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Learning Facial Action Units from Web Images with Scalable Weakly Supervised Clustering
We present a scalable weakly supervised clustering approach to learn facial action units (AUs) from large, freely available web images. Unlike most existing methods (e.g., CNNs) that rely on fully annotated data, our method exploits web images with inaccurate annotations. Specifically, we derive a w...
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| Veröffentlicht in: | Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit |
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| Hauptverfasser: | , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2018
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6594709/ https://ncbi.nlm.nih.gov/pubmed/31244515 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/CVPR.2018.00223 |
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