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3D Semantic Occupancy Prediction on Occ3D-nuScenes v1.0 (val)

83mIoUAutoOcc
4.989625.242345.49565.7477Mar 11, 2025May 29, 2025Aug 16, 2025Nov 3, 2025Jan 21, 2026Apr 10, 2026Jun 29, 2026

Evaluation results

MethodLinks
AutoOcc2025.098312.710.57.820.45.817.618.524.3—12.955.524.227.1—36.64.235.6————
GaussianFlowOccFPS=10.22025.0946.96.89.71917.24.211.89.310.3—12.36131.234.8—12.41.814.7————
OccNeRFFPS=5.42025.0946.40.71.86.66.63.70.32.93.2—6.652.82425—9.72.918.6————
BEVDet4D + COTRImage Backbone=Swin-B2026.0246.2—————————————————74.9———
BEVDet4D + COTRImage Backbone=Swin-B2026.0646.2—————————————————74.9———
GaussTRFPS=0.32025.0944.56.58.521.824.36.315.57.91.9—17.23717.27.2—106.121.2————
BEVDet4D + COTRImage Backbone=ResNet-502026.0244.5—————————————————75———
BEVDet4D + COTRImage Backbone=ResNet-502026.0644.5—————————————————75———
SelfOccFPS=7.42025.0944.10.20.56.710.400.12.10—7.756.126.925.7—4.6013.4————
SGEImage Backbone=VoVNetV2-992026.0643.5—————————————————71.7———
GaussianOccFPS=5.42025.0942.91.85.814.613.61.32.889.8—9.644.620.117.6—10.30.68.6————
LaGS-2sImage Backbone=VoVNetV2-992026.0240.7—————————————————67.3———
LaGS-2sImage Backbone=VoVNetV2-992026.0640.7—————————————————67.3———
BEVDet4D + COTRImage Backbone=ResNet-50, Note=Restricted baseline without CFSG2026.0640.2—————————————————71.7———
BEVDet4DImage Backbone=ResNet-502026.0239.3—————————————————73.8———
BEVDet4DImage Backbone=ResNet-502026.0639.3—————————————————73.8———
EasyOccFPS=5.4, Supervision=Easy3D-Labels2025.0938.91.96.715.121.72.78.115.311.1—12.855.827.922.1—17.31.416.1————
GaussianOcc + Easy3D-LabelsFPS=5.4, Supervision=Easy3D-Labels, 2D semantic loss=false2025.0938.81.75.916.222.32.38.415.710.2—13.455.327.423.4—17116————
OccNeRF + Easy3D-LabelsFPS=5.4, Supervision=Easy3D-Labels, 2D semantic loss=true2025.0938.51.98.216.722.117.714.712.8—13.855.92822.7—17.2115.8————
OccFormerImage Backbone=ResNet-502026.0237.4—————————————————70.1———
OccFormerImage Backbone=ResNet-502026.0637.4—————————————————70.1———
SurroundOccImage Backbone=ResNet-1012026.0234.6—————————————————65.5———
BEVDet4D + COTR*Image Backbone=ResNet-50, restricted_baseline=true2026.0234.6—————————————————66.3———
SurroundOccImage Backbone=ResNet-1012026.0634.6—————————————————65.5———
SelfOcc + Easy3D-LabelsFPS=7.4, Supervision=Easy3D-Labels2025.0934.51.75.414.522.22.66.415.48.9—12.85526.821.6—9.3111.3————
TPVFormerImage Backbone=ResNet-502026.0234.2—————————————————66.8———
TPVFormerImage Backbone=ResNet-502026.0634.2—————————————————66.8———
TrackOcc‡Image Backbone=ResNet-50, official_code_trained=true2026.0232.1—————————————————63.7———
TrackOccImage Backbone=ResNet-502026.0632.1—————————————————63.7———
DistillNeRFFPS=2.82025.0929.11.42.110.210.12.625.54.6—7.94316.915—15.11.414.1————
CTF-OccInput=C2025.0328.5339.3320.5638.2942.2416.9324.5222.7221.0522.9831.1153.3337.9833.2320.7918——————
TT-OccLiDARInput=C&L2025.0327.4132.4416.0816.8822.5628.3221.0614.3420.0210.3314.4752.631.437.2148.0245.37——————
BEVFormerInput=C2025.0326.8837.8317.8740.4442.437.3623.8821.8120.9822.3830.755.353628.0620.0417.69——————
OccFlowNetInput=C&L2025.0326.1427.526343220.425.918.620.22628.76237.839.52926.8——————
RenderOccInput=C2025.0323.9327.5614.3619.9120.5611.9612.4212.1414.3420.8118.9468.8542.0143.9417.3622.61——————
DeGOsupervision=weakly supervised2026.0518.056.6310.6818.1517.553.8312.889.5610.8—12.3666.1934.7137.69—12.980.9515.7145.3810.3433.4611.04
TT-OccCameraInput=C2025.0316.721.5110.4610.714.7211.8912.339.7112.24.377.9248.2723.728.3114.1320.24——————
TT-OccFPS=0.72025.0916.721.510.510.714.711.912.39.712.2—7.948.323.728.3—20.24.414.1————
GaussianFlowreproduced_results=true, supervision=weakly supervised2026.0516.276.899.8117.4115.934.0110.78.689.84—11.8759.1729.9432.2—12.360.7914.4140.399.5929.629.73
VEON-LiDARInput=C&L2025.0315.1410.46.217.712.78.57.66.55.58.211.854.525.530.225.425.4——————
VEONsupervision=weakly supervised2026.0513.954.82.714.710.9113.84.74—9.646.521.122.1—23.75.324.8—7.1527.643.73
GaussTRsupervision=weakly supervised2026.0513.262.095.2214.0720.435.77.085.123.93—13.3639.4415.6822.89—21.870.9221.1745.197.7924.215.81
LangOccsupervision=weakly supervised2026.0512.042.77.25.813.90.510.86.48.7—1142.112.527.2—14.53.214.1—7.0222.088.13
LangOccInput=C2025.0311.843.196.314.20.410.86.293.810.743.79.526.419.626.4——————
GaussianTRInput=C2025.0311.72.095.2214.0720.435.77.085.123.930.9213.3639.4415.6822.8921.1721.87——————
GaussianOccInput=C2025.0311.261.795.8214.5813.551.32.827.959.760.569.6144.5920.117.588.6110.29——————
GaussianOccsupervision=weakly supervised2026.0511.261.795.8214.5813.551.32.827.959.76—9.6144.5920.117.58—10.290.568.61—6.7722.855.53
OccNeRFInput=C2025.0310.810.830.825.1312.493.50.233.11.840.523.952.6220.8124.7518.4513.19——————
OccNeRFsupervision=weakly supervised2026.0510.810.830.825.1312.493.50.233.11.84—3.952.6220.8124.75—13.190.5218.4522.813.2425.961.38
SelfOccInput=C2025.0310.540.150.665.4612.5400.82.1008.2555.4926.326.5414.225.6——————
SelfOccsupervision=weakly supervised2026.0510.540.150.665.4612.5400.82.10—8.2555.4926.326.54—5.6014.2245.01325.631.19
DistillNeRFsupervision=weakly supervised2026.0510.121.352.0810.2110.092.561.985.544.62—7.943.0216.8615.02—15.061.4314.0629.114.7820.83.2
DistillNeRFInput=C2025.038.931.352.0810.2110.092.561.985.544.621.437.943.0216.8615.0214.0615.06——————
SimpleOccInput=C2025.037.990.671.183.217.631.020.261.80.261.072.8140.4418.317.0113.4210.84——————