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Amit Aides

4 accepted papers

2019

LaSO: Label-Set Operations Networks for Multi-Label Few-Shot Learning

CVPR 2019oral

Example synthesis is one of the leading methods to tackle the problem of few-shot learning, where only a small number of samples per class are available. However, current synthesis approaches only address the scenario of a single category label per image. In this work, we propose a novel technique f…

Cited by 154PDFScholar
2019

RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection

CVPR 2019poster

Distance metric learning (DML) has been successfully applied to object classification, both in the standard regime of rich training data and in the few-shot scenario, where each category is represented by only a few examples. In this work, we propose a new method for DML that simultaneously learns t…

Cited by 461PDFScholar
2018

Robust Audiovisual Liveness Detection for Biometric Authentication Using Deep Joint Embedding and Dynamic Time Warping

ICASSP 2018accepted

We address the problem of liveness detection in audiovisual recordings for preventing spoofing attacks in biometric authentication systems. We assume that liveness is detected from a recording of a speaker saying a predefined phrase and that another recording of the same phrase is a priori available…

Cited by 0SourceScholar