Multi-Range View Aggregation Network with Vision Transformer Feature Fusion for 3D Object Retrieval

Page view(s)
122
Checked on Jan 15, 2025
Multi-Range View Aggregation Network with Vision Transformer Feature Fusion for 3D Object Retrieval
Title:
Multi-Range View Aggregation Network with Vision Transformer Feature Fusion for 3D Object Retrieval
Journal Title:
IEEE Transactions on Multimedia
Publication Date:
22 February 2023
Citation:
Lin, D., Li, Y., Cheng, Y., Prasad, S., Guo, A., & Cao, Y. (2023). Multi-Range View Aggregation Network with Vision Transformer Feature Fusion for 3D Object Retrieval. IEEE Transactions on Multimedia, 1–12. https://doi.org/10.1109/tmm.2023.3246229
Abstract:
View-based methods have achieved state-of-the-art performance in 3D object retrieval. However, view-based methods still encounter two major challenges. The first is how to leverage the inter-view correlation to enhance view-level visual features. The second is how to effectively fuse view-level features into a discriminative global descriptor. Towards these two challenges, we propose a multi-range view aggregation network (MRVANet) with a vision transformer based feature fusion scheme for 3D object retrieval. Unlike the existing methods which only consider aggregating neighboring or adjacent views which could bring in redundant information, we propose a multi-range view aggregation module to enhance individual view representations through view aggregation beyond only neighboring views but also incorporate the views at different ranges. Furthermore, to generate the global descriptor from view-level features, we propose to employ the multi-head self-attention mechanism introduced by vision transformer to fuse the view-level features. Extensive experiments conducted on three public datasets including ModelNet40, ShapeNet Core55 and MCB-A demonstrate the superiority of the proposed network over the state-of-the-art methods in 3D object retrieval.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR - INDUSTRY ALIGNMENT FUND - INDUSTRY COLLABORATION PROJECTS (IAF-ICP)
Grant Reference no. : I2001E0073
Description:
© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISSN:
1941-0077
1520-9210
Files uploaded:

File Size Format Action
tmm-main-final-revised.pdf 9.59 MB PDF Request a copy