The KITTI Vision Benchmark Suite

Regionlets detector based on multiple sources
object proposals. The detection results are
further refined by Regionlets Re-localization.


Details will be given in
http://www.xiaoyumu.com/project/kitti

This is an updated version of our results
submitted on Oct 6th which achieved:

Benchmark Easy Moderate Hard
Car (Detection) 84.27% 75.68% 59.20%
Pedestrian (Detection) 68.79% 55.01% 49.75%
Cyclist (Detection) 56.96% 44.65% 39.05%


Papers are at:

Regionlets + CNN:
http://www.xiaoyumu.com/s/PDF/Regionlets-pami.pdf
http://www.xiaoyumu.com/s/PDF/cnnRegionlet.pdf

Regionlets + Re-localization:

http://www.xiaoyumu.com/s/PDF/Regionlets_relocali
zation.pdf

No parameters

@inproceedings{Wang2015PAMI,
author = {Xiaoyu Wang and Ming Yang and Shenghuo
Zhu and Yuanqing Lin},
title = {Regionlets for Generic Object
Detection},
booktitle = {T-PAMI},
year = {2015},
}

@inproceedings{Zou2014BMVC,
author = {Will Y. Zou and Xiaoyu Wang and Miao
Sun and Yuanqing Lin},
title = {Generic Object Detection with Dense
Neural Patterns and Regionlets},
booktitle = {British Machine Vision Conference},
year = {2014},
}

@inproceedings{Regionlets-Relocalization,
author = {Chengjiang Long and Xiaoyu Wang and
Gang Hua and Ming Yang and Yuanqing Lin},
title = {Accurate Object Detection with Location
Relaxation and Regionlets Relocalization},
booktitle = {Asian Conference on Computer
Vision},
year = {2014},
}