TY - GEN
T1 - Deep correlation features for image style classification
AU - Chu, Wei Ta
AU - Wu, Yi Ling
PY - 2016/10/1
Y1 - 2016/10/1
N2 - This paper presents a comprehensive study of deep correlation features on image style classification. Inspired by that correlation between feature maps can effectively describe image texture, we design and transform various such correlations into style vectors, and investigate classification performance brought by different variants. In addition to intra-layer correlation, we also propose inter-layer correlation and verify its benefit. Through extensive experiments on image style classification and artist classification, we demonstrate that the proposed style vectors significantly outperforms CNN features coming from fully-connected layers, as well as outperforms the state-of-the-art deep representation.
AB - This paper presents a comprehensive study of deep correlation features on image style classification. Inspired by that correlation between feature maps can effectively describe image texture, we design and transform various such correlations into style vectors, and investigate classification performance brought by different variants. In addition to intra-layer correlation, we also propose inter-layer correlation and verify its benefit. Through extensive experiments on image style classification and artist classification, we demonstrate that the proposed style vectors significantly outperforms CNN features coming from fully-connected layers, as well as outperforms the state-of-the-art deep representation.
UR - http://www.scopus.com/inward/record.url?scp=84994681110&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84994681110&partnerID=8YFLogxK
U2 - 10.1145/2964284.2967251
DO - 10.1145/2964284.2967251
M3 - Conference contribution
AN - SCOPUS:84994681110
T3 - MM 2016 - Proceedings of the 2016 ACM Multimedia Conference
SP - 402
EP - 406
BT - MM 2016 - Proceedings of the 2016 ACM Multimedia Conference
PB - Association for Computing Machinery, Inc
T2 - 24th ACM Multimedia Conference, MM 2016
Y2 - 15 October 2016 through 19 October 2016
ER -