TY - GEN
T1 - Attention to describe products with attributes
AU - Li, Shuohao
AU - Yamaguchi, Kota
AU - Okatani, Takayuki
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Number 15H05919 and 16H05863
Publisher Copyright:
© 2017 MVA Organization All Rights Reserved.
PY - 2017/7/19
Y1 - 2017/7/19
N2 - In e-commerce environment, shop owners and advertisers give descriptive details of the product to attract potential customers. Can a computer vision technique recognize and describe the details of a product in the same way? In this paper, we study how the attention mechanism benefits in product phrase generation with attributes. We present a phrase generation model consisting of convolutional neural networks, recurrent neural networks, and the attention mechanism to look into the detail of the image. We construct attribute-rich phrases from metadata in Easy dataset that consist of an adjective, a material tag, and product category, and learn the model to describe products. Our empirical results suggest that our model improves the description quality in both machine-translation metric and human evaluation.
AB - In e-commerce environment, shop owners and advertisers give descriptive details of the product to attract potential customers. Can a computer vision technique recognize and describe the details of a product in the same way? In this paper, we study how the attention mechanism benefits in product phrase generation with attributes. We present a phrase generation model consisting of convolutional neural networks, recurrent neural networks, and the attention mechanism to look into the detail of the image. We construct attribute-rich phrases from metadata in Easy dataset that consist of an adjective, a material tag, and product category, and learn the model to describe products. Our empirical results suggest that our model improves the description quality in both machine-translation metric and human evaluation.
UR - http://www.scopus.com/inward/record.url?scp=85027838470&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85027838470&partnerID=8YFLogxK
U2 - 10.23919/MVA.2017.7986839
DO - 10.23919/MVA.2017.7986839
M3 - Conference contribution
AN - SCOPUS:85027838470
T3 - Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
SP - 215
EP - 218
BT - Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IAPR International Conference on Machine Vision Applications, MVA 2017
Y2 - 8 May 2017 through 12 May 2017
ER -