RFIW 2017: LPQ-SIEDA for Large Scale Kinship Verification

Oualid Laiadi, A. Ouamane, A. Benakcha, A. Taleb-Ahmed
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引用次数: 7

Abstract

As a part of the RFIW 2017 Data Challenge Workshop, we demonstrate performance on the large-scale FIW dataset, along with several pre-existing image collections. Noticing available version of SIEDA method work well on smaller datasets (i.e. Cornell and UB KinFace datasets) than on FIW, we propose modifications to address this disparity in results.
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RFIW 2017: LPQ-SIEDA大规模亲属关系验证
作为RFIW 2017数据挑战研讨会的一部分,我们演示了大规模FIW数据集以及几个预先存在的图像集合的性能。注意到现有版本的SIEDA方法在较小的数据集(即Cornell和UB KinFace数据集)上比在FIW上工作得更好,我们提出修改以解决结果中的这种差异。
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Kin-Verification Model on FIW Dataset Using Multi-Set Learning and Local Features RFIW 2017: LPQ-SIEDA for Large Scale Kinship Verification Session details: Keynote & Invited Talks Recent Progress in Deep Reinforcement Learning for Computer Vision and NLP KinNet
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