Deep learning for describing e-commerce images from noisy online data

We propose a deep learning model that generates descriptions about product images on an e-commerce site. The model consists of convolutional neural networks and recurrent neural networks. We first extract clean, useful training data set from noisy data on the web using natural language processing techniques. Then, we trained the model with product images and their titles. This project is a collaboration with Communication Science Laboratory at Tohoku university.




Learning to Describe E-Commerce Images from Noisy Online Data
Asian Conference on Computer Vision (ACCV) 2016
Yashima, T., Okazaki, N., Inui, K., Yamaguchi, K., & Okatani, T.