Watson, Jamie;
Aleotti, Filippo;
Sayed, Mohamed;
Qureshi, Zawar;
Mac Aodha, Oisin;
Brostow, Gabriel;
Firman, Michael;
(2024)
AirPlanes: Accurate Plane Estimation via 3D-Consistent Embeddings.
In:
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024.
(pp. pp. 5270-5280).
Institute of Electrical and Electronics Engineers (IEEE)
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Abstract
Extracting planes from a 3D scene is useful for downstream tasks in robotics and augmented reality. In this paper we tackle the problem of estimating the planar surfaces in a scene from posed images. Our first finding is that a surprisingly competitive baseline results from combining popular clustering algorithms with recent improvements in 3D geometry estimation. However, such purely geometric methods are understandably oblivious to plane semantics, which are crucial to discerning distinct planes. To overcome this limitation, we propose a method that predicts multi-view consistent plane embeddings that complement geometry when clustering points into planes. We show through extensive evaluation on the ScanNetV2 dataset that our new method outperforms existing approaches and our strong geometric baseline for the task of plane estimation.
| Type: | Proceedings paper |
|---|---|
| Title: | AirPlanes: Accurate Plane Estimation via 3D-Consistent Embeddings |
| Event: | IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) |
| Location: | Seattle, WA, USA |
| Dates: | 16th-22nd June 2024 |
| ISBN-13: | 979-8-3503-5301-3 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/CVPR52733.2024.00504 |
| Publisher version: | https://doi.org/10.1109/cvpr52733.2024.00504 |
| 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. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10203445 |
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