【PLPR】Progressive Learning for Person Re-Identification with One Example
【PLPR】Progressive Learning for Person Re-Identification with One Example
Bibtex
@article{plpr,
title = {Progressive Learning for Person Re-Identification with One Example},
author = {Wu, Yu and Lin, Yutian and Dong, Xuanyi and Yan, Yan and Bian, Wei and Yang, Yi},
journal= {IEEE Transactions on Image Processing},
year = {2019},
volume = {28},
number = {6},
pages = {2872-2881},
doi = {10.1109/TIP.2019.2891895},
ISSN = {1057-7149},
month = {June},
}
Public information
IEEE Transactions on Image Processing (TIP), 2019
Fields
- Person Re-ID
- One-shot Learning
Code link
https://github.com/Yu-Wu/One-Example-Person-ReID
Main work
compare with EUG, author impoved the utilize of the unlabeled samples, aiming to optimize the accuracy of estimation for labels and selection for persudo sample with right labels.
Key technology
- CNN
- feature extraction
- metric of samply similarity
Framework
Dataset
- Market-1501
- DukeMTMC-reID
- MARS
- DukeMTMC-VideoReID