SimSC: a simple framework for semantic correspondence with temperature learning
We propose SimSC, a remarkably simple framework, to address the problem of semantic matching only based on the feature backbone. We discover that when fine-tuning ImageNet pre-trained backbone on the semantic matching task, L2 normalization of the feature map, a standard procedure in feature matchin...
| Main Authors: | , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
ArXiv
2023
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