CG-SSD

Corner Guided Single Stage 3D Object Detector from LiDAR Point Cloud

Ruiqi Ma, Chi Chen, Bisheng Yang, Deren Li, Haiping Wang, Yangzi Cong, Zongtian Hu

State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University Engineering Research Center of Space-Time Data Capturing and Smart Application, the Ministry of Education of P.R.C., China

This is the official implementation for "Corner Guided Single Stage 3D Object Detector from LiDAR Point Cloud".

Please refer ONCE_Benchmark for installation.

train model

python tools/train.py --cfg_file tools/cfgs/once_models/sup_models/cgssd.yaml

CG-SSD

1. Result on ONCE testing set

   Model	AP@50			mAP
   	Vehicle	Pedestrian	Cyclist
   PointRCNN	52.00	8.73	34.02	31.58
   PointPillar	69.52	17.28	49.63	45.47
   SECOND	69.71	26.09	59.92	51.90
   PV-RCNN	76.98	22.66	61.93	53.85
   CenterPoint	66.35	51.80	65.57	61.24
   CG-SSD	68.00	52.81	67.50	62.77

2. Result on ONCE Validation Set

   Model	Vehicle(AP@50)				Pedestrian(AP@50)				Cyclist(AP@50)				mAP
   	overall	0-30m	30-50m	50m-inf	overall	0-30m	30-50m	50m-inf	overall	0-30m	30-50m	50m-inf
   PointRCNN	52.09	74.45	40.89	16.81	4.28	6.17	2.40	0.91	29.84	46.03	20.94	5.46	28.74
   PointPillars	68.57	80.86	62.07	47.04	17.63	19.74	15.15	10.23	46.81	58.33	40.32	25.86	44.34
   SECOND	71.19	84.04	63.02	47.25	26.44	29.33	24.05	18.05	58.04	69.96	52.43	34.61	51.89
   PV-RCNN	77.77	89.39	72.55	58.64	23.50	25.61	22.84	17.27	59.37	71.66	52.58	36.17	53.55
   CenterPoint	66.79	80.10	59.55	43.39	49.90	56.24	42.61	26.27	63.45	74.28	57.94	41.48	60.05
   CG-SSD	67.60	80.22	61.23	44.77	51.50	58.72	43.36	27.76	65.79	76.27	60.84	43.35	61.63

PLGU-IN

1. Result on ONCE validation set

   Model	AP@50			mAP
   	Vehicle	Pedestrian	Cyclist
   PointPillars	68.57	17.63	46.81	44.34
   PointPillars +auxiliary module	70.45 (+1.88)	18.97 (+1.34)	53.71 (+6.9)	47.71 (+3.37)
   SECOND	71.19	26.44	58.04	51.89
   SECOND +auxiliary module	71.10 (-0.09)	38.27 (+11.83)	61.89 (+3.85)	57.09 (+5.2)
   PV-RCNN	77.77	23.50	59.37	53.55
   PV-RCNN +auxiliary module	79.20 (+1.43)	37.19 (+13.69)	65.39 (+6.02)	60.60 (+7.05)

2. Result on Waymo validation set

   Model	Vehicle/APH		Pedestrian/APH		Cyclist/APH
   	L1	L2	L1	L2	L1	L2
   PointPillars	69.83	61.64	46.32	40.64	51.75	49.80
   PointPillars +auxiliary module	71.87 (+2.04)	63.93 (+2.29)	60.55 (+14.23)	53.57 (+12.93)	63.86 (+12.11)	61.51 (+11.71)
   SECOND	70.34	62.02	54.24	47.49	55.62	53.53
   SECOND +auxiliary module	71.65 (+1.31)	63.78 (+1.76)	58.01 (+3.77)	51.03 (+3.54)	63.31 (+7.69)	61.01 (+7.48)
   PV-RCNN	74.74	66.80	61.24	53.95	64.25	61.82
   PV-RCNN +auxiliary module	76.53 (+1.79)	67.97 (+1.17)	66.62 (+5.38)	58.36 (+4.41)	69.63 (+5.38)	67.12 (+5.3)

Citation

If the paper is useful for your research, please consider cite:

@article{MA202233, title = {CG-SSD: Corner guided single stage 3D object detection from LiDAR point cloud}, journal = {ISPRS Journal of Photogrammetry and Remote Sensing}, volume = {191}, pages = {33-48}, year = {2022}, issn = {0924-2716}, doi = {https://doi.org/10.1016/j.isprsjprs.2022.07.006}, url = {https://www.sciencedirect.com/science/article/pii/S0924271622001769}, author = {Ruiqi Ma and Chi Chen and Bisheng Yang and Deren Li and Haiping Wang and Yangzi Cong and Zongtian Hu} }