Skip to content

"Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection". Pattern Recognition 85C (2019) pp. 161-171

License

Notifications You must be signed in to change notification settings

Li-Chengyang/IAF-RCNN

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 

Repository files navigation

Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection

Editted by Chengyang Li, Zhejiang University.

Detection performance

Note: Since the original annotations of the test set contain many problematic bounding boxes, we use the improved testing annotations provided by Liu et al. to enable a reliable comparison.

Downloads

Detection results

Citing our paper

If you find our work useful in your research, please consider citing:

@article{li2019illumination,
  title={Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection},
  author={Li, Chengyang and Song, Dan and Tong, Ruofeng and Tang, Min},
  journal={Pattern Recognition},
  volume={85C},
  pages={161-171},
  year={2019},
  publisher={Elsevier}
}

About

"Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection". Pattern Recognition 85C (2019) pp. 161-171

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published