Specialized re-ranking: A novel retrieval-verification framework for cloth changing person re-identification

Abstract

Cloth changing person re-identification(Re-ID) can work under more complicated scenarios with higher security than normal Re-ID and biometric techniques and is therefore extremely valuable in applications. Meanwhile, the wide range of appearance flexibility results in more similar-looking, confusing images, which is the weakness of the widely used retrieval methods. In this work, we shed light on how to handle these similar images. Specifically, we propose a novel retrieval-verification framework. Given an image, the retrieval module will search for a shot list of similar images quickly. Our proposed verification network will then compare the probe image with these candidate images by contrasting local details for their similarity scores. An innovative ranking strategy is also introduced to achieve a good balance between retrieval and verification results. Comprehensive experiments are conducted to show the effectiveness of our framework and its capability in improving the state-of-the-art methods remarkably on both synthetic and realistic datasets.