Fotis, V., Romanelis, I., Mylonas, G., Kalogeras, A., & Moustakas, K. (2026). PReP: Efficient Context-Based Shape Retrieval for Missing Parts. IEEE Transactions on Multimedia, 28, 7074-7086. https://doi.org/10.1109/TMM.2026.3668613

@article{bea94a8425da462f978a7cfe780ddb74,
title = "PReP: Efficient Context-Based Shape Retrieval for Missing Parts",
abstract = "In this paper, we study the problem of shape part retrieval in the point cloud domain. Existing shape retrieval methods typically rely on the presence of a complete query object, but what if the part of interest is missing? We present the Part Retrieval Pipeline (PReP), which combines metric learning techniques with a trained classification model to evaluate the suitability of potential replacement parts from a database, within an application scenario aimed at circular economy. Through a progressively more difficult training procedure, PReP learns to recognize suitable parts based solely on shape context. Owing to its compact parameterization and low computational requirements, it can search a repository of tens of thousands of spare parts in just a few seconds. We also establish an alternative baseline approach for comparison, document the unique challenges associated with this task, and identify key design choices to address them.",
keywords = "Circular economy, Databases, Feature extraction, Pipelines, Point cloud compression, Shape, Solid modeling, Three-dimensional displays, Training, Transformers, Vectors, Deep learning, Part retrieval, Point clouds, Shape retrieval",
author = "Vlassis Fotis and Ioannis Romanelis and Georgios Mylonas and Athanasios Kalogeras and Konstantinos Moustakas",
year = "2026",
doi = "10.1109/TMM.2026.3668613",
language = "English",
volume = "28",
pages = "7074--7086",
journal = "IEEE Transactions on Multimedia",
issn = "1520-9210",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
}