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- W2792416245 abstract "Same-style clothes retrieval is a task to search images which contain exactly the same designing style clothes. For such a task, too limited training data makes the problem of how to gain suitable same-style feature representations challenging but significant. In this paper, we adopt a memory-augmented deep neural network, also called as a few-shot learning model, to collect possibly same-style images. Besides, we present an object-aware clothes retrieval framework to further enhance the same-style feature representations, in which object focusing regions through object detection are first obtained, and a multi-task Siamese network is designed for ranking feature learning provided with some same-style or non-same-style image pairs. Experiments results show that our proposed solution is effective to discover more same-style images precisely, and further achieve the satisfied performance on same-style clothes retrieval." @default.
- W2792416245 created "2018-03-29" @default.
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- W2792416245 date "2018-01-01" @default.
- W2792416245 modified "2023-10-16" @default.
- W2792416245 title "Same-Style Products Mining for Clothes Retrieval" @default.
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- W2792416245 doi "https://doi.org/10.1007/978-981-10-8530-7_44" @default.
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