The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
Learning Deep Representation for Face Alignment with Auxiliary Attributes
Open accessAbstract
In this study, we show that landmark detection or face alignment task is not a single and independent problem. Instead, its robustness can be greatly improved with auxiliary information. Specifically, we jointly optimize landmark detection together with the recognition of heterogeneous but subtly correlated facial attributes, such as gender, expression, and appearance attributes. This is non-trivial since different attribute inference tasks have different learning difficulties and convergence rates. To address this problem, we formulate a novel tasks-constrained deep model, which not only learns the inter-task correlation but also employs dynamic task coefficients to facilitate the optimization convergence when learning multiple complex tasks. Extensive evaluations show that the proposed task-constrained learning (i) outperforms existing face alignment methods, especially in dealing with faces with severe occlusion and pose variation, and (ii) reduces model complexity drastically compared to the state-of-the-art methods based on cascaded deep model.
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Cited by
Ranjan, R., Patel, V. M., & Chellappa, R. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2781233 · Cited by 1,333
A survey on deep learning based face recognition
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Face Alignment in Full Pose Range: A 3D Total Solution
Zhu, X., Liu, X., Lei, Z., & Li, S. Z. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2778152 · Cited by 391
Lu, Y., Kumar, A., Zhai, S., Cheng, Y., Javidi, T., & Feris, R. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.126 · Cited by 371
Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression
Wang, X., Bo, L., & Fuxin, L. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00707 · Cited by 313
Metadata
- Authors
- Zhang, Z., Luo, P., Loy, C. C., & Tang, X.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2016-05-01
- Volume
- 38
- Issue
- 5
- Pages
- 918-930
- ISSN
- 0162-8828 (ISSN-L)
- 2160-9292
- OpenAlex
- W1795776638
- Cited by
- 424
- References
- 64
- FWCI
- 41.30
- Type
- journal article
- Language
- en
- Open access
- green
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