• Selwon K and Szymański J. (2024). A Review of Explainable Fashion Compatibility Modeling Methods. ACM Computing Surveys. 56:11. (1-29). Online publication date: 30-Nov-2024.

    https://doi.org/10.1145/3664614

  • Mishra K, Mishra A, Barwal P and Lal R. (2024). Natural Language Processing and Machine Learning-Based Solution of Cold Start Problem Using Collaborative Filtering Approach. Electronics. 10.3390/electronics13214331. 13:21. (4331).

    https://www.mdpi.com/2079-9292/13/21/4331

  • Islam S, Joardar S and Sekh* A. (2023). A Survey on Fashion Image Retrieval. ACM Computing Surveys. 56:6. (1-25). Online publication date: 30-Jun-2024.

    https://doi.org/10.1145/3636552

  • Ding Y, Lai Z, Mok P and Chua T. (2023). Computational Technologies for Fashion Recommendation: A Survey. ACM Computing Surveys. 56:5. (1-45). Online publication date: 31-May-2024.

    https://doi.org/10.1145/3627100

  • Deldjoo Y, Nazary F, Ramisa A, McAuley J, Pellegrini G, Bellogin A and Noia T. (2023). A Review of Modern Fashion Recommender Systems. ACM Computing Surveys. 56:4. (1-37). Online publication date: 30-Apr-2024.

    https://doi.org/10.1145/3624733

  • Jing P, Zhang K, Liu X, Li Y, Liu Y and Su Y. Dual Preference Perception Network for Fashion Recommendation in Social Internet of Things. IEEE Internet of Things Journal. 10.1109/JIOT.2023.3319386. 11:5. (7893-7903).

    https://ieeexplore.ieee.org/document/10286302/

  • Yuan Y, Zhang W, Deng Y and Lam W. Multimodal Fashion Knowledge Extraction as Captioning. Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region. (52-62).

    https://doi.org/10.1145/3624918.3625315

  • Liu X, Liu Y, Qian Y, Jiang Y and Ling H. (2023). Learning consumer preferences through textual and visual data: a multi-modal approach. Electronic Commerce Research. 10.1007/s10660-023-09780-8.

    https://link.springer.com/10.1007/s10660-023-09780-8

  • Shirkhani S, Mokayed H, Saini R and Chai H. (2023). Study of AI-Driven Fashion Recommender Systems. SN Computer Science. 10.1007/s42979-023-01932-9. 4:5.

    https://link.springer.com/10.1007/s42979-023-01932-9

  • Vo A, Le T, Pham H and Nguyen B. (2023). An efficient framework for outfit compatibility prediction towards occasion. Neural Computing and Applications. 10.1007/s00521-023-08431-1. 35:19. (14213-14226). Online publication date: 1-Jul-2023.

    https://link.springer.com/10.1007/s00521-023-08431-1

  • Vivek B, Bhattacharya G, Gubbi J, V B, Pal A and Balamuralidhar P. (2023). Personalized Outfit Compatibility Prediction Using Outfit Graph Network 2023 International Joint Conference on Neural Networks (IJCNN). 10.1109/IJCNN54540.2023.10191458. 978-1-6654-8867-9. (1-8).

    https://ieeexplore.ieee.org/document/10191458/

  • Mo D, Zou X, Pang K and Wong W. (2023). Towards private stylists via personalized compatibility learning. Expert Systems with Applications. 10.1016/j.eswa.2023.119632. 219. (119632). Online publication date: 1-Jun-2023.

    https://linkinghub.elsevier.com/retrieve/pii/S0957417423001331

  • De Divitiis L, Becattini F, Baecchi C and Del Bimbo A. (2023). Disentangling Features for Fashion Recommendation. ACM Transactions on Multimedia Computing, Communications, and Applications. 19:1s. (1-21). Online publication date: 28-Feb-2023.

    https://doi.org/10.1145/3531017

  • Lu Z, Hu Y, Yu C, Jiang Y, Chen Y and Zeng B. (2023). Personalized Fashion Recommendation With Discrete Content-Based Tensor Factorization. IEEE Transactions on Multimedia. 25. (5053-5064). Online publication date: 1-Jan-2023.

    https://doi.org/10.1109/TMM.2022.3186744

  • Tarek I, Munna F, Mojumder A, Rahman M, Hossain M and Andersson K. (2023). A Hybrid Hotel Recommendation Using Collaborative, Content Based and Knowledge Based Approach. Intelligent Computing & Optimization. 10.1007/978-3-031-19958-5_98. (1049-1057).

    https://link.springer.com/10.1007/978-3-031-19958-5_98

  • Suvarna B and Balakrishna S. (2022). An Efficient Fashion Recommendation System using a Deep CNN Model 2022 International Conference on Automation, Computing and Renewable Systems (ICACRS). 10.1109/ICACRS55517.2022.10029063. 978-1-6654-6084-2. (1179-1183).

    https://ieeexplore.ieee.org/document/10029063/

  • Werneck H, Silva N, Mito C, Pereira A, Dias D, Albergaria E and Rocha L. Introducing Contextual Information in an Ensemble Recommendation System for Fashion Domains. Proceedings of the Brazilian Symposium on Multimedia and the Web. (222-229).

    https://doi.org/10.1145/3539637.3557058

  • Ram D, Roy B and Soni V. (2022). 3D Grid Based Virtual Trial Room 2022 IEEE World Conference on Applied Intelligence and Computing (AIC). 10.1109/AIC55036.2022.9848947. 978-1-6654-7988-2. (252-259).

    https://ieeexplore.ieee.org/document/9848947/

  • Zou X, Pang K, Zhang W and Wong W. (2022). How Good Is Aesthetic Ability of a Fashion Model? 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 10.1109/CVPR52688.2022.02052. 978-1-6654-6946-3. (21168-21177).

    https://ieeexplore.ieee.org/document/9879586/

  • Wang Z, Guo B, Cui H, Ding Y and Yu Z. (2022). Fashion Meets Bot: What Should the Bot Wear? 2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD). 10.1109/CSCWD54268.2022.9776077. 978-1-6654-0527-0. (932-937).

    https://ieeexplore.ieee.org/document/9776077/

  • K S and Prabhu S. (2022). Influence of Consumer Decisions by Recommendar system in fashion e-commerce website 2022 International Conference on Decision Aid Sciences and Applications (DASA). 10.1109/DASA54658.2022.9765312. 978-1-6654-9501-1. (421-424).

    https://ieeexplore.ieee.org/document/9765312/

  • Yuan Y and Lam W. Sentiment Analysis of Fashion Related Posts in Social Media. Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining. (1310-1318).

    https://doi.org/10.1145/3488560.3498423

  • Ding Y, Ma Y, Wong W and Chua T. Modeling Instant User Intent and Content-Level Transition for Sequential Fashion Recommendation. IEEE Transactions on Multimedia. 10.1109/TMM.2021.3088281. 24. (2687-2700).

    https://ieeexplore.ieee.org/document/9451610/

  • Mameli M, Paolanti M, Pietrini R, Pazzaglia G, Frontoni E and Zingaretti P. Deep Learning Approaches for Fashion Knowledge Extraction From Social Media: A Review. IEEE Access. 10.1109/ACCESS.2021.3137893. 10. (1545-1576).

    https://ieeexplore.ieee.org/document/9661397/

  • Zagidullina D and Makarov I. (2022). Outfit Recommendation using Graph Neural Networks via Visual Similarity. Analysis of Images, Social Networks and Texts. 10.1007/978-3-031-16500-9_18. (208-222).

    https://link.springer.com/10.1007/978-3-031-16500-9_18

  • Werneck H, Silva N, Mito C, Pereira A, Tuler E, Dias D and Rocha L. (2022). A Stacking Recommender System Based on Contextual Information for Fashion Retails. Computational Science and Its Applications – ICCSA 2022. 10.1007/978-3-031-10522-7_38. (560-574).

    https://link.springer.com/10.1007/978-3-031-10522-7_38

  • Deldjoo Y, Di Noia T, Malitesta D and Merra F. (2022). Leveraging Content-Style Item Representation for Visual Recommendation. Advances in Information Retrieval. 10.1007/978-3-030-99739-7_10. (84-92).

    https://link.springer.com/10.1007/978-3-030-99739-7_10

  • Jaradat S, Dokoohaki N, Pampín H and Shirvany R. (2022). Fashion Recommender Systems. Recommender Systems Handbook. 10.1007/978-1-0716-2197-4_26. (1015-1055).

    https://link.springer.com/10.1007/978-1-0716-2197-4_26

  • Zheng H, Wu K, Park J, Zhu W and Luo J. (2021). Personalized Fashion Recommendation from Personal Social Media Data: An Item-to-Set Metric Learning Approach 2021 IEEE International Conference on Big Data (Big Data). 10.1109/BigData52589.2021.9671563. 978-1-6654-3902-2. (5014-5023).

    https://ieeexplore.ieee.org/document/9671563/

  • Yuan Y, Park M and Huh J. (2021). A Proposal for Clothing Size Recommendation System Using Chinese Online Shopping Malls: The New Era of Data. Applied Sciences. 10.3390/app112311215. 11:23. (11215).

    https://www.mdpi.com/2076-3417/11/23/11215

  • Chen H, Lin Y, Wang F and Yang H. Tops, Bottoms, and Shoes: Building Capsule Wardrobes via Cross-Attention Tensor Network. Proceedings of the 15th ACM Conference on Recommender Systems. (453-462).

    https://doi.org/10.1145/3460231.3474258

  • Sun Y, Wong W and Zou X. (2022). A Multi-Task Model for Multi-Attribute Fashion Recognition and Retrieval. AATCC Journal of Research. 10.14504/ajr.8.S1.14. 8:1_suppl. (105-116). Online publication date: 1-Sep-2021.

    http://journals.sagepub.com/doi/10.14504/ajr.8.S1.14

  • Li H, Mao X, Xu M and Jin X. (2021). Deep-based Self-refined Face-top Coordination. ACM Transactions on Multimedia Computing, Communications, and Applications. 17:3. (1-23). Online publication date: 31-Aug-2021.

    https://doi.org/10.1145/3446970

  • Ding Y, Ma Y, Wong W and Chua T. Leveraging Two Types of Global Graph for Sequential Fashion Recommendation. Proceedings of the 2021 International Conference on Multimedia Retrieval. (73-81).

    https://doi.org/10.1145/3460426.3463638

  • Yuan Y and Lam W. Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. (839-848).

    https://doi.org/10.1145/3404835.3462881

  • Lu Z, Hu Y, Chen Y and Zeng B. (2021). Personalized Outfit Recommendation with Learnable Anchors 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 10.1109/CVPR46437.2021.01253. 978-1-6654-4509-2. (12717-12726).

    https://ieeexplore.ieee.org/document/9577993/

  • Bhure B, Bansod P, Amgaokar M, Lodiwale S, Orkey A and Mohod A. (2021). A Review on Outfit Fashion Recommendation System. International Journal of Scientific Research in Computer Science, Engineering and Information Technology. 10.32628/CSEIT217368. (220-222). Online publication date: 20-May-2021.

    https://ijsrcseit.com/paper/CSEIT217368.pdf

  • Jiang J, Maldeniya D, Lerman K and Ferrara E. (2021). The Wide, the Deep, and the Maverick. Proceedings of the ACM on Human-Computer Interaction. 5:CSCW1. (1-26). Online publication date: 13-Apr-2021.

    https://doi.org/10.1145/3449290

  • Hou S, Wang Y, Ning B and Liang W. (2021). Climaxing VR Character with Scene-Aware Aesthetic Dress Synthesis 2021 IEEE Virtual Reality and 3D User Interfaces (VR). 10.1109/VR50410.2021.00026. 978-1-6654-1838-6. (57-64).

    https://ieeexplore.ieee.org/document/9417796/

  • Huaiguang W, Yan L, Baohua J, Wenjun S and Bin L. (2021). Multi-Modal Input Mode via Graph Neural Networks for Outfit Compatibility. International Journal of Performability Engineering. 10.23940/ijpe.21.01.p5.5059. 17:1. (50).

    http://www.ijpe-online.com/EN/10.23940/ijpe.21.01.p5.5059

  • Liu X, Sun Y, Liu Z and Lin D. Learning Diverse Fashion Collocation by Neural Graph Filtering. IEEE Transactions on Multimedia. 10.1109/TMM.2020.3018021. 23. (2894-2901).

    https://ieeexplore.ieee.org/document/9172047/

  • Hidayati S, Goh T, Chan J, Hsu C, See J, Wong L, Hua K, Tsao Y and Cheng W. Dress With Style: Learning Style From Joint Deep Embedding of Clothing Styles and Body Shapes. IEEE Transactions on Multimedia. 10.1109/TMM.2020.2980195. 23. (365-377).

    https://ieeexplore.ieee.org/document/9034172/

  • Kawanishi Y, Murase H, Komorita S and Naito S. Aggregating Everyday Outfits by Incremental Clustering With Interactive User Adaptation. IEEE Access. 10.1109/ACCESS.2021.3104973. 9. (121467-121475).

    https://ieeexplore.ieee.org/document/9514515/

  • Islam S, Joardar S and Sekh A. (2021). RingFIR: A Large Volume Earring Dataset for Fashion Image Retrieval. Computer Vision and Image Processing. 10.1007/978-981-16-1092-9_9. (100-111).

    https://link.springer.com/10.1007/978-981-16-1092-9_9

  • Madan M, Chouragade A and Vempati S. (2021). The Joy of Dressing Is an Art: Outfit Generation Using Self-attention Bi-LSTM. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. 10.1007/978-3-030-86517-7_14. (218-233).

    https://link.springer.com/10.1007/978-3-030-86517-7_14

  • De Divitiis L, Becattini F, Baecchi C and Del Bimbo A. (2021). Garment Recommendation with Memory Augmented Neural Networks. Pattern Recognition. ICPR International Workshops and Challenges. 10.1007/978-3-030-68790-8_23. (282-295).

    http://link.springer.com/10.1007/978-3-030-68790-8_23

  • Bettaney E, Hardwick S, Zisimopoulos O and Chamberlain B. (2021). Fashion Outfit Generation for E-Commerce. Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track. 10.1007/978-3-030-67670-4_21. (339-354).

    http://link.springer.com/10.1007/978-3-030-67670-4_21

  • Celikik M, Kirmse M, Denk T, Gagliardi P, Mbarek S, Pham D and Ramallo A. (2021). Outfit Generation and Recommendation—An Experimental Study. Recommender Systems in Fashion and Retail. 10.1007/978-3-030-66103-8_7. (117-137).

    http://link.springer.com/10.1007/978-3-030-66103-8_7

  • Zhang J, Terveen L and Dunne L. (2021). The Ensemble-Building Challenge for Fashion Recommendation: Investigation of In-Home Practices and Assessment of Garment Combinations. Recommender Systems in Fashion and Retail. 10.1007/978-3-030-66103-8_6. (101-116).

    http://link.springer.com/10.1007/978-3-030-66103-8_6

  • Yuan S, Zhong L and Li L. (2020). WhatFits- Deep Learning for Clothing Collocation 2020 7th International Conference on Behavioural and Social Computing (BESC). 10.1109/BESC51023.2020.9348320. 978-1-7281-8605-4. (1-4).

    https://ieeexplore.ieee.org/document/9348320/

  • Kwon H, Han J and Han K. ART (Attractive Recommendation Tailor). Proceedings of the 29th ACM International Conference on Information & Knowledge Management. (2573-2580).

    https://doi.org/10.1145/3340531.3412687

  • Bigi W, Baecchi C and Del Bimbo A. Automatic Interest Recognition from Posture and Behaviour. Proceedings of the 28th ACM International Conference on Multimedia. (2472-2480).

    https://doi.org/10.1145/3394171.3413530

  • Verma D, Gulati K and Shah R. (2020). Addressing the Cold-Start Problem in Outfit Recommendation Using Visual Preference Modelling 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM). 10.1109/BigMM50055.2020.00043. 978-1-7281-9325-0. (251-256).

    https://ieeexplore.ieee.org/document/9232532/

  • Sagar D, Garg J, Kansal P, Bhalla S, Shah R and Yu Y. (2020). PAI-BPR: Personalized Outfit Recommendation Scheme with Attribute-wise Interpretability 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM). 10.1109/BigMM50055.2020.00039. 978-1-7281-9325-0. (221-230).

    https://ieeexplore.ieee.org/document/9232589/

  • Lin Y, Ren P, Chen Z, Ren Z, Ma J and de Rijke M. Explainable Outfit Recommendation with Joint Outfit Matching and Comment Generation. IEEE Transactions on Knowledge and Data Engineering. 10.1109/TKDE.2019.2906190. 32:8. (1502-1516).

    https://ieeexplore.ieee.org/document/8669792/

  • Hsiao W and Grauman K. (2020). ViBE: Dressing for Diverse Body Shapes 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 10.1109/CVPR42600.2020.01107. 978-1-7281-7168-5. (11056-11066).

    https://ieeexplore.ieee.org/document/9156794/

  • Abugabah A, Cheng X and Wang J. (2020). Learning Context-Aware Outfit Recommendation. Symmetry. 10.3390/sym12060873. 12:6. (873).

    https://www.mdpi.com/2073-8994/12/6/873

  • Tangseng P and Okatani T. (2020). Toward Explainable Fashion Recommendation 2020 IEEE Winter Conference on Applications of Computer Vision (WACV). 10.1109/WACV45572.2020.9093367. 978-1-7281-6553-0. (2142-2151).

    https://ieeexplore.ieee.org/document/9093367/

  • Wu Q, Zhao P and Cui Z. Visual and Textual Jointly Enhanced Interpretable Fashion Recommendation. IEEE Access. 10.1109/ACCESS.2020.2978272. 8. (68736-68746).

    https://ieeexplore.ieee.org/document/9046774/

  • Karessli N, Guigourès R and Shirvany R. (2020). Learning Size and Fit from Fashion Images. Fashion Recommender Systems. 10.1007/978-3-030-55218-3_6. (111-131).

    http://link.springer.com/10.1007/978-3-030-55218-3_6

  • Elahi M and Qi L. (2020). Fashion Recommender Systems in Cold Start. Fashion Recommender Systems. 10.1007/978-3-030-55218-3_1. (3-21).

    http://link.springer.com/10.1007/978-3-030-55218-3_1

  • Lin C, Zhao Q, Li J and Rao W. (2019). Size Prediction for Online Clothing Shopping with Heterogeneous Information 2019 15th International Conference on Computational Intelligence and Security (CIS). 10.1109/CIS.2019.00045. 978-1-7281-6092-4. (177-181).

    https://ieeexplore.ieee.org/document/9023656/

  • Gao G, Liu L, Wang L and Zhang Y. (2019). Fashion clothes matching scheme based on Siamese Network and AutoEncoder. Multimedia Systems. 10.1007/s00530-019-00617-9. 25:6. (593-602). Online publication date: 1-Dec-2019.

    http://link.springer.com/10.1007/s00530-019-00617-9

  • Yuan L, Li C, Cao J and Zhao Q. (2019). Rank minimization on tensor ring: an efficient approach for tensor decomposition and completion. Machine Learning. 10.1007/s10994-019-05846-7.

    http://link.springer.com/10.1007/s10994-019-05846-7

  • Deng C, Yin M, Liu X, Wang X and Yuan B. (2019). High-performance Hardware Architecture for Tensor Singular Value Decomposition: Invited Paper 2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD). 10.1109/ICCAD45719.2019.8942082. 978-1-7281-2350-9. (1-6).

    https://ieeexplore.ieee.org/document/8942082/

  • Song X, Han X, Li Y, Chen J, Xu X and Nie L. GP-BPR. Proceedings of the 27th ACM International Conference on Multimedia. (320-328).

    https://doi.org/10.1145/3343031.3350956

  • Song X, Nie L and Wang Y. (2019). Compatibility Modeling: Data and Knowledge Applications for Clothing Matching. Synthesis Lectures on Information Concepts, Retrieval, and Services. 10.2200/S00952ED1V01Y201909ICR069. 11:3. (1-138). Online publication date: 2-Oct-2019.

    https://www.morganclaypool.com/doi/10.2200/S00952ED1V01Y201909ICR069

  • Yu C, Hu Y, Chen Y and Zeng B. (2019). Personalized Fashion Design 2019 IEEE/CVF International Conference on Computer Vision (ICCV). 10.1109/ICCV.2019.00914. 978-1-7281-4803-8. (9045-9054).

    https://ieeexplore.ieee.org/document/9010857/

  • Shin Y, Yeo Y, Sagong M, Ji S and Ko S. (2019). Deep Fashion Recommendation System with Style Feature Decomposition 2019 IEEE 9th International Conference on Consumer Electronics (ICCE-Berlin). 10.1109/ICCE-Berlin47944.2019.8966228. 978-1-7281-2745-3. (301-305).

    https://ieeexplore.ieee.org/document/8966228/

  • Chen W, Huang P, Xu J, Guo X, Guo C, Sun F, Li C, Pfadler A, Zhao H and Zhao B. POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. (2662-2670).

    https://doi.org/10.1145/3292500.3330652

  • Chen X, Chen H, Xu H, Zhang Y, Cao Y, Qin Z and Zha H. Personalized Fashion Recommendation with Visual Explanations based on Multimodal Attention Network. Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. (765-774).

    https://doi.org/10.1145/3331184.3331254

  • Stefani M, Stefanis V and Garofalakis J. (2019). CFRS: A Trends-Driven Collaborative Fashion Recommendation System 2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA). 10.1109/IISA.2019.8900681. 978-1-7281-4959-2. (1-4).

    https://ieeexplore.ieee.org/document/8900681/

  • Hwangbo H and Kim Y. (2019). Session-Based Recommender System for Sustainable Digital Marketing. Sustainability. 10.3390/su11123336. 11:12. (3336).

    https://www.mdpi.com/2071-1050/11/12/3336

  • Gu X, Wong Y, Shou L, Peng P, Chen G and Kankanhalli M. Multi-Modal and Multi-Domain Embedding Learning for Fashion Retrieval and Analysis. IEEE Transactions on Multimedia. 10.1109/TMM.2018.2876822. 21:6. (1524-1537).

    https://ieeexplore.ieee.org/document/8496862/

  • Karessli N, Guigoures R and Shirvany R. (2019). SizeNet: Weakly Supervised Learning of Visual Size and Fit in Fashion Images 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 10.1109/CVPRW.2019.00046. 978-1-7281-2506-0. (335-343).

    https://ieeexplore.ieee.org/document/9025680/

  • Park S, Shin M, Ham S, Choe S and Kang Y. (2019). Study on Fashion Image Retrieval Methods for Efficient Fashion Visual Search 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 10.1109/CVPRW.2019.00042. 978-1-7281-2506-0. (316-319).

    https://ieeexplore.ieee.org/document/9025533/

  • Lu Z, Hu Y, Jiang Y, Chen Y and Zeng B. (2019). Learning Binary Code for Personalized Fashion Recommendation 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 10.1109/CVPR.2019.01081. 978-1-7281-3293-8. (10554-10562).

    https://ieeexplore.ieee.org/document/8954472/

  • Sonie O, Chelliah M and Sural S. Concept to Code: Deep Learning for Fashion Recommendation. Companion Proceedings of The 2019 World Wide Web Conference. (1319-1320).

    https://doi.org/10.1145/3308560.3320100

  • Mohammed Abdulla G, Singh S and Borar S. Shop your Right Size: A System for Recommending Sizes for Fashion products. Companion Proceedings of The 2019 World Wide Web Conference. (327-334).

    https://doi.org/10.1145/3308560.3316599

  • Yin R, Li K, Lu J and Zhang G. Enhancing Fashion Recommendation with Visual Compatibility Relationship. The World Wide Web Conference. (3434-3440).

    https://doi.org/10.1145/3308558.3313739

  • Lin Y, Ren P, Chen Z, Ren Z, Ma J and de Rijke M. Improving Outfit Recommendation with Co-supervision of Fashion Generation. The World Wide Web Conference. (1095-1105).

    https://doi.org/10.1145/3308558.3313614

  • Cui Z, Li Z, Wu S, Zhang X and Wang L. Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks. The World Wide Web Conference. (307-317).

    https://doi.org/10.1145/3308558.3313444

  • Lomov I and Makarov I. (2019). Generative Models for Fashion Industry using Deep Neural Networks 2019 2nd International Conference on Computer Applications & Information Security (ICCAIS). 10.1109/CAIS.2019.8769486. 978-1-7281-0108-8. (1-6).

    https://ieeexplore.ieee.org/document/8769486/

  • Feng Z, Yu Z, Jing Y, Wu S, Song M, Yang Y and Jiang J. (2019). Interpretable Partitioned Embedding for Intelligent Multi-item Fashion Outfit Composition. ACM Transactions on Multimedia Computing, Communications, and Applications. 15:2s. (1-20). Online publication date: 30-Apr-2019.

    https://doi.org/10.1145/3326332

  • Zhou W, Mok P, Zhou Y, Zhou Y, Shen J, Qu Q and Chau K. (2019). Fashion Recommendations through Cross-media Information Retrieval. Journal of Visual Communication and Image Representation. 10.1016/j.jvcir.2019.03.003. Online publication date: 1-Mar-2019.

    https://linkinghub.elsevier.com/retrieve/pii/S1047320319300963

  • Sonie O, Chelliah M and Sural S. Personalised Fashion Recommendation using Deep Learning. Proceedings of the ACM India Joint International Conference on Data Science and Management of Data. (368-368).

    https://doi.org/10.1145/3297001.3297066

  • Hu Y and Jiang W. (2019). Recommending Costume Matching with User Preference and Expert’s Suggestion. Smart City and Informatization. 10.1007/978-981-15-1301-5_37. (473-485).

    http://link.springer.com/10.1007/978-981-15-1301-5_37

  • Hidayati S, Hsu C, Chang Y, Hua K, Fu J and Cheng W. What Dress Fits Me Best?. Proceedings of the 26th ACM international conference on Multimedia. (438-446).

    https://doi.org/10.1145/3240508.3240546

  • Guigourès R, Ho Y, Koriagin E, Sheikh A, Bergmann U and Shirvany R. A hierarchical bayesian model for size recommendation in fashion. Proceedings of the 12th ACM Conference on Recommender Systems. (392-396).

    https://doi.org/10.1145/3240323.3240388

  • Jiang Y, XU Q and Cao X. (2018). Outfit Recommendation with Deep Sequence Learning 2018 IEEE Fourth International Conference on Multimedia Big Data (BigMM). 10.1109/BigMM.2018.8499079. 978-1-5386-5321-0. (1-5).

    https://ieeexplore.ieee.org/document/8499079/

  • Ramesh N and Moh T. Outfit recommender system. Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. (903-910).

    /doi/10.5555/3382225.3382417

  • Ramesh N and Moh T. (2018). Outfit Recommender System 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 10.1109/ASONAM.2018.8508656. 978-1-5386-6051-5. (903-910).

    https://ieeexplore.ieee.org/document/8508656/

  • Valle D, Ziviani N and Veloso A. (2018). Effective Fashion Retrieval Based on Semantic Compositional Networks 2018 International Joint Conference on Neural Networks (IJCNN). 10.1109/IJCNN.2018.8489494. 978-1-5090-6014-6. (1-8).

    https://ieeexplore.ieee.org/document/8489494/

  • Sun G, Cheng Z, Wu X and Peng Q. (2018). Personalized clothing recommendation combining user social circle and fashion style consistency. Multimedia Tools and Applications. 77:14. (17731-17754). Online publication date: 1-Jul-2018.

    https://doi.org/10.1007/s11042-017-5245-1

  • Song X, Feng F, Han X, Yang X, Liu W and Nie L. Neural Compatibility Modeling with Attentive Knowledge Distillation. The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval. (5-14).

    https://doi.org/10.1145/3209978.3209996

  • Han X, Wu Z, Wu Z, Yu R and Davis L. (2018). VITON: An Image-Based Virtual Try-on Network 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 10.1109/CVPR.2018.00787. 978-1-5386-6420-9. (7543-7552).

    https://ieeexplore.ieee.org/document/8578885/

  • Hsiao W and Grauman K. (2018). Creating Capsule Wardrobes from Fashion Images 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 10.1109/CVPR.2018.00748. 978-1-5386-6420-9. (7161-7170).

    https://ieeexplore.ieee.org/document/8578846/

  • Liu Y, Gao Y, Bian L, Wang W and Li Z. (2018). How to Wear Beautifully? Clothing Pair Recommendation. Journal of Computer Science and Technology. 10.1007/s11390-018-1836-1. 33:3. (522-530). Online publication date: 1-May-2018.

    http://link.springer.com/10.1007/s11390-018-1836-1

  • Kato N, Osone H, Sato D, Muramatsu N and Ochiai Y. DeepWear. Proceedings of the Twelfth International Conference on Tangible, Embedded, and Embodied Interaction. (529-536).

    https://doi.org/10.1145/3173225.3173302

  • Tangseng P, Yamaguchi K and Okatani T. (2018). Recommending Outfits from Personal Closet 2018 IEEE Winter Conference on Applications of Computer Vision (WACV). 10.1109/WACV.2018.00036. 978-1-5386-4886-5. (269-277).

    https://ieeexplore.ieee.org/document/8354140/

  • Hwangbo H, Kim Y and Cha K. (2018). Recommendation system development for fashion retail e-commerce. Electronic Commerce Research and Applications. 10.1016/j.elerap.2018.01.012. 28. (94-101). Online publication date: 1-Mar-2018.

    https://linkinghub.elsevier.com/retrieve/pii/S1567422318300152

  • Kikuchi T, Endo Y, Kanamori Y, Hashimoto T and Mitani J. (2018). Transferring pose and augmenting background for deep human-image parsing and its applications. Computational Visual Media. 10.1007/s41095-017-0098-0. 4:1. (43-54). Online publication date: 1-Mar-2018.

    http://link.springer.com/10.1007/s41095-017-0098-0

  • Zhang X, Jia J, Gao K, Zhang Y, Zhang D, Li J and Tian Q. Trip Outfits Advisor: Location-Oriented Clothing Recommendation. IEEE Transactions on Multimedia. 10.1109/TMM.2017.2696825. 19:11. (2533-2544).

    https://ieeexplore.ieee.org/document/7907314/

  • Han X, Wu Z, Jiang Y and Davis L. Learning Fashion Compatibility with Bidirectional LSTMs. Proceedings of the 25th ACM international conference on Multimedia. (1078-1086).

    https://doi.org/10.1145/3123266.3123394

  • Li J, Lu K, Huang Z and Shen H. Two Birds One Stone. Proceedings of the 25th ACM international conference on Multimedia. (898-906).

    https://doi.org/10.1145/3123266.3123316

  • Song X, Feng F, Liu J, Li Z, Nie L and Ma J. NeuroStylist. Proceedings of the 25th ACM international conference on Multimedia. (753-761).

    https://doi.org/10.1145/3123266.3123314

  • Chen J, Wang C and Wang J. Modeling the Intransitive Pairwise Image Preference from Multiple Angles. Proceedings of the 25th ACM international conference on Multimedia. (351-359).

    https://doi.org/10.1145/3123266.3123285

  • Kikuchi T, Endo Y, Kanamori Y, Hashimoto T and Mitani J. Transferring pose and augmenting background variation for deep human image parsing. Proceedings of the 25th Pacific Conference on Computer Graphics and Applications. (7-12).

    https://doi.org/10.2312/pg.20171317

  • Tangseng P, Yamaguchi K and Okatani T. (2017). Recommending Outfits from Personal Closet 2017 IEEE International Conference on Computer Vision Workshop (ICCVW). 10.1109/ICCVW.2017.267. 978-1-5386-1034-3. (2275-2279).

    http://ieeexplore.ieee.org/document/8265477/

  • Hsiao W and Grauman K. (2017). Learning the Latent “Look”: Unsupervised Discovery of a Style-Coherent Embedding from Fashion Images 2017 IEEE International Conference on Computer Vision (ICCV). 10.1109/ICCV.2017.451. 978-1-5386-1032-9. (4213-4222).

    http://ieeexplore.ieee.org/document/8237713/

  • Chen J, Wang C, Wang J, Ying X and Wang X. Learning the Personalized Intransitive Preferences of Images. IEEE Transactions on Image Processing. 10.1109/TIP.2017.2709941. 26:9. (4139-4153).

    http://ieeexplore.ieee.org/document/7935528/

  • Lu Z, Hu Y and Zeng B. Sampling for approximate maximum search in factorized tensor. Proceedings of the 26th International Joint Conference on Artificial Intelligence. (2400-2406).

    /doi/10.5555/3172077.3172222

  • Liu Q, Wu S and Wang L. DeepStyle. Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. (841-844).

    https://doi.org/10.1145/3077136.3080658

  • Cheng Z, Wu X, Liu Y and Hua X. (2017). Video eCommerce++. IEEE Transactions on Multimedia. 19:6. (1170-1183). Online publication date: 1-Jun-2017.

    https://doi.org/10.1109/TMM.2016.2647386

  • Ma Y, Jia J, Zhou S, Fu J, Liu Y and Tong Z. Towards better understanding the clothing fashion styles. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence. (38-44).

    /doi/10.5555/3298239.3298246

  • Sanchez-Riera J, Lin J, Hua K, Cheng W and Tsui A. (2017). i-Stylist: Finding the Right Dress Through Your Social Networks. MultiMedia Modeling. 10.1007/978-3-319-51811-4_54. (662-673).

    http://link.springer.com/10.1007/978-3-319-51811-4_54

  • Yang L, Rodriguez H, Crucianu M and Ferecatu M. (2017). Fully Convolutional Network with Superpixel Parsing for Fashion Web Image Segmentation. MultiMedia Modeling. 10.1007/978-3-319-51811-4_12. (139-151).

    http://link.springer.com/10.1007/978-3-319-51811-4_12

  • Yan Y, Wei Z and Chen C. (2016). Are you what you look like? Exploring correlations in personality type and their wearing 2016 Visual Communications and Image Processing (VCIP). 10.1109/VCIP.2016.7805549. 978-1-5090-5316-2. (1-4).

    http://ieeexplore.ieee.org/document/7805549/

  • Li Z, Li H and Shao L. (2016). Improving Online Customer Shopping Experience with Computer Vision and Machine Learning Methods. HCI in Business, Government, and Organizations: eCommerce and Innovation. 10.1007/978-3-319-39396-4_39. (427-436).

    http://link.springer.com/10.1007/978-3-319-39396-4_39