Improving few-shot learning by spatially-aware matching and crosstransformer
Current few-shot learning models capture visual object relations in the so-called meta-learning setting under a fixed-resolution input. However, such models have a limited generalization ability under the scale and location mismatch between objects, as only few samples from target classes are provid...
| Huvudupphovsmän: | , , |
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| Materialtyp: | Conference item |
| Språk: | English |
| Publicerad: |
Springer
2023
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