Technology of Graphic & Image
|
App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 8
2506-2510

Outfit compatibility prediction model based on hypergraph representation

Li Jian1,2
Li Zhuo1,2,3
Ma Tianxiang4
Liang Jifeng4
1. School of Microelectronics, Tianjin University, Tianjin 300072, China
2. Tianjin Microelectronics Technology Key Laboratory of Imaging & Perception, Tianjin 300072, China
3. Peng Cheng Laboratory, Shenzhen Guangdong 518000, China
4. State Grid Hebei Electric Power Co. , Ltd. , Electric Power Research Institute, Shijiazhuang 050021, China
DOI: 10.19734/j.issn.1001-3695.2022.01.0038

Abstract

In order to solve the problem of the existing research work focuses on the compatibility of paired items, this paper proposed an outfit compatibility prediction model based on hypergraph representation. The model constructed a fashion hypergraph based on the category information of fashion items and the collocation relationship between different fashion items in the existing dataset, where each hypernode represented an item, and each hyperedge represented an outfit made up of multiple items. To better infer outfit compatibility from the hypergraph, the model converted hypergraphs into traditional graphs, and it used the graph neural network to simulate the complex interaction between nodes. Finally, it introduced the attention mechanism to calculate the outfit compatibility score to strengthen the predictive ability of the model. Experimental results show that in the outfit fill-in-the-blank task and the outfit compatibility prediction task, the model achieves an accuracy rate of 77.29% and 96.23% respectively, which is significantly improved compared with other baseline models.

Foundation Support

天津市自然科学基金资助项目(20JCQNJC01490)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.01.0038
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 8
Section: Technology of Graphic & Image
Pages: 2506-2510
Serial Number: 1001-3695(2022)08-046-2506-05

Publish History

[2022-04-02] Accepted Paper
[2022-08-05] Printed Article

Cite This Article

李健, 李卓, 马天祥, 等. 基于超图表示的服装兼容性预测模型 [J]. 计算机应用研究, 2022, 39 (8): 2506-2510. (Li Jian, Li Zhuo, Ma Tianxiang, et al. Outfit compatibility prediction model based on hypergraph representation [J]. Application Research of Computers, 2022, 39 (8): 2506-2510. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)