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METHOD FOR GENERATING DESCRIPTIONS FOR CLOTHING IMAGES TO SUPPORT INTELLIGENT SYSTEM

S Sharmila Shetty, Ashwija Shetty, Deeksha Poojary, Karthik Kille, Mrs. Sivapuram Jayasri

Mrs. Sivapuram Jayasri
(Project Guide) Assistant Professor,

Department of Information Science and Engineering A J Institute of Engineering and Technology Mangalore, Karnataka, India Jayasree@ajiet.edu.in

Abstract— Image captioning aims to generate descriptions of images with natural language sentences automatically. Most methods tackle this problem in an end-to-end fashion in recent years, which generates captions directly from image-level features but ignores high-level semantic information. The method that introduced the attribute concept into the CNN- RNN framework made a considerable improvement while the performance depended on the manually selected attributes heavily. Image captioning, i.e., automatically generating natural language image descriptions, is useful for the visually impaired, and for natural language-based image search. Image captioning has increasingly large domains of application, and fashion is not an exception. Having automatic item descriptions is of great interest for fashion web platforms hosting sometimes hundreds of thousands of images. This system is one of the first to tackle image captioning for fashion images. To contribute to addressing dataset diversity issues, we introduced the InFashAIv1 dataset containing almost 16.000 African fashion item images with their titles, prices, and general descriptions.