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Found 5 papers, 2 papers with code
Double Trouble? Impact and Detection of Duplicates in Face Image Datasets
Additional steps based on face recognition and face image quality assessment models reduce false positives, and facilitate the deduplication of the face images both for intra- and inter-subject duplicate sets.
Considerations on the Evaluation of Biometric Quality Assessment Algorithms
Additionally, a discard fraction limit or range must be selected to compute pAUC values, which can then be used to quantitatively rank quality assessment algorithms.
Effect of Lossy Compression Algorithms on Face Image Quality and Recognition
This work investigates the effect of lossy image compression on a state-of-the-art face recognition model, and on multiple face image quality assessment models.
Face Image Quality Assessment: A Literature Survey
The performance of face analysis and recognition systems depends on the quality of the acquired face data, which is influenced by numerous factors.
Deep Learning-based Single Image Face Depth Data Enhancement
All tested enhancer types exclusively use depth data as input, which differs from methods that enhance depth based on additional input data such as visible light color images.
