registration
Papers with tag registration
2022
- nerf2nerf: Pairwise Registration of Neural Radiance FieldsLily Goli, Daniel Rebain, Sara Sabour, Animesh Garg, and Andrea TagliasacchiIn 2022
We introduce a technique for pairwise registration of neural fields thatextends classical optimization-based local registration (i.e. ICP) to operateon Neural Radiance Fields (NeRF) – neural 3D scene representations trainedfrom collections of calibrated images. NeRF does not decompose illumination andcolor, so to make registration invariant to illumination, we introduce theconcept of a ”surface field” – a field distilled from a pre-trained NeRFmodel that measures the likelihood of a point being on the surface of anobject. We then cast nerf2nerf registration as a robust optimization thatiteratively seeks a rigid transformation that aligns the surface fields of thetwo scenes. We evaluate the effectiveness of our technique by introducing adataset of pre-trained NeRF scenes – our synthetic scenes enable quantitativeevaluations and comparisons to classical registration techniques, while ourreal scenes demonstrate the validity of our technique in real-world scenarios.Additional results available at: https://nerf2nerf.github.io
Registration of neural radiance fields. 从nerf中提取surface fields, 然后求解两个surface fields的rigid transformation.
registration nerf@inproceedings{nerf2nerf, title = {nerf2nerf: Pairwise Registration of Neural Radiance Fields}, author = {Goli, Lily and Rebain, Daniel and Sabour, Sara and Garg, Animesh and Tagliasacchi, Andrea}, year = {2022}, tags = {registration, nerf}, sida = {Registration of neural radiance fields. 从nerf中提取surface fields, 然后求解两个surface fields的rigid transformation.}, }