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Self-Supervised Pillar Motion Learning for Autonomous Driving

<p align='left'> <img src='example.gif' width='675'/> </p>

Chenxu Luo, Xiaodong Yang, Alan Yuille <br> Self-Supervised Pillar Motion Learning for Autonomous Driving, CVPR 2021<br> [Paper] [Poster] [YouTube]

Getting Started

Installation

Install PyTorch, PyTorch3D, Apex, nuScenes Devkit

Data Preparation

python tools/create_data nuscenes_data_prep --root_path /path/to/nuscenes

Our optical flow model used for the cross-sensor regularization is available here.

Training

python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py configs/nusc_pillarmotion.py --work_dir experiments/pillarmotion/

Citation

Please cite the following paper if this repo helps your research:

@InProceedings{Luo_2021_CVPR,
    author    = {Luo, Chenxu and Yang, Xiaodong and Yuille, Alan},
    title     = {Self-Supervised Pillar Motion Learning for Autonomous Driving},
    booktitle = {Computer Vision and Pattern Recognition (CVPR)},
    year      = {2021}
}

License

Copyright (C) 2021 QCraft. All rights reserved. Licensed under the CC BY-NC-SA 4.0 (Attribution-NonCommercial-ShareAlike 4.0 International). The code is released for academic research use only. For commercial use, please contact business@qcraft.ai.