LWSIS

March 6, 2023 · View on GitHub

An official implementation of AAAI2023 paper "LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous Driving"

Models

ModelBackboneAnnotationsLr_scheduleMask_APDownload
BoxInstR-50box1x33.65link(访问码:pmw0)
BoxInstR-101box1x34.39link
PointSupR-50box+point1x43.80link
PointSupR-101box+point1x44.72link
LWSIS+BoxInstR-503dbox+pc1x35.65link(访问码:hy6a)
LWSIS+BoxInstR-1013dbox+pc1x36,22link
LWSIS+PointSupR-503dbox+pc1x45.46link
LWSIS+PointSupR-1013dbox+pc1x46.17link

Here we explain different annotations used in the exp. 'box' means only using the 2D bounding box annotation for each instance, 'point' means using a specific number of points with human annotation indicating the background/foreground, '3dbox' means using the 3D bounding box annotations for each instance and 'pc' means the original point cloud.

Install

First install Detectron2 following the official guide: INSTALL.md.

Please use Detectron2 with commit id 9eb4831 if you have any issues related to Detectron2.

Then build LWSIS with:

git clone git@github.com:Serenos/LWSIS.git
cd LWSIS
python setup.py build develop

Quick Start

  • Download the nuscenes origin datasets to ${HOME}/datasets/. The folder structure shall be like this:

    • nuscenes
      • annotations
      • lidarseg
      • maps
      • samples
      • sweeps
      • v1.0-trainval
      • v1.0-mini
  • Download nuInsSeg3d_train(访问码:4aml), nuInsSeg3d_val(访问码:luw8) and put it into the nuscenes/annotations folder.

  • Training

    bash tools/train.sh configs/BoxInst/MS_R_50_1x_nuscenes.yaml Boxinst_LWSIS 000
    
  • Evaluation

    bash tools/test.sh configs/BoxInst/MS_R_50_1x_nuscenes.yaml output/Boxinst_LWSIS/000/model_final.pth 
    

nuInsSeg Dataset and devkit

We supplement instance mask annotation for nuScenes dataset. For more detail, please follow the nuinsseg-devkit.

Acknowledgements

The authors are grateful to School of Computer Science, Beijing Institute of Technology, Shanghai AI Laboratory, Inceptio, 4SKL-IOTSC, CIS, University of Macau.

The code is based on Adlaidet.