cfernandezlab / CFL

Tensorflow implementation of our end-to-end model to recover 3D layouts. Also with equirectangular convolutions!
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About results of EquiConvs and StdConvs #32

Open EricPengShuai opened 2 years ago

EricPengShuai commented 2 years ago

From the results of your paper, I find that the network constructed by Equirectangular Convolutions (EquiConvs) has no great improvement in indicators compared with the network constructed by traditional convolution (StdConvs). How can you explain the benefits of EquiConvs in processing ERP projection images?

In addition, the computation time of the network constructed by EquiConvs is 10 times that of the network constructed by StdConvs. So what are the advantages of EquiConvs compared to StdConvs?

jmfacil commented 2 years ago

These points are addressed in the paper.

On Thu, Mar 10, 2022 at 7:17 PM Shuai Peng @.***> wrote:

From the results of your paper, I find that the network constructed by Equirectangular Convolutions (EquiConvs) has no great improvement in indicators compared with the network constructed by traditional convolution (StdConvs). How can you explain the benefits of EquiConvs in processing ERP projection images?

In addition, the computation time of the network constructed by EquiConvs is 10 times that of the network constructed by StdConvs. So what are the advantages of EquiConvs compared to StdConvs?

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José M. Fácil Ph.D. Student in Computer Vision Website: http://webdiis.unizar.es/~jmfacil/ University of Zaragoza, Spain