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pro vyhledávání: '"Jain, Anil"'
Watermarking is an essential technique for embedding an identifier (i.e., watermark message) within digital images to assert ownership and monitor unauthorized alterations. In face recognition systems, watermarking plays a pivotal role in ensuring da
Externí odkaz:
http://arxiv.org/abs/2409.16056
Autor:
Grosz, Steven, Zhao, Rui, Ranjan, Rajeev, Wang, Hongcheng, Aggarwal, Manoj, Medioni, Gerard, Jain, Anil
This paper improves upon existing data pruning methods for image classification by introducing a novel pruning metric and pruning procedure based on importance sampling. The proposed pruning metric explicitly accounts for data separability, data inte
Externí odkaz:
http://arxiv.org/abs/2409.13915
The use of multiple modalities (e.g., face and fingerprint) or multiple algorithms (e.g., three face comparators) has shown to improve the recognition accuracy of an operational biometric system. Over time a biometric system may evolve to add new mod
Externí odkaz:
http://arxiv.org/abs/2408.11271
Forensic sketch-to-mugshot matching is a challenging task in face recognition, primarily hindered by the scarcity of annotated forensic sketches and the modality gap between sketches and photographs. To address this, we propose CLIP4Sketch, a novel a
Externí odkaz:
http://arxiv.org/abs/2408.01233
Biometric recognition has primarily addressed closed-set identification, assuming all probe subjects are in the gallery. However, most practical applications involve open-set biometrics, where probe subjects may or may not be present in the gallery.
Externí odkaz:
http://arxiv.org/abs/2407.16133
Autor:
Grosz, Steven A., Jain, Anil K.
The scarcity of large-scale palmprint databases poses a significant bottleneck to advancements in contactless palmprint recognition. To address this, researchers have turned to synthetic data generation. While Generative Adversarial Networks (GANs) h
Externí odkaz:
http://arxiv.org/abs/2406.00287
The recent progress in generative models has revolutionized the synthesis of highly realistic images, including face images. This technological development has undoubtedly helped face recognition, such as training data augmentation for higher recogni
Externí odkaz:
http://arxiv.org/abs/2404.18890
Autor:
Grosz, Steven A., Jain, Anil K.
The utilization of synthetic data for fingerprint recognition has garnered increased attention due to its potential to alleviate privacy concerns surrounding sensitive biometric data. However, current methods for generating fingerprints have limitati
Externí odkaz:
http://arxiv.org/abs/2404.13791
In this paper, we address the challenge of making ViT models more robust to unseen affine transformations. Such robustness becomes useful in various recognition tasks such as face recognition when image alignment failures occur. We propose a novel me
Externí odkaz:
http://arxiv.org/abs/2403.14852
Evaluating the risk level of adversarial images is essential for safely deploying face authentication models in the real world. Popular approaches for physical-world attacks, such as print or replay attacks, suffer from some limitations, like includi
Externí odkaz:
http://arxiv.org/abs/2311.11753