A distilled 11.6M-parameter point cloud segmentation student matches the accuracy of a 100M+ parameter teacher on ScanNet and stays close on nuScenes, using affinity and cross-sample similarity losses.
Point-to-voxel knowledge distillation for lidar semantic segmentation
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SRKD: Towards Efficient 3D Point Cloud Segmentation via Structure- and Relation-aware Knowledge Distillation
A distilled 11.6M-parameter point cloud segmentation student matches the accuracy of a 100M+ parameter teacher on ScanNet and stays close on nuScenes, using affinity and cross-sample similarity losses.