A regression deep learning approach for fashion compatibility

In the ever-evolving world of fashion, building the perfect outfit can be a challenge. We propose a fashion recommendation system, which we call Visual Search, that uses computer vision and deep learning to ensure that it has a co-ordinated set of fashion recommendations. It looks at photos of incomplete outfits, recognizes existing items, and suggests the most compatible missing piece. At the heart of our system lies a compatibility model made of a Convolutional Neural Network and bidirectional Long Short Term Memory to generate a complementary missing piece. To complete the recommendation process, we incorporated a similarity model, based on Vision Transformer. This model meticulously compares the generated image to the catalog items, selecting the one that most closely matches the generated image in terms of visual features. ; TexP@CT Mobilizing Pact - Innovation Pact for the Digitalization of Textiles and Clothing, project no. 61, to Reinforce the Competitiveness and Resilience of the National Economy, financed through Component 5 - Capitalization and Business Innovation, of the European funds allocated to Portugal by the Recovery and Resilience Plan (PRR), under the European Union’s (EU) Recovery and Resilience Mechanism, as part of Next Generation EU (https://recuperarportugal.gov.pt/ ), for the period 2021 - 2026. CMAT: partially supported by FCT- ‘Fundação para a Ciência e a Tecnologia’, within projects UIDP/00013/2020 and UIDB/00013/2020 (DOI 10.54499/UIDP/00013/2020 and DOI 10.54499/UIDB/00013/2020).