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Found 4 papers, 1 papers with code
Single Domain Dynamic Generalization for Iris Presentation Attack Detection
To tackle the above issues, we propose a Single Domain Dynamic Generalization (SDDG) framework, which simultaneously exploits domain-invariant and domain-specific features on a per-sample basis and learns to generalize to various unseen domains with numerous natural images.
Few-shot One-class Domain Adaptation Based on Frequency for Iris Presentation Attack Detection
We thus define a new domain adaptation setting called Few-shot One-class Domain Adaptation (FODA), where adaptation only relies on a limited number of target bonafide samples.
Unimodal-Concentrated Loss: Fully Adaptive Label Distribution Learning for Ordinal Regression
In this paper, we emphatically summarize that learning an adaptive label distribution on ordinal regression tasks should follow three principles.
Re-Identification Supervised Texture Generation
The estimation of 3D human body pose and shape from a single image has been extensively studied in recent years.
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