Hadjivelichkov, D;
Zwane, S;
Deisenroth, MP;
Agapito, L;
Kanoulas, D;
(2025)
Semantic Cross-Pose Correspondence from a Single Example.
In:
Proceedings of the 2025 IEEE International Conference on Robotics and Automation (ICRA).
(pp. pp. 1414-1420).
IEEE: Atlanta, GA, USA.
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Abstract
This article focuses on predicting how an object can be transformed to a semantically meaningful pose relative to another object, given only one or few examples. Current pose correspondence methods rely on vast 3D object datasets and do not actively consider semantic information, which limits the objects to which they can be applied. We present a novel method for learning cross-object pose correspondence. The proposed method detects interacting object parts, performs one-shot part correspondence, and uses geometric and visual-semantic features. Given one example of two objects posed relative to each other, the model can learn how to transfer the demonstrated relations to unseen object instances. Supplementary details can be found at https://sites.google.com/view/semantic-pose-correspondence
| Type: | Proceedings paper |
|---|---|
| Title: | Semantic Cross-Pose Correspondence from a Single Example |
| Event: | 2025 IEEE International Conference on Robotics and Automation (ICRA) |
| Dates: | 19 May 2025 - 23 May 2025 |
| ISBN-13: | 979-8-3315-4139-2 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ICRA55743.2025.11128585 |
| Publisher version: | https://doi.org/10.1109/ICRA55743.2025.11128585 |
| 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: | Point cloud compression, Solid modeling, Three-dimensional displays, Accuracy, Semantics, Robot vision systems, Predictive models, Rendering (computer graphics), Trajectory, Robotics and automation |
| 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/10215493 |
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