Parallel Attention Network for Robust Cattle Face Recognition in Wild Environments

A novel parallel attention network, PANet, achieves state-of-the-art accuracy of 88.03% on the first large-scale cattle face recognition dataset for wild environments, ICRWE, by effectively capturing local and global features through parallel attention modules.