Robust Face Recognition via Multimodal Deep Face Representation

  title={Robust Face Recognition via Multimodal Deep Face Representation},
  author={Changxing Ding and Dacheng Tao},
  journal={IEEE Transactions on Multimedia},
Face images appearing in multimedia applications, e.g., social networks and digital entertainment, usually exhibit dramatic pose, illumination, and expression variations, resulting in considerable performance degradation for traditional face recognition algorithms. [] Key Method The set of CNNs extracts complementary facial features from multimodal data. Then, the extracted features are concatenated to form a high-dimensional feature vector, whose dimension is compressed by SAE.

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Trunk-Branch Ensemble Convolutional Neural Networks for Video-Based Face Recognition

  • Changxing DingD. Tao
  • Computer Science
    IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2018
A Trunk-Branch Ensemble CNN model (TBE-CNN), which extracts complementary information from holistic face images and patches cropped around facial components, achieves state-of-the-art performance on three popular video face databases: PaSC, COX Face, and YouTube Faces.

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Unconstrained Face Verification Based on Monogenic Binary Pattern and Convolutional Neural Network

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DeepFace: Closing the Gap to Human-Level Performance in Face Verification

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