This is a Pytorch implementations of "HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching".
Model | Sceneflow Finalpass, EPE | δ<0.1(%) | δ<1.0(%) | δ<3.0(%) | GMac(G) | Checkpoint | |
---|---|---|---|---|---|---|---|
HitNet-XL | 0.3762 | 82.1971 | 96.2759 | 98.1472 | 386.6757 | ckpt | converted copy of original tensorflow model |
HitNet | 0.5486 | 75.1038 | 94.5830 | 97.3138 | 50.5048 | ckpt | |
StereoNet | 0.7566 | 50.0250 | 91.0111 | 96.2597 | 106.7765 | ckpt | 8x downsample |
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Compile and install cuda op
pip install ./ext_op
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Replace dataset path in preprocess/plane_fitting.py and script/hitnet_sf_finalpass.sh
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Robust plane fitting
python preprocess/plane_fitting_sf.py
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Training
bash script/hitnet_sf_finalpass.sh
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Replace dataset path in eval.py
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Evaluation
python eval.py --model HITNet --ckpt ckpt/{ckpt_name} --data_type SceneFlow --data_root_val {path} --data_list_val lists/sceneflow_test.list
python predict.py --model HITNet --ckpt ckpt/{ckpt_name} --images {left.png} {right.png} --output {disp.png}
@article{tankovich2020hitnet,
title={HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching},
author={Tankovich, Vladimir and H{\"a}ne, Christian and Fanello, Sean and Zhang, Yinda and Izadi, Shahram and Bouaziz, Sofien},
journal={arXiv preprint arXiv:2007.12140},
year={2020}
}
However, if you find this implementation or pre-trained models helpful, please consider to cite:
@misc{hang2021tinyhitnet,
title={TinyHITNet},
author={zjjMaiMai},
howpublished={\url{https://github.com/zjjMaiMai/TinyHITNet}},
year={2021}
}