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Multi-feature fusion for fine-grained sketch-based image retrieval.
- Source :
- Multimedia Tools & Applications; Oct2023, Vol. 82 Issue 24, p38067-38076, 10p
- Publication Year :
- 2023
-
Abstract
- Fine-grained sketch-based image retrieval has become an important research topic in the computer vision area. To take advantage of more fine-grained information, we proposed a multi-feature fusion network for fine-grained sketch-based image retrieval. Multi-feature consists of a coarse-grained feature and two fine-grained features which can make better use of fine-grained information. Moreover, a mixed attention module is introduced into the network to extract more discriminating features. Finally, we use the DR-triplet loss to achieve more optimal directions of pair displacements to improve the retrieval performance. Experiments on two extended FG-SBIR datasets, QMUL-Shoe and QMUL-Chair, prove the effectiveness of our method. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13807501
- Volume :
- 82
- Issue :
- 24
- Database :
- Complementary Index
- Journal :
- Multimedia Tools & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 172755202
- Full Text :
- https://doi.org/10.1007/s11042-022-14115-0