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tjiiv-cprg / EPro-PnP

[CVPR 2022 Oral, Best Student Paper] EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

Home Page:https://www.youtube.com/watch?v=TonBodQ6EUU

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is there any existed work that apply this fantastic algorithm to BOP test?

minghuiwsw opened this issue · comments

commented

Hi, first congratulate and respect to your great work!
I find the dataset structure in your "data preparation" part is different from that of the official BOP dataset, i.e. the official BOP dataset may not contain VOC2012 as background and the content in LM is different from yours. So I wonder how to test on BOP dataset (using BOP toolkit) with your EPro-pnp. Is there any suggestions or existed work? Thanks a lot!

commented

Hi! We have not yet tested EPro-PnP using the BOP toolkit, since all the data interfaces are from the original CDPN implementation. The authors of CDPN did provide another codebase for BOP, though, which might be helpful.