Yan, Xingguang;
Lin, Liqiang;
Mitra, Niloy J;
Lischinski, Dani;
Cohen-Or, Daniel;
Huang, Hui;
(2022)
ShapeFormer: Transformer-based Shape Completion via Sparse Representation.
In:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
(pp. pp. 6229-6239).
IEEE: New Orleans, LA, USA.
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Abstract
We present ShapeFormer, a transformer-based network that produces a distribution of object completions, conditioned on incomplete, and possibly noisy, point clouds. The resultant distribution can then be sampled to generate likely completions, each exhibiting plausible shape details while being faithful to the input. To facilitate the use of transformers for 3D, we introduce a compact 3D representation, vector quantized deep implicit function (VQDIF), that utilizes spatial sparsity to represent a close approximation of a 3D shape by a short sequence of discrete variables. Experiments demonstrate that ShapeFormer outperforms prior art for shape completion from ambiguous partial inputs in terms of both completion quality and diversity. We also show that our approach effectively handles a variety of shape types, incomplete patterns, and real-world scans.
| Type: | Proceedings paper |
|---|---|
| Title: | ShapeFormer: Transformer-based Shape Completion via Sparse Representation |
| Event: | 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) |
| Location: | New Orleans, LA |
| Dates: | 18 Jun 2022 - 24 Jun 2022 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/CVPR52688.2022.00614 |
| Publisher version: | https://doi.org/10.1109/CVPR52688.2022.00614 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Computer Science, Computer Science, Artificial Intelligence, Imaging Science & Photographic Technology, Science & Technology, Technology |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10162116 |
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