🔥 RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation [ECCV 2024 Oral]

Coming soon!

Updates

• [2024.08] RAPiD was selected as an ✨ Oral ✨ at ECCV 2024.
• [2024.07] Our paper is available on arXiv, click here to check it out. The code will be available later.

Citation

If you are making use of this work in any way, you must please reference the following paper in any report, publication, presentation, software release or any other associated materials:

RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation (Li Li, Hubert P. H. Shum and Toby P. Breckon), In Proc. Eur. Conf. Comput. Vis. (ECCV), 2024. [homepage] [pdf] [video] [poster]

@inproceedings{li2024rapidseg,
  title = {{{RAPiD-Seg}}: {{Range-Aware}} {{Pointwise Distance Distribution}} {{Networks}} for {{3D LiDAR Segmentation}}},
  author = {Li, Li and Shum, Hubert P. H. and Breckon, Toby P.},
  keywords = {point cloud, semantic segmentation, invariance feature, pointwise distance distribution, autonomous driving},
  year = {2024},
  month = jul,
  publisher = {{Springer}},
  booktitle = {European Conference on Computer Vision (ECCV)},
}