Computer Vision in Fashion Trend Analysis and Applications

Authors

DOI:

https://doi.org/10.47611/jsrhs.v11i1.2464

Keywords:

Computer Vision, Fashion Trend Analysis, Fashion Recommendations, Fashion Forecasting, Visual Compatibility, Fashion Creativity, Deep Learning Methods

Abstract

Computer vision is a field of artificial intelligence that allows computers to derive relevant information from visual inputs and take actions accordingly. In this paper, we will study the involvement of computer vision in fashion trend analysis and its applications. We begin by understanding the general context of computer vision. We will then discuss the role that computer vision plays in the fashion industry. We will move on to see how over time, computer vision has solved and is still advancing in visual search, fashion style and trend analysis, fashion style compatibility, fashion forecasting, and fashion creativity in the order of increasing complexity. Then, we will discuss the significance of computer vision in the current complex tasks of fashion style analysis, fashion recommendations, and fashion forecasting, while reviewing some of their existing deep learning methodologies. We will then discuss the significance of deep learning in today’s approach to solving fashion trend analysis problems. Finally, we will overview the future directions of computer vision, leading us to a novel concept of fashion creativity that still requires further future study to solve potential tasks like cultural inclusivity in the fashion sphere.

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Author Biographies

Varnika Jain, National Public School - Koramangala

Department/Stream: Science stream (PCMC)

Rank: High School Senior Student

Bio: Varnika Jain (she/her) is a high school Science student and is a Computer Engineering aspirant who has a real zest for Mathematics, Computer Science, and Design Thinking. She strives to amalgamate her interests in Engineering and Design by applying the principles of design-thinking and scientific approach to problem-solving. She interests herself in leadership roles, fashion and product design competitions, and STEM-related academic activities, and is committed to employing creativity in technology to produce social and global solutions.

Catherine Wah, Google Inc.

Advisor   Department: N/A Rank: Staff Software Engineer Bio: Catherine Wah (she/her) is a software engineer/technical lead manager working on natural language understanding for the Google Assistant. During her tenure at Google, she has also worked on Google Photos, developing features like Photo Search and smart sharing. Catherine holds a B.S. in electrical engineering from the University of Illinois at Urbana-Champaign and a PhD in computer science from the University of California San Diego, with a focus in computer vision and machine learning; her graduate work has been cited nearly 4000 times.

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Published

02-28-2022

How to Cite

Jain, V., & Wah, C. (2022). Computer Vision in Fashion Trend Analysis and Applications. Journal of Student Research, 11(1). https://doi.org/10.47611/jsrhs.v11i1.2464

Issue

Vol. 11 No. 1 (2022)

Section

HS Review Articles

Copyright (c) 2022 Varnika Jain; Catherine Wah

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