Refine module input discrepancy

[dvansa-eurecat]

Hi! We observed some discrepancy between the code and the paper regarding the inputs that go through the Refine() module. On the paper (according to Figure 4.) the input is a concatenation of depth estimations comming from the 2 branches (Equirectangular and projected Cubemap) making it a 2 channel Tensor.

But on the code, the concatenation additionally includes the RGB input tensor making it a 5 channel Tensor mixing color and depth information:
https://github.com/Yeh-yu-hsuan/BiFuse/blob/6fb1cbe8a3c3891a9067f595ba2af9d14f8ae1c6/models/FCRN.py#L522

Which one of the 2 approaches is the correct one?

Also, on the last projection to bring the Cubemap branch output to Equirectangular, the transformation is done in 2 steps:
https://github.com/Yeh-yu-hsuan/BiFuse/blob/6fb1cbe8a3c3891a9067f595ba2af9d14f8ae1c6/models/FCRN.py#L519-L520

Couldn't the transformation self.ce.C2E() be directly applied to the Cubemap branch output (as the Fusion blocks do)?