AABLSTM: A Novel Multi-task Based CNN-RNN Deep Model for Fashion Analysis
| العنوان: | AABLSTM: A Novel Multi-task Based CNN-RNN Deep Model for Fashion Analysis |
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| المؤلفون: | Xianlin Zhang, Mengling Shen, Xueming Li, Xiaojie Wang |
| المصدر: | ACM Transactions on Multimedia Computing, Communications, and Applications. 19:1-18 |
| بيانات النشر: | Association for Computing Machinery (ACM), 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Computer Networks and Communications, Hardware and Architecture |
| الوصف: | With the rapid growth of online commerce and fashion-related applications, visual clothing analysis and recognition has become a hotspot in computer vision. In this paper, we propose a novel AABLSTM network, which is based on deep CNN-RNN, to solve the visual fashion analysis of clothing category classification, attribute detection, and landmark localization. The designed fashion model is leveraged with the multi-task driven mechanism as follows: firstly, a bidirectional LSTM (Bi-LSTM) branch is proposed for efficiently mining the semantic association between related attributes so as to improve the precision of clothing category classification and attribute detection; then, an imitated hourglass sub-network of “down-up sampling” is constructed for boosting the accuracy of fashion landmark localization; and finally, a specially designed multi-loss function is constructed to better optimize the network training. Extensive experimental results on large-scale fashion datasets demonstrate the superior performance of our approach. |
| تدمد: | 1551-6865 1551-6857 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::5a1306156ff24c77c865addb02bc5395 https://doi.org/10.1145/3519029 |
| رقم الأكسشن: | edsair.doi...........5a1306156ff24c77c865addb02bc5395 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15516865 15516857 |
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