Height-Guided Projection Reparameterization for
Camera-LiDAR Occupancy

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📖 Overview

🚀 Get Started

# Create and activate the conda environment
conda create -n HiPR python=3.8 -y
conda activate HiPR

# Install PyTorch dependencies (for CUDA 11.8)
pip install torch==2.0.1+cu118 torchvision==0.15.2+cu118 -f https://download.pytorch.org/whl/torch_stable.html

# Install MMCV dependencies
git clone https://github.com/open-mmlab/mmcv
cd mmcv
git checkout 1.x # Use the stable 1.x branch
MMCV_WITH_OPS=1 pip install -e . -v
cd ..

# Install MMDetection and MMSegmentation
pip install mmdet==2.28.2 mmsegmentation==0.30.0

# Install the OccStudio
pip install -v -e .

# Install other dependencies
pip install torchmetrics timm dcnv4 ninja spconv transformers IPython einops numba
pip install numpy==1.23.4 # Pin numpy version for compatibility

# (Optional for SparseOcc)
cd mmdet3d/models/sparseocc/csrc
pip install -v -e .

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🎮 Training and Testing

# Training
bash tools/dist_train.sh [CONFIG_FILE] [WORK_DIR] [NUM_GPUS]

# Testing
bash tools/dist_test.sh [CONFIG_FILE] [CHECKPOINT_PATH] [NUM_GPUS]
bash tools/dist_test_ray.sh [CONFIG_FILE] [CHECKPOINT_PATH] [NUM_GPUS]

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📦 Checkpoints

Trained model weights are available at:

👉 Google Drive Checkpoints

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🙏 Acknowledgements

This project is built upon the excellent open-source codebases from the community. We sincerely thank the authors and contributors for their great work.

• OccStudio
• FB-Occ
• ProtoOcc

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📄 Citation

If you find this project useful, please consider citing our work:

@article{hipr2026,
  title={Height-Guided Projection Reparameterization for Camera-LiDAR Occupancy},
  author={},
  journal={arXiv preprint arXiv:XXXX.XXXXX},
  year={2026}
}