Methods › Computer Vision › Point Cloud Representations › PolarNet

PolarNet

6 papers tagged archive 2025-07-28

Introduced by Yang Zhang et al. in PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

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.

PaperSource

Papers archive 2025-07-28

6 shown of 6, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

14 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
3D Semantic Segmentation2
Autonomous Driving2
LIDAR Semantic Segmentation2
Object Detection2
Segmentation2
Semantic Segmentation2
object-detection2
Cell Detection1
Decision Making1
Multi-Task Learning1
Real-Time Semantic Segmentation1
Robot Manipulation1
Robot Manipulation Generalization1
Robust 3D Semantic Segmentation1

Usage over time archive 2025-07-28

Papers per year tagged with PolarNet: 2020 to 2023, peak 2 2 0 2020: 2 papers 2020 2021: 2 papers 2021 2022: 1 paper 2022 2023: 1 paper 2023
Papers per year the archive tags with this method, by the paper's archive date (6 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Point Cloud Representations

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