Nov 7, 2023 · We propose HCCNet, an efficient yet effective semantic matching method which exploits the full potential of multi-scale correlation maps.

In this work, we shift our focus away from mining global match-wise relations, to better leveraging the multi-scale correlation maps holding various semantics.

In this work, we shift our focus away from mining global match-wise relations, to better leveraging the multi-scale correlation maps holding various semantics.

We propose HCCNet, an efficient yet effective semantic matching method which exploits the full potential of multi-scale correlation maps.

We propose HCCNet, an efficient yet effective semantic matching method which exploits the full potential of multi-scale correlation maps.

To provide an in-depth analysis on feature slicing, we plot input C and hidden ζ(CWhid) correlation statistics from our point- wise convolution in Fig. 2 where ...

Official PyTorch implementation of HCCNet: Efficient Semantic Matching with Hypercolumn Correlation (WACV '24 Oral, Best paper finalist (top 0.6%))

A quantitative analysis of the examples shows that non-agreeing t-participles appear significantly more often in East Aukštaitian than in South Aukštaitian. It ...

Efficient Semantic Matching with Hypercolumn Correlation ... Recent studies show that leveraging the match-wise relationships within the 4D correlation map yields ...

Efficient Semantic Matching with Hypercolumn Correlation. S Kim, J Min, M Cho. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer ...