Personalized Fashion Compatibility Modeling via Metapath-guided Heterogeneous Graph Learning

Author:

Guan Weili1,Jiao Fangkai2,Song Xuemeng2,Wen Haokun2,Yeh Chung-Hsing1,Chang Xiaojun3

Affiliation:

1. Monash University, Melbourne, VIC, Australia

2. Shandong University, Qingdao, China

3. University of Technology Sydney, Sydney, NSW, Australia

Funder

Australian Research Council

Publisher

ACM

Reference40 articles.

1. Sami Abu-El-Haija , Amol Kapoor , Bryan Perozzi , and Joonseok Lee . 2019 . NGCN: Multi-scale Graph Convolution for Semi-supervised Node Classification . In Proceedings of the Conference on Uncertainty in Artificial Intelligence. AUAI Press, 841--851 . Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, and Joonseok Lee. 2019. NGCN: Multi-scale Graph Convolution for Semi-supervised Node Classification. In Proceedings of the Conference on Uncertainty in Artificial Intelligence. AUAI Press, 841--851.

2. Neural Compatibility Ranking for Text-based Fashion Matching

3. Context-Aware Visual Compatibility Prediction

4. Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks

5. Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2019 . BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding . In Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics. ACL, 4171--4186 . Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics. ACL, 4171--4186.

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