A knowledge-sharing semi-supervised approach for fashion clothes classification and attribute prediction
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-021-02178-3.pdf
Reference57 articles.
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2. Li, Y., Tang, S., Ye, Y., Ma, J.: Spatial-aware non-local attention for fashion landmark detection. In: Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), pp. 820–825 (2019)
3. Wang,W., Xu, Y., Shen, J., Zhu, S.-C.: Attentive fashion grammar network for fashion landmark detection and clothing category classification. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4271–4280 (2018)
4. Liu, Z., Luo, P., Qiu, S., Wang, X., Tang, X.: Deepfashion: Powering robust clothes recognition and retrieval with rich annotations. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1096–1104 (2016)
5. Lee, S., Eun, H., Oh, S., Kim, W., Jung, C., Kim, C.: Landmark-free clothes recognition with a two-branch feature selective network. Electron. Lett. 55(13), 745 (2019)
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