Computer Vision / Deep Learning / Fashion&Art


Team Member

Hello! I'm Yu-Ting Chang.

I receieved my B.S. degree in ECE Department at Taiwan National Chiao Tung University in 2015. I am currently a first-year M.S. student in UC Merced Vision and Learning Lab, advised by Prof. Ming-Hsuan Yang.

My research covers the field of Computer Vision and Deep Learning. I focus on developing neural networks in the application of image/video generation and synthesis.

Latest CV

Research Interest

Computer Vision

I have strong multimedia cumputing background and I am especially interested in image editing techniques.

Deep Learning

I am interested in ML algorithms. I especially focus on building deep learning architectures by Keras and PyTorch.


I love fashion and art! I am insterested in image retrieval, recommendation system, and style transfer techniques.


1. Fashion World Map: Understanding Cities Through Streetwear Fashion
Yu-Ting Chang, Wen-Huang Cheng, Kai-Lung Hua, Bo Wu
ACM International Conference on Multimedia (ACM MM), 2017

2. Fashion Eye: Understanding Streetwear Fashion Style
Yu-Ting Chang, Min-Jhih Huang, Jorga Hu Yu, Cheng-Chun Hsu, Kai-Lung Hua, Wen-Huang Cheng
ACM Multimedia 2017 China Pre-conference (Invited Demonstration), 2017

3. What Dress Fits Me Best?: Fashion Recommendation on the Clothing Style forPersonal Body Shape
Shintami Chusnul Hidayati, Cheng-Chun Hsu, Yu-Ting Chang, Kai-Lung Hua, Jianlong Fu, Wen-Huang Cheng
ACM International Conference on Multimedia (ACM MM), 2018

  • Congratulations!

    Apr. 2017

    My work was accepted as a full paper by the 25th ACM Multimedia!

    I'm going to attend 2017 ACM Multimedia Conference @ Mountain View, CA, USA

    Online Paper

  • Congratulations!

    Sep. 2017

    I'm going to present Fashion World Map demo system at 2017 China Multimedia Conference (ChinaMM) @ Guangzhou, China

    Demo Website




Fashion World Map: Understanding Cities Through Streetwear Fashion

Published at 2017 ACM Multimedia

  • Portfolio Item


    A novel framework for depicting the street fashion of a city by discovering fashion items in a particular look that are most iconic for the city.

    Portfolio Item

    Global Street Fashion Dataset

    I collected Global Fashion Dataset which contains over 400K street fashion pictures and their user provided associated data.

    Portfolio Item


    We aim to explore the iconic item of a city based on deep neural networks and PCST algorithm.

  • Portfolio Item

    Fashion World Map

    We create a fashion world map which shows the iconic street fashion of global major cities. It shows how the visual impression of local fashion cultures across the world can be depicted, modeled, and analyzed.

    Portfolio Item


    We provided insights and observations according to our result. We can infer the Correlation of Clothing Color and City Latitude, Influence of International Clothing Brands on Local Fashion.

    Portfolio Item

    Online Demo

    A developed system to discover the city components from the user’s outfit. The application can profile the fashion taste of the users and offer smart insights embedded within the picture.

Be fearless in the pursuitof what sets your soul on fire


  • Portfolio Item

    2017 ACM Multimedia

    Oct. 2017 @ California, USA

    Portfolio Item

    2017 ChinaMM

    Sep. 2017 @ Guangzhou, China

    Portfolio Item

    2017 Taiwan HCI Workshop

    Nov. 2017 @ Taipei, Taiwan

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311 S&E Building 2 UC Merced, CA 95343


(+1) 650-224-9608