Name
Abstract | ||
|---|---|---|
With the proliferation of the online fashion industry, there have been increased efforts towards building cutting-edge solutions for personalising fashion recommendation. Despite this, the technology is still limited by its poor performance on new entities, i.e. the cold-start problem. We attempt to address the cold-start problem for new users, by leveraging a novel visual preference modelling approach on a small set of input images. Additionally, we describe our proposed strategy to incorporate the modelled preference in occasion-oriented outfit recommendation. Finally, we propose Fashionist: a real-time web application to demonstrate our approach enabling personalised and diverse outfit recommendation for cold-start scenarios. Check out https://youtu.be/kuKgPCkoPy0 for demonstration.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3394171.3414446 | MM '20: The 28th ACM International Conference on Multimedia
Seattle
WA
USA
October, 2020 |
DocType | ISBN | Citations |
Conference | 978-1-4503-7988-5 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dhruv Verma | 1 | 1 | 1.02 |
| Kshitij Gulati | 2 | 0 | 0.34 |
| Vasu Goel | 3 | 0 | 1.01 |
| Rajiv Ratn Shah | 4 | 223 | 59.73 |