2015 IEEE International Conference on Computer Vision (ICCV) 2015
DOI: 10.1109/iccv.2015.382
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Where to Buy It: Matching Street Clothing Photos in Online Shops

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Cited by 397 publications
(341 citation statements)
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“…Results on the region of interest based classification task results in a top-1 accuracy of 15% and a top-3 accuracy of 49%. The accuracy of the clothing type classification task is relatively low, but similar results are obtained in state-of-the-art approaches [19,20]. This accuracy shows the necessity for manual verification of the classification results.…”
Section: Fig 2 Class Distribution Of Collected Clothing Datasetsupporting
confidence: 54%
See 1 more Smart Citation
“…Results on the region of interest based classification task results in a top-1 accuracy of 15% and a top-3 accuracy of 49%. The accuracy of the clothing type classification task is relatively low, but similar results are obtained in state-of-the-art approaches [19,20]. This accuracy shows the necessity for manual verification of the classification results.…”
Section: Fig 2 Class Distribution Of Collected Clothing Datasetsupporting
confidence: 54%
“…In recent years, the research community has actively been focusing on the automatic classification and detection of clothes in digital content [19][20][21]. Unfortunately, due to the large visual differences between images on e-commerce websites (photographed on a clean, white background with clear lighting conditions) and those retrieved from in-the-wild videos, this problem is still largely unsolved.…”
Section: Clothing Recognition and Annotationmentioning
confidence: 99%
“…In the case of fashion e-commerce, a specific item being sold is normally depicted worn by a model and tastefully combined with other garments to make it look more attractive. Existing approaches for recommendation or retrieval focus on images only, and normally require hard-to-obtain datasets for training [7], omitting the metadata associated with the ecommerce products such as titles, colors, series of tags, descriptions, etc. that can be used to improve the information obtained from the images.…”
Section: Introductionmentioning
confidence: 99%
“…Most existing on-line shopping websites only provide the images of the product itself, or better, provide how skinny model wearing the clothing with clean background. Cross-domain retrieval and recommendation remains a challenging problem due to the large discrepancy between different domains, such as the background, pose, illumination [12,13,14,15].…”
Section: Introductionmentioning
confidence: 99%
“…They are build based on the bi-directional, (i.e., both street-to-shop and shop-to-street), cross-domain clothing retrieval. In street-to-shop clothing retrieval [11,12], given a daily human photo taken in the street view, similar garments from on-line shops are retrieved using the proposed cross-domain image retrieval solution. In shop-to-street clothing retrieval, for a shop item (e.g., a blue skirt), we show how ordinary people wearing this item on street by shop-to-street clothing retrieval.…”
Section: Introductionmentioning
confidence: 99%