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3D clothing data models have been learned from the real clothing data, but it is difficult to predict the exact segmentation mask of a garment as it varies depending on the size. The accurate segmentation of clothes has become a problem over the last few years due to automatic product detection for enhancing the shopping experience for consumers. The ability to recognize the associated attributes and clothing products will increase the shopping experience for consumers. In the fashion domain, the recent five years literature in computer vision focused on seeking solutions for the recognition of clothes. Still, there has been a gap in the efforts by the fashion designers and computer vision communities. This work proposes a deep learning framework that can learn how to detect and segment clothing objects accurately. We propose a clothing segmentation framework having novel feature extraction and fusion modules …