Zero-shot learning via category-specific visual-semantic mapping and label refinement
Zero-shot learning (ZSL) aims to classify a test instance from an unseen category based on the training instances from seen categories in which the gap between seen categories and unseen categories is generally bridged via visual-semantic mapping between the low-level visual feature space and the in...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/142785 |