python demo/FLIR/demo_train_FLIR.py

python demo/FLIR/demo_mAP_FLIR.py

python demo/FLIR/demo_draw_FLIR.py    

# Example thermal only
python demo/FLIR/demo_FLIR_save_predictions.py --dataset_path /path/to/your/dataset --fusion_method thermal_only --model_path trained_models/FLIR/models/thermal_only/out_model_thermal_only.pth
# Example early fusion
python demo/FLIR/demo_FLIR_save_predictions.py --dataset_path /path/to/your/dataset --fusion_method early_fusion --model_path trained_models/FLIR/models/early_fusion/out_model_early_fusion.pth
# Example middle fusion
python demo/FLIR/demo_FLIR_save_predictions.py --dataset_path /path/to/your/dataset --fusion_method middle_fusion --model_path trained_models/FLIR/models/middle_fusion/out_model_middle_fusion.pth

python demo/FLIR/demo_probEn.py --dataset_path /path/to/your/dataset --prediction_path out/  --score_fusion probEn --box_fusion v-avg

@inproceedings{chen2022multimodal,
  title={Multimodal object detection via probabilistic ensembling},
  author={Chen, Yi-Ting and Shi, Jinghao and Ye, Zelin and Mertz, Christoph and Ramanan, Deva and Kong, Shu},
  booktitle={Computer Vision--ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part IX},
  pages={139--158},
  year={2022},
  organization={Springer}
}