Dynamic Semantic Complementary Network for Zero-Shot Learning
Chen, Shuhuang Chen, Shiming Hong, Ziming Shao, Yuanjie You, Xinge
Chen, Shuhuang
Chen, Shiming
Hong, Ziming
Shao, Yuanjie
You, Xinge
Supervisor
Department
Computer Vision
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Type
Journal article
Date
2025
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Language
English
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Abstract
Zero-Shot Learning (ZSL) transfers knowledge from seen to unseen classes by associating visual features with shared semantic information. However, semantic information consists of high-level attributes with complex visual characteristics and the contrasting low-level attributes. Existing ZSL methods tend to oversimplify visual-semantic associations by ignoring high-level attributes, resulting in incomplete utilization of semantic information and limited knowledge transfer. To address this issue, we propose a novel Dynamic Semantic Complementary Network (DSCN). Based on training a main subnet that obtains complete semantic information, DSCN dynamically calculates and selects the ignored semantic information with a novel semantic utilization metric. An auxiliary subnet is then used to learn the ignored semantic information. Finally, we deploy complementary knowledge distillation to conduct effective knowledge interactions between the two subnets. DSCN makes full use of semantic information through the mutual complementarity between two subnets. Extensive experiments on three benchmark datasets (CUB, SUN and AWA2) demonstrate that DSCN achieves superior performance by maximizing semantic utilization, surpassing existing state-of-the-art methods.
Citation
S. Chen, S. Chen, Z. Hong, Y. Shao and X. You, "Dynamic Semantic Complementary Network for Zero-Shot Learning," in IEEE Transactions on Emerging Topics in Computational Intelligence, doi: 10.1109/TETCI.2025.3573239
Source
IEEE Transactions on Emerging Topics in Computational Intelligence
Conference
Keywords
Image Classification, Knowledge Distillation, Semantic Utilization Metric, Zero-shot Learning, Benchmarking, Information Use, Knowledge Management, Knowledge Transfer, Semantic Web, Semantics, Dynamic Semantic, Images Classification, Knowledge Distillation, Learning Methods, Learning Transfer, Low-level Attributes, Semantic Utilization Metric, Semantics Information, Subnets, Visual Feature, Image Classification
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IEEE