The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Paper Doll Parsing: Retrieving Similar Styles to Parse Clothing Items
Abstract
Clothing recognition is an extremely challenging problem due to wide variation in clothing item appearance, layering, and style. In this paper, we tackle the clothing parsing problem using a retrieval based approach. For a query image, we find similar styles from a large database of tagged fashion images and use these examples to parse the query. Our approach combines parsing from: pre-trained global clothing models, local clothing models learned on the fly from retrieved examples, and transferred parse masks (paper doll item transfer) from retrieved examples. Experimental evaluation shows that our approach significantly outperforms state of the art in parsing accuracy.
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Cites
Fast approximate energy minimization via graph cuts
Boykov, Y., Veksler, O., & Zabih, R. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.969114 · Cited by 6,988
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Hariharan, B., Arbelaez, P., Girshick, R., & Malik, J. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298642 · Cited by 1,511
Look into Person: Joint Body Parsing & Pose Estimation Network and a New Benchmark
Liang, X., Gong, K., Shen, X., & Lin, L. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2820063 · Cited by 365
Instance-Level Human Parsing via Part Grouping Network
Gong, K., Liang, X., Li, Y., Chen, Y., Yang, M., & Lin, L. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01225-0_47 · Cited by 363
Learning Fashion Compatibility with Bidirectional LSTMs
Han, X., Wu, Z., Jiang, Y.-G., & Davis, L. S. (2017) · Proceedings of the 25th ACM international conference on Multimedia · doi:10.1145/3123266.3123394 · Cited by 325
Human Parsing with Contextualized Convolutional Neural Network
Liang, X., Xu, C., Shen, X., Yang, J., Liu, S., Tang, J., Lin, L., & Yan, S. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.163 · Cited by 245
Metadata
- Authors
- Yamaguchi, K., Kiapour, M. H., & Berg, T. L.
- Venue
- 2013 IEEE International Conference on Computer Vision
- Publisher
- IEEE
- Published
- 2013-12
- Pages
- 3519-3526
- OpenAlex
- W2121339428
- Cited by
- 275
- References
- 1
- FWCI
- 13.44
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Yamaguchi, K., Kiapour, M. H., & Berg, T. L. (2013). Paper Doll Parsing: Retrieving Similar Styles to Parse Clothing Items. 2013 IEEE International Conference on Computer Vision. https://doi.org/10.1109/iccv.2013.437
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
