May 26, 2017 · In this paper, we learn a similarity function that considers the interactions of features in the grids not only from the same spatial positions, ...

Abstract— Either global (e.g., intensity histograms and coefficients of sparse representation) or local (e.g., scale-invariant.

Oct 27, 2022 · This paper proposes a Siamese network with non-local correlation attention (SiamNCA). First, a non-local correlation attention module is proposed.

Here Nonlocal similarity learning based is used, in this nonlocal feature considers all pairs of grids among the target and its background samples and ...

Oct 1, 2018 · In this paper, we learn a similarity function that considers the interactions of features in the grids not only from the same spatial positions, ...

Sep 21, 2020 · Among it, an appearance memory network explores spatio-temporal non-local similarity to learn the dense correspondence between the segmentation ...

First, a non-local correlation attention module is proposed to integrate the long-range information into the o=similarity matrix, and give each sample in the ...

The right branch is the proposed method with contrast similarity learning to improve the similarity of the same objects without label informa- tion. which is ...

The advantages of the proposed sparse representation method are two-folds: 1) It can properly fuse the observation groups with reliable and unreliable features ...

Feb 27, 2024 · In this paper, we present a novel anchor-free visual tracking framework, referred to as feature dynamic activation siamese network (SiamFDA).