3D Object Detection on V2X-Real Gaussian Pose Noise σ = 0.4 (test) benchmark leaderboard · SOTA2 Research

3D Object Detection on V2X-Real Gaussian Pose Noise σ = 0.4 (test)

84.27AP@0.3 (Vehicle)HyDRA w AG-PGO

Evaluation Results

Method	Links
HyDRA w AG-PGO2026.03		84.27	16.62	51.89	50.93	71.16	3.61	42.35	39.04	29.17	0.07	35.69	21.64
HyDRA w AG-PGO2026.03		84.27	16.62	51.89	50.93	71.16	3.61	42.35	39.04	29.17	0.07	35.69	21.64
E2E Training2026.03		83.9	9.51	52.13	48.51	72.57	1.53	45.97	40.02	25.8	0.01	22.5	16.1
E2E Training2026.03		83.9	9.51	52.13	48.51	72.57	1.53	45.97	40.02	25.8	0.01	22.5	16.1
HEAL2026.03		83.76	11.65	53.27	49.65	73.12	1.94	37.01	37.36	31.07	0.01	17.51	16.2
HEAL2026.03		83.76	11.65	53.27	49.65	73.12	1.94	37.01	37.36	31.07	0.01	17.51	16.2
HyDRA w CoAlign2026.03		82.06	12.63	50.16	48.28	66.57	2.44	36.31	35.11	18.24	0.04	21.81	13.36
HyDRA w CoAlign2026.03		82.06	12.63	50.16	48.28	66.57	2.44	36.31	35.11	18.24	0.04	21.81	13.36
MPDA2026.03		80.96	15.36	54.12	50.14	75.33	3.06	51.46	43.28	41.15	0.07	34.12	25.11
MPDA2026.03		80.96	15.36	54.12	50.14	75.33	3.06	51.46	43.28	41.15	0.07	34.12	25.11
GenComm2026.03		80.6	11.04	50.9	47.51	74.71	2.13	46.81	41.22	34.75	0.02	28.13	20.97
GenComm2026.03		80.6	11.04	50.9	47.51	74.71	2.13	46.81	41.22	34.75	0.02	28.13	20.97
CodeFilling2026.03		75.9	10.88	49.41	45.4	64.58	1.96	42.84	36.46	21.42	0.02	15.61	12.35
CodeFilling2026.03		75.9	10.88	49.41	45.4	64.58	1.96	42.84	36.46	21.42	0.02	15.61	12.35
Late Fusion2026.03		52.44	23.9	37.19	37.84	35.68	10.84	19.11	21.88	6.91	0.46	6.85	4.74
Late Fusion2026.03		52.44	23.9	37.19	37.84	35.68	10.84	19.11	21.88	6.91	0.46	6.85	4.74