Semanic Scene Understanding

Semantic Scene Completion


We evaluate geometric completion and semantic estimation and rank the methods according to the confidence weighted mean intersection-over-union (mIoU). Geometric completion is evaluated via completeness and accuracy at a threshold of 20cm. Completeness is calculated as the fraction of ground truth points of which the distances to their closest reconstructed points are below the threshold. Accuracy instead measures the percentage of reconstructed points that are within a distance threshold to the ground truth points. As our ground truth reconstruction may not be complete, we prevent punishing reconstructed points by dividing the space into observed and unobserved regions, which are determined by the unobserved volume from a 3D occupancy map obtained using OctoMap. We further measure the F1 score as the harmonic mean of the completeness and the accuracy.

Method Setting Code Accuracy Completeness F1 mIoU Class Runtime Environment
1 EncDec 41.36 41.23 41.29 9.07 NVIDIA V100
Y. Liao, J. Xie and A. Geiger: KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D. ARXIV 2021.
2 SimultaneousSampling 80.37 29.49 43.15 3.88 3 h NVIDIA V100
3 Raw Input 98.24 19.07 32.35 0.00 NVIDIA V100
Y. Liao, J. Xie and A. Geiger: KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D. ARXIV 2021.
Table as LaTeX | Only published Methods





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