基于关键点注意力和通道注意力的服装分类算法

doi:10.13229/j.cnki.jdxbgxb20190755

Abstract

Abstract:

In order to solve the problems of clothing landmark detection, category classification and attribute prediction, a novel deep neural network based on the combination of landmark attention mechanism and channel attention mechanism was proposed. First, the network predicts clothing landmarks by convoluting the input feature map to extract features, deconvoluting to restore the feature map size. Then, it acquires the connection between the landmarks by adding a non-local structure, thus, obtaining the landmark attention. The landmark attention module emphasizes the characteristics of the discriminative area in the clothing, and then new feature maps are generated. In addition, channel attention increases the weight of some feature maps which are more useful for category classification and attribute prediction. The experimental results on the DeepFashion dataset show that the proposed method can improve the accuracy of category classification and the recall rate of attribute prediction compared with the existing methods.

Key words: computer application, clothing category classification, clothing attribute prediction, deep learning, attention mechanism

CLC Number:

TP391

Hong-wei ZHAO,Xiao-han LIU,Yuan ZHANG,Li-li FAN,Man-li LONG,Xue-bai ZANG. Clothing classification algorithm based on landmark attention and channel attention[J].Journal of Jilin University(Engineering and Technology Edition), 2020, 50(5): 1765-1770.

Figures/Tables 6

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References 17

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方法	左领口	右领口	左袖口	右袖口	左腰线	右腰线	左下摆	右下摆	平均值
文献[1]	0.0854	0.0902	0.0973	0.0935	0.0854	0.0845	0.0812	0.0823	0.0872
文献[2]	0.0628	0.0637	0.0658	0.0621	0.0726	0.0702	0.0658	0.0663	0.0660
文献[14]	0.0570	0.0611	0.0672	0.0647	0.0703	0.0694	0.0624	0.0627	0.0643
文献[3]	0.0332	0.0346	0.0487	0.0519	0.0442	0.0429	0.0620	0.0639	0.0474
本文	0.0385	0.0390	0.0546	0.0570	0.0489	0.0517	0.0552	0.0585	0.0504

方法	分类		纹理		面料		形状		部分
方法	top-3	top-5	top-3	top-5	top-3	top-5	top-3	top-5	top-3	top-5
文献[15]	43.73	66.26	24.21	32.65	25.38	36.06	23.39	31.26	26.31	33.24
文献[16]	59.48	79.58	36.15	48.15	36.64	48.52	35.89	46.93	39.17	50.14
文献[1]	82.58	90.17	37.46	49.52	39.30	49.84	39.37	48.59	44.13	54.02
文献[17]	86.30	92.80	53.60	63.20	39.10	48.80	50.10	59.50	38.80	48.90
文献[3]	91.16	96.12	56.17	65.83	43.20	53.52	58.28	67.80	46.97	57.42
本文	91.24	95.94	57.11	66.62	44.25	54.52	59.56	68.92	47.60	58.01

Clothing classification algorithm based on landmark attention and channel attention

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