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Person Recognition in Personal Photo Collections
AbstractRecognising persons in everyday photos presents major challenges (occluded faces, different clothing, locations, etc.) for machine vision. We propose a convnet based person recognition system on which we provide an in-depth analysis of informativeness of different body cues, impact of training data, and the common failure modes of the system. In addition, we discuss the limitations of existing benchmarks and propose more challenging ones. Our method is simple and is built on open source and open data, yet it improves the state of the art results on a large dataset of social media photos (PIPA).
Related Material
[pdf][bibtex]@InProceedings{Oh_2015_ICCV,
author = {Oh, Seong Joon and Benenson, Rodrigo and Fritz, Mario and Schiele, Bernt},
title = {Person Recognition in Personal Photo Collections},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
month = {December},
year = {2015}
}
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