High-res multi-view results

This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

Accuracy [%]: The fraction of the reconstruction which is closer to the ground truth than the evaluation threshold distance (*). Larger is better.
Completeness [%]: The fraction of the ground truth which is closer to the reconstruction than the evaluation threshold distance (*). Larger is better.
F₁ score [%]: The harmonic mean of accuracy and completeness, used to rank methods based on both metrics. Larger is better.
Time [s]: The runtime of the method. Smaller is better.

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.

Method	all	high-res multi-view	indoor	outdoor	botani.	boulde.	bridge	door	exhibi.	lectur.	living.	lounge	observ.	old co.	statue	terrac.

LCM-MVSNet		86.90 1	88.67 1	81.57 20	91.50 1	63.30 103	84.80 24	87.77 7	86.18 1	96.26 2	96.06 2	90.32 1	84.49 47	68.08 80	97.05 3	96.93 1

TDRefinement		86.32 2	86.33 2	86.29 1	88.64 28	81.19 6	88.84 2	90.72 1	78.27 7	87.95 17	92.53 13	79.37 12	84.79 44	74.51 34	96.15 4	92.88 9

abl_6		84.92 3	85.70 3	82.57 14	86.72 39	79.27 8	87.56 5	86.08 16	77.48 9	88.12 16	91.53 30	81.18 6	84.31 52	78.12 21	94.47 35	84.15 112

HPM-MVS_fast		84.59 4	85.10 4	83.06 4	88.60 29	75.83 23	86.27 19	86.89 11	73.69 18	86.17 39	91.70 25	78.23 16	85.20 37	79.45 11	94.91 26	88.15 61

ACMMP		84.22 5	84.84 6	82.35 17	89.23 22	76.66 22	87.65 4	85.89 18	71.03 30	85.85 45	90.58 50	78.77 14	85.78 27	79.37 14	95.17 18	84.62 99
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
LTVRE_ROB	75.46 1	84.22 5	84.98 5	81.94 19	84.82 59	75.40 26	91.60 1	87.80 5	73.52 19	88.90 13	93.06 7	71.39 58	81.53 89	81.53 3	92.15 67	88.91 47
Andreas Kuhn, Heiko HirschmÃ¼ller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
HPM-MVS		84.12 7	84.63 7	82.60 12	88.21 32	74.40 31	85.24 22	87.21 9	70.69 33	85.14 53	90.42 58	78.99 13	86.62 9	80.83 6	94.93 25	86.79 72

CP-MVS		84.12 7	84.55 8	82.80 9	89.42 18	79.74 7	88.19 3	84.43 37	71.96 27	84.70 60	90.56 51	77.12 18	86.18 18	79.24 16	95.36 14	82.49 145

mPP-MVS		84.01 9	84.39 9	82.88 5	90.65 4	81.38 5	87.08 9	82.79 65	72.41 23	85.11 55	90.85 43	76.65 21	84.89 41	79.30 15	94.63 32	82.35 147

COLMAP_ROB	72.78 3	83.75 10	84.11 13	82.68 11	82.97 85	74.39 32	87.18 7	88.18 4	78.98 5	86.11 41	91.47 32	79.70 11	85.76 28	66.91 96	95.46 13	87.89 63
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ACMMPR		83.62 11	83.93 15	82.69 10	89.78 11	77.51 18	87.01 11	84.19 44	70.23 34	84.49 62	90.67 49	75.15 32	86.37 12	79.58 9	94.26 42	84.18 111

APD-MVS_3200maxsize		83.57 12	84.33 10	81.31 26	82.83 87	73.53 40	85.50 21	87.45 8	74.11 16	86.45 35	90.52 54	80.02 10	84.48 48	77.73 23	94.34 39	85.93 81

region2R		83.54 13	83.86 17	82.58 13	89.82 10	77.53 16	87.06 10	84.23 43	70.19 36	83.86 67	90.72 48	75.20 30	86.27 15	79.41 13	94.25 43	83.95 115

XVS		83.51 14	83.73 18	82.85 7	89.43 16	77.61 14	86.80 13	84.66 32	72.71 21	82.87 74	90.39 60	73.86 42	86.31 13	78.84 17	94.03 46	84.64 97

LPG-MVS_test		83.47 15	84.33 10	80.90 32	87.00 36	70.41 56	82.04 41	86.35 12	69.77 38	87.75 18	91.13 35	81.83 3	86.20 16	77.13 26	95.96 7	86.08 77

HFP-MVS		83.39 16	84.03 14	81.48 22	89.25 20	75.69 24	87.01 11	84.27 40	70.23 34	84.47 63	90.43 55	76.79 19	85.94 24	79.58 9	94.23 44	82.82 136

MTAPA		83.19 17	83.87 16	81.13 29	91.16 2	78.16 12	84.87 23	80.63 106	72.08 24	84.93 56	90.79 44	74.65 36	84.42 49	80.98 4	94.75 28	80.82 175

MP-MVS		83.19 17	83.54 21	82.14 18	90.54 5	79.00 9	86.42 18	83.59 54	71.31 28	81.26 93	90.96 40	74.57 38	84.69 45	78.41 19	94.78 27	82.74 139

PGM-MVS		83.07 19	83.25 26	82.54 15	89.57 14	77.21 20	82.04 41	85.40 23	67.96 45	84.91 58	90.88 41	75.59 27	86.57 10	78.16 20	94.71 30	83.82 116

SteuartSystems-ACMMP		83.07 19	83.64 19	81.35 25	85.14 55	71.00 50	85.53 20	84.78 30	70.91 31	85.64 46	90.41 59	75.55 28	87.69 3	79.75 7	95.08 21	85.36 88
Skip Steuart: Steuart Systems R&D Blog.
MPTG		83.01 21	83.63 20	81.13 29	91.16 2	78.16 12	82.72 37	80.63 106	72.08 24	84.93 56	90.79 44	74.65 36	84.42 49	80.98 4	94.75 28	80.82 175

APDe-MVS		82.88 22	84.14 12	79.08 49	84.80 61	66.72 77	86.54 16	85.11 26	72.00 26	86.65 33	91.75 24	78.20 17	87.04 7	77.93 22	94.32 40	83.47 123

ACMP	69.50 8	82.64 23	83.38 23	80.40 36	86.50 41	69.44 62	82.30 38	86.08 16	66.80 50	86.70 32	89.99 69	81.64 5	85.95 23	74.35 35	96.11 5	85.81 83
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
MP-MVS-pluss		82.54 24	83.46 22	79.76 40	88.88 27	68.44 70	81.57 44	86.33 14	63.17 90	85.38 52	91.26 34	76.33 22	84.67 46	83.30 1	94.96 24	86.17 76
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
#test#		82.40 25	82.71 31	81.48 22	89.25 20	75.69 24	84.47 26	84.27 40	64.45 74	84.47 63	90.43 55	76.79 19	85.94 24	76.01 30	94.23 44	82.82 136

ACMMP_Plus		82.33 26	83.28 25	79.46 45	89.28 19	69.09 68	83.62 31	84.98 27	64.77 71	83.97 66	91.02 38	75.53 29	85.93 26	82.00 2	94.36 38	83.35 129

ACMM	69.25 9	82.11 27	83.31 24	78.49 56	88.17 33	73.96 34	83.11 34	84.52 36	66.40 54	87.45 23	89.16 82	81.02 7	80.52 127	74.27 36	95.73 9	80.98 172
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PMVS	70.70 6	81.70 28	83.15 27	77.36 68	90.35 6	82.82 3	82.15 39	79.22 129	74.08 17	87.16 27	91.97 19	84.80 2	76.97 178	64.98 112	93.61 50	72.28 249
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
UA-Net		81.56 29	82.28 33	79.40 46	88.91 26	69.16 66	84.67 25	80.01 121	75.34 13	79.80 113	94.91 3	69.79 68	80.25 131	72.63 43	94.46 36	88.78 51

CPTT-MVS		81.51 30	81.76 35	80.76 34	89.20 23	78.75 10	86.48 17	82.03 74	68.80 41	80.92 101	88.52 94	72.00 53	82.39 77	74.80 31	93.04 56	81.14 168

ACMH+	66.64 10	81.20 31	82.48 32	77.35 69	81.16 107	62.39 107	80.51 49	87.80 5	73.02 20	87.57 21	91.08 37	80.28 9	82.44 76	64.82 113	96.10 6	87.21 70

APD-MVS		81.13 32	81.73 36	79.36 47	84.47 67	70.53 55	83.85 30	83.70 51	69.43 40	83.67 69	88.96 90	75.89 26	86.41 11	72.62 44	92.95 57	81.14 168
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
3Dnovator+	73.19 2	81.08 33	80.48 43	82.87 6	81.41 104	72.03 42	84.38 27	86.23 15	77.28 11	80.65 104	90.18 67	59.80 149	87.58 4	73.06 41	91.34 79	89.01 42

DeepC-MVS	72.44 4	81.00 34	80.83 42	81.50 21	86.70 40	70.03 60	82.06 40	87.00 10	59.89 118	80.91 102	90.53 52	72.19 49	88.56 1	73.67 39	94.52 34	85.92 82
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OPM-MVS		80.99 35	81.63 38	79.07 50	86.86 38	69.39 63	79.41 63	84.00 49	65.64 58	85.54 50	89.28 77	76.32 23	83.47 62	74.03 37	93.57 51	84.35 109

LS3D		80.99 35	80.85 41	81.41 24	78.37 135	71.37 46	87.45 6	85.87 19	77.48 9	81.98 81	89.95 70	69.14 71	85.26 34	66.15 103	91.24 81	87.61 66

XVG-ACMP-BASELINE		80.54 37	81.06 40	78.98 51	87.01 35	72.91 41	80.23 55	85.56 20	66.56 53	85.64 46	89.57 74	69.12 72	80.55 126	72.51 45	93.37 52	83.48 122

PEN-MVS		80.46 38	82.91 28	73.11 125	89.83 9	39.02 266	77.06 90	82.61 68	80.04 3	90.60 8	92.85 9	74.93 35	85.21 36	63.15 122	95.15 19	95.09 2

PS-CasMVS		80.41 39	82.86 30	73.07 126	89.93 7	39.21 263	77.15 88	81.28 90	79.74 4	90.87 6	92.73 11	75.03 34	84.93 40	63.83 119	95.19 17	95.07 3

DTE-MVSNet		80.35 40	82.89 29	72.74 136	89.84 8	37.34 280	77.16 87	81.81 78	80.45 2	90.92 5	92.95 8	74.57 38	86.12 22	63.65 120	94.68 31	94.76 6

SD-MVS		80.28 41	81.55 39	76.47 73	83.57 76	67.83 74	83.39 33	85.35 25	64.42 77	86.14 40	87.07 110	74.02 41	80.97 114	77.70 24	92.32 66	80.62 180

WR-MVS_H		80.22 42	82.17 34	74.39 95	89.46 15	42.69 242	78.24 75	82.24 71	78.21 8	89.57 11	92.10 18	68.05 82	85.59 29	66.04 105	95.62 11	94.88 5

HPM-MVS++		79.89 43	79.80 49	80.18 38	89.02 24	78.44 11	83.49 32	80.18 118	64.71 73	78.11 133	88.39 97	65.46 102	83.14 67	77.64 25	91.20 82	78.94 197

HSP-MVS		79.69 44	79.17 54	81.27 28	89.70 12	77.46 19	87.16 8	80.58 109	64.94 70	81.05 98	88.38 98	57.10 195	87.10 6	79.75 7	83.87 195	79.24 194

XVG-OURS-SEG-HR		79.62 45	79.99 47	78.49 56	86.46 42	74.79 30	77.15 88	85.39 24	66.73 51	80.39 108	88.85 92	74.43 40	78.33 165	74.73 33	85.79 163	82.35 147

XVG-OURS		79.51 46	79.82 48	78.58 55	86.11 44	74.96 29	76.33 100	84.95 28	66.89 47	82.75 76	88.99 88	66.82 92	78.37 164	74.80 31	90.76 96	82.40 146

CP-MVSNet		79.48 47	81.65 37	72.98 129	89.66 13	39.06 265	76.76 92	80.46 111	78.91 6	90.32 9	91.70 25	68.49 77	84.89 41	63.40 121	95.12 20	95.01 4

OMC-MVS		79.41 48	78.79 56	81.28 27	80.62 109	70.71 54	80.91 47	84.76 31	62.54 95	81.77 83	86.65 127	71.46 56	83.53 61	67.95 86	92.44 63	89.60 35

v7n		79.37 49	80.41 44	76.28 77	78.67 134	55.81 145	79.22 64	82.51 70	70.72 32	87.54 22	92.44 14	68.00 84	81.34 99	72.84 42	91.72 69	91.69 12

TSAR-MVS + MP.		79.05 50	78.81 55	79.74 41	88.94 25	67.52 75	86.61 15	81.38 89	51.71 205	77.15 140	91.42 33	65.49 101	87.20 5	79.44 12	87.17 151	84.51 104

v52		78.96 51	79.79 50	76.46 74	73.03 224	54.90 148	78.48 70	83.48 55	64.43 75	91.19 4	91.54 28	72.08 50	81.11 107	76.45 28	87.47 140	93.38 7

V4		78.96 51	79.79 50	76.46 74	73.02 225	54.90 148	78.48 70	83.47 56	64.43 75	91.20 3	91.54 28	72.08 50	81.11 107	76.45 28	87.46 142	93.38 7

mvs_tets		78.93 53	78.67 58	79.72 42	84.81 60	73.93 35	80.65 48	76.50 169	51.98 203	87.40 24	91.86 21	76.09 25	78.53 155	68.58 75	90.20 103	86.69 74

test_djsdf		78.88 54	78.27 61	80.70 35	81.42 103	71.24 48	83.98 28	75.72 174	52.27 198	87.37 25	92.25 16	68.04 83	80.56 124	72.28 49	91.15 83	90.32 33

HQP_MVS		78.77 55	78.78 57	78.72 53	85.18 53	65.18 88	82.74 35	85.49 21	65.45 60	78.23 131	89.11 84	60.83 140	86.15 19	71.09 53	90.94 88	84.82 94

anonymousdsp		78.60 56	77.80 65	81.00 31	78.01 140	74.34 33	80.09 56	76.12 170	50.51 221	89.19 12	90.88 41	71.45 57	77.78 173	73.38 40	90.60 98	90.90 27

OurMVSNet-221017-0		78.57 57	78.53 60	78.67 54	80.48 110	64.16 95	80.24 54	82.06 73	61.89 99	88.77 14	93.32 5	57.15 193	82.60 75	70.08 65	92.80 58	89.25 37

jajsoiax		78.51 58	78.16 62	79.59 44	84.65 63	73.83 37	80.42 51	76.12 170	51.33 210	87.19 26	91.51 31	73.79 44	78.44 159	68.27 78	90.13 107	86.49 75

CNVR-MVS		78.49 59	78.59 59	78.16 60	85.86 48	67.40 76	78.12 78	81.50 82	63.92 81	77.51 138	86.56 131	68.43 79	84.82 43	73.83 38	91.61 72	82.26 150

DeepPCF-MVS	71.07 5	78.48 60	77.14 70	82.52 16	84.39 71	77.04 21	76.35 98	84.05 47	56.66 148	80.27 109	85.31 152	68.56 76	87.03 8	67.39 91	91.26 80	83.50 121

DP-MVS		78.44 61	79.29 53	75.90 82	81.86 99	65.33 86	79.05 65	84.63 35	74.83 15	80.41 107	86.27 137	71.68 54	83.45 63	62.45 126	92.40 64	78.92 198

NCCC		78.25 62	78.04 63	78.89 52	85.61 50	69.45 61	79.80 60	80.99 103	65.77 57	75.55 163	86.25 139	67.42 87	85.42 30	70.10 64	90.88 94	81.81 159

test_0402		78.17 63	79.48 52	74.24 97	83.50 77	59.15 131	72.52 144	74.60 184	75.34 13	88.69 15	91.81 22	75.06 33	82.37 78	65.10 111	88.68 125	81.20 165

Anonymous20231211		77.74 64	80.26 45	70.19 167	83.05 82	43.39 236	75.86 110	76.74 168	75.91 12	85.92 43	96.14 1	80.85 8	75.59 193	53.58 186	94.27 41	91.58 13

AllTest		77.66 65	77.43 67	78.35 58	79.19 125	70.81 51	78.60 68	88.64 2	65.37 63	80.09 111	88.17 101	70.33 63	78.43 160	55.60 168	90.90 92	85.81 83

PS-MVSNAJss		77.54 66	77.35 68	78.13 62	84.88 58	66.37 80	78.55 69	79.59 126	53.48 189	86.29 38	92.43 15	62.39 122	80.25 131	67.90 87	90.61 97	87.77 64

ACMH	63.62 14	77.50 67	80.11 46	69.68 174	79.61 116	56.28 143	78.81 66	83.62 53	63.41 89	87.14 28	90.23 66	76.11 24	73.32 208	67.58 88	94.44 37	79.44 192
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CDPH-MVS		77.33 68	77.06 71	78.14 61	84.21 72	63.98 97	76.07 105	83.45 57	54.20 178	77.68 137	87.18 107	69.98 66	85.37 31	68.01 82	92.72 61	85.08 92

DeepC-MVS_fast	69.89 7	77.17 69	76.33 80	79.70 43	83.90 75	67.94 72	80.06 58	83.75 50	56.73 147	74.88 171	85.32 151	65.54 100	87.79 2	65.61 109	91.14 84	83.35 129
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
v748		76.93 70	77.95 64	73.87 102	73.94 198	52.44 164	75.90 108	79.98 122	65.34 65	86.97 30	91.77 23	67.40 88	78.40 162	70.23 62	90.01 108	90.76 31

X-MVStestdata		76.81 71	74.79 96	82.85 7	89.43 16	77.61 14	86.80 13	84.66 32	72.71 21	82.87 74	9.95 346	73.86 42	86.31 13	78.84 17	94.03 46	84.64 97

test_prior3		76.71 72	77.19 69	75.27 89	82.15 95	59.85 124	75.57 113	84.33 38	58.92 125	76.53 153	86.78 118	67.83 85	83.39 64	69.81 67	92.76 59	82.58 141

train_agg		76.38 73	76.55 75	75.86 83	85.47 51	69.32 64	76.42 96	78.69 140	54.00 182	76.97 141	86.74 121	66.60 93	81.10 109	72.50 46	91.56 73	77.15 213

agg_prior3		76.32 74	76.33 80	76.28 77	85.86 48	70.13 59	76.50 94	78.26 150	53.41 191	75.78 159	86.49 133	66.58 95	81.57 88	72.50 46	91.56 73	77.15 213

v13		76.23 75	77.02 72	73.86 104	74.61 184	48.80 183	76.91 91	81.10 97	62.66 93	87.02 29	91.01 39	59.76 150	81.41 94	71.29 52	88.78 124	91.38 14

TranMVSNet+NR-MVSNet		76.13 76	77.66 66	71.56 154	84.61 65	42.57 243	70.98 175	78.29 149	68.67 43	83.04 73	89.26 78	72.99 47	80.75 123	55.58 171	95.47 12	91.35 15

v12		76.03 77	76.79 73	73.76 106	74.45 186	48.60 189	76.59 93	81.11 94	62.22 98	86.79 31	90.74 47	59.51 151	81.40 96	71.01 55	88.67 126	91.29 16

agg_prior1		75.89 78	76.41 78	74.31 96	84.44 69	66.02 82	76.12 104	78.62 143	54.40 176	76.95 143	86.85 115	66.44 96	80.34 129	72.45 48	91.42 77	76.57 218

V9		75.82 79	76.53 76	73.66 107	74.28 190	48.37 190	76.26 101	81.10 97	61.73 101	86.59 34	90.43 55	59.16 157	81.42 93	70.71 58	88.56 127	91.21 19

SixPastTwentyTwo		75.77 80	76.34 79	74.06 100	81.69 101	54.84 150	76.47 95	75.49 176	64.10 80	87.73 20	92.24 17	50.45 223	81.30 101	67.41 90	91.46 76	86.04 79

v11		75.76 81	76.51 77	73.48 114	74.28 190	47.81 202	76.16 103	81.28 90	61.56 102	86.39 36	90.38 61	59.32 155	81.41 94	70.85 56	88.41 129	91.23 17

RPSCF		75.76 81	74.37 102	79.93 39	74.81 175	77.53 16	77.53 82	79.30 128	59.44 120	78.88 122	89.80 72	71.26 59	73.09 210	57.45 151	80.89 230	89.17 40

v10		75.69 83	76.20 83	74.16 98	74.44 188	48.69 185	75.84 111	82.93 64	59.02 124	85.92 43	89.17 81	58.56 166	82.74 73	70.73 57	89.14 120	91.05 21

V14		75.58 84	76.26 82	73.55 112	74.10 197	48.13 195	75.91 107	81.07 100	61.19 105	86.34 37	90.11 68	58.80 161	81.40 96	70.40 60	88.43 128	91.12 20

Effi-MVS+-dtu		75.43 85	72.28 142	84.91 2	77.05 149	83.58 2	78.47 72	77.70 157	57.68 132	74.89 170	78.13 237	64.80 107	84.26 53	56.46 161	85.32 178	86.88 71

v15		75.37 86	76.01 84	73.44 115	73.91 201	47.87 201	75.55 115	81.04 101	60.76 110	86.11 41	89.76 73	58.53 167	81.40 96	70.11 63	88.32 130	91.04 23

wuykxyi23d		75.33 87	76.75 74	71.04 157	78.83 132	85.01 1	71.78 160	61.00 256	53.47 190	96.33 1	93.38 4	73.07 45	68.04 259	65.65 108	97.28 2	60.07 317

Regformer-2		75.32 88	74.47 100	77.88 63	74.22 193	66.65 78	72.77 141	77.54 159	68.47 44	80.44 106	72.08 287	70.60 62	80.97 114	70.08 65	84.02 193	86.01 80

F-COLMAP		75.29 89	73.99 107	79.18 48	81.73 100	71.90 43	81.86 43	82.98 62	59.86 119	72.27 202	84.00 170	64.56 110	83.07 69	51.48 194	87.19 150	82.56 143

HQP-MVS		75.24 90	75.01 95	75.94 81	82.37 90	58.80 133	77.32 84	84.12 45	59.08 121	71.58 207	85.96 148	58.09 174	85.30 33	67.38 92	89.16 118	83.73 119

TAPA-MVS	65.27 12	75.16 91	74.29 104	77.77 65	74.86 174	68.08 71	77.89 79	84.04 48	55.15 161	76.19 158	83.39 175	66.91 90	80.11 135	60.04 137	90.14 106	85.13 90
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
IS-MVSNet		75.10 92	75.42 92	74.15 99	79.23 123	48.05 198	79.43 61	78.04 155	70.09 37	79.17 120	88.02 105	53.04 210	83.60 59	58.05 148	93.76 49	90.79 29

v8		75.07 93	75.64 88	73.35 117	73.42 207	47.46 211	75.20 120	81.45 85	60.05 116	85.64 46	89.26 78	58.08 176	81.80 86	69.71 69	87.97 136	90.79 29

v17		75.03 94	75.59 89	73.36 116	73.56 203	47.66 206	75.48 116	81.45 85	60.58 112	85.55 49	89.02 86	58.36 169	81.47 90	69.69 70	86.59 157	90.96 24

UniMVSNet (Re)		75.00 95	75.48 91	73.56 111	83.14 81	47.92 200	70.41 181	81.04 101	63.67 84	79.54 115	86.37 136	62.83 116	81.82 85	57.10 155	95.25 16	90.94 26

PHI-MVS		74.92 96	74.36 103	76.61 70	76.40 157	62.32 108	80.38 52	83.15 60	54.16 180	73.23 191	80.75 209	62.19 125	83.86 55	68.02 81	90.92 91	83.65 120

DU-MVS		74.91 97	75.57 90	72.93 131	83.50 77	45.79 228	69.47 191	80.14 119	65.22 66	81.74 85	87.08 108	61.82 128	81.07 111	56.21 164	94.98 22	91.93 10

UniMVSNet_NR-MVSNet		74.90 98	75.65 87	72.64 138	83.04 83	45.79 228	69.26 193	78.81 138	66.66 52	81.74 85	86.88 114	63.26 114	81.07 111	56.21 164	94.98 22	91.05 21

v16		74.89 99	75.41 93	73.35 117	73.54 204	47.62 207	75.47 117	81.45 85	60.58 112	85.46 51	88.97 89	58.27 170	81.47 90	69.66 71	85.25 179	90.95 25

nrg030		74.87 100	75.99 85	71.52 155	74.90 173	49.88 178	74.10 134	82.58 69	54.55 175	83.50 71	89.21 80	71.51 55	75.74 191	61.24 130	92.34 65	88.94 46

Vis-MVSNet		74.85 101	74.56 98	75.72 84	81.63 102	64.64 92	76.35 98	79.06 134	62.85 92	73.33 189	88.41 96	62.54 120	79.59 141	63.94 118	82.92 202	82.94 133
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Regformer-4		74.64 102	73.67 110	77.55 66	74.74 177	64.49 94	72.91 138	75.42 179	67.45 46	80.24 110	72.07 290	68.98 73	80.19 134	70.29 61	80.91 228	87.98 62

v18		74.60 103	75.06 94	73.22 122	73.29 213	47.36 215	75.02 121	81.47 84	60.01 117	85.13 54	88.44 95	57.93 184	81.47 90	69.26 72	85.02 183	90.84 28

MVS_0304		74.55 104	73.47 114	77.80 64	77.41 148	63.88 98	75.75 112	83.67 52	63.55 86	66.12 252	82.16 196	60.20 144	86.15 19	65.37 110	86.98 153	83.38 126

MSLP-MVS++		74.48 105	75.78 86	70.59 161	84.66 62	62.40 106	78.65 67	84.24 42	60.55 114	77.71 136	81.98 198	63.12 115	77.64 174	62.95 123	88.14 132	71.73 254

Regformer-1		74.28 106	73.63 112	76.21 80	74.22 193	64.12 96	72.77 141	75.46 178	66.86 49	79.27 118	72.08 287	69.29 70	78.74 151	68.73 74	84.02 193	85.77 86

AdaColmap		74.22 107	74.56 98	73.20 123	81.95 97	60.97 116	79.43 61	80.90 104	65.57 59	72.54 200	81.76 202	70.98 61	85.26 34	47.88 222	90.00 109	73.37 237

CSCG		74.12 108	74.39 101	73.33 119	79.35 120	61.66 113	77.45 83	81.98 75	62.47 97	79.06 121	80.19 215	61.83 127	78.79 150	59.83 139	87.35 145	79.54 191

PAPM_NR		73.91 109	74.16 105	73.16 124	81.90 98	53.50 159	81.28 45	81.40 88	66.17 55	73.30 190	83.31 180	59.96 145	83.10 68	58.45 147	81.66 218	82.87 134

EPP-MVSNet		73.86 110	73.38 117	75.31 88	78.19 137	53.35 161	80.45 50	77.32 163	65.11 68	76.47 155	86.80 116	49.47 225	83.77 56	53.89 183	92.72 61	88.81 50

mvs-test1		73.81 111	70.69 161	83.18 3	77.05 149	81.39 4	75.39 118	77.70 157	57.68 132	71.19 216	74.72 267	64.80 107	83.66 58	56.46 161	81.19 226	84.50 105

K. test v3		73.67 112	73.61 113	73.87 102	79.78 114	55.62 146	74.69 130	62.04 253	66.16 56	84.76 59	93.23 6	49.47 225	80.97 114	65.66 107	86.67 156	85.02 93

NR-MVSNet		73.62 113	74.05 106	72.33 147	83.50 77	43.71 235	65.65 240	77.32 163	64.32 78	75.59 162	87.08 108	62.45 121	81.34 99	54.90 174	95.63 10	91.93 10

v7		73.59 114	73.69 109	73.28 121	74.42 189	48.68 186	72.74 143	81.98 75	54.76 171	82.07 80	85.05 157	58.53 167	82.22 82	67.99 83	85.66 167	88.95 45

DP-MVS Recon		73.57 115	72.69 136	76.23 79	82.85 86	63.39 101	74.32 132	82.96 63	57.75 131	70.35 224	81.98 198	64.34 111	84.41 51	49.69 207	89.95 110	80.89 173

CNLPA		73.44 116	73.03 129	74.66 91	78.27 136	75.29 27	75.99 106	78.49 145	65.39 62	75.67 161	83.22 185	61.23 136	66.77 271	53.70 185	85.33 177	81.92 158

MCST-MVS		73.42 117	73.34 119	73.63 110	81.28 105	59.17 130	74.80 127	83.13 61	45.50 255	72.84 193	83.78 173	65.15 104	80.99 113	64.54 114	89.09 121	80.73 178

v1192		73.40 118	73.42 115	73.32 120	74.65 183	48.67 187	72.21 147	81.73 79	52.76 196	81.85 82	84.56 164	57.12 194	82.24 81	68.58 75	87.33 146	89.06 41

114514_t		73.40 118	73.33 120	73.64 109	84.15 74	57.11 140	78.20 76	80.02 120	43.76 268	72.55 199	86.07 146	64.00 112	83.35 66	60.14 136	91.03 87	80.45 183

FC-MVSNet-test		73.32 120	74.78 97	68.93 185	79.21 124	36.57 282	71.82 159	79.54 127	57.63 136	82.57 77	90.38 61	59.38 154	78.99 145	57.91 149	94.56 33	91.23 17

v1144		73.29 121	73.39 116	73.01 127	74.12 196	48.11 196	72.01 152	81.08 99	53.83 186	81.77 83	84.68 162	58.07 177	81.91 84	68.10 79	86.86 154	88.99 44

TSAR-MVS + GP.		73.08 122	71.60 151	77.54 67	78.99 131	70.73 53	74.96 122	69.38 223	60.73 111	74.39 178	78.44 234	57.72 187	82.78 72	60.16 135	89.60 113	79.11 196

v1240		73.06 123	73.14 122	72.84 133	74.74 177	47.27 217	71.88 158	81.11 94	51.80 204	82.28 79	84.21 167	56.22 201	82.34 79	68.82 73	87.17 151	88.91 47

IterMVS-LS		73.01 124	73.12 124	72.66 137	73.79 202	49.90 175	71.63 162	78.44 146	58.22 128	80.51 105	86.63 128	58.15 173	79.62 139	62.51 124	88.20 131	88.48 59
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CANet		73.00 125	71.84 146	76.48 72	75.82 165	61.28 114	74.81 125	80.37 113	63.17 90	62.43 269	80.50 212	61.10 138	85.16 39	64.00 117	84.34 189	83.01 132

v144192		72.99 126	73.06 128	72.77 134	74.58 185	47.48 209	71.90 157	80.44 112	51.57 207	81.46 92	84.11 169	58.04 178	82.12 83	67.98 84	87.47 140	88.70 52

MVS_111021_HR		72.98 127	72.97 131	72.99 128	80.82 108	65.47 85	68.81 198	72.77 194	57.67 134	75.76 160	82.38 193	71.01 60	77.17 176	61.38 129	86.15 159	76.32 219

v1921920		72.96 128	72.98 130	72.89 132	74.67 180	47.58 208	71.92 156	80.69 105	51.70 206	81.69 87	83.89 171	56.58 199	82.25 80	68.34 77	87.36 144	88.82 49

v1neww		72.93 129	73.07 126	72.48 141	73.41 209	47.46 211	72.17 148	80.26 115	55.63 154	81.63 89	85.07 155	57.97 180	81.28 102	66.55 101	84.98 185	88.70 52

v7new		72.93 129	73.07 126	72.48 141	73.41 209	47.46 211	72.17 148	80.26 115	55.63 154	81.63 89	85.07 155	57.97 180	81.28 102	66.55 101	84.98 185	88.70 52

v6		72.93 129	73.08 125	72.48 141	73.42 207	47.47 210	72.17 148	80.25 117	55.63 154	81.65 88	85.04 158	57.95 183	81.28 102	66.56 100	85.01 184	88.70 52

CLD-MVS		72.88 132	72.36 140	74.43 94	77.03 151	54.30 154	68.77 201	83.43 58	52.12 200	76.79 148	74.44 271	69.54 69	83.91 54	55.88 167	93.25 55	85.09 91
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
Regformer-3		72.86 133	72.28 142	74.62 92	74.74 177	60.18 121	72.91 138	71.76 202	64.74 72	78.42 127	72.07 290	67.00 89	76.28 186	67.97 85	80.91 228	87.39 68

EI-MVSNet-Vis-set		72.78 134	71.87 145	75.54 86	74.77 176	59.02 132	72.24 146	71.56 205	63.92 81	78.59 123	71.59 297	66.22 97	78.60 153	67.58 88	80.32 236	89.00 43

PCF-MVS	63.80 13	72.70 135	71.69 148	75.72 84	78.10 138	60.01 123	73.04 137	81.50 82	45.34 258	79.66 114	84.35 166	65.15 104	82.65 74	48.70 214	89.38 117	84.50 105
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
EI-MVSNet-UG-set		72.63 136	71.68 149	75.47 87	74.67 180	58.64 136	72.02 151	71.50 206	63.53 87	78.58 125	71.39 300	65.98 98	78.53 155	67.30 94	80.18 237	89.23 38

divwei89l23v2f112		72.60 137	72.73 133	72.19 148	73.10 220	47.00 221	71.48 163	79.11 131	55.01 162	81.23 95	84.95 159	57.45 190	80.89 120	66.58 98	85.67 165	88.68 56

v1		72.60 137	72.73 133	72.19 148	73.12 219	47.01 220	71.48 163	79.10 133	55.01 162	81.24 94	84.92 161	57.46 189	80.90 119	66.59 97	85.67 165	88.68 56

v1141		72.59 139	72.73 133	72.19 148	73.10 220	47.00 221	71.48 163	79.11 131	55.01 162	81.23 95	84.94 160	57.45 190	80.89 120	66.58 98	85.65 168	88.68 56

FIs		72.56 140	73.80 108	68.84 189	78.74 133	37.74 276	71.02 174	79.83 123	56.12 150	80.88 103	89.45 75	58.18 171	78.28 166	56.63 157	93.36 53	90.51 32

v2v482		72.55 141	72.58 137	72.43 144	72.92 230	46.72 225	71.41 168	79.13 130	55.27 158	81.17 97	85.25 153	55.41 203	81.13 106	67.25 95	85.46 173	89.43 36

canonicalmvs		72.29 142	73.38 117	69.04 182	74.23 192	47.37 214	73.93 135	83.18 59	54.36 177	76.61 150	81.64 204	72.03 52	75.34 195	57.12 154	87.28 148	84.40 107

Effi-MVS+		72.10 143	72.28 142	71.58 153	74.21 195	50.33 171	74.72 129	82.73 66	62.62 94	70.77 219	76.83 244	69.96 67	80.97 114	60.20 134	78.43 255	83.45 125

MVS_111021_LR		72.10 143	71.82 147	72.95 130	79.53 118	73.90 36	70.45 180	66.64 233	56.87 144	76.81 147	81.76 202	68.78 74	71.76 232	61.81 127	83.74 197	73.18 239

testing_2		72.01 145	72.36 140	70.95 158	70.79 241	48.70 184	72.81 140	78.09 154	48.79 231	84.46 65	89.15 83	57.90 185	78.55 154	61.55 128	87.74 137	85.61 87

pmmvs6		71.82 146	73.66 111	66.31 211	75.94 164	42.01 245	66.99 222	72.53 197	63.45 88	76.43 156	92.78 10	72.95 48	69.69 244	51.41 195	90.46 100	87.22 69

PLC	62.01 16	71.79 147	70.28 163	76.33 76	80.31 112	68.63 69	78.18 77	81.24 92	54.57 174	67.09 249	80.63 210	59.44 152	81.74 87	46.91 229	84.17 190	78.63 199
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
VDDNet		71.60 148	73.13 123	67.02 203	86.29 43	41.11 251	69.97 184	66.50 234	68.72 42	74.74 173	91.70 25	59.90 146	75.81 189	48.58 216	91.72 69	84.15 112

3Dnovator	65.95 11	71.50 149	71.22 156	72.34 146	73.16 215	63.09 104	78.37 73	78.32 147	57.67 134	72.22 204	84.61 163	54.77 204	78.47 157	60.82 133	81.07 227	75.45 224

WR-MVS		71.20 150	72.48 138	67.36 200	84.98 57	35.70 291	64.43 252	68.66 226	65.05 69	81.49 91	86.43 135	57.57 188	76.48 184	50.36 203	93.32 54	89.90 34

V42		71.06 151	70.83 159	71.72 152	67.25 274	47.14 218	65.94 236	80.35 114	51.35 209	83.40 72	83.23 183	59.25 156	78.80 149	65.91 106	80.81 232	89.23 38

FMVSNet1		71.06 151	72.48 138	66.81 205	77.65 146	40.68 253	71.96 153	73.03 190	61.14 106	79.45 117	90.36 63	60.44 142	75.20 197	50.20 204	88.05 133	84.54 101

API-MVS		70.97 153	71.51 153	69.37 175	75.20 169	55.94 144	80.99 46	76.84 165	62.48 96	71.24 214	77.51 240	61.51 132	80.96 118	52.04 190	85.76 164	71.22 258

VDD-MVS		70.81 154	71.44 154	68.91 187	79.07 130	46.51 226	67.82 212	70.83 217	61.23 104	74.07 182	88.69 93	59.86 147	75.62 192	51.11 197	90.28 102	84.61 100

EG-PatchMatch MVS		70.70 155	70.88 158	70.16 168	82.64 89	58.80 133	71.48 163	73.64 188	54.98 165	76.55 151	81.77 201	61.10 138	78.94 146	54.87 175	80.84 231	72.74 244

Baseline_NR-MVSNet		70.62 156	73.19 121	62.92 234	76.97 152	34.44 300	68.84 196	70.88 216	60.25 115	79.50 116	90.53 52	61.82 128	69.11 246	54.67 177	95.27 15	85.22 89

alignmvs		70.54 157	71.00 157	69.15 181	73.50 205	48.04 199	69.85 187	79.62 124	53.94 185	76.54 152	82.00 197	59.00 159	74.68 201	57.32 152	87.21 149	84.72 96

MG-MVS		70.47 158	71.34 155	67.85 196	79.26 122	40.42 258	74.67 131	75.15 182	58.41 127	68.74 235	88.14 104	56.08 202	83.69 57	59.90 138	81.71 217	79.43 193

UGNet		70.20 159	69.05 171	73.65 108	76.24 159	63.64 99	75.87 109	72.53 197	61.48 103	60.93 281	86.14 143	52.37 214	77.12 177	50.67 200	85.21 180	80.17 188
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
PVSNet_Blended_VisFu		70.04 160	68.88 176	73.53 113	82.71 88	63.62 100	74.81 125	81.95 77	48.53 233	67.16 248	79.18 230	51.42 220	78.38 163	54.39 181	79.72 245	78.60 200

Fast-Effi-MVS+-dtu		70.00 161	68.74 181	73.77 105	73.47 206	64.53 93	71.36 169	78.14 153	55.81 153	68.84 234	74.71 268	65.36 103	75.75 190	52.00 191	79.00 249	81.03 170

MVSFormer		69.93 162	69.03 173	72.63 139	74.93 171	59.19 128	83.98 28	75.72 174	52.27 198	63.53 265	76.74 245	43.19 252	80.56 124	72.28 49	78.67 253	78.14 205

MVS_Test		69.84 163	70.71 160	67.24 201	67.49 273	43.25 238	69.87 186	81.22 93	52.69 197	71.57 210	86.68 124	62.09 126	74.51 203	66.05 104	78.74 251	83.96 114

TransMVSNet (Re)		69.62 164	71.63 150	63.57 228	76.51 156	35.93 289	65.75 239	71.29 210	61.05 107	75.02 168	89.90 71	65.88 99	70.41 242	49.79 206	89.48 115	84.38 108

EI-MVSNet		69.61 165	69.01 174	71.41 156	73.94 198	49.90 175	71.31 171	71.32 208	58.22 128	75.40 166	70.44 301	58.16 172	75.85 187	62.51 124	79.81 242	88.48 59

Gipuma		69.55 166	72.83 132	59.70 261	63.63 295	53.97 156	80.08 57	75.93 172	64.24 79	73.49 187	88.93 91	57.89 186	62.46 285	59.75 141	91.55 75	62.67 311
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
BH-untuned		69.39 167	69.46 166	69.18 180	77.96 141	56.88 141	68.47 207	77.53 160	56.77 146	77.79 135	79.63 222	60.30 143	80.20 133	46.04 233	80.65 233	70.47 263

v148		69.38 168	69.39 167	69.36 176	69.14 257	44.56 232	68.83 197	72.70 195	54.79 169	78.59 123	84.12 168	54.69 205	76.74 183	59.40 142	82.20 206	86.79 72

1121		69.23 169	68.26 185	72.12 151	88.36 31	71.40 45	68.59 202	62.06 251	43.80 267	74.75 172	86.18 140	52.92 211	76.85 181	54.47 178	83.27 200	68.12 283

PAPR		69.20 170	68.66 182	70.82 159	75.15 170	47.77 203	75.31 119	81.11 94	49.62 227	66.33 251	79.27 227	61.53 131	82.96 70	48.12 220	81.50 220	81.74 160

QAPM		69.18 171	69.26 169	68.94 184	71.61 239	52.58 163	80.37 53	78.79 139	49.63 226	73.51 186	85.14 154	53.66 209	79.12 143	55.11 173	75.54 271	75.11 228

LCM-MVSNet-Re		69.10 172	71.57 152	61.70 245	70.37 247	34.30 301	61.45 275	79.62 124	56.81 145	89.59 10	88.16 103	68.44 78	72.94 211	42.30 254	87.33 146	77.85 210

EPNet		69.10 172	67.32 192	74.46 93	68.33 266	61.27 115	77.56 81	63.57 245	60.95 108	56.62 302	82.75 187	51.53 219	81.24 105	54.36 182	90.20 103	80.88 174
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test4		69.04 174	68.95 175	69.32 179	69.52 253	48.10 197	70.69 179	78.25 151	45.90 252	80.99 99	82.24 194	51.91 215	78.11 171	58.46 146	82.58 205	81.74 160

DI_MVS_plusplus_test		69.01 175	69.04 172	68.93 185	69.54 252	46.74 224	70.14 182	75.49 176	46.64 248	78.30 129	83.18 186	58.80 161	78.86 147	57.14 153	82.15 207	81.18 166

test_normal		68.88 176	68.88 176	68.88 188	69.43 255	47.03 219	69.85 187	74.83 183	46.06 251	78.30 129	83.29 181	58.76 165	78.23 167	57.51 150	81.90 211	81.36 164

DELS-MVS		68.83 177	68.31 183	70.38 162	70.55 246	48.31 191	63.78 257	82.13 72	54.00 182	68.96 233	75.17 263	58.95 160	80.06 136	58.55 145	82.74 203	82.76 138
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023
Fast-Effi-MVS+		68.81 178	68.30 184	70.35 163	74.66 182	48.61 188	66.06 235	78.32 147	50.62 220	71.48 213	75.54 257	68.75 75	79.59 141	50.55 202	78.73 252	82.86 135

OpenMVS	62.51 15	68.76 179	68.75 180	68.78 190	70.56 245	53.91 157	78.29 74	77.35 162	48.85 230	70.22 226	83.52 174	52.65 213	76.93 179	55.31 172	81.99 209	75.49 223

VPA-MVSNet		68.71 180	70.37 162	63.72 227	76.13 161	38.06 274	64.10 254	71.48 207	56.60 149	74.10 181	88.31 99	64.78 109	69.72 243	47.69 224	90.15 105	83.37 128

BH-RMVSNet		68.69 181	68.20 187	70.14 169	76.40 157	53.90 158	64.62 249	73.48 189	58.01 130	73.91 184	81.78 200	59.09 158	78.22 168	48.59 215	77.96 260	78.31 202

pm-mvs1		68.40 182	69.85 165	64.04 224	73.10 220	39.94 260	64.61 250	70.50 218	55.52 157	73.97 183	89.33 76	63.91 113	68.38 256	49.68 208	88.02 134	83.81 117

GBi-Net		68.30 183	68.79 178	66.81 205	73.14 216	40.68 253	71.96 153	73.03 190	54.81 166	74.72 174	90.36 63	48.63 230	75.20 197	47.12 226	85.37 174	84.54 101

test1		68.30 183	68.79 178	66.81 205	73.14 216	40.68 253	71.96 153	73.03 190	54.81 166	74.72 174	90.36 63	48.63 230	75.20 197	47.12 226	85.37 174	84.54 101

TinyColmap		67.98 185	69.28 168	64.08 223	67.98 270	46.82 223	70.04 183	75.26 180	53.05 193	77.36 139	86.79 117	59.39 153	72.59 221	45.64 235	88.01 135	72.83 242

xiu_mvs_v1_base_debu		67.87 186	67.07 194	70.26 164	79.13 127	61.90 110	67.34 217	71.25 211	47.98 238	67.70 239	74.19 276	61.31 133	72.62 218	56.51 158	78.26 257	76.27 220

xiu_mvs_v1_base		67.87 186	67.07 194	70.26 164	79.13 127	61.90 110	67.34 217	71.25 211	47.98 238	67.70 239	74.19 276	61.31 133	72.62 218	56.51 158	78.26 257	76.27 220

xiu_mvs_v1_base_debi		67.87 186	67.07 194	70.26 164	79.13 127	61.90 110	67.34 217	71.25 211	47.98 238	67.70 239	74.19 276	61.31 133	72.62 218	56.51 158	78.26 257	76.27 220

MAR-MVS		67.72 189	66.16 198	72.40 145	74.45 186	64.99 91	74.87 123	77.50 161	48.67 232	65.78 255	68.58 315	57.01 197	77.79 172	46.68 231	81.92 210	74.42 232
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
LF4IMVS		67.50 190	67.31 193	68.08 194	58.86 320	61.93 109	71.43 167	75.90 173	44.67 263	72.42 201	80.20 214	57.16 192	70.44 240	58.99 144	86.12 160	71.88 252

FMVSNet2		67.48 191	68.21 186	65.29 216	73.14 216	38.94 267	68.81 198	71.21 214	54.81 166	76.73 149	86.48 134	48.63 230	74.60 202	47.98 221	86.11 161	82.35 147

MSDG		67.47 192	67.48 191	67.46 199	70.70 244	54.69 152	66.90 224	78.17 152	60.88 109	70.41 223	74.76 265	61.22 137	73.18 209	47.38 225	76.87 264	74.49 231

ANet_high		67.08 193	69.94 164	58.51 268	57.55 328	27.09 332	58.43 292	76.80 166	63.56 85	82.40 78	91.93 20	59.82 148	64.98 278	50.10 205	88.86 123	83.46 124

LFMVS		67.06 194	67.89 189	64.56 219	78.02 139	38.25 272	70.81 178	59.60 260	65.18 67	71.06 217	86.56 131	43.85 248	75.22 196	46.35 232	89.63 112	80.21 186

MIMVSNet1		66.57 195	69.23 170	58.59 267	81.26 106	37.73 277	64.06 255	57.62 268	57.02 143	78.40 128	90.75 46	62.65 117	58.10 297	41.77 260	89.58 114	79.95 189

tfpnnormal		66.48 196	67.93 188	62.16 243	73.40 211	36.65 281	63.45 259	64.99 241	55.97 151	72.82 194	87.80 106	57.06 196	69.10 247	48.31 219	87.54 139	80.72 179

diffmvs		66.15 197	65.86 199	67.01 204	62.31 300	44.43 234	68.81 198	72.93 193	48.13 236	62.12 270	83.33 179	57.96 182	72.29 223	59.83 139	77.31 263	84.33 110

VPNet		65.58 198	67.56 190	59.65 262	79.72 115	30.17 325	60.27 283	62.14 249	54.19 179	71.24 214	86.63 128	58.80 161	67.62 262	44.17 239	90.87 95	81.18 166

PVSNet_BlendedMVS		65.38 199	64.30 204	68.61 191	69.81 249	49.36 179	65.60 242	78.96 135	45.50 255	59.98 286	78.61 233	51.82 216	78.20 169	44.30 237	84.11 191	78.27 203

TAMVS		65.31 200	63.75 208	69.97 173	82.23 94	59.76 126	66.78 225	63.37 246	45.20 259	69.79 228	79.37 226	47.42 236	72.17 224	34.48 299	85.15 182	77.99 209

mvs_anonymous		65.08 201	65.49 200	63.83 226	63.79 293	37.60 278	66.52 228	69.82 222	43.44 272	73.46 188	86.08 145	58.79 164	71.75 233	51.90 192	75.63 270	82.15 151

FMVSNet3		65.00 202	65.16 201	64.52 220	69.47 254	37.56 279	66.63 226	70.38 219	51.55 208	74.72 174	83.27 182	37.89 279	74.44 204	47.12 226	85.37 174	81.57 162

BH-w/o		64.81 203	64.29 205	66.36 210	76.08 163	54.71 151	65.61 241	75.23 181	50.10 224	71.05 218	71.86 296	54.33 207	79.02 144	38.20 279	76.14 267	65.36 299

cascas		64.59 204	62.77 222	70.05 171	75.27 168	50.02 174	61.79 272	71.61 203	42.46 276	63.68 264	68.89 312	49.33 227	80.35 128	47.82 223	84.05 192	79.78 190

TR-MVS		64.59 204	63.54 211	67.73 198	75.75 167	50.83 170	63.39 260	70.29 220	49.33 228	71.55 211	74.55 269	50.94 221	78.46 158	40.43 267	75.69 269	73.89 235

PM-MVS		64.49 206	63.61 210	67.14 202	76.68 155	75.15 28	68.49 206	42.85 331	51.17 213	77.85 134	80.51 211	45.76 237	66.31 274	52.83 189	76.35 266	59.96 319

jason		64.47 207	62.84 221	69.34 178	76.91 154	59.20 127	67.15 221	65.67 235	35.29 307	65.16 257	76.74 245	44.67 243	70.68 237	54.74 176	79.28 248	78.14 205
jason: jason.
xiu_mvs_v2_base		64.43 208	63.96 206	65.85 215	77.72 145	51.32 168	63.63 258	72.31 200	45.06 262	61.70 271	69.66 306	62.56 118	73.93 207	49.06 212	73.91 280	72.31 248

pmmvs-eth3d		64.41 209	63.27 213	67.82 197	75.81 166	60.18 121	69.49 190	62.05 252	38.81 290	74.13 180	82.23 195	43.76 249	68.65 254	42.53 253	80.63 235	74.63 230

CDS-MVSNet		64.33 210	62.66 223	69.35 177	80.44 111	58.28 137	65.26 245	65.66 236	44.36 264	67.30 247	75.54 257	43.27 251	71.77 231	37.68 282	84.44 188	78.01 208
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PS-MVSNAJ		64.27 211	63.73 209	65.90 214	77.82 143	51.42 167	63.33 261	72.33 199	45.09 261	61.60 272	68.04 316	62.39 122	73.95 206	49.07 211	73.87 281	72.34 247

ab-mvs		64.11 212	65.13 203	61.05 252	71.99 237	38.03 275	67.59 213	68.79 225	49.08 229	65.32 256	86.26 138	58.02 179	66.85 269	39.33 269	79.79 244	78.27 203

CANet_DTU		64.04 213	63.83 207	64.66 218	68.39 263	42.97 240	73.45 136	74.50 185	52.05 202	54.78 310	75.44 262	43.99 247	70.42 241	53.49 188	78.41 256	80.59 181

VNet		64.01 214	65.15 202	60.57 256	73.28 214	35.61 292	57.60 294	67.08 231	54.61 173	66.76 250	83.37 177	56.28 200	66.87 267	42.19 255	85.20 181	79.23 195

lupinMVS		63.36 215	61.49 230	68.97 183	74.93 171	59.19 128	65.80 238	64.52 243	34.68 312	63.53 265	74.25 274	43.19 252	70.62 238	53.88 184	78.67 253	77.10 215

MVSTER		63.29 216	61.60 228	68.36 193	59.77 315	46.21 227	60.62 281	71.32 208	41.83 279	75.40 166	79.12 231	30.25 318	75.85 187	56.30 163	79.81 242	83.03 131

OpenMVS_ROB	54.93 17	63.23 217	63.28 212	63.07 233	69.81 249	45.34 230	68.52 205	67.14 230	43.74 269	70.61 222	79.22 228	47.90 234	72.66 217	48.75 213	73.84 282	71.21 259

IterMVS		63.12 218	62.48 224	65.02 217	66.34 281	52.86 162	63.81 256	62.25 248	46.57 249	71.51 212	80.40 213	44.60 244	66.82 270	51.38 196	75.47 272	75.38 226
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
HyFIR lowres test		63.01 219	60.47 236	70.61 160	83.04 83	54.10 155	59.93 285	72.24 201	33.67 318	69.00 232	75.63 256	38.69 272	76.93 179	36.60 289	75.45 273	80.81 177

GA-MVS		62.91 220	61.66 226	66.66 209	67.09 276	44.49 233	61.18 279	69.36 224	51.33 210	69.33 230	74.47 270	36.83 280	74.94 200	50.60 201	74.72 277	80.57 182

PVSNet_Blended		62.90 221	61.64 227	66.69 208	69.81 249	49.36 179	61.23 278	78.96 135	42.04 278	59.98 286	68.86 313	51.82 216	78.20 169	44.30 237	77.77 262	72.52 245

view600		62.88 222	62.90 217	62.82 235	72.97 226	33.66 306	66.10 231	55.01 284	57.05 139	72.66 195	82.56 189	31.60 303	72.78 212	42.64 249	85.55 169	82.02 152

view800		62.88 222	62.90 217	62.82 235	72.97 226	33.66 306	66.10 231	55.01 284	57.05 139	72.66 195	82.56 189	31.60 303	72.78 212	42.64 249	85.55 169	82.02 152

conf0.05thres1000		62.88 222	62.90 217	62.82 235	72.97 226	33.66 306	66.10 231	55.01 284	57.05 139	72.66 195	82.56 189	31.60 303	72.78 212	42.64 249	85.55 169	82.02 152

tfpn		62.88 222	62.90 217	62.82 235	72.97 226	33.66 306	66.10 231	55.01 284	57.05 139	72.66 195	82.56 189	31.60 303	72.78 212	42.64 249	85.55 169	82.02 152

USDC		62.80 226	63.10 215	61.89 244	65.19 287	43.30 237	67.42 216	74.20 186	35.80 305	72.25 203	84.48 165	45.67 238	71.95 230	37.95 281	84.97 187	70.42 265

Vis-MVSNet (Re-imp)		62.74 227	63.21 214	61.34 250	72.19 233	31.56 323	67.31 220	53.87 291	53.60 188	69.88 227	83.37 177	40.52 266	70.98 236	41.40 261	86.78 155	81.48 163

MDA-MVSNet-bldmvs		62.34 228	61.73 225	64.16 221	61.64 304	49.90 175	48.11 317	57.24 274	53.31 192	80.95 100	79.39 225	49.00 228	61.55 289	45.92 234	80.05 239	81.03 170

wuyk23d		61.97 229	66.25 197	49.12 300	58.19 326	60.77 118	66.32 229	52.97 297	55.93 152	90.62 7	86.91 113	73.07 45	35.98 341	20.63 340	91.63 71	50.62 331

thres600view7		61.82 230	61.38 231	63.12 232	71.81 238	34.93 297	64.64 248	56.99 275	54.78 170	70.33 225	79.74 221	32.07 299	72.42 222	38.61 275	83.46 198	82.02 152

PAPM		61.79 231	60.37 237	66.05 212	76.09 162	41.87 246	69.30 192	76.79 167	40.64 285	53.80 316	79.62 223	44.38 245	82.92 71	29.64 319	73.11 284	73.36 238

MVP-Stereo		61.56 232	59.22 242	68.58 192	79.28 121	60.44 119	69.20 194	71.57 204	43.58 271	56.42 303	78.37 235	39.57 269	76.46 185	34.86 298	60.16 326	68.86 281
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CMPMVS	48.73 20	61.54 233	60.89 234	63.52 229	61.08 307	51.55 166	68.07 210	68.00 229	33.88 314	65.87 254	81.25 206	37.91 278	67.71 260	49.32 210	82.60 204	71.31 257
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
conf200view11		61.42 234	61.09 232	62.43 242	72.14 234	35.01 295	65.42 243	56.99 275	55.23 159	70.71 220	79.90 217	32.07 299	72.09 225	35.61 294	81.73 213	80.18 187

RPMNet		61.25 235	61.55 229	60.36 258	66.37 279	48.24 193	70.93 176	54.45 289	54.66 172	61.35 274	86.77 120	33.29 290	63.22 282	55.93 166	70.17 298	69.62 274

thres100view900		61.17 236	61.09 232	61.39 249	72.14 234	35.01 295	65.42 243	56.99 275	55.23 159	70.71 220	79.90 217	32.07 299	72.09 225	35.61 294	81.73 213	77.08 216

Patchmtry		60.91 237	63.01 216	54.62 285	66.10 283	26.27 336	67.47 215	56.40 279	54.05 181	72.04 205	86.66 125	33.19 291	60.17 292	43.69 240	87.45 143	77.42 211

EU-MVSNet		60.82 238	60.80 235	60.86 255	68.37 264	41.16 250	72.27 145	68.27 228	26.96 339	69.08 231	75.71 255	32.09 298	67.44 263	55.59 170	78.90 250	73.97 233

pmmvs4		60.78 239	59.04 244	66.00 213	73.06 223	57.67 139	64.53 251	60.22 258	36.91 300	65.96 253	77.27 241	39.66 268	68.54 255	38.87 272	74.89 276	71.80 253

thres400		60.77 240	59.97 239	63.15 231	70.78 242	35.35 293	63.27 262	57.47 269	53.00 194	68.31 236	77.09 242	32.45 296	72.09 225	35.61 294	81.73 213	82.02 152

MVS		60.62 241	59.97 239	62.58 240	68.13 268	47.28 216	68.59 202	73.96 187	32.19 323	59.94 288	68.86 313	50.48 222	77.64 174	41.85 258	75.74 268	62.83 309

tfpn200view9		60.35 242	59.97 239	61.51 247	70.78 242	35.35 293	63.27 262	57.47 269	53.00 194	68.31 236	77.09 242	32.45 296	72.09 225	35.61 294	81.73 213	77.08 216

Patchmatch-RL test		59.95 243	59.12 243	62.44 241	72.46 232	54.61 153	59.63 286	47.51 318	41.05 283	74.58 177	74.30 273	31.06 312	65.31 275	51.61 193	79.85 241	67.39 287

1314		59.83 244	58.86 250	62.74 239	65.71 285	44.78 231	68.59 202	72.63 196	33.54 321	61.05 278	67.29 320	43.62 250	71.26 235	49.49 209	67.84 311	72.19 250

IB-MVS	49.67 18	59.69 245	56.96 263	67.90 195	68.19 267	50.30 172	61.42 276	65.18 240	47.57 244	55.83 306	67.15 321	23.77 341	79.60 140	43.56 242	79.97 240	73.79 236
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021
1112_ss		59.48 246	58.99 245	60.96 254	77.84 142	42.39 244	61.42 276	68.45 227	37.96 295	59.93 289	67.46 318	45.11 241	65.07 277	40.89 264	71.81 289	75.41 225

FPMVS		59.43 247	60.07 238	57.51 273	77.62 147	71.52 44	62.33 265	50.92 306	57.40 137	69.40 229	80.00 216	39.14 270	61.92 288	37.47 285	66.36 314	39.09 341

CVMVSNet		59.21 248	58.44 255	61.51 247	73.94 198	47.76 204	71.31 171	64.56 242	26.91 340	60.34 283	70.44 301	36.24 282	67.65 261	53.57 187	68.66 308	69.12 279

CR-MVSNet		58.96 249	58.49 254	60.36 258	66.37 279	48.24 193	70.93 176	56.40 279	32.87 322	61.35 274	86.66 125	33.19 291	63.22 282	48.50 217	70.17 298	69.62 274

EPNet_dtu		58.93 250	58.52 253	60.16 260	67.91 271	47.70 205	69.97 184	58.02 265	49.73 225	47.28 331	73.02 285	38.14 275	62.34 286	36.57 290	85.99 162	70.43 264
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test_1112_low_res		58.78 251	58.69 252	59.04 265	79.41 119	38.13 273	57.62 293	66.98 232	34.74 310	59.62 290	77.56 239	42.92 254	63.65 281	38.66 274	70.73 295	75.35 227

PatchMatch-RL		58.68 252	57.72 257	61.57 246	76.21 160	73.59 39	61.83 271	49.00 313	47.30 246	61.08 276	68.97 310	50.16 224	59.01 295	36.06 293	68.84 306	52.10 330

thresconf0.02		58.38 253	58.88 246	56.91 276	68.66 258	31.96 319	62.04 267	51.95 300	50.99 214	67.57 242	75.91 251	28.59 328	69.07 248	42.77 245	81.40 221	69.70 269

tfpn_n400		58.38 253	58.88 246	56.91 276	68.66 258	31.96 319	62.04 267	51.95 300	50.99 214	67.57 242	75.91 251	28.59 328	69.07 248	42.77 245	81.40 221	69.70 269

tfpnconf		58.38 253	58.88 246	56.91 276	68.66 258	31.96 319	62.04 267	51.95 300	50.99 214	67.57 242	75.91 251	28.59 328	69.07 248	42.77 245	81.40 221	69.70 269

tfpnview11		58.38 253	58.88 246	56.91 276	68.66 258	31.96 319	62.04 267	51.95 300	50.99 214	67.57 242	75.91 251	28.59 328	69.07 248	42.77 245	81.40 221	69.70 269

tfpn1000		58.28 257	58.86 250	56.53 280	68.05 269	32.26 316	62.58 264	51.67 305	51.25 212	67.38 246	75.95 250	27.24 333	68.83 252	43.51 243	82.11 208	68.49 282

CHOSEN 1792x2688		58.09 258	56.30 267	63.45 230	79.95 113	50.93 169	54.07 303	65.59 237	28.56 336	61.53 273	74.33 272	41.09 262	66.52 273	33.91 303	67.69 312	72.92 241

HY-MVS	49.31 19	57.96 259	57.59 258	59.10 264	66.85 277	36.17 286	65.13 247	65.39 239	39.24 288	54.69 312	78.14 236	44.28 246	67.18 266	33.75 304	70.79 294	73.95 234

Patchmatch-test1		57.81 260	58.04 256	57.13 274	70.17 248	41.07 252	65.19 246	53.38 295	43.34 275	61.00 279	71.94 294	45.20 240	62.69 284	41.81 259	70.31 297	67.63 286

tpmp4_e23		57.57 261	55.46 274	63.93 225	66.48 278	41.56 249	71.68 161	60.65 257	35.64 306	55.35 309	76.25 248	29.53 324	75.41 194	34.40 300	69.12 305	74.83 229

thres200		57.55 262	57.02 262	59.17 263	67.89 272	34.93 297	58.91 290	57.25 273	50.24 222	64.01 262	71.46 299	32.49 295	71.39 234	31.31 310	79.57 246	71.19 260

CostFormer		57.35 263	56.14 268	60.97 253	63.76 294	38.43 269	67.50 214	60.22 258	37.14 299	59.12 291	76.34 247	32.78 293	71.99 229	39.12 271	69.27 304	72.47 246

tfpn_ndepth		56.91 264	57.30 261	55.71 281	67.22 275	33.26 311	61.72 273	53.98 290	48.49 234	64.16 261	71.94 294	27.65 332	68.71 253	40.49 266	80.08 238	65.17 301

tpm2		56.12 265	54.64 277	60.55 257	66.24 282	36.01 287	68.14 209	56.77 278	33.60 320	58.25 295	75.52 259	30.25 318	74.33 205	33.27 305	69.76 303	71.32 256

no-one		56.11 266	55.62 272	57.60 272	62.68 297	49.23 181	39.12 336	58.99 263	33.72 316	60.98 280	80.90 208	36.07 283	60.36 291	30.68 312	97.40 1	63.22 308

tpmvs		55.84 267	55.45 275	57.01 275	60.33 311	33.20 312	65.89 237	59.29 262	47.52 245	56.04 304	73.60 279	31.05 313	68.06 258	40.64 265	64.64 317	69.77 268

gg-mvs-nofinetune		55.75 268	56.75 265	52.72 289	62.87 296	28.04 331	68.92 195	41.36 339	71.09 29	50.80 322	92.63 12	20.74 344	66.86 268	29.97 317	72.41 286	63.25 307

test20.03		55.74 269	57.51 259	50.42 293	59.89 314	32.09 317	50.63 310	49.01 312	50.11 223	65.07 258	83.23 183	45.61 239	48.11 312	30.22 315	83.82 196	71.07 262

MS-PatchMatch		55.59 270	54.89 276	57.68 271	69.18 256	49.05 182	61.00 280	62.93 247	35.98 303	58.36 294	68.93 311	36.71 281	66.59 272	37.62 284	63.30 320	57.39 323

XXY-MVS		55.19 271	57.40 260	48.56 303	64.45 291	34.84 299	51.54 309	53.59 293	38.99 289	63.79 263	79.43 224	56.59 198	45.57 317	36.92 288	71.29 291	65.25 300

FMVSNet5		55.08 272	55.54 273	53.71 286	65.80 284	33.50 310	56.22 296	52.50 299	43.72 270	61.06 277	83.38 176	25.46 338	54.87 300	30.11 316	81.64 219	72.75 243

PatchmatchNet		54.60 273	54.27 279	55.59 282	65.17 289	39.08 264	66.92 223	51.80 304	39.89 286	58.39 293	73.12 284	31.69 302	58.33 296	43.01 244	58.38 335	69.38 277
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MIMVSNet		54.39 274	56.12 269	49.20 298	72.57 231	30.91 324	59.98 284	48.43 315	41.66 280	55.94 305	83.86 172	41.19 261	50.42 306	26.05 326	75.38 274	66.27 295

Anonymous20231206		54.13 275	55.82 270	49.04 301	70.89 240	35.96 288	51.73 308	50.87 307	34.86 308	62.49 268	79.22 228	42.52 256	44.29 326	27.95 324	81.88 212	66.88 291

JIA-IIPM		54.03 276	51.62 289	61.25 251	59.14 319	55.21 147	59.10 288	47.72 317	50.85 219	50.31 326	85.81 149	20.10 346	63.97 280	36.16 292	55.41 340	64.55 305

tpm cat1		54.02 277	52.63 285	58.19 269	64.85 290	39.86 261	66.26 230	57.28 272	32.16 324	56.90 300	70.39 303	32.75 294	65.30 276	34.29 301	58.79 331	69.41 276

testgi		54.00 278	56.86 264	45.45 311	58.20 325	25.81 337	49.05 313	49.50 311	45.43 257	67.84 238	81.17 207	51.81 218	43.20 330	29.30 320	79.41 247	67.34 289

PatchFormer-LS_test		53.94 279	52.64 284	57.85 270	61.87 302	39.59 262	61.60 274	57.63 267	40.65 284	54.52 313	58.64 335	29.07 327	64.18 279	46.78 230	62.98 322	69.78 267

PatchT		53.35 280	56.47 266	43.99 318	64.19 292	17.46 345	59.15 287	43.10 329	52.11 201	54.74 311	86.95 112	29.97 321	49.98 309	43.62 241	74.40 278	64.53 306

DWT-MVSNet_test		53.04 281	51.12 292	58.77 266	61.23 305	38.67 268	62.16 266	57.74 266	38.24 292	51.76 320	59.07 334	21.36 343	67.40 264	44.80 236	63.76 319	70.25 266

LP		53.02 282	52.27 288	55.27 283	55.76 337	40.55 256	55.64 299	55.07 282	42.46 276	56.95 299	73.21 283	33.67 289	54.18 304	38.41 277	59.29 330	71.08 261

testmv		52.91 283	54.31 278	48.71 302	72.13 236	36.18 285	50.26 311	47.78 316	44.15 265	64.61 259	79.78 220	38.18 274	50.20 308	21.96 337	69.93 300	59.75 320

new-patchmatchnet		52.89 284	55.76 271	44.26 317	59.94 313	6.31 351	37.36 340	50.76 308	41.10 281	64.28 260	79.82 219	44.77 242	48.43 311	36.24 291	87.61 138	78.03 207

YYNet1		52.58 285	53.50 281	49.85 294	54.15 343	36.45 284	40.53 331	46.55 321	38.09 294	75.52 164	73.31 282	41.08 263	43.88 327	41.10 262	71.14 293	69.21 278

MDA-MVSNet_test_wron		52.57 286	53.49 282	49.81 295	54.24 342	36.47 283	40.48 332	46.58 320	38.13 293	75.47 165	73.32 281	41.05 264	43.85 328	40.98 263	71.20 292	69.10 280

pmmvs5		52.49 287	52.58 286	52.21 291	54.99 340	32.38 315	55.45 300	53.84 292	32.15 325	55.49 308	74.81 264	38.08 276	57.37 298	34.02 302	74.40 278	66.88 291

UnsupCasMVSNet_eth		52.26 288	53.29 283	49.16 299	55.08 339	33.67 305	50.03 312	58.79 264	37.67 296	63.43 267	74.75 266	41.82 259	45.83 316	38.59 276	59.42 329	67.98 285

N_pmnet		52.06 289	51.11 293	54.92 284	59.64 316	71.03 49	37.42 339	61.62 255	33.68 317	57.12 297	72.10 286	37.94 277	31.03 345	29.13 323	71.35 290	62.70 310

PVSNet	43.83 21	51.56 290	51.17 291	52.73 288	68.34 265	38.27 271	48.22 316	53.56 294	36.41 301	54.29 314	64.94 324	34.60 286	54.20 303	30.34 314	69.87 301	65.71 298

tpm		50.60 291	52.42 287	45.14 313	65.18 288	26.29 335	60.30 282	43.50 328	37.41 297	57.01 298	79.09 232	30.20 320	42.32 332	32.77 307	66.36 314	66.81 293

test-LLR		50.43 292	50.69 295	49.64 296	60.76 308	41.87 246	53.18 305	45.48 326	43.41 273	49.41 327	60.47 332	29.22 325	44.73 323	42.09 256	72.14 287	62.33 313

tpmrst		50.15 293	51.38 290	46.45 308	56.05 333	24.77 339	64.40 253	49.98 309	36.14 302	53.32 317	69.59 307	35.16 285	48.69 310	39.24 270	58.51 334	65.89 296

UnsupCasMVSNet_bld		50.01 294	51.03 294	46.95 304	58.61 322	32.64 314	48.31 315	53.27 296	34.27 313	60.47 282	71.53 298	41.40 260	47.07 314	30.68 312	60.78 325	61.13 315

WTY-MVS		49.39 295	50.31 296	46.62 307	61.22 306	32.00 318	46.61 321	49.77 310	33.87 315	54.12 315	69.55 308	41.96 258	45.40 319	31.28 311	64.42 318	62.47 312

ADS-MVSNet2		48.76 296	47.25 305	53.29 287	55.90 335	40.54 257	47.34 319	54.99 288	31.41 331	50.48 323	72.06 292	31.23 309	54.26 302	25.93 327	55.93 337	65.07 302

test-mter		48.56 297	48.20 302	49.64 296	60.76 308	41.87 246	53.18 305	45.48 326	31.91 329	49.41 327	60.47 332	18.34 347	44.73 323	42.09 256	72.14 287	62.33 313

test1235678		48.41 298	49.60 298	44.83 315	68.52 262	33.81 304	46.33 323	45.89 323	38.72 291	58.46 292	72.08 287	29.85 323	47.82 313	19.67 341	66.91 313	52.88 328

Patchmatch-test		47.93 299	49.96 297	41.84 322	57.42 329	24.26 340	48.75 314	41.49 338	39.30 287	56.79 301	73.48 280	30.48 317	33.87 344	29.29 321	72.61 285	67.39 287

test0.0.03 1		47.72 300	48.31 301	45.93 309	55.53 338	29.39 326	46.40 322	41.21 340	43.41 273	55.81 307	67.65 317	29.22 325	43.77 329	25.73 329	69.87 301	64.62 304

sss		47.59 301	48.32 300	45.40 312	56.73 332	33.96 302	45.17 325	48.51 314	32.11 327	52.37 319	65.79 322	40.39 267	41.91 335	31.85 308	61.97 323	60.35 316

pmmvs3		46.71 302	45.09 310	51.55 292	56.76 331	48.25 192	55.78 298	39.53 344	24.13 343	50.35 325	63.40 326	15.90 351	51.08 305	29.29 321	70.69 296	55.33 326

EPMVS		45.74 303	46.53 306	43.39 319	54.14 344	22.33 342	55.02 301	35.00 347	34.69 311	51.09 321	70.20 305	25.92 336	42.04 334	37.19 286	55.50 339	65.78 297

MVS-HIRNet		45.53 304	47.29 304	40.24 326	62.29 301	26.82 334	56.02 297	37.41 345	29.74 335	43.69 342	81.27 205	33.96 288	55.48 299	24.46 332	56.79 336	38.43 342

testpf		45.32 305	48.47 299	35.88 331	53.56 345	26.84 333	58.86 291	42.95 330	47.78 242	46.18 333	63.70 325	13.73 352	50.29 307	50.81 199	58.61 333	30.51 344

TESTMET0.1,1		45.17 306	44.93 311	45.89 310	56.02 334	38.31 270	53.18 305	41.94 337	27.85 337	44.86 337	56.47 337	17.93 348	41.50 337	38.08 280	68.06 309	57.85 322

E-PMN		45.17 306	45.36 309	44.60 316	50.07 346	42.75 241	38.66 337	42.29 335	46.39 250	39.55 344	51.15 342	26.00 335	45.37 320	37.68 282	76.41 265	45.69 337

1111		45.08 308	47.96 303	36.43 330	59.56 317	14.82 347	43.56 326	45.65 324	45.60 253	60.04 284	75.47 260	9.31 354	34.46 342	23.66 333	68.76 307	60.02 318

testus		45.03 309	46.49 307	40.65 325	62.53 298	25.24 338	42.54 328	46.23 322	31.16 333	57.69 296	62.90 327	34.60 286	42.33 331	17.72 343	63.01 321	54.37 327

PMMVS		44.69 310	43.95 315	46.92 305	50.05 347	53.47 160	48.08 318	42.40 333	22.36 344	44.01 341	53.05 339	42.60 255	45.49 318	31.69 309	61.36 324	41.79 339

ADS-MVSNet		44.62 311	45.58 308	41.73 323	55.90 335	20.83 343	47.34 319	39.94 343	31.41 331	50.48 323	72.06 292	31.23 309	39.31 338	25.93 327	55.93 337	65.07 302

EMVS		44.61 312	44.45 314	45.10 314	48.91 348	43.00 239	37.92 338	41.10 341	46.75 247	38.00 346	48.43 344	26.42 334	46.27 315	37.11 287	75.38 274	46.03 336

dp		44.09 313	44.88 312	41.72 324	58.53 323	23.18 341	54.70 302	42.38 334	34.80 309	44.25 340	65.61 323	24.48 340	44.80 322	29.77 318	49.42 343	57.18 324

DSMNet-mixed		43.18 314	44.66 313	38.75 328	54.75 341	28.88 329	57.06 295	27.42 351	13.47 345	47.27 332	77.67 238	38.83 271	39.29 339	25.32 331	60.12 327	48.08 333

CHOSEN 280x420		41.62 315	39.89 321	46.80 306	61.81 303	51.59 165	33.56 342	35.74 346	27.48 338	37.64 347	53.53 338	23.24 342	42.09 333	27.39 325	58.64 332	46.72 335

PVSNet_0	36.71 22	41.12 316	40.78 318	42.14 320	59.97 312	40.13 259	40.97 330	42.24 336	30.81 334	44.86 337	49.41 343	40.70 265	45.12 321	23.15 335	34.96 345	41.16 340

test2356		40.85 317	40.47 319	41.98 321	58.78 321	28.65 330	39.45 334	40.98 342	31.95 328	48.47 329	56.63 336	12.54 353	44.41 325	15.84 345	59.58 328	52.88 328

test12356		38.35 318	40.80 317	31.01 332	58.31 324	9.09 350	36.67 341	46.65 319	33.65 319	44.39 339	60.94 331	17.56 349	39.23 340	16.01 344	53.03 341	44.72 338

PMMVS2		37.74 319	40.87 316	28.36 335	42.41 350	5.35 352	24.61 343	27.75 350	32.15 325	47.85 330	70.27 304	35.85 284	29.51 346	19.08 342	67.85 310	50.22 332

new_pmnet		37.55 320	39.80 322	30.79 333	56.83 330	16.46 346	39.35 335	30.65 349	25.59 341	45.26 335	61.60 330	24.54 339	28.02 347	21.60 338	52.80 342	47.90 334

PNet_i23d		36.76 321	36.63 324	37.12 329	58.19 326	33.00 313	39.86 333	32.55 348	48.44 235	39.64 343	51.31 341	6.89 356	41.83 336	22.29 336	30.55 346	36.54 343

MVE	27.91 23	36.69 322	35.64 325	39.84 327	43.37 349	35.85 290	19.49 344	24.61 352	24.68 342	39.05 345	62.63 329	38.67 273	27.10 348	21.04 339	47.25 344	56.56 325
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
pcd1.5k->3k		35.00 323	36.93 323	29.21 334	84.62 64	0.00 356	0.00 346	78.90 137	0.00 350	0.00 352	0.00 352	78.26 15	0.00 353	0.00 350	90.55 99	87.62 65

.test1245		34.47 324	40.38 320	16.73 336	59.56 317	14.82 347	43.56 326	45.65 324	45.60 253	60.04 284	75.47 260	9.31 354	34.46 342	23.66 333	0.55 350	0.90 347

cdsmvs_eth3d_5k		17.71 325	23.62 326	0.00 341	0.00 355	0.00 356	0.00 346	70.17 221	0.00 350	0.00 352	74.25 274	68.16 81	0.00 353	0.00 350	0.00 352	0.00 350

tmp_tt		11.98 326	14.73 327	3.72 338	2.28 352	4.62 353	19.44 345	14.50 354	0.47 347	21.55 348	9.58 347	25.78 337	4.57 350	11.61 346	27.37 347	1.96 346

ab-mvs-re		5.62 327	7.50 328	0.00 341	0.00 355	0.00 356	0.00 346	0.00 358	0.00 350	0.00 352	67.46 318	0.00 359	0.00 353	0.00 350	0.00 352	0.00 350

pcd_1.5k_mvsjas		5.20 328	6.93 329	0.00 341	0.00 355	0.00 356	0.00 346	0.00 358	0.00 350	0.00 352	0.00 352	62.39 122	0.00 353	0.00 350	0.00 352	0.00 350

test123		4.43 329	5.78 330	0.39 340	0.97 353	0.28 354	46.33 323	0.45 356	0.31 348	0.62 350	1.50 350	0.61 358	0.11 352	0.56 348	0.63 349	0.77 349

testmvs		4.06 330	5.28 331	0.41 339	0.64 354	0.16 355	42.54 328	0.31 357	0.26 349	0.50 351	1.40 351	0.77 357	0.17 351	0.56 348	0.55 350	0.90 347

sosnet-low-res		0.00 331	0.00 332	0.00 341	0.00 355	0.00 356	0.00 346	0.00 358	0.00 350	0.00 352	0.00 352	0.00 359	0.00 353	0.00 350	0.00 352	0.00 350

sosnet		0.00 331	0.00 332	0.00 341	0.00 355	0.00 356	0.00 346	0.00 358	0.00 350	0.00 352	0.00 352	0.00 359	0.00 353	0.00 350	0.00 352	0.00 350

uncertanet		0.00 331	0.00 332	0.00 341	0.00 355	0.00 356	0.00 346	0.00 358	0.00 350	0.00 352	0.00 352	0.00 359	0.00 353	0.00 350	0.00 352	0.00 350

Regformer		0.00 331	0.00 332	0.00 341	0.00 355	0.00 356	0.00 346	0.00 358	0.00 350	0.00 352	0.00 352	0.00 359	0.00 353	0.00 350	0.00 352	0.00 350

uanet		0.00 331	0.00 332	0.00 341	0.00 355	0.00 356	0.00 346	0.00 358	0.00 350	0.00 352	0.00 352	0.00 359	0.00 353	0.00 350	0.00 352	0.00 350

test_part2					85.90 45	66.44 79				84.61 61

test_part1								84.94 29				75.17 31			93.83 48	82.50 144

test_all								84.66 32

sam_mvs1												31.41 307

sam_mvs												31.21 311

semantic-postprocess				72.49 140	73.34 212	58.20 138		65.55 238	48.10 237	76.91 145	82.64 188	42.25 257	78.84 148	61.20 131	77.89 261	80.44 184

ambc				70.10 170	77.74 144	50.21 173	74.28 133	77.93 156		79.26 119	88.29 100	54.11 208	79.77 138	64.43 115	91.10 85	80.30 185

MTGPA								80.63 106

test_post1							66.63 226				2.08 348	30.66 316	59.33 294	40.34 268

test_post											1.99 349	30.91 314	54.76 301

patchmatchnet-post											68.99 309	31.32 308	69.38 245

GG-mvs-BLEND				52.24 290	60.64 310	29.21 328	69.73 189	42.41 332		45.47 334	52.33 340	20.43 345	68.16 257	25.52 330	65.42 316	59.36 321

MTMP								19.26 353

gm-plane-assit					62.51 299	33.91 303			37.25 298		62.71 328		72.74 216	38.70 273

test9_res														72.12 51	91.37 78	77.40 212

TEST9					85.47 51	69.32 64	76.42 96	78.69 140	53.73 187	76.97 141	86.74 121	66.84 91	81.10 109

test_8					85.09 56	67.89 73	76.26 101	78.66 142	54.00 182	76.89 146	86.72 123	66.60 93	80.89 120

agg_prior2														70.70 59	90.93 90	78.55 201

agg_prior					84.44 69	66.02 82		78.62 143		76.95 143			80.34 129

TestCases				78.35 58	79.19 125	70.81 51		88.64 2	65.37 63	80.09 111	88.17 101	70.33 63	78.43 160	55.60 168	90.90 92	85.81 83

test_prior4						70.14 58	77.57 80

test_prior2							75.57 113		58.92 125	76.53 153	86.78 118	67.83 85		69.81 67	92.76 59

test_prior				75.27 89	82.15 95	59.85 124		84.33 38					83.39 64			82.58 141

旧先验2							71.17 173		45.11 260	78.54 126			61.28 290	59.19 143

新几何2							71.33 170

新几何1				69.99 172	88.37 30	71.34 47		62.08 250	43.85 266	74.99 169	86.11 144	52.85 212	70.57 239	50.99 198	83.23 201	68.05 284

旧先验1					84.55 66	60.36 120		63.69 244			87.05 111	54.65 206			83.34 199	69.66 273

无先验							74.82 124	70.94 215	47.75 243				76.85 181	54.47 178		72.09 251

原ACMM2							74.78 128

原ACMM1				73.90 101	85.90 45	65.15 90		81.67 80	50.97 218	74.25 179	86.16 142	61.60 130	83.54 60	56.75 156	91.08 86	73.00 240

test222					87.30 34	69.15 67	67.85 211	59.59 261	41.06 282	73.05 192	85.72 150	48.03 233			80.65 233	66.92 290

testdata2													67.30 265	48.34 218

segment_acmp												68.30 80

testdata				64.13 222	85.87 47	63.34 102		61.80 254	47.83 241	76.42 157	86.60 130	48.83 229	62.31 287	54.46 180	81.26 225	66.74 294

testdata1							68.34 208		57.24 138

test12				76.51 71	82.28 93	60.94 117		81.64 81		73.60 185		64.88 106	85.19 38		90.42 101	83.38 126

plane_prior7					85.18 53	66.21 81

plane_prior6					84.18 73	65.31 87						60.83 140

plane_prior5								85.49 21					86.15 19	71.09 53	90.94 88	84.82 94

plane_prior4											89.11 84

plane_prior3						65.67 84			63.82 83	78.23 131

plane_prior2							82.74 35		65.45 60

plane_prior1					84.46 68

plane_prior						65.18 88	80.06 58		61.88 100						89.91 111

n2								0.00 358

nn								0.00 358

door-mid								55.02 283

lessismore_v0				72.75 135	79.60 117	56.83 142		57.37 271		83.80 68	89.01 87	47.45 235	78.74 151	64.39 116	86.49 158	82.69 140

LGP-MVS_train				80.90 32	87.00 36	70.41 56		86.35 12	69.77 38	87.75 18	91.13 35	81.83 3	86.20 16	77.13 26	95.96 7	86.08 77

test11								82.71 67

door								52.91 298

HQP5-MVS						58.80 133

HQP-NCC					82.37 90		77.32 84		59.08 121	71.58 207

ACMP_Plane					82.37 90		77.32 84		59.08 121	71.58 207

BP-MVS														67.38 92

HQP4-MVS										71.59 206			85.31 32			83.74 118

HQP3-MVS								84.12 45							89.16 118

HQP2-MVS												58.09 174

NP-MVS					83.34 80	63.07 105					85.97 147

MDTV_nov1_ep13_2view						18.41 344	53.74 304		31.57 330	44.89 336		29.90 322		32.93 306		71.48 255

MDTV_nov1_ep13			54.05 280		65.54 286	29.30 327	59.00 289	55.22 281	35.96 304	52.44 318	75.98 249	30.77 315	59.62 293	38.21 278	73.33 283

ACMMP++_ref															89.47 116

ACMMP++															91.96 68

Test By Simon												62.56 118

ITE_SJBPF				80.35 37	76.94 153	73.60 38		80.48 110	66.87 48	83.64 70	86.18 140	70.25 65	79.90 137	61.12 132	88.95 122	87.56 67

DeepMVS_CX				11.83 337	15.51 351	13.86 349		11.25 355	5.76 346	20.85 349	26.46 345	17.06 350	9.22 349	9.69 347	13.82 348	12.42 345

High-resolution multi-view benchmark