GetNet: Get Target Area for Image Pairing

TL;DR

GetNet is a novel approach that combines STN and Siamese networks to efficiently identify target areas in image pairs, improving speed and accuracy for tasks like object matching.

Contribution

The paper introduces GetNet, an improved method that integrates STN with Siamese networks for better target area detection in image pairing tasks.

Findings

Achieves competitive speed and accuracy in image pairing

Outperforms traditional methods in efficiency

Effective in object category matching

Abstract

Image pairing is an important research task in the field of computer vision. And finding image pairs containing objects of the same category is the basis of many tasks such as tracking and person re-identification, etc., and it is also the focus of our research. Existing traditional methods and deep learning-based methods have some degree of defects in speed or accuracy. In this paper, we made improvements on the Siamese network and proposed GetNet. The proposed method GetNet combines STN and Siamese network to get the target area first and then perform subsequent processing. Experiments show that our method achieves competitive results in speed and accuracy.