Reconstruction and enhancement techniques for overcoming occlusion in face recognition
Filip Pleško,
Tomáš Goldmann,
Kamil Malinka
Abstract:Face occlusions on CCTV cameras obscure important key facial features, preventing face recognition (FR) systems from recognizing people. This work mainly focuses on reconstructing these missing facial parts using Generative Adversarial Neural Networks (GANs) to improve FR accuracy while maintaining a low False Acceptance Rate (FAR). In addition, we are trying to improve the generated images further by using different image enhancement methods to test whether they can be used to improve the FR accuracy. To test… Show more
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