Szczegóły publikacji
Opis bibliograficzny
Leveraging vision in transformers model for point cloud pattern matching / Patryk Najgebauer, Rafał Grycuk, Rafał SCHERER // W: Artificial Intelligence and Soft Computing : 24th International Conference, ICAISC 2025 : Zakopane, Poland, June 22–26, 2025 : proceedings , Pt. 2 / eds. Leszek Rutkowski, [et al.]. — Cham : Springer Nature Switzerland, cop. 2026. — ( Lecture Notes in Computer Science ; ISSN 0302-9743. Lecture Notes in Artificial Intelligence ; 15949 ). — ISBN: 978-3-032-03707-7; e-ISBN: 978-3-032-03708-4. — S. 179–186. — Bibliogr., Abstr. — Publikacja dostępna online od: 2025-11-01. — R. Scherer - dod. afiliacja: Czȩstochowa University of Technology
Autorzy (3)
- Najgebauer Patryk
- Grycuk Rafał
- AGHScherer Rafał
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 164446 |
|---|---|
| Data dodania do BaDAP | 2026-01-22 |
| DOI | 10.1007/978-3-032-03708-4_14 |
| Rok publikacji | 2026 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Artificial Intelligence and Soft Computing 2025 |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
In this article, we propose a method for comparing arbitrary sets of point clouds based on pattern descriptors. The method is specifically designed to process large outdoor 3D laser scans characterized by highly variable point density, which changes with distance from the scan center. To generate pattern descriptors, we utilize a modified encoder block from a Vision in Transformer model, trained with a differential loss function. The model is trained on scanner-specific data, enabling it to generalize to any scans without requiring retraining.
