SA-Det3D: Self-Attention Based Context-Aware 3D Object Detection

@article{Bhattacharyya2021SADet3DSB,
  title={SA-Det3D: Self-Attention Based Context-Aware 3D Object Detection},
  author={Prarthana Bhattacharyya and Chengjie Huang and K. Czarnecki},
  journal={2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)},
  year={2021},
  pages={3022-3031}
}
Existing point-cloud based 3D object detectors use convolution-like operators to process information in a local neighbourhood with fixed-weight kernels and aggregate global context hierarchically. However, non-local neural networks and self-attention for 2D vision have shown that explicitly modeling long-range interactions can lead to more robust and competitive models. In this paper, we propose two variants of self-attention for contextual modeling in 3D object detection by augmenting… 

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