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HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching

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HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching

This is a Pytorch implementations of "HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching".


Accuracy

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

Training

  1. Compile and install cuda op

    pip install ./ext_op
  2. Replace dataset path in preprocess/plane_fitting.py and script/hitnet_sf_finalpass.sh

  3. Robust plane fitting

    python preprocess/plane_fitting_sf.py
    
  4. Training

    bash script/hitnet_sf_finalpass.sh

Evaluation

  1. Replace dataset path in eval.py

  2. Evaluation

    python eval.py --model HITNet --ckpt ckpt/{ckpt_name} --data_type SceneFlow --data_root_val {path} --data_list_val lists/sceneflow_test.list

Predict

python predict.py --model HITNet --ckpt ckpt/{ckpt_name} --images {left.png} {right.png} --output {disp.png}

Citation

@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}
}

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