BKISemanticMapping

Bayesian Spatial Kernel Smoothing for Scalable Dense Semantic Mapping

<img src="https://raw.githubusercontent.com/ganlumomo/BKISemanticMapping/master/github/toy_example_semantic_csm.png" width="300"><img src="https://raw.githubusercontent.com/ganlumomo/BKISemanticMapping/master/github/toy_example_semantic_bki.png" width="300"> <img src="https://raw.githubusercontent.com/ganlumomo/BKISemanticMapping/master/github/toy_example_semantic_csm_variance.png" width="300"><img src="https://raw.githubusercontent.com/ganlumomo/BKISemanticMapping/master/github/toy_example_semantic_bki_variance.png" width="300">

Quantitative results on SemanticKITTI dataset sequence 00-10 for 19 semantic classes. SqueezeSegV2-kNN (Sq.-kNN)

| Sequence | Method | Car | Bicycle | Motorcycle | Truck | Other Vehicle | Person | Bicyclist | Motorcyclist | Road | Parking | Sidewalk | Other Ground | Building | Fence | Vegetation | Trunk | Terrain | Pole | Traffic Sign | Average | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 00 | Sq.-KNN | 92.1 | 18.3 | 55.0 | 76.5 | 62.9 | 34.2 | 52.0 | 61.4 | 94.7 | 71.0 | 87.9 | 1.2 | 89.8 | 54.6 | 82.2 | 53.1 | 79.3 | 38.6 | 51.5 | 60.9 | | | S-CMS | 95.6 | 23.5 | 69.8 | 88.3 | 74.4 | 47.9 | 71.6 | 56.9 | 96.3 | 78.1 | 91.2 | 3.1 | 93.6 | 64.2 | 87.4 | 70.1 | 83.5 | 61.1 | 70.7 | 69.9 | | | S-BKI | 96.9 | 26.5 | 75.8 | 93.5 | 80.1 | 61.5 | 77.5 | 71.0 | 96.2 | 79.2 | 91.5 | 6.6 | 94.6 | 66.5 | 88.9 | 73.4 | 84.5 | 65.8 | 76.2 | 75.0 | | 01 | Sq.-KNN | 83.8 | n/a | n/a | n/a | 82.9 | n/a | n/a | 67.9 | 92.6 | n/a | n/a | 70.5 | 58.0 | 71.4 | 72.1 | 18.0 | 71.5 | 21.8 | 68.9 | 64.0 | | | S-CMS | 89.8 | n/a | n/a | n/a | 91.0 | n/a | n/a | 70.3 | 93.4 | n/a | n/a | 74.2 | 64.4 | 73.8 | 75.1 | 26.3 | 74.7 | 31.9 | 78.7 | 70.3 | | | S-BKI | 91.0 | n/a | n/a | n/a | 96.0 | n/a | n/a | 70.7 | 94.3 | n/a | n/a | 75.2 | 67.1 | 75.1 | 76.4 | 30.6 | 76.1 | 36.2 | 81.4 | 72.5 | | 02 | Sq.-KNN | 90.9 | 14.5 | 50.8 | n/a | 56.4 | 38.6 | n/a | 59.9 | 93.9 | 68.1 | 84.9 | 50.9 | 79.1 | 66.1 | 82.5 | 48.9 | 68.3 | 25.7 | 35.9 | 59.7 | | | S-CSM | 95.4 | 28.5 | 73.4 | n/a | 80.3 | 60.3 | n/a | 75.1 | 94.8 | 74.4 | 87.4 | 61.7 | 85.0 | 71.8 | 86.7 | 66.9 | 72.9 | 43.5 | 55.7 | 71.4 | | | S-BKI | 95.8 | 31.1 | 76.4 | n/a | 83.3 | 62.5 | n/a | 79.5 | 94.8 | 75.0 | 87.4 | 63.6 | 85.6 | 72.1 | 87.1 | 68.8 | 73.4 | 45.9 | 60.4 | 73.1 | | 03 | Sq.-KNN | 88.4 | 21.9 | n/a | 12.4 | 60.1 | 16.3 | n/a | n/a | 92.8 | 57.9 | 83.2 | n/a | 77.4 | 70.1 | 79.3 | 41.6 | 62.3 | 35.9 | 47.3 | 56.5 | | | S-CSM | 92.4 | 29.7 | n/a | 23.1 | 65.4 | 17.6 | n/a | n/a | 94.3 | 69.4 | 86.9 | n/a | 80.4 | 73.8 | 83.2 | 52.3 | 66.9 | 53.5 | 62.0 | 63.0 | | | S-BKI | 94.5 | 42.4 | n/a | 48.8 | 73.6 | 23.8 | n/a | n/a | 94.3 | 73.2 | 87.2 | n/a | 82.1 | 74.7 | 84.1 | 55.7 | 67.4 | 57.3 | 66.7 | 68.0 | | 04 | Sq.-KNN | 84.9 | n/a | n/a | n/a | 68.1 | 20.8 | n/a | n/a | 95.8 | 26.1 | 68.4 | 61.5 | 49.3 | 76.4 | 82.6 | 14.0 | 67.6 | 36.0 | 44.6 | 56.9 | | | S-CSM | 88.3 | n/a | n/a | n/a | 71.2 | 23.2 | n/a | n/a | 96.5 | 40.5 | 72.5 | 64.0 | 52.1 | 78.5 | 85.5 | 19.4 | 72.5 | 50.8 | 57.6 | 62.3 | | | S-BKI | 87.7 | n/a | n/a | n/a | 82.5 | 37.3 | n/a | n/a | 96.2 | 55.7 | 72.3 | 68.3 | 56.9 | 80.3 | 87.1 | 24.4 | 72.7 | 55.5 | 67.0 | 67.5 | | 05 | Sq.-KNN | 89.1 | 8.6 | 15.4 | 82.5 | 70.9 | 31.0 | 55.0 | n/a | 94.7 | 84.8 | 85.0 | 61.5 | 87.0 | 72.4 | 75.5 | 30.3 | 64.6 | 27.6 | 39.5 | 59.8 | | | S-CSM | 93.4 | 15.4 | 28.9 | 86.4 | 78.4 | 39.8 | 69.4 | n/a | 96.4 | 90.1 | 88.5 | 70.0 | 90.9 | 77.7 | 81.2 | 46.8 | 69.5 | 47.6 | 57.4 | 68.2 | | | S-BKI | 93.2 | 27.4 | 46.0 | 89.0 | 84.1 | 47.5 | 83.3 | n/a | 94.2 | 88.0 | 83.6 | 75.2 | 92.4 | 75.3 | 82.1 | 53.5 | 69.5 | 50.2 | 63.3 | 72.1 | | 06 | Sq.KNN | 85.4 | 17.1 | 50.2 | 86.7 | 66.1 | 27.6 | 64.3 | n/a | 87.6 | 56.0 | 74.9 | 66.5 | 83.9 | 38.4 | 61.9 | 32.0 | 89.5 | 40.1 | 52.7 | 60.1 | | | S-CSM | 91.8 | 22.7 | 62.5 | 89.8 | 75.4 | 43.3 | 92.1 | n/a | 91.1 | 68.2 | 80.4 | 70.5 | 89.4 | 49.3 | 69.7 | 50.1 | 92.2 | 60.0 | 77.9 | 70.9 | | | S-BKI | 92.6 | 28.7 | 67.9 | 93.5 | 81.4 | 62.7 | 95.4 | n/a | 90.3 | 70.7 | 79.9 | 71.8 | 91.7 | 53.6 | 73.7 | 54.7 | 91.9 | 66.4 | 84.8 | 75.1 | | 07 | Sq.-KNN | 92.4 | 21.3 | 64.0 | 83.6 | 69.8 | 53.2 | 63.6 | n/a | 93.9 | 75.9 | 89.3 | n/a | 90.9 | 59.7 | 76.5 | 45.9 | 82.8 | 40.2 | 54.0 | 68.1 | | | S-CSM | 94.9 | 25.9 | 76.8 | 82.6 | 81.5 | 64.2 | 88.0 | n/a | 95.8 | 80.9 | 92.0 | n/a | 93.8 | 66.6 | 80.8 | 59.8 | 84.7 | 55.4 | 73.2 | 76.2 | | | S-BKI | 93.8 | 29.2 | 80.2 | 82.7 | 87.8 | 70.1 | 92.7 | n/a | 93.9 | 77.0 | 87.7 | n/a | 94.1 | 63.4 | 81.4 | 84.1 | 84.5 | 53.2 | 77.6 | 77.2 | | 08 | Sq.-KNN | 86.7 | 14.4 | 24.6 | 21.0 | 23.3 | 23.5 | 40.9 | n/a | 90.1 | 32.4 | 74.8 | 1.2 | 79.6 | 42.7 | 79.2 | 36.5 | 71.1 | 28.3 | 24.8 | 44.1 | | | S-CSM | 90.5 | 23.0 | 34.9 | 26.8 | 29.1 | 32.4 | 49.4 | n/a | 92.6 | 38.7 | 79.0 | 1.1 | 84.6 | 51.6 | 83.3 | 48.3 | 72.9 | 44.1 | 31.6 | 50.8 | | | S-BKI | 92.3 | 30.0 | 39.7 | 29.3 | 32.1 | 38.8 | 54.7 | n/a | 92.9 | 40.9 | 79.9 | 1.1 | 86.6 | 54.6 | 84.9 | 52.3 | 74.2 | 47.9 | 34.7 | 53.7 | | 09 | Sq.-KNN | 89.2 | 5.3 | 48.0 | 79.8 | 61.3 | 37.3 | n/a | n/a | 91.0 | 59.0 | 79.9 | 38.9 | 80.9 | 62.9 | 77.0 | 32.3 | 61.7 | 31.8 | 52.6 | 58.2 | | | S-CSM | 93.9 | 12.2 | 71.9 | 85.6 | 71.6 | 47.5 | n/a | n/a | 91.8 | 67.0 | 83.1 | 23.4 | 88.9 | 65.7 | 82.6 | 42.9 | 64.9 | 52.4 | 53.0 | 64.6 | | | S-BKI | 96.0 | 22.8 | 80.2 | 90.5 | 79.7 | 60.7 | n/a | n/a | 91.7 | 70.0 | 83.8 | 30.7 | 90.8 | 69.1 | 84.0 | 46.3 | 66.0 | 59.1 | 58.2 | 69.4 | 10 | Sq.-KNN | 84.0 | 8.1 | 36.2 | 49.3 | 10.2 | 40.9 | n/a | n/a | 89.4 | 59.6 | 78.5 | 42.7 | 76.7 | 64.2 | 77.6 | 29.0 | 67.8 | 30.7 | 47.9 | 52.0 | | | S-CSM | 91.0 | 14.6 | 51.8 | 67.7 | 16.6 | 52.8 | n/a | n/a | 92.1 | 69.7 | 83.7 | 51.3 | 81.7 | 70.0 | 82.2 | 43.3 | 72.4 | 51.7 | 64.1 | 62.1 | | | S-BKI | 93.8 | 24.6 | 60.3 | 76.2 | 21.2 | 65.0 | n/a | n/a | 92.3 | 73.4 | 84.8 | 54.5 | 83.0 | 71.2 | 83.4 | 47.3 | 73.4 | 56.2 | 67.9 | 66.4 | | Average | Sq.-KNN | 87.9 | 14.4 | 43.0 | 61.5 | 57.5 | 32.3 | 55.2 | 63.1 | 92.4 | 59.1 | 80.7 | 43.9 | 77.5 | 61.7 | 76.9 | 34.7 | 71.5 | 32.4 | 47.2 | 57.6 | | | S-CSM | 92.5 | 21.7 | 58.7 | 68.8 | 66.8 | 42.9 | 74.1 | 67.4 | 94.1 | 67.7 | 84.5 | 46.6 | 82.3 | 67.5 | 81.6 | 47.8 | 75.2 | 50.2 | 62.0 | 65.9 | | | S-BKI | 93.4 | 29.2 | 65.8 | 75.4 | 72.9 | 93.0 | 80.7 | 73.7 | 93.7 | 72.3 | 83.8 | 49.0 | 84.1 | 68.7 | 83.0 | 53.7 | 75.8 | 54.0 | 67.1 | 72.1 |

Quantitative results on SemanticKITTI dataset sequence 00-10 for 19 semantic classes. Darknet53-kNN (Da-kNN)

| Sequence | Method | Car | Bicycle | Motorcycle | Truck | Other Vehicle | Person | Bicyclist | Motorcyclist | Road | Parking | Sidewalk | Other Ground | Building | Fence | Vegetation | Trunk | Terrain | Pole | Traffic Sign | Average | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 00 | Da-kNN | 0.960| 0.418 | 0.828 | 0.928 | 0.902 | 0.703 | 0.726 | 0.573 | 0.971 | 0.874 | 0.939 | 0.311 | 0.967 | 0.817 | 0.930 | 0.792 | 0.906 | 0.733 | 0.852 | 0.796 | | | S-CSM | 0.975 | 0.476 | 0.897 | 0.957 | 0.937 | 0.787 | 0.829 | 0.640 | 0.974 | 0.891 | 0.949 | 0.419 | 0.977 | 0.852 | 0.948 | 0.864 | 0.924 | 0.832 | 0.897 | 0.843 | | | S-BKI | 0.980 | 0.509 | 0.917 | 0.972 | 0.955 | 0.830 | 0.865 | 0.790 | 0.971 | 0.888 | 0.943 | 0.426 | 0.980 | 0.855 | 0.953 | 0.878 | 0.928 | 0.847 | 0.900 | 0.862 | | 01 | Da-kNN | 0.860 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.582 | 0.956 | 0.000 | 0.000 | 0.832 | 0.924 | 0.793 | 0.873 | 0.557 | 0.863 | 0.606 | 0.887 | 0.460 | | | S-CSM | 0.870 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.534 | 0.962 | 0.000 | 0.000 | 0.843 | 0.929 | 0.806 | 0.880 | 0.600 | 0.874 | 0.694 | 0.922 | 0.469 | | | S-BKI | 0.889 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.586 | 0.963 | 0.000 | 0.000 | 0.849 | 0.959 | 0.825 | 0.895 | 0.691 | 0.883 | 0.747 | 0.942 | 0.486 | | 02 | Da-kNN | 0.952 | 0.292 | 0.819 | 0.000 | 0.877 | 0.698 | 0.023 | 0.754 | 0.968 | 0.887 | 0.924 | 0.755 | 0.927 | 0.852 | 0.934 | 0.753 | 0.880 | 0.637 | 0.738 | 0.720 | | | S-CSM | 0.961 | 0.339 | 0.859 | 0.000 | 0.908 | 0.798 | 0.020 | 0.754 | 0.966 | 0.894 | 0.924 | 0.780 | 0.942 | 0.861 | 0.943 | 0.824 | 0.895 | 0.723 | 0.807 | 0.747 | | | S-BKI | 0.970 | 0.398 | 0.896 | 0.000 | 0.936 | 0.855 | 0.015 | 0.858 | 0.963 | 0.897 | 0.922 | 0.806 | 0.952 | 0.863 | 0.948 | 0.845 | 0.902 | 0.748 | 0.839 | 0.769 | | 03 | Da-kNN | 0.943 | 0.393 | 0.000 | 0.712 | 0.889 | 0.473 | 0.000 | 0.000 | 0.971 | 0.828 | 0.935 | 0.000 | 0.930 | 0.880 | 0.951 | 0.645 | 0.922 | 0.722 | 0.782 | 0.630 | | | S-CSM | 0.957 | 0.525 | 0.000 | 0.685 | 0.903 | 0.496 | 0.000 | 0.000 | 0.973 | 0.852 | 0.942 | 0.000 | 0.947 | 0.895 | 0.961 | 0.709 | 0.935 | 0.802 | 0.827 | 0.653 | | | S-BKI | 0.970 | 0.684 | 0.000 | 0.705 | 0.939 | 0.618 | 0.000 | 0.000 | 0.971 | 0.871 | 0.937 | 0.000 | 0.955 | 0.894 | 0.964 | 0.724 | 0.938 | 0.820 | 0.837 | 0.675 | |