Learning by aligning: Visible-infrared person re-identification using cross-modal correspondences

H Park, S Lee, J Lee, B Ham - Proceedings of the IEEE/CVF …, 2021 - openaccess.thecvf.com
We address the problem of visible-infrared person re-identification (VI-reID), that is,
retrieving a set of person images, captured by visible or infrared cameras, in a cross-modal …

Drone-based RGB-infrared cross-modality vehicle detection via uncertainty-aware learning

Y Sun, B Cao, P Zhu, Q Hu - … on Circuits and Systems for Video …, 2022 - ieeexplore.ieee.org
Drone-based vehicle detection aims at detecting vehicle locations and categories in aerial
images. It empowers smart city traffic management and disaster relief. Researchers have …

Cross-domain image retrieval: methods and applications

X Zhou, X Han, H Li, J Wang, X Liang - International Journal of Multimedia …, 2022 - Springer
Cross-domain images have been witnessed in an increasing number of applications. This
new trend triggers demands for cross-domain image retrieval (CDIR), which finds images in …

Work together: Correlation-identity reconstruction hashing for unsupervised cross-modal retrieval

L Zhu, X Wu, J Li, Z Zhang, W Guan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Unsupervised cross-modal hashing has attracted considerable attention to support large-
scale cross-modal retrieval. Although promising progresses have been made so far, existing …

Less is better: Exponential loss for cross-modal matching

J Wei, Y Yang, X Xu, J Song, G Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep metric learning has become a key component of cross-modal retrieval. By learning to
pull the features of matched instances closer while pushing the features of mismatched …