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SynLiDAR

Introduced by Aoran Xiao et al. in Transfer Learning from Synthetic to Real LiDAR Point Cloud for Semantic Segmentation12 Jul 2021 archive 2025-07-28

SynLiDAR is a large-scale synthetic LiDAR sequential point cloud dataset with point-wise annotations. 13 sequences of LiDAR point cloud with around 20k scans (over 19 billion points and 32 semantic classes) are collected from virtual urban cities, suburban towns, neighborhood, and harbor.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
3D Source-Free Domain Adaptation SynLiDAR-to-SemanticKITTI TTYD mIoU 32.4 Train Till You Drop: Towards Stable and Robust... valeoai/ttyd 1 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 20. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
Train Till You Drop: Towards Stable and Robust Source-free Unsupervised 3D Domain Adaptation 1 1 6 Sep 2024 ran 10 of 19 samples (9 unverified; 19 pointer-only for licence)

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • SynLiDAR
  • SynLiDAR-to-SemanticKITTI

2 variant names, as the archive lists them.

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