Clothing Image Parsing Method Based on Multi-scale Fusion Enhancement

Abstract:

By using the features of each level in convolutional neural network， a clothing image parsing method based on multi-scale fusion enhancement was proposed. Through the fusion enhancement module， the semantic information and the features in different scales were effectively fused with the consideration of global information. The results show that the average F1 score on the Fashion Clothing test set reaches 60.57%， and the mean intersection over union（MIoU） on the Look Into Person（LIP） validation set reaches 54.93%. The method can effectively improve the accuracy of clothing image parsing.