How to use Tensorflow Model Zoo frozen graphs in an Estimator pipeline?
After a lot of research, I came to the conclusion that this is doable, but would require a lot of work.

Essentially, the steps to achieve such a transformation are as follows:


Use this version of the model exporter (or any other solution) to re-export the savedmodel with its variables (by default, the Model Zoo does not give the variables, only an inference-ready model).
Load the model using the SavedModel API, i.e. loaded = tf.saved_model.load(...).
Extract the inference function: inference_func = loaded.signatures['serving_default'].
Define your loss function. This part is the most complex because the existing functions are part of the Object Detection API which is pretty much outdated. Tensorflow is already working on the upgrade of the API but at the time of writing this, they still expect a couple more months to finish it.
Set up your Dataset.
Train your model.


The best option is probably to wait for the new release of the official OD API.