Hong Kong Polytechnic University and Alibaba have jointly established a fashion dataset for systematic analysis and labeling of fashion images based on fashion characteristics and key points of a piece of clothing. By integrating fashion knowledge and machine learning formulation, the establishment of the dataset will enable machines to better understand fashion, bringing a new horizon to the fashion retail industry through the application of AI (Artificial Intelligence).
The dataset can greatly facilitate understanding fashion images and related algorithm design and developing machine learning. It would help improve the accuracy of online fashion image searching, enhance the effectiveness of cross-selling and up-selling, create an innovative buying experience and facilitate the customization of online shopping platforms.
Fashion attributes are the basic design elements of an apparel and their combination determines the product category and styles of a fashion item. With the wide variety of fashion attributes, attribute recognition is a complicated process. A systemic classification of fashion attributes is essential to accurately label fashion attributes, facilitating research on deep learning and algorithm design for fashion image searching, navigating tagging and mix-and-match ideas, etc.
Fashion AI is a bridge that connects AI with fashion. It aims to explore the wider applications of AI in scenarios including fashion mix-and-match with the hope of bringing new values to the fashion industry.