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Found 8 papers, 1 papers with code
On Hallucinating Context and Background Pixels from a Face Mask using Multi-scale GANs
We propose a multi-scale GAN model to hallucinate realistic context (forehead, hair, neck, clothes) and background pixels automatically from a single input face mask.
Fast Face Image Synthesis with Minimal Training
Our method samples face components from a pool of multiple face images of real identities to generate the synthetic texture.
Performance of Humans in Iris Recognition: The Impact of Iris Condition and Annotation-driven Verification
Results suggest that: (a) people improve their identity verification accuracy when asked to annotate matching and non-matching regions between the pair of images, (b) images depicting the same eye with large difference in pupil dilation were the most challenging to subjects, but benefited well from the annotation-driven classification, (c) humans performed better than iris recognition algorithms when verifying genuine pairs of post-mortem and disease-affected eyes (i. e., samples showing deformations that go beyond the distortions of a healthy iris due to pupil dilation), and (d) annotation does not improve accuracy of analyzing images from identical twins, which remain confusing for people.
Domain-Specific Human-Inspired Binarized Statistical Image Features for Iris Recognition
One important point is that all applications of BSIF in iris recognition have used the original BSIF filters, which were trained on image patches extracted from natural images.
Beyond Pixels: Image Provenance Analysis Leveraging Metadata
Creative works, whether paintings or memes, follow unique journeys that result in their final form.
Image Provenance Analysis at Scale
Given a large corpus of images and a query image, an interesting further step is to retrieve the set of original images whose content is present in the query image, as well as the detailed sequences of transformations that yield the query image given the original images.
SREFI: Synthesis of Realistic Example Face Images
In this paper, we propose a novel face synthesis approach that can generate an arbitrarily large number of synthetic images of both real and synthetic identities.
The ND-IRIS-0405 Iris Image Dataset
Image datasets acquired in 2004-2005 at Notre Dame with this LG 2200 have been used in the ICE 2005 and ICE 2006 iris biometric evaluations.
