SimSC: A Simple Framework for Semantic Correspondence with Temperature Learning

[https://arxiv.org/pdf/2305.02385.pdf](https://arxiv.org/pdf/2305.02385.pdf)

By: Xinghui Li, Kai Han, Xingchen Wan, Victor Adrian Prisacariu, University of Oxford, The University of Hong Kong

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>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 matching, produces an overly smooth matching distribution and significantly hinders the fine-tuning process. By setting an …

computervision feature fine-tuning framework imagenet kong map normalization oxford semantic standard university university of oxford