This repo contains source codes for the arXiv preprint "AirCode: A Robust Object Encoding Method"
Object matching comparison when the objects are non-rigid and the view is changed, left is the result of our method while right is the result of NetVLAD
Relocalization on KITTI datasets
- Python 3.7
- Torchvision 0.8.0
- PyTorch 1.7.0
- OpenCV 4.4.0
- Matplotlib 3.3.3
- NumPy 1.19.2
- Pyyaml 5.3.1
Four datasets are used in our experiments.
For relocalization experiment. Three sequences are selected, and they are "00", "05" and "06".
For multi-object matching experiment. Four sequences are selected, and they are "0002", "0003", "0006", "0010".
For single-object matching experiment. We select three sequences from VOT2019 datasets and they are "bluecar", "bus6" and "humans_corridor_occ_2_A", because the tracked objects in these sequences are included in coco datasets, which are the data we used to train mask-rcnn.
For single-object matching experiment. We select five sequences and they are "BlurBody", "BlurCar2", "Human2", "Human7" and "Liquor".
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Extract object descrptors
python experiments/place_recogination/online_relocalization.py -c config/experiment_tracking.yaml -g 1 -s PATH_TO_SAVE_MIDDLE_RESULTS -d PATH_TO_DATASET -m PATH_TO_MODELS
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Compute precision-recall curves
python experiments/place_recogination/offline_process.py -c config/experiment_place_recognization.yaml -d PATH_TO_DATASET -n PATH_TO_MIDDLE_RESULTS -s PATH_TO_SAVE_RESULTS
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Compute top-K relocalization results
python experiments/place_recogination/offline_topK.py -c config/experiment_place_recognization.yaml -d PATH_TO_DATASET -n PATH_TO_MIDDLE_RESULTS -s PATH_TO_SAVE_RESULTS
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Run multi-object matching experiment in KITTI Tracking Datasets Modify the config file and run
python experiments/object_tracking/object_tracking.py -c config/experiment_tracking.yaml -g 1 -s PATH_TO_SAVE_RESULTS -d PATH_TO_DATASET -m PATH_TO_MODELS
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Run single-object matching experiment in OTB or VOT Datasets Modify the config file and run
python experiments/object_tracking/single_object_tracking.py -c config/experiment_tracking.yaml -g 1 -s PATH_TO_SAVE_RESULTS -d PATH_TO_DATASET -m PATH_TO_MODELS