For Pedestrian Attribute Analysis and Person Retrieval in Real Surveillance Scenarios
RAPv1
A Richly Annotated Dataset for Pedestrian Attribute Recognition, ACPR 2015
Overview
Paper
Download
BibTex
RAPv2
A Richly Annotated Pedestrian Dataset for Person Retrieval in Real Surveillance Scenarios, TIP 2018
Overview
Paper
Download
BibTex
Strong Baseline
Rethinking of Pedestrian Attribute Recognition: A Reliable Evaluation under Zero-Shot Pedestrian Identity Setting, arxiv 2021
Overview
Paper
Code
BibTex
RAPv1 BibTex
@inproceedings{li2015deepmar,
author = {Dangwei Li and Xiaotang Chen and Kaiqi Huang},
title = {Multi-attribute Learning for Pedestrian Attribute Recognition in Surveillance Scenarios},
booktitle = {ACPR},
pages={111--115},
year = {2015}
}
RAPv2 BibTex
@ARTICLE{8510891,
author={D. {Li} and Z. {Zhang} and X. {Chen} and K. {Huang}},
journal={IEEE Transactions on Image Processing},
title={A Richly Annotated Pedestrian Dataset for Person Retrieval in Real Surveillance Scenarios},
year={2019},
volume={28},
number={4},
pages={1575-1590},
}
Baseline BibTex
@article{jia2021rethinking,
title={Rethinking of Pedestrian Attribute Recognition: A Reliable Evaluation under Zero-Shot Pedestrian Identity Setting},
author={Jia, Jian and Huang, Houjing and Chen, Xiaotang and Huang, Kaiqi},
journal={arXiv preprint arXiv:2107.03576},
year={2021}
}