The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Occlusion Robust Face Recognition Based on Mask Learning With Pairwise Differential Siamese Network
Open accessAbstract
Deep Convolutional Neural Networks (CNNs) have been pushing the frontier of face recognition over past years. However, existing CNN models are far less accurate when handling partially occluded faces. These general face models generalize poorly for occlusions on variable facial areas. Inspired by the fact that human visual system explicitly ignores the occlusion and only focuses on the non-occluded facial areas, we propose a mask learning strategy to find and discard corrupted feature elements from recognition. A mask dictionary is firstly established by exploiting the differences between the top conv features of occluded and occlusion-free face pairs using innovatively designed pairwise differential siamese network (PDSN). Each item of this dictionary captures the correspondence between occluded facial areas and corrupted feature elements, which is named Feature Discarding Mask (FDM). When dealing with a face image with random partial occlusions, we generate its FDM by combining relevant dictionary items and then multiply it with the original features to eliminate those corrupted feature elements from recognition. Comprehensive experiments on both synthesized and realistic occluded face datasets show that the proposed algorithm significantly outperforms the state-of-the-art systems.
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Self-citationFully convolutional networks for semantic segmentation
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Cited by
Generalizing Face Forgery Detection with High-frequency Features
Luo, Y., Zhang, Y., Yan, J., & Liu, W. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.01605 · Cited by 609
Self-citationPast, Present, and Future of Face Recognition: A Review
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Metadata
- Authors
- Song, L., Gong, D., Li, Z., Liu, C., & Liu, W.
- Venue
- 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
- Publisher
- IEEE
- Published
- 2019-10
- Pages
- 773-782
- OpenAlex
- W2981408674
- Cited by
- 267
- References
- 44
- FWCI
- 12.23
- Type
- conference paper
- Language
- en
- Open access
- green
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- Song, L., Gong, D., Li, Z., Liu, C., & Liu, W. (2019). Occlusion Robust Face Recognition Based on Mask Learning With Pairwise Differential Siamese Network. 2019 IEEE/CVF International Conference on Computer Vision (ICCV). https://doi.org/10.1109/iccv.2019.00086
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