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In theory yes, but one problem with the monocular depth estimation models is that it only provides "normalized" depth. If you want to get the actual depth (which I guess you do), you need to calculate the scale in every frame. And this model will not be able to help with that because you already have a dense depth map. You could get this scale if you had some sparse depth points (from some low resolution depth sensor) by performing a regression between the sparse absolute depth points and the "normalize" depth at those points.
The way I see this model, it could help to get the absolute dense depth map directly from the sparse absolute depth without the need to do any regression, by filling the sparse depth map. So, it is more like a replacement for those models.
I have also uploaded an example for tflite in case it helps:
https://github.com/ibaiGorordo/TFLite-msg_chn_wacv20-depth-completion
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