Conference item
NeuroMorph: unsupervised shape interpolation and correspondence in one go
- Abstract:
-
We present NeuroMorph, a new neural network architecture that takes as input two 3D shapes and produces in one go, i.e. in a single feed forward pass, a smooth interpolation and point-to-point correspondences between them. The interpolation, expressed as a deformation field, changes the pose of the source shape to resemble the target, but leaves the object identity unchanged. NeuroMorph uses an elegant architecture combining graph convolutions with global feature pooling to extract local feat...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Bibliographic Details
- Publisher:
- IEEE Publisher's website
- Host title:
- 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Pages:
- 7469-7479
- Publication date:
- 2021-11-13
- Acceptance date:
- 2021-06-01
- Event title:
- Conference on Computer Vision and Pattern Recognition (CVPR 2021)
- Event location:
- Virtual event
- Event website:
- https://cvpr2021.thecvf.com/
- Event start date:
- 2021-06-19
- Event end date:
- 2021-06-25
- DOI:
- EISSN:
-
2575-7075
- ISSN:
-
1063-6919
- EISBN:
- 9781665445092
- ISBN:
- 9781665445108
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1237039
- Local pid:
- pubs:1237039
- Deposit date:
- 2022-02-28
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2021
- Rights statement:
- © 2021 IEEE.
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from IEEE at: https://doi.org/10.1109/CVPR46437.2021.00739
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