The surge in online shopping has heightened the demand for interactive fashion design retrieval. Existing methods, however, exhibit imperfections in attribute segmentation, attributed to the specificity of clothing attributes. The attention region often encounters multiple attributes overlapping, causing changes in one attribute to affect irrelevant ones, resulting in poor retrieval accuracy. This paper addresses this challenge by proposing a deep neural network for fashion retrieval based on multi-attention attribute manipulation. In this approach, the feature extraction module sifts the extr...
