Please refer to low-light-object-detection-detectron2 for installation requirements
Create a new folder named "exdark" in the "low-light-object-detection-detectron2/data" folder. Create a new folder named "exdark" in the "low-light-object-detection-mmdetection/data" folder.
Download the ExDark dataset and copy the images into "low-light-object-detection-detectron2/data/exdark/images/" and "low-light-object-detection-mmdetection/data/exdark/images/" folders.
Create a new folder named "darkface" in the "low-light-object-detection-detectron2/data" folder. Create a new folder named "darkface" in the "low-light-object-detection-mmdetection/data" folder.
Download the DARK FACE dataset and copy the images into "low-light-object-detection-detectron2/data/darkface/images/" and "low-light-object-detection-mmdetection/data/darkface/images/" folders.
To train the ExDark and DARK FACE using FeatEnHancer based Featurized Query R-CNN run the following commands: The training utilizes 2 GPU's
sh low-light-object-detection-detectron2/train_exdark.sh
sh low-light-object-detection-detectron2/train_darkface.sh
To train the ExDark and DARK FACE using FeatEnHancer based RetinaNet run the following commands: The training utilizes 6 GPU's
sh low-light-object-detection-mmdetection/exec_script_exdark.sh
sh low-light-object-detection-mmdetection/exec_script_darkface.sh
Model | mAP | Config |
---|---|---|
FeatEnHancer + Featurized Query R-CNN | 86.3 | config |
Model | mAP | Config |
---|---|---|
FeatEnHancer + Featurized Query R-CNN | 69.0 | config |
This work would not be possible without the following codebases. We gratefully thank the authors and collaborators for their wonderful works:
Featurized Query R-CNN,
detectron2,
mmdetection,
mmsegmentation, and
mmtracking
The proposed FeatEnHancer is released under the Creative Commons Attribution-NonCommercial 4.0 International Licence.
If you find FeatEnHancer useful in your research or applications, please consider giving us a star :star: and citing it by the following BibTeX entry.
@InProceedings{FeatEnHancer_Hashmi_ICCV23,
author = {Hashmi, Khurram Azeem and Kallempudi, Goutham and Stricker, Didier and Afzal, Muhammad Zeshan},
title = {FeatEnHancer: Enhancing Hierarchical Features for Object Detection and Beyond Under Low-Light Vision},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2023},
pages = {6725-6735}
}