So you may have seen a website called Teachable Machine that allows you to classify custom poses. They use the older PoseNet model which I do not recommend anymore but essentially I believe they take the outputs one of the higher layers of that model and then add a simple multi layer perceptron to the end of that which is then trained to classify the poses (the original model is not re-trained of course as that would need all the original training data which they dont have so its frozen).
Essentially you have a trained pose model that you dont want to retrain per se, but you just want to retrain some final custom layers yourself to detect poses from the knowledge the pose model already has - a form of transfer learning if you will.
I actually am in the process of writing an EdX course for TensorFlow.js 1 and just completed writing an example that shows how to load the raw MoveNet model from TF Hub which theoretically you could inspect with model.summary (in JavaScript) and then build upon. See this link:

  
      

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Also check this example I wrote which shows how to grab some intermediate layer which you could then feed into your own custom trainable layers as inputs.

  
      

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