88 research outputs found

    Rethinking Domain Generalization for Face Anti-spoofing: Separability and Alignment

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    This work studies the generalization issue of face anti-spoofing (FAS) models on domain gaps, such as image resolution, blurriness and sensor variations. Most prior works regard domain-specific signals as a negative impact, and apply metric learning or adversarial losses to remove them from feature representation. Though learning a domain-invariant feature space is viable for the training data, we show that the feature shift still exists in an unseen test domain, which backfires on the generalizability of the classifier. In this work, instead of constructing a domain-invariant feature space, we encourage domain separability while aligning the live-to-spoof transition (i.e., the trajectory from live to spoof) to be the same for all domains. We formulate this FAS strategy of separability and alignment (SA-FAS) as a problem of invariant risk minimization (IRM), and learn domain-variant feature representation but domain-invariant classifier. We demonstrate the effectiveness of SA-FAS on challenging cross-domain FAS datasets and establish state-of-the-art performance.Comment: Accepted in CVPR202

    MicroRNA-196a-5p targeting LRP1B modulates phenotype of thyroid carcinoma cells

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    Introduction: Thyroid cancer (TC) is a common endocrine malignancy, comprising nearly one-third of all head and neck malignancies worldwide. MicroRNAs (miRNAs) have been implicated in the malignant progression of multiple cancers; however, their contribution to thyroid diseases has not been fully explored. Material and methods: This study aimed to illustrate the regulatory mechanism of microRNA-196a-5p in TC progression and to investigate whether microRNA-196a-5p affects progression of TC cells by targeting low-density lipoprotein receptor-associated protein 1B (LRP1B). MicroRNA-196a-5p and LRP1B expression status in TC cells and normal human thyroid cells was detected by quantative reverse transcription polymerase chain reaction (qRT-PCR) and western blot. Dual-luciferase reporter assay, cell counting kit-8 (CCK-8) assay, scratch healing assay, and Transwell assay were also performed. Results: The results showed that microRNA-196a-5p expression was up-regulated and LRP1B expression was down regulated in TC cells. In addition, the upregulation of microRNA-196a-5p facilitated progression of TC cells. Silencing microRNA-196a-5p led to the opposite results. Dual-luciferase reporter assay offered evidence for microRNA-196a-5p targeting LRP1B in TC. MicroRNA-196a-5p could target LRP1B to facilitate proliferation, invasion, and migration of TC cells. Conclusion: Overall, this study revealed that microRNA-196a-5p may be a cancer-promoting microRNA that plays an important role in TC progression
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