LiDAR-based Panoptic Segmentation on SemanticKITTI 1.0 (test) benchmark leaderboard · SOTA2 Research

LiDAR-based Panoptic Segmentation on SemanticKITTI 1.0 (test)

64.2PQP-RangeFormer

Evaluation Results

Method	Links
P-RangeFormer2023.03		64.2	69.5	75.9	83.8	63.6	73	86.8	64.6	78.1	81.7	72
P-RangeFormer2023.03		61.8	67.6	73.8	83.1	60.3	69.6	86.3	62.9	76.8	80.8	71
P-PHNet2023.03		61.5	67.9	72.1	84.8	63.8	70.4	90.7	59.9	73.3	80.5	66
EfficientLPS2023.03		57.4	63.2	68.7	83	53.1	60.5	87.8	60.5	74.6	79.5	61.4
DS-Net2022.03		55.9	62.5	66.7	82.3	55.1	62.8	87.2	56.5	69.5	78.7	61.6
DS-Net2023.03		55.9	62.5	66.7	82.3	55.1	62.8	87.2	56.5	69.5	78.7	61.6
Panoptic-PolarNet2022.03		54.1	60.7	65	81.4	53.3	60.6	87.2	54.8	68.1	77.2	59.5
P-PolarNet2023.03		54.1	60.7	65	81.4	53.3	60.6	87.2	54.8	68.1	77.2	59.5
MaskRange2023.03		53.1	59.2	64.6	81.2	44.9	53	83.5	59.1	73.1	79.5	61.8
PanosterK2022.03		52.7	59.9	64.1	80.7	49.4	58.5	83.3	55.1	68.2	78.8	59.9
Panoster2023.03		52.7	59.9	64.1	80.7	49.4	58.5	83.3	55.1	68.2	78.8	59.9
4D-PLS2022.03		50.3	57.8	61	81.6	—	—	—	—	—	—	61.3
KPConv + PV-RCNN2022.03		50.2	57.5	61.4	80	43.2	51.4	80.2	55.9	68.7	79.9	62.8
KPConv + PointPillars2022.03		44.5	52.5	54.4	80	32.7	38.7	81.5	53.1	65.9	79	58.8
KPConv + PointPillars2023.03		44.5	52.5	54.4	80	32.7	38.7	81.5	53.1	65.9	79	58.8
LPASD2022.03		38	47	48.2	76.5	25.6	31.8	76.8	47.1	60.1	76.2	50.9
RangeNet++ + PointPillars2022.03		37.1	45.9	47	75.9	20.2	25.2	75.2	49.3	62.8	76.5	52.4
RangeNet++ + PointPillars2023.03		37.1	45.9	47	75.9	20.2	25.2	75.2	49.3	62.8	76.5	52.4