This is the code for paper: Person Re-Identification via Recurrent Feature Aggregation, Yichao Yan, Bingbing Ni, Zhichao Song, chao Ma, Yan Yan, xiaokang Yang, In ECCV 2016.
Tested on Ubuntu 14.04. Compile by the command line:
make all
make pycaffe
See examples/re-id for the examples in our paper.
Please cite our paper in your publications if it helps your research:
@inproceedings{DBLP:conf/eccv/YanNSMYY16,
author = {Yichao Yan and Bingbing Ni and
Zhichao Song and
Chao Ma and
Yan Yan and
Xiaokang Yang},
title = {Person Re-identification via Recurrent Feature Aggregation},
booktitle = {Computer Vision - {ECCV} 2016 - 14th European Conference, Amsterdam,
The Netherlands, October 11-14, 2016, Proceedings, Part {VI}},
pages = {701--716},
year = {2016}
}
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and community contributors.
Check out the project site for all the details like
- DIY Deep Learning for Vision with Caffe
- Tutorial Documentation
- BVLC reference models and the community model zoo
- Installation instructions
and step-by-step examples.
Please join the caffe-users group or gitter chat to ask questions and talk about methods and models. Framework development discussions and thorough bug reports are collected on Issues.
Happy brewing!
Caffe is released under the BSD 2-Clause license. The BVLC reference models are released for unrestricted use.
Please cite Caffe in your publications if it helps your research:
@article{jia2014caffe,
Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
Journal = {arXiv preprint arXiv:1408.5093},
Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
Year = {2014}
}