Code for CVPR 2024 paper Exploring Orthogonality in Open World Object Detection.
coco_to_voc.py
.datasets/JPEGImages
and annotations to datasets/Annotations
.bash run_owod.sh
Evaluation for open world object detection:
bash test_owod.sh
bash run_iod.sh
python demo.py -i LIST_OF_IMAGES
The following results were obtained with four NVIDIA 2080 Ti GPUs, using the checkpoints at this link.
Open world object detection on M-OWODB and S-OWODB:
Incremental object detection on PASCAL VOC:
If you find this code useful, please consider citing:
@inproceedings{sun2024exploring,
title={Exploring Orthogonality in Open World Object Detection},
author={Sun, Zhicheng and Li, Jinghan and Mu, Yadong},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={17302--17312},
year={2024},
}
Our implementation is based on RandBox which uses Detectron2 and Sparse R-CNN.