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Occupancy Prediction on EmbodiedOcc-ScanNet 1.0 (test)

53.3Overall IoURoboOcc
8.444820.089931.73543.3801Apr 30, 2026

Evaluation results

MethodLinks
RoboOccLearning Paradigm=Fully supervised learning, Annotation (Geo.)=Occupancy, Annotation (Sem.)=✓2026.0453.321.9444.5739.5438.4851.2857.0463.0936.743.0554.4234.3844.05
EmbodiedOcc++Learning Paradigm=Fully supervised learning, Annotation (Geo.)=Occupancy, Annotation (Sem.)=✓2026.0452.227.943.938.740.64957.959.236.837.853.534.143.6
EmbodiedOccLearning Paradigm=Fully supervised learning, Annotation (Geo.)=Occupancy, Annotation (Sem.)=✓2026.0451.5222.744.637.43850.156.759.735.438.45232.942.53
GaussianFormerLearning Paradigm=Fully supervised learning, Annotation (Geo.)=Occupancy, Annotation (Sem.)=✓2026.0438.021733.621.521.729.447.837.124.315.536.216.827.36
SurroundOccLearning Paradigm=Fully supervised learning, Annotation (Geo.)=Occupancy, Annotation (Sem.)=✓2026.0437.0412.731.822.52229.944.736.524.611.534.418.226.27
TPVFormerLearning Paradigm=Fully supervised learning, Annotation (Geo.)=Occupancy, Annotation (Sem.)=✓2026.0435.881.6230.5412.0313.2235.4751.3949.7925.633.643.1516.2325.7
FreeOcc (rgbd)Learning Paradigm=Training-free, Annotation (Geo.)=✗, Annotation (Sem.)=✗, Modality=rgbd2026.0434.46.5626.4621.6915.1521.0222.0923.6115.877.488.28615.84
FreeOcc (mono)Learning Paradigm=Training-free, Annotation (Geo.)=✗, Annotation (Sem.)=✗, Modality=monocular2026.0431.293.1623.4916.1413.1119.6621.6423.4313.764.018.045.9813.86
GaussTRLearning Paradigm=Self-supervised learning, Annotation (Geo.)=Poses, Annotation (Sem.)=✗2026.0415.631.27.784.292.674.5211.2710.955.310.94.211.344.95
GaussianOccLearning Paradigm=Self-supervised learning, Annotation (Geo.)=Poses, Annotation (Sem.)=✗2026.0410.173.815.092.532.563.8410.269.95.370.52.331.194.34