Hello all
I stumbled over this paper:

  
      
      arXiv.org
  
  
    

DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image... 16

We present the DeepHist - a novel Deep Learning framework for augmenting a
network by histogram layers and demonstrate its strength by addressing
image-to-image translation problems. Specifically, given an input image and a
reference color...


  
  
    
    
  
  


Looks extremely interesting. I’m working on an image-to-image translation model and have been unsuccessfully trying to implement a histogram loss.
Now unfortunately I’m too stupid to translate the math in this paper into Pytorch code.
Maybe someone more intelligent here in the forum can?