3D Object Detection on View-of-Delft (VoD) In Driving Corridor (val)

90.62AP3D (Car)R4Det

Evaluation results

Method
R4Det2026.03	90.62	66.47	93.96	—	—	83.68
CVFusion2026.03	89.86	68.79	88.62	—	—	82.42
SDCM2026.01	89.07	67.04	89.24	—	—	81.78
Li et al.2026.01	88.86	62.43	87.07	—	—	79.45
HGSFusion2024.12	88.28	62.61	87.49	79.46	—	—
HSGFusion2026.01	87.24	58.66	87.49	—	—	77.79
SGDet3D2026.01	81.13	60.91	90.22	—	—	77.42
SGDet3D2026.02	81.13	60.91	90.22	—	—	77.42
SGDet3D2026.03	81.13	60.91	90.22	—	—	77.42
ZFusion2026.01	80.44	52.68	90.01	—	—	74.38
IS-Fusion2026.01	80.42	55.5	88.33	—	—	74.75
TL-4DRCF2024.12	79.49	53.76	76.5	69.92	—	—
TL-4DRCF2026.01	79.49	53.76	76.5	—	—	69.92
SFGFusion2026.01	79.1	53.63	88.6	—	—	73.77
FUTR3D2024.12	78.66	43.1	86.19	69.32	—	—
FUTR3D2026.01	78.66	43.1	86.19	—	—	69.32
FUTR3D2026.02	78.66	43.1	86.19	—	—	69.32
FUTR3D2026.03	78.66	43.1	86.19	—	—	69.32
DSFusion2026.01	78.21	61.22	87.73	—	—	75.72
DRIFT (attention)2026.03	77	52.5	87.8	—	—	72.4
MAFF-Net2026.01	72.78	57.81	87.4	—	—	72.5
MUFASA2026.01	72.5	50.28	88.51	—	—	70.43
RCBEVDet2024.12	72.48	49.89	87.01	69.8	—	—
RCBEVDet2026.01	72.48	49.89	87.01	—	—	69.8
RCBEVDet2026.02	72.48	49.89	87.01	—	—	69.8
RCBEVDet2026.04	72.48	49.89	87.01	—	—	69.8
RCDFNet2026.01	72.46	49.76	89.62	—	—	70.61
DRIFT (attention)2026.03	72.4	52.9	89.3	—	—	71.5
Wang et al.2026.01	72.35	54.1	88.78	—	—	71.74
MMF-BEV2026.04	72.21	48.23	87.2	—	—	69.21
LXL2024.12	72.18	58.3	88.31	72.93	—	—
LXL2026.01	72.18	58.3	88.31	—	—	72.93
LXL2026.02	72.18	58.3	88.31	—	—	72.93
LXL2026.03	72.18	58.3	88.31	—	—	72.93
UniBEVFusion2026.01	72.1	57.71	93.29	—	—	74.37
SD4R2026.02	71.96	52.32	86.1	—	—	70.13
MUFASA2026.03	71.9	47.4	89	—	—	69.4
RCFusion2023.07	71.87	47.5	88.33	69.23	—	—
RCFusion2024.12	71.87	47.5	88.33	69.23	—	—
Duan et al.2026.01	71.87	49.45	86.43	—	—	69.25
RCFusion2026.01	71.87	47.5	88.33	—	—	69.23
RCFusion2026.02	71.87	47.5	88.33	—	—	69.23
RCFusion2026.03	71.87	47.5	88.33	—	—	69.23
RCFusion2026.04	71.87	47.5	88.33	—	—	69.23
SMURF2023.07	71.74	50.54	86.87	69.72	72.05	—
SMURF2026.01	71.74	50.54	86.87	—	—	69.72
SMURF2026.02	71.74	50.54	86.87	—	—	69.72
SMURF2026.03	71.74	50.54	86.87	—	—	69.72
SMURF2026.03	71.7	50.5	86.9	—	—	69.7
RadarPillarNet2024.12	71.65	42.8	83.14	65.86	—	—
RadarPillarNet2026.01	71.65	42.8	83.14	—	—	65.86
RadarPillarNet2026.02	71.65	42.8	83.14	—	—	65.86
RadarPillarNet2026.03	71.65	42.8	83.14	—	—	65.86
CenterPoint2026.03	71.3	47.3	83.7	—	—	67.4
RadarPillars2026.03	71.1	52.3	87.9	—	—	70.5
PointAugmenting2026.01	71.02	48.59	87.57	—	—	69.06
PointAugmenting2026.02	71.02	48.59	87.57	—	—	69.06
MMF-BEV2026.04	70.36	39.23	87.27	—	—	65.62
CenterPoint2026.03	70.3	45.7	83.1	—	—	66.4
LXL-R2026.02	70.26	47.34	87.93	—	—	68.51
BEVFusion2024.12	70.21	45.86	89.48	68.52	—	—
BEVFusion2026.01	70.21	45.86	89.48	—	—	68.52
BEVFusion2026.02	70.21	45.86	89.48	—	—	68.52
BEVFusion2026.03	70.21	45.86	89.48	—	—	68.52
PointPillars2026.03	70.2	47.2	85.1	—	—	67.5
PointPillars2024.12	70.15	47.22	85.07	67.48	—	—
PointPillars2026.01	70.15	47.22	85.07	—	—	67.48
PointPillars2026.02	70.15	47.22	85.07	—	—	67.48
PointPillars2026.03	70.15	47.22	85.07	—	—	67.48
PointPillars2026.04	70.15	47.22	85.07	—	—	67.48
MVFAN (single scan)2026.03	69.8	38.7	84.9	—	—	64.4
Ruddat et al.2026.01	69.1	47.2	84.3	—	—	66.9
MMF-BEV2026.04	67.21	44.48	78.65	—	—	63.44
PillarNeXt2026.02	66.72	39.03	85.08	—	—	63.61
PillarNeXt2026.03	66.7	39	85.1	—	—	63.6
CenterPoint2026.01	62.01	48.18	84.98	—	—	65.06
CenterPoint2026.02	62.01	48.18	84.98	—	—	65.06
CenterPoint2026.03	62.01	48.18	84.98	—	—	65.06
CenterPoint2026.03	62	48.2	85.5	—	—	65.1
MMF-BEV2026.04	55.01	15.78	43.67	—	—	38.15
ImVoxelNet2026.02	49.52	9.68	28.97	—	—	29.39
HGSFusion2026.01	—	—	—	—	—	77.79
IS-Fusion2026.01	—	—	—	—	—	74.75
RCDFNet2026.01	—	—	—	—	—	70.61
SDCM2026.01	—	—	—	—	—	81.78
SFGFusion2026.01	—	—	—	—	—	73.77
SGDet3D2026.01	—	—	—	—	—	77.42
ZFusion2026.01	—	—	—	—	—	74.38