A CNN using pixel-wise binary supervision detects face spoofs, reporting 0% HTER on Replay Mobile and 0.42% ACER on OULU Protocol-1.
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Deep face models trained on MS-Celeb-1M and fine-tuned on VGGFace2 achieve state-of-the-art accuracies on SCFace and ICB-RW low-resolution benchmarks without using any of their training data by leveraging appearance variety, resolution distribution, resolution matching, and probe information content
citing papers explorer
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Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection
A CNN using pixel-wise binary supervision detects face spoofs, reporting 0% HTER on Replay Mobile and 0.42% ACER on OULU Protocol-1.
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Exploring Factors for Improving Low Resolution Face Recognition
Deep face models trained on MS-Celeb-1M and fine-tuned on VGGFace2 achieve state-of-the-art accuracies on SCFace and ICB-RW low-resolution benchmarks without using any of their training data by leveraging appearance variety, resolution distribution, resolution matching, and probe information content