mlsanityData to 7 Oct 2026

3D Shape Knowledge Graph for Cross-domain 3D Shape Retrieval

arXiv 2210.15136 ↗First posted 27 Oct 2022cs.CVcited by 4

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Abstract (arXiv)

The surge in 3D modeling has led to a pronounced research emphasis on the field of 3D shape retrieval. Numerous contemporary approaches have been put forth to tackle this intricate challenge. Nevertheless, effectively addressing the intricacies of cross-modal 3D shape retrieval remains a formidable undertaking, owing to inherent modality-based disparities. This study presents an innovative notion, termed "geometric words", which functions as elemental constituents for representing entities through combinations. To establish the knowledge graph, we employ geometric words as nodes, connecting them via shape categories and geometry attributes. Subsequently, we devise a unique graph embedding method for knowledge acquisition. Finally, an effective similarity measure is introduced for retrieval purposes. Importantly, each 3D or 2D entity can anchor its geometric terms within the knowledge graph, thereby serving as a link between cross-domain data. As a result, our approach facilitates multiple cross-domain 3D shape retrieval tasks. We evaluate the proposed method's performance on the ModelNet40 and ShapeNetCore55 datasets, encompassing scenarios related to 3D shape retrieval and cross-domain retrieval. Furthermore, we employ the established cross-modal dataset (MI3DOR) to assess cross-modal 3D shape retrieval. The resulting experimental outcomes, in conjunction with comparisons against state-of-the-art techniques, clearly highlight the superiority of our approach.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 32 of its 76 references that are in the map. First posted on arXiv 27 Oct 2022.

Builds on

32 of 76 references.

References · 32

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20 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 2.

4 papers.

  1. 2025Fully-Geometric Cross-Attention for Point Cloud Registrationcited by 3
  2. 2024PReP: Efficient context-based shape retrieval for missing partscited by 0
  3. 2026Clustering-Enhanced Domain Adaptation for Cross-Domain Intrusion Detection in Industrial Control Systemscited by 0
  4. 2026Medoid Prototype Alignment for Cross-Plant Unknown Attack Detection in Industrial Control Systemscited by 0