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Contrastively-reinforced Attention Convolutional Neural Network for Fine-grained Image Recognition
British Machine Vision Conference
Fine-grained visual classification is inherently challenging because of its inter-class similarity and intra-class variance. However, by contrasting the images with same/different labels, a human can instinctively notice that the key clues lie in certain objects while other objects are ignorable. Inspired by this, we propose Contrastively-reinforced Attention Convolutional Neural Network (CRA-CNN), which reinforces the attention awareness of deep activations. CRA-CNN mainly contains two parts:dblp:conf/bmvc/LiuWKM20 fatcat:gf4fajmgtfcfplxwfshyopw6le