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3D Reconstruction on ShapeNet

85.8mIoU (Car)

2D-3D self-consistency framework

Updated 3d ago

Evaluation Results

Method	Links
2D-3D self-consistency framework 2018.11		85.8	-	69.2	-	-	-	56.7	-	-	-	-	-	70.6	-
Matryoshka 2018.11		85	-	64.7	-	-	-	54.7	-	-	-	-	-	68.1	-
R2N2 2017.05		83.38	96.31	54.25	77.47	67.84	85.82	51.74	72.66	55.89	77.54	49.5	69.82	62.1	81.23
PSGN 2018.11		83.1	-	60.1	-	-	-	54.4	-	-	-	-	-	65.9	-
voxel tube 2018.11		82.1	-	67.1	-	-	-	55	-	-	-	-	-	68.1	-
OGN 2018.11		81.6	-	58.7	-	-	-	48.3	-	-	-	-	-	62.9	-
3D-R2N2 2018.11		79.8	-	51.3	-	-	-	46.6	-	-	-	-	-	59.2	-
RP+NN 2017.05		67.44	65.08	46.71	41.87	54.67	50.79	34.49	28.29	30.81	25.01	31.16	24.77	44.65	39.85
PTN 2017.05		65.93	85.04	44.22	67.21	51.88	71.8	37.36	50.81	35.56	53.67	33.74	47.25	45.72	64.09
RP 2017.05		65.21	87.13	43.44	66.94	52.42	70.23	37.17	50.48	31.97	44.64	32.1	43.77	44.42	61.23
McRecon 2017.05		61.42	86.74	45.23	68.77	54.58	74.73	43.65	62.12	42.04	57.41	40.09	57.7	48.49	68.51
VC 2017.05		57.84	54.3	34.52	29.36	52.57	49.41	40.48	35.09	35.49	30.11	33.87	27.88	43.36	38.57
McRecon 2017.05		56.22	82.44	37.27	59.11	37.91	55.97	35.03	48.28	35.32	45.82	29.53	39.12	40.36	57.29
RP+NN 2017.05		54.51	55.82	20.57	15.6	27.67	22.85	15.56	10.56	12.85	8.72	17.58	11.83	25.97	22.67
PTN 2017.05		44.37	77.25	33.52	55.68	33.09	49.47	22.41	31.78	19.77	28	21.45	28.84	29.31	46.2
RP 2017.05		37.91	72.5	25.08	49.97	34.27	50.93	19.3	33.61	18.21	26.64	21.88	30.03	25.77	44.52
VC 2017.05		26.05	24.02	10.92	8.06	26.27	24.51	20.35	18.52	17.35	15.46	13.03	10.64	19.86	17.81