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ResearchFormerly WizWand

Semantic Segmentation on SemanticKITTI v1.0 (val)

72.3mIoUPTv3
33.19643.34853.563.652Dec 15, 2023May 17, 2024Oct 19, 2024Mar 22, 2025Aug 24, 2025Jan 25, 2026Jun 29, 2026
Updated 4mo ago

Evaluation results

MethodLinks
PTv3Year=2024, Pre-training=PPT2023.1272.3
PTv3Year=2024, Pre-training=M3Net2023.1272
MinkUNetYear=2024, Pre-training=PPT2023.1271.4
PTv3Year=20242023.1270.8
OA-CNNsYear=20242023.1270.6
PTv2Year=20222023.1270.3
MinkUNetYear=2024, Pre-training=M3Net2023.1269.9
2DPASSYear=20222023.1269.3
WaffleIronYear=20232023.1268
SphereFormerYear=20232023.1267.8
RangeFormerYear=20232023.1267.6
SPVNASYear=20202023.1264.7
Cylinder3DYear=20212023.1264.3
MinkUNetYear=20192023.1263.8
DGNet (RandLA-Net)Setting=0.1%, Backbone=RandLA-Net2024.1051.8
RPSCSetting=0.1%2024.1050.9
SQNSetting=0.1%2024.1050.8
CMCRLabeling Ratio=1%2024.1249.86
SuperFlowPresent at=ECCV’24, Labeling Ratio=1%2024.1249.07
CSCPresent at=CVPR’24, Labeling Ratio=1%2024.1247.2
observability-constrained test-time prompt tuningTrainable Parameters (%)=0.72%, Per-frame Adaptation Time (s)=0.032026.0646.72
SealPresent at=NeurIPS’23, Labeling Ratio=1%2024.1246.63
HGLTrainable Parameters (%)=100%, Per-frame Adaptation Time (s)=0.552026.0645.06
ST-SLidRPresent at=CVPR’23, Labeling Ratio=1%2024.1244.72
SLidRPresent at=CVPR’22, Labeling Ratio=1%2024.1244.6
PPKTPresent at=Arxiv’21, Labeling Ratio=1%2024.1244
DepthContrastPresent at=ICCV’21, Labeling Ratio=1%2024.1241.5
DGNet (RandLA-Net)Setting=0.01%, Backbone=RandLA-Net2024.1041.2
PointContrastPresent at=ECCV’20, Labeling Ratio=1%2024.1241.1
GIPSOTrainable Parameters (%)=100%, Per-frame Adaptation Time (s)=3.212026.0640.28
RandomLabeling Ratio=1%2024.1239.5
SQNSetting=0.01%2024.1039.1
TentTrainable Parameters (%)=100%, Per-frame Adaptation Time (s)=0.372026.0638.06
Source2026.0637.4
CPCMSetting=0.01%2024.1034.7