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Semantic Segmentation on SemanticKITTI (test)

75.6mIoULSK3DNet
64.78467.59270.473.208Jul 31, 2020Jul 20, 2021Jul 10, 2022Jun 29, 2023Jun 18, 2024Jun 7, 2025May 28, 2026

Evaluation results

MethodLinks
LSK3DNet#Params=28.8M, Joint training=false2026.0475.6—————————————————————
PTv3Training Protocol=Multi-dataset joint training (PPT [92])2023.1275.5—————————————————————
PTv3 + PPTYear=20242023.0875.5—————————————————————
PPT + PTv3Params.=46.3M, Training Protocol=supervised pre-training (fine-tuned)2023.0875.5—————————————————————
PTv3/PPT#Params=46.3M, Joint training=true2026.0475.5—————————————————————
Volt-B#Params=94.3M, Joint training=true2026.0475.2—————————————————————
PTv3 + M3NetYear=20242023.0875.1—————————————————————
SphereFormer2023.0374.8—70.170.559.667.77980.475.391.869.778.241.393.872.886.775.172.466.872.997.5—
SphereFormerTraining Protocol=Trained from scratch2023.1274.8—————————————————————
SphereFormerYear=20232023.0874.8—————————————————————
SphereFormerParams.=32.3M2023.0874.8—————————————————————
SphereFormerApproach Type=3D Voxel Based2023.1174.8—70.170.559.667.77980.475.391.869.778.241.393.872.886.775.172.466.872.997.5—
SphereFormerModality=3D-only2025.0374.8—————————————————————
SphereFormer#Params=32.3M, Joint training=false2026.0474.8—————————————————————
DITRModality=2D-3D fusion2025.0374.4—————————————————————
PTv3Training Protocol=Trained from scratch2023.1274.2—————————————————————
PTv3Year=20242023.0874.2—————————————————————
PTv3Params.=46.2M2023.0874.2—————————————————————
PTv3Modality=3D-only2025.0374.2—————————————————————
PTv3#Params=46.1M, Joint training=false2026.0474.2—————————————————————
RangeFormerYear=20232023.0873.3—————————————————————
2DPASS2023.0372.9—63.663.461.161.577.981.374.189.767.474.74093.572.986.273.9716570.497—
2DPASS2023.1272.9—63.663.461.161.577.981.374.189.767.474.74093.572.986.273.9716570.497—
2DPASSTraining Protocol=Trained from scratch2023.1272.9—————————————————————
2DPASSYear=20222023.0872.9—————————————————————
2DPASSModality=2D-3D fusion2025.0372.9—————————————————————
2DPASS2026.0572.9—63.663.461.161.577.981.374.189.767.474.74093.572.986.273.9716570.497—
PTv2Training Protocol=Trained from scratch2023.1272.6—————————————————————
PTv2Year=20222023.0872.6—————————————————————
PTv2Modality=3D-only2025.0372.6—————————————————————
PTv2#Params=12.8M, Joint training=false2026.0472.6—————————————————————
ConDaFormer2023.1272—66.569.362.664.873.673.165.188.370.572.835.792.770.784.973.969.765.271.397.3—
PVKD2023.0371.2—69.353.567.960.275.173.550.591.877.570.94192.469.486.573.871.964.965.897—
PVKDSpConv free=false2023.0171.2—67.969.353.560.275.173.550.591.870.992.477.54169.486.573.871.964.965.897—
PVKD2023.1271.2—69.353.567.960.275.173.550.591.877.570.94192.469.486.573.871.964.965.897—
PVKDYear=20222023.0871.2—————————————————————
(AF)2-S3Net2023.0370.8—6381.440.24076.481.777.79266.876.245.892.569.678.66863.16473.394.3—
WaffleIronSpConv free=true2023.0170.8—7069.840.459.677.175.541.590.670.493.576.438.972.386.775.771.766.271.997.2—
(AF)2-S3Net2023.1270.8—6381.440.24076.481.777.79266.876.245.892.569.678.66863.16473.394.3—
AF2S3NetTraining Protocol=Trained from scratch2023.1270.8—————————————————————
WaffleIronYear=20232023.0870.8—————————————————————
LinKInput representation=Voxel2023.0370.7—58.456.652.964.272.37769.190.668.276.234.59268.885.774.370.564.869.597.4—
GASNSpConv free=false2023.0170.7—65.85859.36180.482.746.389.866.292.374.630.169.687.37372.566.171.696.9—
SDSeg3DSpConv free=false2023.0170.4—58.754.254.965.270.274.452.290.969.493.276.741.971.186.174.371.165.470.697.4—
RPVNetType=Fusion Network, Voxel resolution=0.05m, Augmentation=instance CutMix2021.0370.3—68.468.744.261.175.974.473.493.470.380.733.393.572.186.575.171.764.861.497.6—
RPVNet2023.0370.3—68.468.744.261.175.974.443.493.470.380.733.393.572.186.575.171.764.861.497.6—
RPVNetInput representation=Range map + Point cloud + Voxel2023.0370.3—68.468.744.261.175.974.473.493.470.380.733.393.572.186.575.171.764.861.497.6—
RPVNetSpConv free=false2023.0170.3—68.468.744.261.175.974.443.493.470.393.580.733.372.186.575.171.764.861.497.6—
RPVNet2023.1270.3—68.468.744.261.175.974.443.493.470.380.733.393.572.186.575.171.764.861.497.6—
RPVNet2026.0570.3—68.468.744.261.175.974.443.493.470.380.733.393.572.186.575.171.764.861.497.6—
(AF)2-S3Net2021.0269.7—65.486.839.241.180.780.474.391.368.872.553.587.963.270.268.553.761.57194.5—
AF2S3Type=Voxel-based2021.0369.7—65.486.839.241.180.780.474.391.368.872.553.587.963.270.268.553.761.57194.5—
(AF)2-S3NetInput representation=Voxel2023.0369.7—65.486.839.241.180.780.474.391.368.872.553.587.963.270.268.553.761.57194.5—
(AF)^2-S3NetSpConv free=false2023.0169.7—65.486.839.241.180.780.474.391.368.887.972.553.563.270.268.553.761.57194.5—
(AF)2-S3NetApproach Type=3D Voxel Based2023.1169.7—65.486.839.241.180.780.474.391.368.872.553.587.963.270.268.553.761.57194.5—
xModel-KD2026.0569.1—5573.878.555.575.5595592.95479.45089.957.587.971.474.158.250.496.2—
Cylinder3D2023.0368.9—67.663.850.858.573.769.24892.2657732.390.766.585.672.569.862.466.297.1—
Cylinder3D2023.1268.9—67.663.850.858.573.769.24892.2657732.390.766.585.672.569.862.466.297.1—
Cylinder3D2026.0568.9—67.663.850.858.573.769.24892.2657732.390.766.585.672.569.862.466.297.1—
MinkInput representation=Voxel2023.0368—51.856.443.356.870.275.751.889.967.874.832.991.566.586.274.67163.57097.1—
Cylinder3Dpost-processing=applied, test ensemble (flip & rotation)=applied2020.1167.8—67.6645958.673.967.93691.465.175.532.39166.585.471.868.562.665.697.1—
Cylinder3DType=Voxel-based2021.0367.8—67.6645958.673.967.93691.465.175.532.39166.585.471.868.562.665.697.1—
Cylinder3DInput representation=Voxel2023.0367.8—67.6645958.673.967.93691.465.175.532.39166.585.471.868.562.665.697.1—
Cylinder3DRepresentation Type=Voxel-based2023.0167.8—67.6645958.673.967.93691.465.175.532.39166.585.471.868.562.665.697.1—
Cylinder3DSpConv free=false2023.0167.8—67.66450.858.673.967.93691.465.19175.532.366.585.471.868.562.665.697.1—
Cylinder3DTraining Protocol=Trained from scratch2023.1267.8—————————————————————
Cylinder3DYear=20212023.0867.8—————————————————————
Cylinder3DParams.=26.1M2023.0867.8—————————————————————
Cylinder3DApproach Type=3D Voxel Based2023.1167.8—67.6645958.673.967.93691.465.175.532.39166.585.471.868.562.665.697.1—
Cylinder3DModality=3D-only2025.0367.8—————————————————————
Cylinder3D#Params=26.1M, Joint training=false2026.0467.8—————————————————————
DRINetInput representation=Point cloud + Voxel2023.0367.5—575643.354.569.475.158.990.76575.226.291.567.385.272.668.863.56696.9—
2DPASS* (baseline)SpConv free=false, inputs=lidar data only2023.0167.4—51.155.854.951.676.879.830.389.862.191.973.833.568.786.572.371.363.770.296.3—
SPVNASArchitecture Group=multi-view fusion networks2020.1267—50.650.456.65867.467.150.390.267.675.421.891.666.986.173.47164.367.397.2—
SPVNAS2021.0267—50.650.456.65867.467.150.390.267.675.421.891.666.986.173.47164.367.397.2—
SPVNASType=Fusion Network2021.0367—50.650.456.65867.467.150.390.267.675.421.891.666.986.173.47164.367.397.2—
SPVNAS2023.0367—50.650.456.65867.467.150.390.267.675.421.891.666.986.173.47164.367.397.2—
SPVNASInput representation=Point cloud + Voxel2023.0367—50.650.456.65867.467.150.390.267.675.421.891.666.986.173.47164.367.397.2—
SPVNAS2023.1267—50.650.456.65867.467.150.390.267.675.421.891.666.986.173.47164.367.397.2—
BaselineModel type=LiDAR-only2026.0567—55586051.676.8555589.85773.85291.968.786.56571.36049.396.3—
SPVNAS#Params (M)=12.5, #MAdds (G)=73.8, Latency (ms)=259.92020.0766.4—————————————————————
SPVNAS#Params (M)=12.5, #MACs (G)=73.8, Latency (ms)=2592020.0766.4—————————————————————
SPVNASpost-processing=applied, test ensemble (flip & rotation)=applied2020.1166.4—————————————————————
SPVNASSpConv free=false2023.0166.4—51.550.859.858.865.765.243.790.267.691.375.216.965.986.173.47164.266.997.3—
SPVNASTraining Protocol=Trained from scratch2023.1266.4—————————————————————
SPVNASYear=20202023.0866.4—————————————————————
SPVNASParams.=10.8M2023.0866.4—————————————————————
SPVNASModality=3D-only2025.0366.4—————————————————————
SPVNAS#Params=10.8M, Joint training=false2026.0466.4—————————————————————
SPVNAS#Params (M)=7.5, #MAdds (G)=34.1, Latency (ms)=166.12020.0766—————————————————————
JS3C-NetSize=50K pts2020.1266—59.352.954.34669.565.439.988.961.972.131.992.570.884.569.867.960.768.795.8—
JS3C-Net2023.0366—59.352.954.34669.565.439.988.961.972.131.992.570.884.569.867.960.768.795.8—
JS3C-NetSpConv free=false2023.0166—59.352.954.34669.565.439.988.861.992.572.131.970.884.569.86860.768.795.8—
JS3C-Net2023.1266—59.352.954.34669.565.439.988.961.972.131.992.570.884.569.867.960.768.795.8—
GFNetSpConv free=true2023.0165.4—53.248.331.747.362.857.344.793.672.59480.831.273.985.271.169.361.86896—
AMVNetArchitecture Group=multi-view fusion networks2020.1265.3—59.954.248.845.77165.71190.17175.832.492.469.185.671.769.662.767.296.2—
AMVNetType=Fusion Network2021.0365.3—59.954.248.845.77165.71190.17175.832.492.469.185.671.769.662.767.296.2—
AMVNetSpConv free=true2023.0165.3—59.954.248.845.77165.71190.17192.475.832.469.185.671.769.662.767.296.2—
SPVNAS#Params (M)=5.1, #MAdds (G)=24.4, Latency (ms)=144.32020.0765.2—————————————————————
SVASegSpConv free=false2023.0165.2—56.45749.156.370.66715.492.365.991.476.523.666.185.272.967.863.965.296.7—