Improving Face Authetication Using Virtual Samples
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Each smile is unique: one person surely smiles in different ways (e.g. closing/opening the eyes or mouth). Given one input image of a neutral face, can we generate multiple smile videos with distinctive characteristics? To tackle this one-to-many video gen ...
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In this work, we first revise some extensions of the standard Hopfield model in the low storage limit, namely the correlated attractor case and the multitasking case recently introduced by the authors. The former case is based on a modification of the Hebb ...
In this paper, we present a continuous attractor network model, which we hypothesize will give some suggestion of the mechanisms underlying several neural processes, such as velocity tuning to visual stimulus, sensory discrimination, sensorimotor-transform ...
In this paper, we present a simple yet effective way to improve a face verification system by generating multiple virtual samples from the unique image corresponding to an access request. These images are generated using simple geometric transformations. T ...
The performance of face verification systems has steadily improved over the last few years. State-of-the-art methods often use the gray-scale face image as input. In this paper, we use an additional feature to the face image: the skin color. The feature se ...
Body accelerations during human walking are recorded by a portable measuring device. A new method for parameterising body accelerations is introduced. The parameters are presented to a Kohonen neural network classifier and the feasibility of identification ...