PolarNet is an improved grid representation for online, single-scan LiDAR point clouds. Instead of using common spherical or bird's-eye-view projection, the polar bird's-eye-view representation balances the points across grid cells in a polar coordinate system, indirectly aligning a segmentation network's attention with the long-tailed distribution of the points along the radial axis.
Source: PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic SegmentationPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Object Detection | 2 | 12.50% |
Autonomous Driving | 2 | 12.50% |
3D Semantic Segmentation | 2 | 12.50% |
LIDAR Semantic Segmentation | 2 | 12.50% |
Semantic Segmentation | 2 | 12.50% |
Multi-Task Learning | 1 | 6.25% |
Robot Manipulation | 1 | 6.25% |
Cell Detection | 1 | 6.25% |
Decision Making | 1 | 6.25% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |