Unsupervised Object Detection with LiDAR Clues

@article{Tian2021UnsupervisedOD,
  title={Unsupervised Object Detection with LiDAR Clues},
  author={Haofei Tian and Yuntao Chen and Jifeng Dai and Zhaoxiang Zhang and Xizhou Zhu},
  journal={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2021},
  pages={5958-5968}
}
  • Haofei Tian, Yuntao Chen, Xizhou Zhu
  • Published 25 November 2020
  • Computer Science, Environmental Science
  • 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Despite the importance of unsupervised object detection, to the best of our knowledge, there is no previous work addressing this problem. One main issue, widely known to the community, is that object boundaries derived only from 2D image appearance are ambiguous and unreliable. To address this, we exploit LiDAR clues to aid unsupervised object detection. By exploiting the 3D scene structure, the issue of localization can be considerably mitigated. We further identify another major issue, seldom… 

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