L'oreal

Robin Kips

Matthieu Perrot

Helga Malaprade

Grégoire Charraud

Géraldine Thiebaut

Loic Tran

Emmanuel Malherbe

Christine Elfakhri

Florent Valceschini

Thibault Chauffier

Loïc Cardon

Claire Crochet

Jean-Christophe Bichon

Vincent Marchal

In some embodiments of the present disclosure, one or more machine learning models are trained to accurately estimate skin color in one or more images regardless of the lighting conditions. In some embodiments, the models can then be used to estimate a skin color in a new image, and that estimated skin color can be used for a variety of purposes. For example, the skin color may be used to generate a recommendation for a foundation shade that accurately matches the skin color, or a recommendation for another cosmetic product that is complimentary with the estimated skin color. Thus, the need for an in-person test of the product is eliminated.

Techniques for identifying skin color in images having uncontrolled lighting conditions

Embodiments of the present disclosure provide systems, methods, and computer-readable media that use machine learning models to enable computing devices to detect and identify cosmetic products in face images. In some embodiments, a model training system may gather training data for building the machine learning models by analyzing face images associated with tagging data. In some embodiments, a recommendation system may be configured to use the machine learning models generated by the model training system to detect products in face images, and to add information based on the detected products to a look data store, and/or to provide recommendations for similar looks from the look data store based on the detected products.

Systems and methods for providing personalized product recommendations using deep learning

Growing community of inventors

Clichy, France

Robin Kips