Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set

In this paper, we address a practical problem of crossscenario clothing retrieval - given a daily human photo captured in general environment, e.g., on street, finding similar clothing in online shops, where the photos are captured more professionally and with clean background. There are large discrepancies between daily photo scenario and online shopping scenario. We first propose to alleviate the human pose discrepancy by locating 30 human parts detected by a well trained human detector. Then, founded on part features, we propose a two-step calculation to obtain more reliable one-to-many similarities between the query daily photo and online shopping photos: 1) the within-scenario one-to-many similarities between a query daily photo and the auxiliary set are derived by direct sparse reconstruction; and 2) by a crossscenario many-to-many similarity transfer matrix inferred offline from an extra auxiliary set and the online shopping set, the reliable cross-scenario one-to-many simil...

• Type: Journal
• Year: 2012
• Where: CVPR
• Authors: Si Liu, Zheng Song, Guangcan Liu, Changsheng Xu, Hanqing Lu, Shuicheng Yan
• Keywords: Computer Vision, Cvpr 2012, Dataset, Nding, Transfer Matrix