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Zero NeRF: Registration with Zero Overlap by Peat, Casey; Batchelor, Oliver; Green, Richard; Atlas, James is a scholarly article available to read on EtoBox.

What is Zero NeRF: Registration with Zero Overlap about?

We present Zero-NeRF, a projective surface registration method that, to the best of our knowledge, offers the first general solution capable of alignment between scene representations with minimal or zero visual correspondence. To do this, we enforce consistency between visible surfaces of partial and complete reconstructions, which allows us to constrain occluded geometry. We use a NeRF as our surface representation and the NeRF rendering pipeline to perform this alignment. To demonstrate the efficacy of our method, we register real-world scenes from opposite sides with infinitesimal overlaps that cannot be accurately registered using prior methods, and we compare these results against widely used registration methods.

Author

Peat, Casey; Batchelor, Oliver; Green, Richard; Atlas, James

Published

2022

Language

EN