Interactive Image Search for Clothing Recommendation
Zhengzhong Zhou, Yifei Xu, Jingjin Zhou, Liqing Zhang · 2016
This demo delivers a novel retrieval system which meets users' multi-dimensional requirements in clothing image search. In this system, users are able to use both image and keywords as query inputs. We employ the color, texture, shape and attributes as additional descriptors to further refine the requirements. We propose the Hybrid Topic (HT) model, a probabilistic network integrating the multi-channel descriptors into a unified framework, to learn the intricate semantic representation of the descriptors above. The proposed model provides an effective multi-modal representation of clothes. Our experiments show that the HT method significantly outperforms the CNN-based deep search methods.