normalized NMEs.
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Related Issues (20)
- cant find AdaptiveWingLoss implement HOT 4
- How to show boundary map HOT 3
- what is the 'boundary_channels' output by Coordconv and how to use them? HOT 1
- Why does the output have one more channel than the num of landmarks? HOT 1
- Training code implementation HOT 8
- what is output dimention? HOT 2
- 68 Facial landmarks model HOT 1
- how visualize result? HOT 2
- About the model's generalization ability HOT 2
- recently can u realese the training code
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- When will the pretrained model on 300W be released? HOT 4
- Two years have passed, have you considered release the train code? HOT 3
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