Klemen Grm and Tim Oblak and Aleš Jaklič and Vitomir Štruc and Peter Peer and Franc Solina (2019) Recovery of superquadric parameters from range images using deep learning. In: BMVA technical meeting: 3D vision with deep learning , 20.2.2019, BCS (British Computer Society) in London. 5 Southampton St WC2E 7HA London United Kingdom . (Unpublished)
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Abstract
With the recent advancements in deep neural computation, we devise a method to recover superquadric parameters from range images using a convolutional neural network. By training our simple, fullyconvolutional architecture on synthetic data images, containing a single superquadric, we achieve encouraging results. In a fixed rotation scenario, the model could already be used in practice, but we still need to improve on prediction of arbitrary rotational parameters in the future.
| Item Type: | Conference or Workshop Item (Poster) |
|---|---|
| Institution: | University of Ljubljana |
| Department: | Faculty of Computer and Information Science |
| Divisions: | Faculty of Computer and Information Science > Computer Vision Laboratory |
| Item ID: | 4392 |
| Date Deposited: | 11 Mar 2019 10:17 |
| Last Modified: | 11 Mar 2019 10:17 |
| URI: | http://eprints.fri.uni-lj.si/id/eprint/4392 |
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- Recovery of superquadric parameters from range images using deep learning (deposited 04 Mar 2019 11:27)
- Recovery of superquadric parameters from range images using deep learning (deposited 11 Mar 2019 10:17)[Currently Displayed]
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