Question about Condition Normalizing Flows

[yanhn]

Thanks for sharing your work. @nkolot
I have this question during using demo.py. Hope you can help me to understand normalizing flow a bit more, thank you.

During stage-2(fitting), I can get an adequate vector Z for a specific image. And I can use pretrained condition normalizing flow to convert such a vector Z into corresponding smpl pose parameters(body_pose and global_orient). But I do a bit more to using normalizing flow in reverse direction to convert smpl parameters back to vector Z(using this function). However, the output vector Z is not even close to the origin adequate vector Z.
I was doing this to test if normalizing flow is a revertable function. But the experiment result is not as expected. Maybe I used normalizing flow in the wrong way? Could you please help me out here?

[nkolot]

Please check Issue #1 where we discuss this problem. Because of the non-uniqueness of the 6D representation the inversion of the orthonormal 6D representation is not guaranteed to get you close to the original latent. However if you invert the output 6d representation (before we convert it to a rotation matrix) it is guaranteed to get mapped back to the z where you started.

[yanhn]

Thanks for your timely reply. I found the answer in Issue #1 .