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The MXNet Implementation of Stacked Hourglass and Stacked SAT for Robust 2D and 3D Face Alignment

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Why is there no Z-axis coordinate in 3d landmarks detection? What is the difference between this and 2D landmarks detection? THANKS!

when i run test.py as your instruction, the visualized result seems not acceptable. there so many face bounding box and each bbox have a face landmark result. this phenomenon look...

Hi, I want to know how you preprocess the data into rec file, what data augmentation has been used?

Hi, am i right, that there is no code provided for "Inside Transformer" and "Outside Transformer"? Only for U-net and Hourglass training/eval part?

Hi, do you have any suggestions on the next problem: While training sdu(nadam,lr=0.00025), this is the loss on validation test: ![image](https://user-images.githubusercontent.com/48060406/53510422-fc2d1e00-3ace-11e9-9454-65b328d3ec94.png) Different model on the same training data was fine...

LocalFileSystem: fail to open "../deploy/mtcnn-model/det1-symbol.json"

I only see the landmarks detection. Where is Face Alignment?