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[2A6-GS-10-05] Generation of Captions Based on Attribute Predictions Highlighting Differences Between Garment Image Pairs
Keywords:Image Captioning, Deep Learning, Consumer Support
Detailed information for comparisons between products is necessary in consumers’ product purchasing process, especially during the information search and choice evaluation phases. However, conventional product descriptions, which are the main source of information, tend to focus only on the product in question, and thus do not adequately express the differences between products. To solve this problem, garments are treated as target products, and a caption-generation method that emphasizes the differences between pairs of garment images using a deep-learning model for image caption-generation is proposed and its effectiveness verified. The proposed method selects and outputs captions that express differences in features from a set of captions generated for input-garment image pairs. Subject experiments confirmed that the proposed method accurately represented the feature differences between garments and provided useful information for consumers to compare garments. In particular, the proposed method is highly effective for garment pairs with similar features.
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