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Focus-mechanism introduced human parsing method in static image
Author(s): 
Pages: 134-139
Year: Issue:  7
Journal: Video Engineering

Keyword:  DCNNResNetHuman parsingFocus mechanism;
Abstract: In view of the human parsing in static image,previous methods cannot focus on the regions that segmented.This will make the performance of these methods become bad.A mechanism is introduced into the proposed method which can focus regions segmented.ResNet is used in the proposed method and adapted to the task of human parsing.According to the problem of human parsing in static images,the loss function,auxiliary loss function and the loss function of the focus mechanism are designed in this paper.In addition,in order to get the auxiliary segmentation labels of the data sets,the segmentation labels and the attention focus map,a data preprocessing algorithm is proposed.Experiments are conducted on Pascal-Person-Part dataset and LIP dataset.Compared with SegNet,FCN-8s,DeepLabV2,Attention,LG-LSTM and Attention + SSL the experiment results show that the proposed method can achieve better human parsing performance.The results of pixel accuracy,mean pixel accuracy and IoU metric indicate the effectiveness of our method and our method can improve the human parsing results.
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