3D Object Detection Models
Point-GNN
Introduced by Shi et al. in Point-GNN: Graph Neural Network for 3D Object Detection in a Point CloudPoint-GNN is a graph neural network for detecting objects from a LiDAR point cloud. It predicts the category and shape of the object that each vertex in the graph belongs to. In Point-GNN, there is an auto-registration mechanism to reduce translation variance, as well as a box merging and scoring operation to combine detections from multiple vertices accurately.
Source: Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud
Papers
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Usage Over Time
Components
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| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
