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Input Aggregated Network for Face Video Representation
[article]
2016
arXiv
pre-print
Recently, deep neural network has shown promising performance in face image recognition. The inputs of most networks are face images, and there is hardly any work reported in literature on network with face videos as input. To sufficiently discover the useful information contained in face videos, we present a novel network architecture called input aggregated network which is able to learn fixed-length representations for variable-length face videos. To accomplish this goal, an aggregation unit
arXiv:1603.06655v1
fatcat:k6aboararzgmxifgfy2kax55ay