The Impact of Background Removal on Performance of Neural Networks for Fashion Image Classification and Segmentation

arXiv:2308.09764v2 Announce Type: replace-cross
Abstract: Fashion understanding is a hot topic in computer vision, with many applications having great business value in the market. Fashion understanding remains a difficult challenge for computer vision due to the immense diversity of garments and various scenes and backgrounds. In this work, we try removing the background from fashion images to boost data quality and increase model performance. Having fashion images of evident persons in fully visible garments, we can utilize Salient Object Detection …

abstract applications arxiv business business value challenge classification computer computer vision cs.ai cs.cv cs.lg diversity fashion hot image impact market networks neural networks performance segmentation type understanding value vision