Point Cloud Models

Point-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


Paper Code Results Date Stars

Tasks


Task Papers Share
3D Object Detection 1 50.00%
Object Detection 1 50.00%

Components


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

Categories