Home / Knowledge / News / Fashion / PolyU & Alibaba join hands for 'FashionAI Dataset'
PolyU & Alibaba join hands for 'FashionAI Dataset'
18
Mar '18
Courtesy: PRNewsfoto/The Hong Kong Polytechnic/ (From left): Prof. Calvin Wong, Prof. Wong Wing-tak, and Menglei Jia
Courtesy: PRNewsfoto/The Hong Kong Polytechnic/ (From left): Prof. Calvin Wong, Prof. Wong Wing-tak, and Menglei Jia
The Institute of Textiles and Clothing (ITC) of The Hong Kong Polytechnic University (PolyU), and the vision and beauty team at Alibaba Group, specialising in vision intelligence and applications, are set to establish the ‘FashionAI Dataset’ for systematic analysis and labelling of fashion images based on ‘fashion attributes’ and ‘key points’ of an apparel.

By integrating fashion knowledge and machine learning formulation, the establishment of the Dataset will enable machine to better understand fashion, bringing a new horizon to the fashion retail industry through the application of AI.

Current fashion image searching technology used on online platforms is based on the whole fashion image to search the exact or other similar images. However, if a customer is interested in some particular fashion attributes of a fashion image and wants to search other fashion items with these attributes, the current searching technology cannot meet the needs of the customer. This greatly limits the potential development and applications for offering more customised shopping experience.

From artificial intelligence (AI) research perspective, this limitation of the current image searching technology is caused by the absence of available fashion image dataset constructed with both fashion professional knowledge and fulfils the requirement of deep learning, that is, the current technology is unable to train a machine to accurately understand and recognise the fashion attributes of each fashion image.

Fostering the application of AI in the fashion industry, a PolyU research team led by Professor Wong, worked closely with Alibaba to develop ‘FashionAI Dataset’ to solve two fundamental problems of the deep learning algorithm; ‘apparel key points detection’ and ‘attribute recognition’.

Key points (for example, neckline, cuff, waistline) and fashion attributes (for example, sleeve length, collar type, skirt style) build the foundation for machine learning in understanding fashion images. The establishment of key points and fashion attribute database enables the computer to effectively and efficiently understand the fashion image which is fundamental for deep learning and recognition algorithms.

The accuracy of key points detection is determined by several factors such as the dimension and shape of the apparel, distance and angle of shooting, or even how the apparel is displayed or the model is posing in a photo. These factors can lead to poor key points detection and result in an inaccurate analysis of fashion images by the computer. Accurate key points detection, can therefore, improve the performance of deep learning algorithms.

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.

The revolutionary 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 effectiveness of cross-selling and up-selling, create innovative buying experience and facilitate customisation of online shopping platforms. (GK)

Fibre2Fashion News Desk – India


Must ReadView All

Courtesy: Businesswire/PrimaLoft

Textiles | On 18th Nov 2018

PrimaLoft unveils PrimaLoft Bio Performance Fabric

PrimaLoft, a leader in advanced material technology, has unveiled...

Higher sales and earnings at Macy's in Q3FY18

Fashion | On 18th Nov 2018

Higher sales and earnings at Macy's in Q3FY18

Higher sales and earnings were recorded at Macy’s, one of the premier ...

Courtesy: Amazon

Apparel/Garments | On 18th Nov 2018

Amazon's new headquarters in New York City, Arlington

Amazon is setting up two new headquarters, one in New York City and...

Interviews View All

Milind Khandwe, Hindoostan Innovation Centre

Milind Khandwe
Hindoostan Innovation Centre

‘Modern technical textile is an indispensable tool for science and...

Shiladitya K Joshi, Truetzschler India Private Limited

Shiladitya K Joshi
Truetzschler India Private Limited

India ITME provides a platform to interact with our stakeholders

Top executives, Fabric manufacturers

Top executives
Fabric manufacturers

Domestic manufacturers would get an edge over imported products

Mario Ploner,

Mario Ploner

<div>Italian company Tecnomeccanica Biellese specialises in planning and...

Urmil Arya,

Urmil Arya

Sushila International, a well established textile organisation established ...

Harsh Shah,

Harsh Shah

Fynd is the central online shopping destination for fashion, offering...

Larry L Kinn, Suominen Corporation

Larry L Kinn
Suominen Corporation

Larry L Kinn, Senior Vice President - Operations Americas of Suominen...

Mohammad Hassan, Biax Fiberfilm

Mohammad Hassan
Biax Fiberfilm

About one in every 20 patients picks up an infection while hospitalised....

Eamonn Tighe, Nature Works LLC

Eamonn Tighe
Nature Works LLC

Eamonn Tighe, Fibres and Nonwovens - Business Development Manager of...

Akta Adani, India Boulevard

Akta Adani
India Boulevard

India Boulevard is a San Francisco-based curated fashion marketplace that...

Chandani Sahi, By Chandani

Chandani Sahi
By Chandani

By Chandani is a womenswear prêt couture brand with fusion silhouettes by...

Rajesh Pratap Singh, Rajesh Pratap Singh

Rajesh Pratap Singh
Rajesh Pratap Singh

<div>Ace fashion designer <b>Rajesh Pratap Singh</b> has used Tencel to...

Press Release

Press Release

Letter to Editor

Letter to Editor

RSS Feed

RSS Feed

Submit your press release on


editorial@fibre2fashion.com

Letter To Editor






(Max. 8000 char.)

Search Companies





SEARCH

Leave your Comments


November 2018

Subscribe today and get the latest update on Textiles, Fashion, Apparel and so on.

news category


Related Categories:

Advanced Search