Low-Rank Bilinear Pooling for Fine-Grained Classification
Low-Rank Bilinear Pooling for Fine-Grained Classification
Pooling second-order local feature statistics to form a high-dimensional bilinear feature has been shown to achieve state-of-the-art performance on a variety of fine-grained classification tasks. To address the computational demands of high feature dimensionality, we propose to represent the covariance features as a matrix and apply a low-rank bilinear classifier. …