Estimation of near-instance-level attribute bottleneck for zero-shot learning
Zero-Shot Learning (ZSL) involves transferring knowledge from seen classes to unseen classes by establishing connections between visual and semantic spaces. Traditional ZSL methods identify novel classes by class-level attribute vectors, which implies an information bottleneck. These approaches ofte...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Springer Nature
2024
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