Apr 5, 2022 · In this paper, we propose the RBGNet framework, a voting-based 3D detector for accurate 3D object detection from point clouds.
The experiments (Table 4) show that our ray-based feature grouping strategy can effectively encode the surface geometry of foreground objects and sig-.
This paper proposes the RBGNet framework, a voting-based 3D detector for accurate 3D object detection from point clouds.
The experiments (Table 4) show that our ray-based feature grouping strategy can effectively encode the surface geometry of foreground objects and sig-.
In this paper, we propose the RBGNet framework, a voting-based 3D detector for accurate 3D object detection from point clouds.
RBGNet: Ray-based Grouping for 3D Object Detection - Semantic Scholar
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The RBGNet framework is proposed, a voting-based 3D detector for accurate 3D object detection from point clouds, and a ray-based feature grouping module.
We propose a 3D object detector that extracts accurate feature representations of object candidates and leverages self-attention on point patches, object ...
May 16, 2023 · RBGNet [34] proposes a ray-based feature grouping module to improve the grouping scheme of VoteNet as well as a foreground-based feature ...
In order to learn better representations of object shape to enhance cluster features for predicting 3D boxes, we propose a ray-based feature grouping module, ...
48.9. FCAF3D: Fully Convolutional Anchor-Free 3D Object Detection. 2021. 13. RBGNet (Geo only). 64.1, 47.2. RBGNet: Ray-based Grouping for 3D Object Detection.