U-Net sounds like a good choice. You could use something like L1 or L2 loss with the Adam optimizer. These settings seem to work well in general.
If you want to find studies or comparisons of SOTA models, you can look at:
  

      paperswithcode.com
  

  
    

Papers with Code - Depth Estimation 2

  **Depth Estimation** is a crucial step towards inferring scene geometry from 2D images. The goal in monocular Depth Estimation is to predict the depth value of each pixel, given only a single RGB image as input.


Source: [DIODE: A Dense Indoor and...


  

  
    
    
  

  


or
  
      

      GitHub
  

  
    

GitHub - scott89/awesome-depth: A curated list of publication for depth...

  A curated list of publication for depth estimation - GitHub - scott89/awesome-depth: A curated list of publication for depth estimation