Learning to Remember Beauty Products

Toan H. Vu, An Dang, Jia Ching Wang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

This paper develops a deep learning model for the beauty product image retrieval problem. The proposed model has two main components-an encoder and a memory. The encoder extracts and aggregates features from a deep convolutional neural network at multiple scales to get feature embeddings. With the use of an attention mechanism and a data augmentation method, it learns to focus on foreground objects and neglect background on images, so can it extract more relevant features. The memory consists of representative states of all database images as its stacks, and it can be updated during training process. Based on the memory, we introduce a distance loss to regularize embedding vectors from the encoder to be more discriminative. Our model is fully end-to-end, requires no manual feature aggregation and post-processing. Experimental results on the Perfect-500K dataset demonstrate the effectiveness of the proposed model with a significant retrieval accuracy.

原文???core.languages.en_GB???
主出版物標題MM 2020 - Proceedings of the 28th ACM International Conference on Multimedia
發行者Association for Computing Machinery, Inc
頁面4728-4732
頁數5
ISBN(電子)9781450379885
DOIs
出版狀態已出版 - 12 10月 2020
事件28th ACM International Conference on Multimedia, MM 2020 - Virtual, Online, United States
持續時間: 12 10月 202016 10月 2020

出版系列

名字MM 2020 - Proceedings of the 28th ACM International Conference on Multimedia

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???event.eventtypes.event.conference???28th ACM International Conference on Multimedia, MM 2020
國家/地區United States
城市Virtual, Online
期間12/10/2016/10/20

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