Self-Supervised Pillar Motion Learning for Autonomous Driving (CVPR 2021)

Self-Supervised Pillar Motion Learning for Autonomous Driving

Chenxu Luo, Xiaodong Yang, Alan Yuille
Self-Supervised Pillar Motion Learning for Autonomous Driving, CVPR 2021
[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 = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2021},
    pages     = {3183-3192}
}

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 [email protected].