Person Recognition in Personal Photo Collections
Abstract
Recognising 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).
Cite
Text
Oh et al. "Person Recognition in Personal Photo Collections." International Conference on Computer Vision, 2015. doi:10.1109/ICCV.2015.440Markdown
[Oh et al. "Person Recognition in Personal Photo Collections." International Conference on Computer Vision, 2015.](https://mlanthology.org/iccv/2015/oh2015iccv-person/) doi:10.1109/ICCV.2015.440BibTeX
@inproceedings{oh2015iccv-person,
title = {{Person Recognition in Personal Photo Collections}},
author = {Oh, Seong Joon and Benenson, Rodrigo and Fritz, Mario and Schiele, Bernt},
booktitle = {International Conference on Computer Vision},
year = {2015},
doi = {10.1109/ICCV.2015.440},
url = {https://mlanthology.org/iccv/2015/oh2015iccv-person/}
}