A direct feature-space approach for 3D LiDAR anomaly segmentation achieves competitive results on existing and new mixed real-synthetic datasets.
Lsk3dnet: Towards effective and efficient 3d perception with large sparse kernels
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Learning to Identify Out-of-Distribution Objects for 3D LiDAR Anomaly Segmentation
A direct feature-space approach for 3D LiDAR anomaly segmentation achieves competitive results on existing and new mixed real-synthetic datasets.