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	63.30 104	84.80 24	87.77 7	86.18 1	96.26 2	96.06 2	90.32 1	84.49 49	68.08 82	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 46	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 54	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 39	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 32	85.85 45	90.58 50	78.77 14	85.78 29	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 60	75.40 26	91.60 1	87.80 5	73.52 19	88.90 13	93.06 7	71.39 59	81.53 91	81.53 3	92.15 68	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 35	85.14 53	90.42 58	78.99 13	86.62 11	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 29	84.70 60	90.56 51	77.12 18	86.18 20	79.24 16	95.36 14	82.49 146

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 25	85.11 55	90.85 43	76.65 21	84.89 43	79.30 15	94.63 32	82.35 148

COLMAP_ROB	72.78 3	83.75 10	84.11 13	82.68 11	82.97 86	74.39 32	87.18 7	88.18 4	78.98 5	86.11 41	91.47 32	79.70 11	85.76 30	66.91 98	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 36	84.49 63	90.67 49	75.15 33	86.37 14	79.58 9	94.26 42	84.18 111

APD-MVS_3200maxsize		83.57 12	84.33 10	81.31 26	82.83 88	73.53 40	85.50 21	87.45 8	74.11 16	86.45 35	90.52 54	80.02 10	84.48 50	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 38	83.86 68	90.72 48	75.20 30	86.27 17	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 33	72.71 23	82.87 75	90.39 60	73.86 43	86.31 15	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 43	86.35 12	69.77 40	87.75 18	91.13 35	81.83 3	86.20 18	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 36	84.47 64	90.43 55	76.79 19	85.94 26	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 26	84.93 56	90.79 44	74.65 37	84.42 51	80.98 4	94.75 28	80.82 176

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 30	81.26 94	90.96 40	74.57 39	84.69 47	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 43	85.40 23	67.96 47	84.91 58	90.88 41	75.59 27	86.57 12	78.16 20	94.71 30	83.82 116

SteuartSystems-ACMMP		83.07 19	83.64 19	81.35 25	85.14 56	71.00 50	85.53 20	84.78 31	70.91 33	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 39	80.63 106	72.08 26	84.93 56	90.79 44	74.65 37	84.42 51	80.98 4	94.75 28	80.82 176

APDe-MVS		82.88 22	84.14 12	79.08 49	84.80 62	66.72 77	86.54 16	85.11 26	72.00 28	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 40	86.08 16	66.80 52	86.70 32	89.99 69	81.64 5	85.95 25	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 46	86.33 14	63.17 92	85.38 52	91.26 34	76.33 22	84.67 48	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 76	84.47 64	90.43 55	76.79 19	85.94 26	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 73	83.97 67	91.02 38	75.53 29	85.93 28	82.00 2	94.36 38	83.35 129

ACMM	69.25 9	82.11 27	83.31 24	78.49 57	88.17 33	73.96 34	83.11 36	84.52 36	66.40 56	87.45 23	89.16 84	81.02 7	80.52 129	74.27 36	95.73 9	80.98 173
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 69	90.35 6	82.82 3	82.15 41	79.22 129	74.08 17	87.16 27	91.97 19	84.80 2	76.97 180	64.98 114	93.61 51	72.28 251
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
ESAPD		81.57 29	82.55 32	78.63 55	85.90 45	66.44 79	83.39 33	84.94 29	73.27 20	84.61 61	89.25 80	75.17 31	86.96 9	72.56 45	93.83 48	82.50 144

UA-Net		81.56 30	82.28 34	79.40 46	88.91 26	69.16 66	84.67 25	80.01 121	75.34 13	79.80 114	94.91 3	69.79 69	80.25 133	72.63 43	94.46 36	88.78 51

CPTT-MVS		81.51 31	81.76 36	80.76 34	89.20 23	78.75 10	86.48 17	82.03 74	68.80 43	80.92 102	88.52 96	72.00 54	82.39 79	74.80 31	93.04 57	81.14 169

ACMH+	66.64 10	81.20 32	82.48 33	77.35 70	81.16 108	62.39 108	80.51 51	87.80 5	73.02 22	87.57 21	91.08 37	80.28 9	82.44 78	64.82 115	96.10 6	87.21 70

APD-MVS		81.13 33	81.73 37	79.36 47	84.47 68	70.53 55	83.85 30	83.70 51	69.43 42	83.67 70	88.96 92	75.89 26	86.41 13	72.62 44	92.95 58	81.14 169
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
3Dnovator+	73.19 2	81.08 34	80.48 44	82.87 6	81.41 105	72.03 42	84.38 27	86.23 15	77.28 11	80.65 105	90.18 67	59.80 150	87.58 4	73.06 41	91.34 80	89.01 42

DeepC-MVS	72.44 4	81.00 35	80.83 43	81.50 21	86.70 40	70.03 60	82.06 42	87.00 10	59.89 120	80.91 103	90.53 52	72.19 50	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 36	81.63 39	79.07 50	86.86 38	69.39 63	79.41 65	84.00 49	65.64 60	85.54 50	89.28 77	76.32 23	83.47 64	74.03 37	93.57 52	84.35 109

LS3D		80.99 36	80.85 42	81.41 24	78.37 136	71.37 46	87.45 6	85.87 19	77.48 9	81.98 82	89.95 70	69.14 72	85.26 36	66.15 105	91.24 82	87.61 66

XVG-ACMP-BASELINE		80.54 38	81.06 41	78.98 51	87.01 35	72.91 41	80.23 57	85.56 20	66.56 55	85.64 46	89.57 74	69.12 73	80.55 128	72.51 47	93.37 53	83.48 122

PEN-MVS		80.46 39	82.91 28	73.11 126	89.83 9	39.02 267	77.06 92	82.61 68	80.04 3	90.60 8	92.85 9	74.93 36	85.21 38	63.15 124	95.15 19	95.09 2

PS-CasMVS		80.41 40	82.86 30	73.07 127	89.93 7	39.21 264	77.15 90	81.28 90	79.74 4	90.87 6	92.73 11	75.03 35	84.93 42	63.83 121	95.19 17	95.07 3

DTE-MVSNet		80.35 41	82.89 29	72.74 137	89.84 8	37.34 281	77.16 89	81.81 78	80.45 2	90.92 5	92.95 8	74.57 39	86.12 24	63.65 122	94.68 31	94.76 6

SD-MVS		80.28 42	81.55 40	76.47 74	83.57 77	67.83 74	83.39 33	85.35 25	64.42 79	86.14 40	87.07 112	74.02 42	80.97 116	77.70 24	92.32 67	80.62 181

WR-MVS_H		80.22 43	82.17 35	74.39 96	89.46 15	42.69 243	78.24 77	82.24 71	78.21 8	89.57 11	92.10 18	68.05 83	85.59 31	66.04 107	95.62 11	94.88 5

HPM-MVS++		79.89 44	79.80 50	80.18 38	89.02 24	78.44 11	83.49 32	80.18 118	64.71 75	78.11 134	88.39 99	65.46 103	83.14 69	77.64 25	91.20 83	78.94 199

HSP-MVS		79.69 45	79.17 55	81.27 28	89.70 12	77.46 19	87.16 8	80.58 109	64.94 72	81.05 99	88.38 100	57.10 196	87.10 6	79.75 7	83.87 196	79.24 196

XVG-OURS-SEG-HR		79.62 46	79.99 48	78.49 57	86.46 42	74.79 30	77.15 90	85.39 24	66.73 53	80.39 109	88.85 94	74.43 41	78.33 167	74.73 33	85.79 164	82.35 148

XVG-OURS		79.51 47	79.82 49	78.58 56	86.11 44	74.96 29	76.33 102	84.95 28	66.89 49	82.75 77	88.99 90	66.82 93	78.37 166	74.80 31	90.76 97	82.40 147

CP-MVSNet		79.48 48	81.65 38	72.98 130	89.66 13	39.06 266	76.76 94	80.46 111	78.91 6	90.32 9	91.70 25	68.49 78	84.89 43	63.40 123	95.12 20	95.01 4

OMC-MVS		79.41 49	78.79 57	81.28 27	80.62 110	70.71 54	80.91 49	84.76 32	62.54 97	81.77 84	86.65 129	71.46 57	83.53 63	67.95 88	92.44 64	89.60 35

v7n		79.37 50	80.41 45	76.28 78	78.67 135	55.81 146	79.22 66	82.51 70	70.72 34	87.54 22	92.44 14	68.00 85	81.34 101	72.84 42	91.72 70	91.69 12

TSAR-MVS + MP.		79.05 51	78.81 56	79.74 41	88.94 25	67.52 75	86.61 15	81.38 89	51.71 207	77.15 141	91.42 33	65.49 102	87.20 5	79.44 12	87.17 152	84.51 104

v52		78.96 52	79.79 51	76.46 75	73.03 225	54.90 149	78.48 72	83.48 55	64.43 77	91.19 4	91.54 28	72.08 51	81.11 109	76.45 28	87.47 141	93.38 7

V4		78.96 52	79.79 51	76.46 75	73.02 226	54.90 149	78.48 72	83.47 56	64.43 77	91.20 3	91.54 28	72.08 51	81.11 109	76.45 28	87.46 143	93.38 7

mvs_tets		78.93 54	78.67 59	79.72 42	84.81 61	73.93 35	80.65 50	76.50 169	51.98 205	87.40 24	91.86 21	76.09 25	78.53 157	68.58 77	90.20 104	86.69 74

test_djsdf		78.88 55	78.27 62	80.70 35	81.42 104	71.24 48	83.98 28	75.72 174	52.27 200	87.37 25	92.25 16	68.04 84	80.56 126	72.28 51	91.15 84	90.32 33

HQP_MVS		78.77 56	78.78 58	78.72 53	85.18 54	65.18 89	82.74 37	85.49 21	65.45 62	78.23 132	89.11 86	60.83 141	86.15 21	71.09 55	90.94 89	84.82 94

anonymousdsp		78.60 57	77.80 66	81.00 31	78.01 141	74.34 33	80.09 58	76.12 170	50.51 224	89.19 12	90.88 41	71.45 58	77.78 175	73.38 40	90.60 99	90.90 27

OurMVSNet-221017-0		78.57 58	78.53 61	78.67 54	80.48 111	64.16 96	80.24 56	82.06 73	61.89 101	88.77 14	93.32 5	57.15 194	82.60 77	70.08 67	92.80 59	89.25 37

jajsoiax		78.51 59	78.16 63	79.59 44	84.65 64	73.83 37	80.42 53	76.12 170	51.33 212	87.19 26	91.51 31	73.79 45	78.44 161	68.27 80	90.13 108	86.49 75

CNVR-MVS		78.49 60	78.59 60	78.16 61	85.86 49	67.40 76	78.12 80	81.50 82	63.92 83	77.51 139	86.56 133	68.43 80	84.82 45	73.83 38	91.61 73	82.26 151

DeepPCF-MVS	71.07 5	78.48 61	77.14 71	82.52 16	84.39 72	77.04 21	76.35 100	84.05 47	56.66 150	80.27 110	85.31 154	68.56 77	87.03 8	67.39 93	91.26 81	83.50 121

DP-MVS		78.44 62	79.29 54	75.90 83	81.86 100	65.33 87	79.05 67	84.63 35	74.83 15	80.41 108	86.27 139	71.68 55	83.45 65	62.45 128	92.40 65	78.92 200

NCCC		78.25 63	78.04 64	78.89 52	85.61 51	69.45 61	79.80 62	80.99 103	65.77 59	75.55 164	86.25 141	67.42 88	85.42 32	70.10 66	90.88 95	81.81 160

test_0402		78.17 64	79.48 53	74.24 98	83.50 78	59.15 132	72.52 146	74.60 184	75.34 13	88.69 15	91.81 22	75.06 34	82.37 80	65.10 113	88.68 126	81.20 166

Anonymous20231211		77.74 65	80.26 46	70.19 168	83.05 83	43.39 237	75.86 112	76.74 168	75.91 12	85.92 43	96.14 1	80.85 8	75.59 195	53.58 188	94.27 41	91.58 13

AllTest		77.66 66	77.43 68	78.35 59	79.19 126	70.81 51	78.60 70	88.64 2	65.37 65	80.09 112	88.17 103	70.33 64	78.43 162	55.60 170	90.90 93	85.81 83

PS-MVSNAJss		77.54 67	77.35 69	78.13 63	84.88 59	66.37 81	78.55 71	79.59 126	53.48 191	86.29 38	92.43 15	62.39 123	80.25 133	67.90 89	90.61 98	87.77 64

ACMH	63.62 14	77.50 68	80.11 47	69.68 175	79.61 117	56.28 144	78.81 68	83.62 53	63.41 91	87.14 28	90.23 66	76.11 24	73.32 210	67.58 90	94.44 37	79.44 194
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CDPH-MVS		77.33 69	77.06 72	78.14 62	84.21 73	63.98 98	76.07 107	83.45 57	54.20 180	77.68 138	87.18 109	69.98 67	85.37 33	68.01 84	92.72 62	85.08 92

DeepC-MVS_fast	69.89 7	77.17 70	76.33 81	79.70 43	83.90 76	67.94 72	80.06 60	83.75 50	56.73 149	74.88 172	85.32 153	65.54 101	87.79 2	65.61 111	91.14 85	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 71	77.95 65	73.87 103	73.94 199	52.44 165	75.90 110	79.98 122	65.34 67	86.97 30	91.77 23	67.40 89	78.40 164	70.23 64	90.01 109	90.76 31

X-MVStestdata		76.81 72	74.79 97	82.85 7	89.43 16	77.61 14	86.80 13	84.66 33	72.71 23	82.87 75	9.95 349	73.86 43	86.31 15	78.84 17	94.03 46	84.64 97

test_prior3		76.71 73	77.19 70	75.27 90	82.15 96	59.85 125	75.57 115	84.33 38	58.92 127	76.53 154	86.78 120	67.83 86	83.39 66	69.81 69	92.76 60	82.58 141

train_agg		76.38 74	76.55 76	75.86 84	85.47 52	69.32 64	76.42 98	78.69 140	54.00 184	76.97 142	86.74 123	66.60 94	81.10 111	72.50 48	91.56 74	77.15 215

agg_prior3		76.32 75	76.33 81	76.28 78	85.86 49	70.13 59	76.50 96	78.26 150	53.41 193	75.78 160	86.49 135	66.58 96	81.57 90	72.50 48	91.56 74	77.15 215

v13		76.23 76	77.02 73	73.86 105	74.61 185	48.80 184	76.91 93	81.10 97	62.66 95	87.02 29	91.01 39	59.76 151	81.41 96	71.29 54	88.78 125	91.38 14

TranMVSNet+NR-MVSNet		76.13 77	77.66 67	71.56 155	84.61 66	42.57 244	70.98 177	78.29 149	68.67 45	83.04 74	89.26 78	72.99 48	80.75 125	55.58 173	95.47 12	91.35 15

v12		76.03 78	76.79 74	73.76 107	74.45 187	48.60 190	76.59 95	81.11 94	62.22 100	86.79 31	90.74 47	59.51 152	81.40 98	71.01 57	88.67 127	91.29 16

agg_prior1		75.89 79	76.41 79	74.31 97	84.44 70	66.02 83	76.12 106	78.62 143	54.40 178	76.95 144	86.85 117	66.44 97	80.34 131	72.45 50	91.42 78	76.57 220

V9		75.82 80	76.53 77	73.66 108	74.28 191	48.37 191	76.26 103	81.10 97	61.73 103	86.59 34	90.43 55	59.16 158	81.42 95	70.71 60	88.56 128	91.21 19

SixPastTwentyTwo		75.77 81	76.34 80	74.06 101	81.69 102	54.84 151	76.47 97	75.49 176	64.10 82	87.73 20	92.24 17	50.45 224	81.30 103	67.41 92	91.46 77	86.04 79

v11		75.76 82	76.51 78	73.48 115	74.28 191	47.81 203	76.16 105	81.28 90	61.56 104	86.39 36	90.38 61	59.32 156	81.41 96	70.85 58	88.41 130	91.23 17

RPSCF		75.76 82	74.37 103	79.93 39	74.81 176	77.53 16	77.53 84	79.30 128	59.44 122	78.88 123	89.80 72	71.26 60	73.09 212	57.45 153	80.89 232	89.17 40

v10		75.69 84	76.20 84	74.16 99	74.44 189	48.69 186	75.84 113	82.93 64	59.02 126	85.92 43	89.17 83	58.56 167	82.74 75	70.73 59	89.14 121	91.05 21

V14		75.58 85	76.26 83	73.55 113	74.10 198	48.13 196	75.91 109	81.07 100	61.19 107	86.34 37	90.11 68	58.80 162	81.40 98	70.40 62	88.43 129	91.12 20

Effi-MVS+-dtu		75.43 86	72.28 143	84.91 2	77.05 150	83.58 2	78.47 74	77.70 157	57.68 134	74.89 171	78.13 239	64.80 108	84.26 55	56.46 163	85.32 179	86.88 71

v15		75.37 87	76.01 85	73.44 116	73.91 202	47.87 202	75.55 117	81.04 101	60.76 112	86.11 41	89.76 73	58.53 168	81.40 98	70.11 65	88.32 131	91.04 23

wuykxyi23d		75.33 88	76.75 75	71.04 158	78.83 133	85.01 1	71.78 162	61.00 256	53.47 192	96.33 1	93.38 4	73.07 46	68.04 262	65.65 110	97.28 2	60.07 321

Regformer-2		75.32 89	74.47 101	77.88 64	74.22 194	66.65 78	72.77 143	77.54 159	68.47 46	80.44 107	72.08 290	70.60 63	80.97 116	70.08 67	84.02 194	86.01 80

F-COLMAP		75.29 90	73.99 108	79.18 48	81.73 101	71.90 43	81.86 45	82.98 62	59.86 121	72.27 203	84.00 172	64.56 111	83.07 71	51.48 196	87.19 151	82.56 143

HQP-MVS		75.24 91	75.01 96	75.94 82	82.37 91	58.80 134	77.32 86	84.12 45	59.08 123	71.58 208	85.96 150	58.09 175	85.30 35	67.38 94	89.16 119	83.73 119

TAPA-MVS	65.27 12	75.16 92	74.29 105	77.77 66	74.86 175	68.08 71	77.89 81	84.04 48	55.15 163	76.19 159	83.39 177	66.91 91	80.11 137	60.04 139	90.14 107	85.13 90
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
IS-MVSNet		75.10 93	75.42 93	74.15 100	79.23 124	48.05 199	79.43 63	78.04 155	70.09 39	79.17 121	88.02 107	53.04 211	83.60 61	58.05 150	93.76 50	90.79 29

v8		75.07 94	75.64 89	73.35 118	73.42 208	47.46 212	75.20 122	81.45 85	60.05 118	85.64 46	89.26 78	58.08 177	81.80 88	69.71 71	87.97 137	90.79 29

v17		75.03 95	75.59 90	73.36 117	73.56 204	47.66 207	75.48 118	81.45 85	60.58 114	85.55 49	89.02 88	58.36 170	81.47 92	69.69 72	86.59 158	90.96 24

UniMVSNet (Re)		75.00 96	75.48 92	73.56 112	83.14 82	47.92 201	70.41 183	81.04 101	63.67 86	79.54 116	86.37 138	62.83 117	81.82 87	57.10 157	95.25 16	90.94 26

PHI-MVS		74.92 97	74.36 104	76.61 71	76.40 158	62.32 109	80.38 54	83.15 60	54.16 182	73.23 192	80.75 211	62.19 126	83.86 57	68.02 83	90.92 92	83.65 120

DU-MVS		74.91 98	75.57 91	72.93 132	83.50 78	45.79 229	69.47 193	80.14 119	65.22 68	81.74 86	87.08 110	61.82 129	81.07 113	56.21 166	94.98 22	91.93 10

UniMVSNet_NR-MVSNet		74.90 99	75.65 88	72.64 139	83.04 84	45.79 229	69.26 195	78.81 138	66.66 54	81.74 86	86.88 116	63.26 115	81.07 113	56.21 166	94.98 22	91.05 21

v16		74.89 100	75.41 94	73.35 118	73.54 205	47.62 208	75.47 119	81.45 85	60.58 114	85.46 51	88.97 91	58.27 171	81.47 92	69.66 73	85.25 180	90.95 25

nrg030		74.87 101	75.99 86	71.52 156	74.90 174	49.88 179	74.10 136	82.58 69	54.55 177	83.50 72	89.21 82	71.51 56	75.74 193	61.24 132	92.34 66	88.94 46

Vis-MVSNet		74.85 102	74.56 99	75.72 85	81.63 103	64.64 93	76.35 100	79.06 134	62.85 94	73.33 190	88.41 98	62.54 121	79.59 143	63.94 120	82.92 203	82.94 133
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Regformer-4		74.64 103	73.67 111	77.55 67	74.74 178	64.49 95	72.91 140	75.42 179	67.45 48	80.24 111	72.07 293	68.98 74	80.19 136	70.29 63	80.91 230	87.98 62

v18		74.60 104	75.06 95	73.22 123	73.29 214	47.36 216	75.02 123	81.47 84	60.01 119	85.13 54	88.44 97	57.93 185	81.47 92	69.26 74	85.02 184	90.84 28

MVS_0304		74.55 105	73.47 115	77.80 65	77.41 149	63.88 99	75.75 114	83.67 52	63.55 88	66.12 254	82.16 198	60.20 145	86.15 21	65.37 112	86.98 154	83.38 126

MSLP-MVS++		74.48 106	75.78 87	70.59 162	84.66 63	62.40 107	78.65 69	84.24 42	60.55 116	77.71 137	81.98 200	63.12 116	77.64 176	62.95 125	88.14 133	71.73 256

Regformer-1		74.28 107	73.63 113	76.21 81	74.22 194	64.12 97	72.77 143	75.46 178	66.86 51	79.27 119	72.08 290	69.29 71	78.74 153	68.73 76	84.02 194	85.77 86

AdaColmap		74.22 108	74.56 99	73.20 124	81.95 98	60.97 117	79.43 63	80.90 104	65.57 61	72.54 201	81.76 204	70.98 62	85.26 36	47.88 224	90.00 110	73.37 239

CSCG		74.12 109	74.39 102	73.33 120	79.35 121	61.66 114	77.45 85	81.98 75	62.47 99	79.06 122	80.19 217	61.83 128	78.79 152	59.83 141	87.35 146	79.54 193

PAPM_NR		73.91 110	74.16 106	73.16 125	81.90 99	53.50 160	81.28 47	81.40 88	66.17 57	73.30 191	83.31 182	59.96 146	83.10 70	58.45 149	81.66 219	82.87 134

EPP-MVSNet		73.86 111	73.38 118	75.31 89	78.19 138	53.35 162	80.45 52	77.32 163	65.11 70	76.47 156	86.80 118	49.47 226	83.77 58	53.89 185	92.72 62	88.81 50

mvs-test1		73.81 112	70.69 162	83.18 3	77.05 150	81.39 4	75.39 120	77.70 157	57.68 134	71.19 217	74.72 270	64.80 108	83.66 60	56.46 163	81.19 228	84.50 105

K. test v3		73.67 113	73.61 114	73.87 103	79.78 115	55.62 147	74.69 132	62.04 253	66.16 58	84.76 59	93.23 6	49.47 226	80.97 116	65.66 109	86.67 157	85.02 93

NR-MVSNet		73.62 114	74.05 107	72.33 148	83.50 78	43.71 236	65.65 242	77.32 163	64.32 80	75.59 163	87.08 110	62.45 122	81.34 101	54.90 176	95.63 10	91.93 10

v7		73.59 115	73.69 110	73.28 122	74.42 190	48.68 187	72.74 145	81.98 75	54.76 173	82.07 81	85.05 159	58.53 168	82.22 84	67.99 85	85.66 168	88.95 45

DP-MVS Recon		73.57 116	72.69 137	76.23 80	82.85 87	63.39 102	74.32 134	82.96 63	57.75 133	70.35 225	81.98 200	64.34 112	84.41 53	49.69 209	89.95 111	80.89 174

CNLPA		73.44 117	73.03 130	74.66 92	78.27 137	75.29 27	75.99 108	78.49 145	65.39 64	75.67 162	83.22 187	61.23 137	66.77 274	53.70 187	85.33 178	81.92 159

MCST-MVS		73.42 118	73.34 120	73.63 111	81.28 106	59.17 131	74.80 129	83.13 61	45.50 258	72.84 194	83.78 175	65.15 105	80.99 115	64.54 116	89.09 122	80.73 179

v1192		73.40 119	73.42 116	73.32 121	74.65 184	48.67 188	72.21 149	81.73 79	52.76 198	81.85 83	84.56 166	57.12 195	82.24 83	68.58 77	87.33 147	89.06 41

114514_t		73.40 119	73.33 121	73.64 110	84.15 75	57.11 141	78.20 78	80.02 120	43.76 271	72.55 200	86.07 148	64.00 113	83.35 68	60.14 138	91.03 88	80.45 184

FC-MVSNet-test		73.32 121	74.78 98	68.93 186	79.21 125	36.57 283	71.82 161	79.54 127	57.63 138	82.57 78	90.38 61	59.38 155	78.99 147	57.91 151	94.56 33	91.23 17

v1144		73.29 122	73.39 117	73.01 128	74.12 197	48.11 197	72.01 154	81.08 99	53.83 188	81.77 84	84.68 164	58.07 178	81.91 86	68.10 81	86.86 155	88.99 44

TSAR-MVS + GP.		73.08 123	71.60 152	77.54 68	78.99 132	70.73 53	74.96 124	69.38 223	60.73 113	74.39 179	78.44 236	57.72 188	82.78 74	60.16 137	89.60 114	79.11 198

v1240		73.06 124	73.14 123	72.84 134	74.74 178	47.27 218	71.88 160	81.11 94	51.80 206	82.28 80	84.21 169	56.22 202	82.34 81	68.82 75	87.17 152	88.91 47

IterMVS-LS		73.01 125	73.12 125	72.66 138	73.79 203	49.90 176	71.63 164	78.44 146	58.22 130	80.51 106	86.63 130	58.15 174	79.62 141	62.51 126	88.20 132	88.48 59
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CANet		73.00 126	71.84 147	76.48 73	75.82 166	61.28 115	74.81 127	80.37 113	63.17 92	62.43 271	80.50 214	61.10 139	85.16 41	64.00 119	84.34 190	83.01 132

v144192		72.99 127	73.06 129	72.77 135	74.58 186	47.48 210	71.90 159	80.44 112	51.57 209	81.46 93	84.11 171	58.04 179	82.12 85	67.98 86	87.47 141	88.70 52

MVS_111021_HR		72.98 128	72.97 132	72.99 129	80.82 109	65.47 86	68.81 200	72.77 194	57.67 136	75.76 161	82.38 195	71.01 61	77.17 178	61.38 131	86.15 160	76.32 221

v1921920		72.96 129	72.98 131	72.89 133	74.67 181	47.58 209	71.92 158	80.69 105	51.70 208	81.69 88	83.89 173	56.58 200	82.25 82	68.34 79	87.36 145	88.82 49

v1neww		72.93 130	73.07 127	72.48 142	73.41 210	47.46 212	72.17 150	80.26 115	55.63 156	81.63 90	85.07 157	57.97 181	81.28 104	66.55 103	84.98 186	88.70 52

v7new		72.93 130	73.07 127	72.48 142	73.41 210	47.46 212	72.17 150	80.26 115	55.63 156	81.63 90	85.07 157	57.97 181	81.28 104	66.55 103	84.98 186	88.70 52

v6		72.93 130	73.08 126	72.48 142	73.42 208	47.47 211	72.17 150	80.25 117	55.63 156	81.65 89	85.04 160	57.95 184	81.28 104	66.56 102	85.01 185	88.70 52

CLD-MVS		72.88 133	72.36 141	74.43 95	77.03 152	54.30 155	68.77 203	83.43 58	52.12 202	76.79 149	74.44 274	69.54 70	83.91 56	55.88 169	93.25 56	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		72.86 134	72.28 143	74.62 93	74.74 178	60.18 122	72.91 140	71.76 202	64.74 74	78.42 128	72.07 293	67.00 90	76.28 188	67.97 87	80.91 230	87.39 68

EI-MVSNet-Vis-set		72.78 135	71.87 146	75.54 87	74.77 177	59.02 133	72.24 148	71.56 205	63.92 83	78.59 124	71.59 300	66.22 98	78.60 155	67.58 90	80.32 238	89.00 43

PCF-MVS	63.80 13	72.70 136	71.69 149	75.72 85	78.10 139	60.01 124	73.04 139	81.50 82	45.34 261	79.66 115	84.35 168	65.15 105	82.65 76	48.70 216	89.38 118	84.50 105
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
EI-MVSNet-UG-set		72.63 137	71.68 150	75.47 88	74.67 181	58.64 137	72.02 153	71.50 206	63.53 89	78.58 126	71.39 303	65.98 99	78.53 157	67.30 96	80.18 239	89.23 38

divwei89l23v2f112		72.60 138	72.73 134	72.19 149	73.10 221	47.00 222	71.48 165	79.11 131	55.01 164	81.23 96	84.95 161	57.45 191	80.89 122	66.58 100	85.67 166	88.68 56

v1		72.60 138	72.73 134	72.19 149	73.12 220	47.01 221	71.48 165	79.10 133	55.01 164	81.24 95	84.92 163	57.46 190	80.90 121	66.59 99	85.67 166	88.68 56

v1141		72.59 140	72.73 134	72.19 149	73.10 221	47.00 222	71.48 165	79.11 131	55.01 164	81.23 96	84.94 162	57.45 191	80.89 122	66.58 100	85.65 169	88.68 56

FIs		72.56 141	73.80 109	68.84 190	78.74 134	37.74 277	71.02 176	79.83 123	56.12 152	80.88 104	89.45 75	58.18 172	78.28 168	56.63 159	93.36 54	90.51 32

v2v482		72.55 142	72.58 138	72.43 145	72.92 231	46.72 226	71.41 170	79.13 130	55.27 160	81.17 98	85.25 155	55.41 204	81.13 108	67.25 97	85.46 174	89.43 36

canonicalmvs		72.29 143	73.38 118	69.04 183	74.23 193	47.37 215	73.93 137	83.18 59	54.36 179	76.61 151	81.64 206	72.03 53	75.34 197	57.12 156	87.28 149	84.40 107

Effi-MVS+		72.10 144	72.28 143	71.58 154	74.21 196	50.33 172	74.72 131	82.73 66	62.62 96	70.77 220	76.83 246	69.96 68	80.97 116	60.20 136	78.43 257	83.45 125

MVS_111021_LR		72.10 144	71.82 148	72.95 131	79.53 119	73.90 36	70.45 182	66.64 233	56.87 146	76.81 148	81.76 204	68.78 75	71.76 234	61.81 129	83.74 198	73.18 241

testing_2		72.01 146	72.36 141	70.95 159	70.79 242	48.70 185	72.81 142	78.09 154	48.79 234	84.46 66	89.15 85	57.90 186	78.55 156	61.55 130	87.74 138	85.61 87

pmmvs6		71.82 147	73.66 112	66.31 212	75.94 165	42.01 246	66.99 224	72.53 197	63.45 90	76.43 157	92.78 10	72.95 49	69.69 246	51.41 197	90.46 101	87.22 69

PLC	62.01 16	71.79 148	70.28 164	76.33 77	80.31 113	68.63 69	78.18 79	81.24 92	54.57 176	67.09 251	80.63 212	59.44 153	81.74 89	46.91 231	84.17 191	78.63 201
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
VDDNet		71.60 149	73.13 124	67.02 204	86.29 43	41.11 252	69.97 186	66.50 234	68.72 44	74.74 174	91.70 25	59.90 147	75.81 191	48.58 218	91.72 70	84.15 112

3Dnovator	65.95 11	71.50 150	71.22 157	72.34 147	73.16 216	63.09 105	78.37 75	78.32 147	57.67 136	72.22 205	84.61 165	54.77 205	78.47 159	60.82 135	81.07 229	75.45 226

WR-MVS		71.20 151	72.48 139	67.36 201	84.98 58	35.70 292	64.43 254	68.66 226	65.05 71	81.49 92	86.43 137	57.57 189	76.48 186	50.36 205	93.32 55	89.90 34

V42		71.06 152	70.83 160	71.72 153	67.25 276	47.14 219	65.94 238	80.35 114	51.35 211	83.40 73	83.23 185	59.25 157	78.80 151	65.91 108	80.81 234	89.23 38

FMVSNet1		71.06 152	72.48 139	66.81 206	77.65 147	40.68 254	71.96 155	73.03 190	61.14 108	79.45 118	90.36 63	60.44 143	75.20 199	50.20 206	88.05 134	84.54 101

API-MVS		70.97 154	71.51 154	69.37 176	75.20 170	55.94 145	80.99 48	76.84 165	62.48 98	71.24 215	77.51 242	61.51 133	80.96 120	52.04 192	85.76 165	71.22 260

VDD-MVS		70.81 155	71.44 155	68.91 188	79.07 131	46.51 227	67.82 214	70.83 217	61.23 106	74.07 183	88.69 95	59.86 148	75.62 194	51.11 199	90.28 103	84.61 100

EG-PatchMatch MVS		70.70 156	70.88 159	70.16 169	82.64 90	58.80 134	71.48 165	73.64 188	54.98 167	76.55 152	81.77 203	61.10 139	78.94 148	54.87 177	80.84 233	72.74 246

Baseline_NR-MVSNet		70.62 157	73.19 122	62.92 235	76.97 153	34.44 301	68.84 198	70.88 216	60.25 117	79.50 117	90.53 52	61.82 129	69.11 248	54.67 179	95.27 15	85.22 89

alignmvs		70.54 158	71.00 158	69.15 182	73.50 206	48.04 200	69.85 189	79.62 124	53.94 187	76.54 153	82.00 199	59.00 160	74.68 203	57.32 154	87.21 150	84.72 96

MG-MVS		70.47 159	71.34 156	67.85 197	79.26 123	40.42 259	74.67 133	75.15 182	58.41 129	68.74 236	88.14 106	56.08 203	83.69 59	59.90 140	81.71 218	79.43 195

UGNet		70.20 160	69.05 172	73.65 109	76.24 160	63.64 100	75.87 111	72.53 197	61.48 105	60.93 283	86.14 145	52.37 215	77.12 179	50.67 202	85.21 181	80.17 190
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		70.04 161	68.88 177	73.53 114	82.71 89	63.62 101	74.81 127	81.95 77	48.53 236	67.16 250	79.18 232	51.42 221	78.38 165	54.39 183	79.72 247	78.60 202

Fast-Effi-MVS+-dtu		70.00 162	68.74 182	73.77 106	73.47 207	64.53 94	71.36 171	78.14 153	55.81 155	68.84 235	74.71 271	65.36 104	75.75 192	52.00 193	79.00 251	81.03 171

MVSFormer		69.93 163	69.03 174	72.63 140	74.93 172	59.19 129	83.98 28	75.72 174	52.27 200	63.53 267	76.74 247	43.19 253	80.56 126	72.28 51	78.67 255	78.14 207

MVS_Test		69.84 164	70.71 161	67.24 202	67.49 275	43.25 239	69.87 188	81.22 93	52.69 199	71.57 211	86.68 126	62.09 127	74.51 205	66.05 106	78.74 253	83.96 114

TransMVSNet (Re)		69.62 165	71.63 151	63.57 229	76.51 157	35.93 290	65.75 241	71.29 210	61.05 109	75.02 169	89.90 71	65.88 100	70.41 244	49.79 208	89.48 116	84.38 108

EI-MVSNet		69.61 166	69.01 175	71.41 157	73.94 199	49.90 176	71.31 173	71.32 208	58.22 130	75.40 167	70.44 304	58.16 173	75.85 189	62.51 126	79.81 244	88.48 59

Gipuma		69.55 167	72.83 133	59.70 263	63.63 297	53.97 157	80.08 59	75.93 172	64.24 81	73.49 188	88.93 93	57.89 187	62.46 288	59.75 143	91.55 76	62.67 315
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
BH-untuned		69.39 168	69.46 167	69.18 181	77.96 142	56.88 142	68.47 209	77.53 160	56.77 148	77.79 136	79.63 224	60.30 144	80.20 135	46.04 235	80.65 235	70.47 265

v148		69.38 169	69.39 168	69.36 177	69.14 258	44.56 233	68.83 199	72.70 195	54.79 171	78.59 124	84.12 170	54.69 206	76.74 185	59.40 144	82.20 207	86.79 72

1121		69.23 170	68.26 186	72.12 152	88.36 31	71.40 45	68.59 204	62.06 251	43.80 270	74.75 173	86.18 142	52.92 212	76.85 183	54.47 180	83.27 201	68.12 287

PAPR		69.20 171	68.66 183	70.82 160	75.15 171	47.77 204	75.31 121	81.11 94	49.62 230	66.33 253	79.27 229	61.53 132	82.96 72	48.12 222	81.50 221	81.74 161

QAPM		69.18 172	69.26 170	68.94 185	71.61 240	52.58 164	80.37 55	78.79 139	49.63 229	73.51 187	85.14 156	53.66 210	79.12 145	55.11 175	75.54 273	75.11 230

LCM-MVSNet-Re		69.10 173	71.57 153	61.70 246	70.37 248	34.30 302	61.45 278	79.62 124	56.81 147	89.59 10	88.16 105	68.44 79	72.94 213	42.30 257	87.33 147	77.85 212

EPNet		69.10 173	67.32 193	74.46 94	68.33 268	61.27 116	77.56 83	63.57 245	60.95 110	56.62 304	82.75 189	51.53 220	81.24 107	54.36 184	90.20 104	80.88 175
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test4		69.04 175	68.95 176	69.32 180	69.52 254	48.10 198	70.69 181	78.25 151	45.90 255	80.99 100	82.24 196	51.91 216	78.11 173	58.46 148	82.58 206	81.74 161

DI_MVS_plusplus_test		69.01 176	69.04 173	68.93 186	69.54 253	46.74 225	70.14 184	75.49 176	46.64 251	78.30 130	83.18 188	58.80 162	78.86 149	57.14 155	82.15 208	81.18 167

test_normal		68.88 177	68.88 177	68.88 189	69.43 256	47.03 220	69.85 189	74.83 183	46.06 254	78.30 130	83.29 183	58.76 166	78.23 169	57.51 152	81.90 212	81.36 165

DELS-MVS		68.83 178	68.31 184	70.38 163	70.55 247	48.31 192	63.78 259	82.13 72	54.00 184	68.96 234	75.17 266	58.95 161	80.06 138	58.55 147	82.74 204	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+		68.81 179	68.30 185	70.35 164	74.66 183	48.61 189	66.06 237	78.32 147	50.62 223	71.48 214	75.54 260	68.75 76	79.59 143	50.55 204	78.73 254	82.86 135

OpenMVS	62.51 15	68.76 180	68.75 181	68.78 191	70.56 246	53.91 158	78.29 76	77.35 162	48.85 233	70.22 227	83.52 176	52.65 214	76.93 181	55.31 174	81.99 210	75.49 225

VPA-MVSNet		68.71 181	70.37 163	63.72 228	76.13 162	38.06 275	64.10 256	71.48 207	56.60 151	74.10 182	88.31 101	64.78 110	69.72 245	47.69 226	90.15 106	83.37 128

BH-RMVSNet		68.69 182	68.20 188	70.14 170	76.40 158	53.90 159	64.62 251	73.48 189	58.01 132	73.91 185	81.78 202	59.09 159	78.22 170	48.59 217	77.96 262	78.31 204

pm-mvs1		68.40 183	69.85 166	64.04 225	73.10 221	39.94 261	64.61 252	70.50 218	55.52 159	73.97 184	89.33 76	63.91 114	68.38 259	49.68 210	88.02 135	83.81 117

GBi-Net		68.30 184	68.79 179	66.81 206	73.14 217	40.68 254	71.96 155	73.03 190	54.81 168	74.72 175	90.36 63	48.63 231	75.20 199	47.12 228	85.37 175	84.54 101

test1		68.30 184	68.79 179	66.81 206	73.14 217	40.68 254	71.96 155	73.03 190	54.81 168	74.72 175	90.36 63	48.63 231	75.20 199	47.12 228	85.37 175	84.54 101

TinyColmap		67.98 186	69.28 169	64.08 224	67.98 272	46.82 224	70.04 185	75.26 180	53.05 195	77.36 140	86.79 119	59.39 154	72.59 223	45.64 237	88.01 136	72.83 244

xiu_mvs_v1_base_debu		67.87 187	67.07 195	70.26 165	79.13 128	61.90 111	67.34 219	71.25 211	47.98 241	67.70 240	74.19 279	61.31 134	72.62 220	56.51 160	78.26 259	76.27 222

xiu_mvs_v1_base		67.87 187	67.07 195	70.26 165	79.13 128	61.90 111	67.34 219	71.25 211	47.98 241	67.70 240	74.19 279	61.31 134	72.62 220	56.51 160	78.26 259	76.27 222

xiu_mvs_v1_base_debi		67.87 187	67.07 195	70.26 165	79.13 128	61.90 111	67.34 219	71.25 211	47.98 241	67.70 240	74.19 279	61.31 134	72.62 220	56.51 160	78.26 259	76.27 222

MAR-MVS		67.72 190	66.16 199	72.40 146	74.45 187	64.99 92	74.87 125	77.50 161	48.67 235	65.78 257	68.58 318	57.01 198	77.79 174	46.68 233	81.92 211	74.42 234
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		67.50 191	67.31 194	68.08 195	58.86 322	61.93 110	71.43 169	75.90 173	44.67 266	72.42 202	80.20 216	57.16 193	70.44 242	58.99 146	86.12 161	71.88 254

FMVSNet2		67.48 192	68.21 187	65.29 217	73.14 217	38.94 268	68.81 200	71.21 214	54.81 168	76.73 150	86.48 136	48.63 231	74.60 204	47.98 223	86.11 162	82.35 148

MSDG		67.47 193	67.48 192	67.46 200	70.70 245	54.69 153	66.90 226	78.17 152	60.88 111	70.41 224	74.76 268	61.22 138	73.18 211	47.38 227	76.87 266	74.49 233

ANet_high		67.08 194	69.94 165	58.51 270	57.55 330	27.09 334	58.43 295	76.80 166	63.56 87	82.40 79	91.93 20	59.82 149	64.98 281	50.10 207	88.86 124	83.46 124

LFMVS		67.06 195	67.89 190	64.56 220	78.02 140	38.25 273	70.81 180	59.60 260	65.18 69	71.06 218	86.56 133	43.85 249	75.22 198	46.35 234	89.63 113	80.21 187

MIMVSNet1		66.57 196	69.23 171	58.59 269	81.26 107	37.73 278	64.06 257	57.62 268	57.02 145	78.40 129	90.75 46	62.65 118	58.10 300	41.77 263	89.58 115	79.95 191

tfpnnormal		66.48 197	67.93 189	62.16 244	73.40 212	36.65 282	63.45 261	64.99 241	55.97 153	72.82 195	87.80 108	57.06 197	69.10 249	48.31 221	87.54 140	80.72 180

diffmvs		66.15 198	65.86 200	67.01 205	62.31 302	44.43 235	68.81 200	72.93 193	48.13 239	62.12 272	83.33 181	57.96 183	72.29 225	59.83 141	77.31 265	84.33 110

VPNet		65.58 199	67.56 191	59.65 264	79.72 116	30.17 327	60.27 286	62.14 249	54.19 181	71.24 215	86.63 130	58.80 162	67.62 265	44.17 241	90.87 96	81.18 167

PVSNet_BlendedMVS		65.38 200	64.30 205	68.61 192	69.81 250	49.36 180	65.60 244	78.96 135	45.50 258	59.98 288	78.61 235	51.82 217	78.20 171	44.30 239	84.11 192	78.27 205

TAMVS		65.31 201	63.75 209	69.97 174	82.23 95	59.76 127	66.78 227	63.37 246	45.20 262	69.79 229	79.37 228	47.42 237	72.17 226	34.48 302	85.15 183	77.99 211

mvs_anonymous		65.08 202	65.49 201	63.83 227	63.79 295	37.60 279	66.52 230	69.82 222	43.44 275	73.46 189	86.08 147	58.79 165	71.75 235	51.90 194	75.63 272	82.15 152

FMVSNet3		65.00 203	65.16 202	64.52 221	69.47 255	37.56 280	66.63 228	70.38 219	51.55 210	74.72 175	83.27 184	37.89 280	74.44 206	47.12 228	85.37 175	81.57 163

BH-w/o		64.81 204	64.29 206	66.36 211	76.08 164	54.71 152	65.61 243	75.23 181	50.10 227	71.05 219	71.86 299	54.33 208	79.02 146	38.20 282	76.14 269	65.36 303

cascas		64.59 205	62.77 223	70.05 172	75.27 169	50.02 175	61.79 275	71.61 203	42.46 279	63.68 266	68.89 315	49.33 228	80.35 130	47.82 225	84.05 193	79.78 192

TR-MVS		64.59 205	63.54 212	67.73 199	75.75 168	50.83 171	63.39 262	70.29 220	49.33 231	71.55 212	74.55 272	50.94 222	78.46 160	40.43 270	75.69 271	73.89 237

PM-MVS		64.49 207	63.61 211	67.14 203	76.68 156	75.15 28	68.49 208	42.85 332	51.17 215	77.85 135	80.51 213	45.76 238	66.31 277	52.83 191	76.35 268	59.96 323

jason		64.47 208	62.84 222	69.34 179	76.91 155	59.20 128	67.15 223	65.67 235	35.29 310	65.16 259	76.74 247	44.67 244	70.68 239	54.74 178	79.28 250	78.14 207
jason: jason.
xiu_mvs_v2_base		64.43 209	63.96 207	65.85 216	77.72 146	51.32 169	63.63 260	72.31 200	45.06 265	61.70 273	69.66 309	62.56 119	73.93 209	49.06 214	73.91 282	72.31 250

pmmvs-eth3d		64.41 210	63.27 214	67.82 198	75.81 167	60.18 122	69.49 192	62.05 252	38.81 293	74.13 181	82.23 197	43.76 250	68.65 257	42.53 256	80.63 237	74.63 232

CDS-MVSNet		64.33 211	62.66 224	69.35 178	80.44 112	58.28 138	65.26 247	65.66 236	44.36 267	67.30 249	75.54 260	43.27 252	71.77 233	37.68 285	84.44 189	78.01 210
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PS-MVSNAJ		64.27 212	63.73 210	65.90 215	77.82 144	51.42 168	63.33 263	72.33 199	45.09 264	61.60 274	68.04 319	62.39 123	73.95 208	49.07 213	73.87 283	72.34 249

ab-mvs		64.11 213	65.13 204	61.05 253	71.99 238	38.03 276	67.59 215	68.79 225	49.08 232	65.32 258	86.26 140	58.02 180	66.85 272	39.33 272	79.79 246	78.27 205

CANet_DTU		64.04 214	63.83 208	64.66 219	68.39 265	42.97 241	73.45 138	74.50 185	52.05 204	54.78 312	75.44 265	43.99 248	70.42 243	53.49 190	78.41 258	80.59 182

VNet		64.01 215	65.15 203	60.57 257	73.28 215	35.61 293	57.60 297	67.08 231	54.61 175	66.76 252	83.37 179	56.28 201	66.87 270	42.19 258	85.20 182	79.23 197

lupinMVS		63.36 216	61.49 231	68.97 184	74.93 172	59.19 129	65.80 240	64.52 243	34.68 315	63.53 267	74.25 277	43.19 253	70.62 240	53.88 186	78.67 255	77.10 217

MVSTER		63.29 217	61.60 229	68.36 194	59.77 317	46.21 228	60.62 284	71.32 208	41.83 282	75.40 167	79.12 233	30.25 319	75.85 189	56.30 165	79.81 244	83.03 131

OpenMVS_ROB	54.93 17	63.23 218	63.28 213	63.07 234	69.81 250	45.34 231	68.52 207	67.14 230	43.74 272	70.61 223	79.22 230	47.90 235	72.66 219	48.75 215	73.84 284	71.21 261

IterMVS		63.12 219	62.48 225	65.02 218	66.34 283	52.86 163	63.81 258	62.25 248	46.57 252	71.51 213	80.40 215	44.60 245	66.82 273	51.38 198	75.47 274	75.38 228
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
HyFIR lowres test		63.01 220	60.47 237	70.61 161	83.04 84	54.10 156	59.93 288	72.24 201	33.67 321	69.00 233	75.63 259	38.69 273	76.93 181	36.60 292	75.45 275	80.81 178

GA-MVS		62.91 221	61.66 227	66.66 210	67.09 278	44.49 234	61.18 282	69.36 224	51.33 212	69.33 231	74.47 273	36.83 281	74.94 202	50.60 203	74.72 279	80.57 183

PVSNet_Blended		62.90 222	61.64 228	66.69 209	69.81 250	49.36 180	61.23 281	78.96 135	42.04 281	59.98 288	68.86 316	51.82 217	78.20 171	44.30 239	77.77 264	72.52 247

view600		62.88 223	62.90 218	62.82 236	72.97 227	33.66 307	66.10 233	55.01 284	57.05 141	72.66 196	82.56 191	31.60 304	72.78 214	42.64 252	85.55 170	82.02 153

view800		62.88 223	62.90 218	62.82 236	72.97 227	33.66 307	66.10 233	55.01 284	57.05 141	72.66 196	82.56 191	31.60 304	72.78 214	42.64 252	85.55 170	82.02 153

conf0.05thres1000		62.88 223	62.90 218	62.82 236	72.97 227	33.66 307	66.10 233	55.01 284	57.05 141	72.66 196	82.56 191	31.60 304	72.78 214	42.64 252	85.55 170	82.02 153

tfpn		62.88 223	62.90 218	62.82 236	72.97 227	33.66 307	66.10 233	55.01 284	57.05 141	72.66 196	82.56 191	31.60 304	72.78 214	42.64 252	85.55 170	82.02 153

USDC		62.80 227	63.10 216	61.89 245	65.19 289	43.30 238	67.42 218	74.20 186	35.80 308	72.25 204	84.48 167	45.67 239	71.95 232	37.95 284	84.97 188	70.42 267

Vis-MVSNet (Re-imp)		62.74 228	63.21 215	61.34 251	72.19 234	31.56 325	67.31 222	53.87 291	53.60 190	69.88 228	83.37 179	40.52 267	70.98 238	41.40 264	86.78 156	81.48 164

MDA-MVSNet-bldmvs		62.34 229	61.73 226	64.16 222	61.64 306	49.90 176	48.11 320	57.24 274	53.31 194	80.95 101	79.39 227	49.00 229	61.55 292	45.92 236	80.05 241	81.03 171

wuyk23d		61.97 230	66.25 198	49.12 302	58.19 328	60.77 119	66.32 231	52.97 297	55.93 154	90.62 7	86.91 115	73.07 46	35.98 344	20.63 343	91.63 72	50.62 335

thres600view7		61.82 231	61.38 232	63.12 233	71.81 239	34.93 298	64.64 250	56.99 275	54.78 172	70.33 226	79.74 223	32.07 300	72.42 224	38.61 278	83.46 199	82.02 153

PAPM		61.79 232	60.37 238	66.05 213	76.09 163	41.87 247	69.30 194	76.79 167	40.64 288	53.80 318	79.62 225	44.38 246	82.92 73	29.64 322	73.11 286	73.36 240

MVP-Stereo		61.56 233	59.22 243	68.58 193	79.28 122	60.44 120	69.20 196	71.57 204	43.58 274	56.42 305	78.37 237	39.57 270	76.46 187	34.86 301	60.16 328	68.86 285
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CMPMVS	48.73 20	61.54 234	60.89 235	63.52 230	61.08 309	51.55 167	68.07 212	68.00 229	33.88 317	65.87 256	81.25 208	37.91 279	67.71 263	49.32 212	82.60 205	71.31 259
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
conf200view11		61.42 235	61.09 233	62.43 243	72.14 235	35.01 296	65.42 245	56.99 275	55.23 161	70.71 221	79.90 219	32.07 300	72.09 227	35.61 297	81.73 214	80.18 188

RPMNet		61.25 236	61.55 230	60.36 260	66.37 281	48.24 194	70.93 178	54.45 289	54.66 174	61.35 276	86.77 122	33.29 291	63.22 285	55.93 168	70.17 300	69.62 278

thres100view900		61.17 237	61.09 233	61.39 250	72.14 235	35.01 296	65.42 245	56.99 275	55.23 161	70.71 221	79.90 219	32.07 300	72.09 227	35.61 297	81.73 214	77.08 218

Patchmtry		60.91 238	63.01 217	54.62 287	66.10 285	26.27 338	67.47 217	56.40 279	54.05 183	72.04 206	86.66 127	33.19 292	60.17 295	43.69 242	87.45 144	77.42 213

EU-MVSNet		60.82 239	60.80 236	60.86 256	68.37 266	41.16 251	72.27 147	68.27 228	26.96 342	69.08 232	75.71 258	32.09 299	67.44 266	55.59 172	78.90 252	73.97 235

pmmvs4		60.78 240	59.04 245	66.00 214	73.06 224	57.67 140	64.53 253	60.22 258	36.91 303	65.96 255	77.27 243	39.66 269	68.54 258	38.87 275	74.89 278	71.80 255

thres400		60.77 241	59.97 240	63.15 232	70.78 243	35.35 294	63.27 264	57.47 269	53.00 196	68.31 237	77.09 244	32.45 297	72.09 227	35.61 297	81.73 214	82.02 153

MVS		60.62 242	59.97 240	62.58 241	68.13 270	47.28 217	68.59 204	73.96 187	32.19 326	59.94 290	68.86 316	50.48 223	77.64 176	41.85 261	75.74 270	62.83 313

tfpn200view9		60.35 243	59.97 240	61.51 248	70.78 243	35.35 294	63.27 264	57.47 269	53.00 196	68.31 237	77.09 244	32.45 297	72.09 227	35.61 297	81.73 214	77.08 218

Patchmatch-RL test		59.95 244	59.12 244	62.44 242	72.46 233	54.61 154	59.63 289	47.51 319	41.05 286	74.58 178	74.30 276	31.06 313	65.31 278	51.61 195	79.85 243	67.39 291

1314		59.83 245	58.86 252	62.74 240	65.71 287	44.78 232	68.59 204	72.63 196	33.54 324	61.05 280	67.29 323	43.62 251	71.26 237	49.49 211	67.84 313	72.19 252

IB-MVS	49.67 18	59.69 246	56.96 265	67.90 196	68.19 269	50.30 173	61.42 279	65.18 240	47.57 247	55.83 308	67.15 324	23.77 343	79.60 142	43.56 244	79.97 242	73.79 238
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		59.48 247	58.99 246	60.96 255	77.84 143	42.39 245	61.42 279	68.45 227	37.96 298	59.93 291	67.46 321	45.11 242	65.07 280	40.89 267	71.81 291	75.41 227

FPMVS		59.43 248	60.07 239	57.51 275	77.62 148	71.52 44	62.33 267	50.92 307	57.40 139	69.40 230	80.00 218	39.14 271	61.92 291	37.47 288	66.36 316	39.09 345

conf0.002		59.26 249	58.88 247	60.40 259	68.66 259	31.96 320	62.04 269	51.95 300	50.99 216	67.57 243	75.91 253	28.59 329	69.07 250	42.77 247	81.40 222	80.18 188

CVMVSNet		59.21 250	58.44 257	61.51 248	73.94 199	47.76 205	71.31 173	64.56 242	26.91 343	60.34 285	70.44 304	36.24 283	67.65 264	53.57 189	68.66 310	69.12 283

CR-MVSNet		58.96 251	58.49 256	60.36 260	66.37 281	48.24 194	70.93 178	56.40 279	32.87 325	61.35 276	86.66 127	33.19 292	63.22 285	48.50 219	70.17 300	69.62 278

EPNet_dtu		58.93 252	58.52 255	60.16 262	67.91 273	47.70 206	69.97 186	58.02 265	49.73 228	47.28 333	73.02 288	38.14 276	62.34 289	36.57 293	85.99 163	70.43 266
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test_1112_low_res		58.78 253	58.69 254	59.04 267	79.41 120	38.13 274	57.62 296	66.98 232	34.74 313	59.62 292	77.56 241	42.92 255	63.65 284	38.66 277	70.73 297	75.35 229

PatchMatch-RL		58.68 254	57.72 259	61.57 247	76.21 161	73.59 39	61.83 274	49.00 314	47.30 249	61.08 278	68.97 313	50.16 225	59.01 298	36.06 296	68.84 308	52.10 334

thresconf0.02		58.38 255	58.88 247	56.91 278	68.66 259	31.96 320	62.04 269	51.95 300	50.99 216	67.57 243	75.91 253	28.59 329	69.07 250	42.77 247	81.40 222	69.70 273

tfpn_n400		58.38 255	58.88 247	56.91 278	68.66 259	31.96 320	62.04 269	51.95 300	50.99 216	67.57 243	75.91 253	28.59 329	69.07 250	42.77 247	81.40 222	69.70 273

tfpnconf		58.38 255	58.88 247	56.91 278	68.66 259	31.96 320	62.04 269	51.95 300	50.99 216	67.57 243	75.91 253	28.59 329	69.07 250	42.77 247	81.40 222	69.70 273

tfpnview11		58.38 255	58.88 247	56.91 278	68.66 259	31.96 320	62.04 269	51.95 300	50.99 216	67.57 243	75.91 253	28.59 329	69.07 250	42.77 247	81.40 222	69.70 273

tfpn1000		58.28 259	58.86 252	56.53 282	68.05 271	32.26 317	62.58 266	51.67 306	51.25 214	67.38 248	75.95 252	27.24 335	68.83 255	43.51 245	82.11 209	68.49 286

CHOSEN 1792x2688		58.09 260	56.30 269	63.45 231	79.95 114	50.93 170	54.07 306	65.59 237	28.56 339	61.53 275	74.33 275	41.09 263	66.52 276	33.91 306	67.69 314	72.92 243

HY-MVS	49.31 19	57.96 261	57.59 260	59.10 266	66.85 279	36.17 287	65.13 249	65.39 239	39.24 291	54.69 314	78.14 238	44.28 247	67.18 269	33.75 307	70.79 296	73.95 236

Patchmatch-test1		57.81 262	58.04 258	57.13 276	70.17 249	41.07 253	65.19 248	53.38 295	43.34 278	61.00 281	71.94 297	45.20 241	62.69 287	41.81 262	70.31 299	67.63 290

tpmp4_e23		57.57 263	55.46 276	63.93 226	66.48 280	41.56 250	71.68 163	60.65 257	35.64 309	55.35 311	76.25 250	29.53 325	75.41 196	34.40 303	69.12 307	74.83 231

thres200		57.55 264	57.02 264	59.17 265	67.89 274	34.93 298	58.91 293	57.25 273	50.24 225	64.01 264	71.46 302	32.49 296	71.39 236	31.31 313	79.57 248	71.19 262

CostFormer		57.35 265	56.14 270	60.97 254	63.76 296	38.43 270	67.50 216	60.22 258	37.14 302	59.12 293	76.34 249	32.78 294	71.99 231	39.12 274	69.27 306	72.47 248

tfpn_ndepth		56.91 266	57.30 263	55.71 283	67.22 277	33.26 312	61.72 276	53.98 290	48.49 237	64.16 263	71.94 297	27.65 334	68.71 256	40.49 269	80.08 240	65.17 305

tpm2		56.12 267	54.64 279	60.55 258	66.24 284	36.01 288	68.14 211	56.77 278	33.60 323	58.25 297	75.52 262	30.25 319	74.33 207	33.27 308	69.76 305	71.32 258

no-one		56.11 268	55.62 274	57.60 274	62.68 299	49.23 182	39.12 339	58.99 263	33.72 319	60.98 282	80.90 210	36.07 284	60.36 294	30.68 315	97.40 1	63.22 312

tpmvs		55.84 269	55.45 277	57.01 277	60.33 313	33.20 313	65.89 239	59.29 262	47.52 248	56.04 306	73.60 282	31.05 314	68.06 261	40.64 268	64.64 319	69.77 272

gg-mvs-nofinetune		55.75 270	56.75 267	52.72 291	62.87 298	28.04 333	68.92 197	41.36 340	71.09 31	50.80 324	92.63 12	20.74 346	66.86 271	29.97 320	72.41 288	63.25 311

test20.03		55.74 271	57.51 261	50.42 295	59.89 316	32.09 318	50.63 313	49.01 313	50.11 226	65.07 260	83.23 185	45.61 240	48.11 315	30.22 318	83.82 197	71.07 264

MS-PatchMatch		55.59 272	54.89 278	57.68 273	69.18 257	49.05 183	61.00 283	62.93 247	35.98 306	58.36 296	68.93 314	36.71 282	66.59 275	37.62 287	63.30 322	57.39 327

XXY-MVS		55.19 273	57.40 262	48.56 305	64.45 293	34.84 300	51.54 312	53.59 293	38.99 292	63.79 265	79.43 226	56.59 199	45.57 320	36.92 291	71.29 293	65.25 304

FMVSNet5		55.08 274	55.54 275	53.71 288	65.80 286	33.50 311	56.22 299	52.50 299	43.72 273	61.06 279	83.38 178	25.46 340	54.87 303	30.11 319	81.64 220	72.75 245

PatchmatchNet		54.60 275	54.27 281	55.59 284	65.17 291	39.08 265	66.92 225	51.80 305	39.89 289	58.39 295	73.12 287	31.69 303	58.33 299	43.01 246	58.38 337	69.38 281
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MIMVSNet		54.39 276	56.12 271	49.20 300	72.57 232	30.91 326	59.98 287	48.43 316	41.66 283	55.94 307	83.86 174	41.19 262	50.42 309	26.05 329	75.38 276	66.27 299

Anonymous20231206		54.13 277	55.82 272	49.04 303	70.89 241	35.96 289	51.73 311	50.87 308	34.86 311	62.49 270	79.22 230	42.52 257	44.29 329	27.95 327	81.88 213	66.88 295

JIA-IIPM		54.03 278	51.62 291	61.25 252	59.14 321	55.21 148	59.10 291	47.72 318	50.85 222	50.31 328	85.81 151	20.10 348	63.97 283	36.16 295	55.41 342	64.55 309

tpm cat1		54.02 279	52.63 287	58.19 271	64.85 292	39.86 262	66.26 232	57.28 272	32.16 327	56.90 302	70.39 306	32.75 295	65.30 279	34.29 304	58.79 333	69.41 280

testgi		54.00 280	56.86 266	45.45 313	58.20 327	25.81 339	49.05 316	49.50 312	45.43 260	67.84 239	81.17 209	51.81 219	43.20 333	29.30 323	79.41 249	67.34 293

PatchFormer-LS_test		53.94 281	52.64 286	57.85 272	61.87 304	39.59 263	61.60 277	57.63 267	40.65 287	54.52 315	58.64 338	29.07 328	64.18 282	46.78 232	62.98 324	69.78 271

PatchT		53.35 282	56.47 268	43.99 320	64.19 294	17.46 347	59.15 290	43.10 330	52.11 203	54.74 313	86.95 114	29.97 322	49.98 312	43.62 243	74.40 280	64.53 310

DWT-MVSNet_test		53.04 283	51.12 294	58.77 268	61.23 307	38.67 269	62.16 268	57.74 266	38.24 295	51.76 322	59.07 337	21.36 345	67.40 267	44.80 238	63.76 321	70.25 268

LP		53.02 284	52.27 290	55.27 285	55.76 339	40.55 257	55.64 302	55.07 282	42.46 279	56.95 301	73.21 286	33.67 290	54.18 307	38.41 280	59.29 332	71.08 263

testmv		52.91 285	54.31 280	48.71 304	72.13 237	36.18 286	50.26 314	47.78 317	44.15 268	64.61 261	79.78 222	38.18 275	50.20 311	21.96 340	69.93 302	59.75 324

new-patchmatchnet		52.89 286	55.76 273	44.26 319	59.94 315	6.31 353	37.36 343	50.76 309	41.10 284	64.28 262	79.82 221	44.77 243	48.43 314	36.24 294	87.61 139	78.03 209

YYNet1		52.58 287	53.50 283	49.85 296	54.15 345	36.45 285	40.53 334	46.55 322	38.09 297	75.52 165	73.31 285	41.08 264	43.88 330	41.10 265	71.14 295	69.21 282

MDA-MVSNet_test_wron		52.57 288	53.49 284	49.81 297	54.24 344	36.47 284	40.48 335	46.58 321	38.13 296	75.47 166	73.32 284	41.05 265	43.85 331	40.98 266	71.20 294	69.10 284

pmmvs5		52.49 289	52.58 288	52.21 293	54.99 342	32.38 316	55.45 303	53.84 292	32.15 328	55.49 310	74.81 267	38.08 277	57.37 301	34.02 305	74.40 280	66.88 295

UnsupCasMVSNet_eth		52.26 290	53.29 285	49.16 301	55.08 341	33.67 306	50.03 315	58.79 264	37.67 299	63.43 269	74.75 269	41.82 260	45.83 319	38.59 279	59.42 331	67.98 289

N_pmnet		52.06 291	51.11 295	54.92 286	59.64 318	71.03 49	37.42 342	61.62 255	33.68 320	57.12 299	72.10 289	37.94 278	31.03 348	29.13 326	71.35 292	62.70 314

PVSNet	43.83 21	51.56 292	51.17 293	52.73 290	68.34 267	38.27 272	48.22 319	53.56 294	36.41 304	54.29 316	64.94 327	34.60 287	54.20 306	30.34 317	69.87 303	65.71 302

tpm		50.60 293	52.42 289	45.14 315	65.18 290	26.29 337	60.30 285	43.50 329	37.41 300	57.01 300	79.09 234	30.20 321	42.32 335	32.77 310	66.36 316	66.81 297

test-LLR		50.43 294	50.69 297	49.64 298	60.76 310	41.87 247	53.18 308	45.48 327	43.41 276	49.41 329	60.47 335	29.22 326	44.73 326	42.09 259	72.14 289	62.33 317

tpmrst		50.15 295	51.38 292	46.45 310	56.05 335	24.77 341	64.40 255	49.98 310	36.14 305	53.32 319	69.59 310	35.16 286	48.69 313	39.24 273	58.51 336	65.89 300

UnsupCasMVSNet_bld		50.01 296	51.03 296	46.95 306	58.61 324	32.64 315	48.31 318	53.27 296	34.27 316	60.47 284	71.53 301	41.40 261	47.07 317	30.68 315	60.78 327	61.13 319

WTY-MVS		49.39 297	50.31 298	46.62 309	61.22 308	32.00 319	46.61 324	49.77 311	33.87 318	54.12 317	69.55 311	41.96 259	45.40 322	31.28 314	64.42 320	62.47 316

ADS-MVSNet2		48.76 298	47.25 307	53.29 289	55.90 337	40.54 258	47.34 322	54.99 288	31.41 334	50.48 325	72.06 295	31.23 310	54.26 305	25.93 330	55.93 339	65.07 306

test-mter		48.56 299	48.20 304	49.64 298	60.76 310	41.87 247	53.18 308	45.48 327	31.91 332	49.41 329	60.47 335	18.34 349	44.73 326	42.09 259	72.14 289	62.33 317

test1235678		48.41 300	49.60 300	44.83 317	68.52 264	33.81 305	46.33 326	45.89 324	38.72 294	58.46 294	72.08 290	29.85 324	47.82 316	19.67 344	66.91 315	52.88 332

Patchmatch-test		47.93 301	49.96 299	41.84 324	57.42 331	24.26 342	48.75 317	41.49 339	39.30 290	56.79 303	73.48 283	30.48 318	33.87 347	29.29 324	72.61 287	67.39 291

test0.0.03 1		47.72 302	48.31 303	45.93 311	55.53 340	29.39 328	46.40 325	41.21 341	43.41 276	55.81 309	67.65 320	29.22 326	43.77 332	25.73 332	69.87 303	64.62 308

sss		47.59 303	48.32 302	45.40 314	56.73 334	33.96 303	45.17 328	48.51 315	32.11 330	52.37 321	65.79 325	40.39 268	41.91 338	31.85 311	61.97 325	60.35 320

pmmvs3		46.71 304	45.09 312	51.55 294	56.76 333	48.25 193	55.78 301	39.53 345	24.13 346	50.35 327	63.40 329	15.90 353	51.08 308	29.29 324	70.69 298	55.33 330

EPMVS		45.74 305	46.53 308	43.39 321	54.14 346	22.33 344	55.02 304	35.00 348	34.69 314	51.09 323	70.20 308	25.92 338	42.04 337	37.19 289	55.50 341	65.78 301

MVS-HIRNet		45.53 306	47.29 306	40.24 328	62.29 303	26.82 336	56.02 300	37.41 346	29.74 338	43.69 344	81.27 207	33.96 289	55.48 302	24.46 335	56.79 338	38.43 346

testpf		45.32 307	48.47 301	35.88 333	53.56 347	26.84 335	58.86 294	42.95 331	47.78 245	46.18 335	63.70 328	13.73 354	50.29 310	50.81 201	58.61 335	30.51 348

TESTMET0.1,1		45.17 308	44.93 313	45.89 312	56.02 336	38.31 271	53.18 308	41.94 338	27.85 340	44.86 339	56.47 340	17.93 350	41.50 340	38.08 283	68.06 311	57.85 326

E-PMN		45.17 308	45.36 311	44.60 318	50.07 348	42.75 242	38.66 340	42.29 336	46.39 253	39.55 346	51.15 345	26.00 337	45.37 323	37.68 285	76.41 267	45.69 341

1111		45.08 310	47.96 305	36.43 332	59.56 319	14.82 349	43.56 329	45.65 325	45.60 256	60.04 286	75.47 263	9.31 356	34.46 345	23.66 336	68.76 309	60.02 322

testus		45.03 311	46.49 309	40.65 327	62.53 300	25.24 340	42.54 331	46.23 323	31.16 336	57.69 298	62.90 330	34.60 287	42.33 334	17.72 346	63.01 323	54.37 331

PMMVS		44.69 312	43.95 317	46.92 307	50.05 349	53.47 161	48.08 321	42.40 334	22.36 347	44.01 343	53.05 342	42.60 256	45.49 321	31.69 312	61.36 326	41.79 343

ADS-MVSNet		44.62 313	45.58 310	41.73 325	55.90 337	20.83 345	47.34 322	39.94 344	31.41 334	50.48 325	72.06 295	31.23 310	39.31 341	25.93 330	55.93 339	65.07 306

EMVS		44.61 314	44.45 316	45.10 316	48.91 350	43.00 240	37.92 341	41.10 342	46.75 250	38.00 348	48.43 347	26.42 336	46.27 318	37.11 290	75.38 276	46.03 340

dp		44.09 315	44.88 314	41.72 326	58.53 325	23.18 343	54.70 305	42.38 335	34.80 312	44.25 342	65.61 326	24.48 342	44.80 325	29.77 321	49.42 345	57.18 328

DSMNet-mixed		43.18 316	44.66 315	38.75 330	54.75 343	28.88 331	57.06 298	27.42 352	13.47 348	47.27 334	77.67 240	38.83 272	39.29 342	25.32 334	60.12 329	48.08 337

CHOSEN 280x420		41.62 317	39.89 323	46.80 308	61.81 305	51.59 166	33.56 345	35.74 347	27.48 341	37.64 349	53.53 341	23.24 344	42.09 336	27.39 328	58.64 334	46.72 339

PVSNet_0	36.71 22	41.12 318	40.78 320	42.14 322	59.97 314	40.13 260	40.97 333	42.24 337	30.81 337	44.86 339	49.41 346	40.70 266	45.12 324	23.15 338	34.96 347	41.16 344

test2356		40.85 319	40.47 321	41.98 323	58.78 323	28.65 332	39.45 337	40.98 343	31.95 331	48.47 331	56.63 339	12.54 355	44.41 328	15.84 348	59.58 330	52.88 332

test12356		38.35 320	40.80 319	31.01 334	58.31 326	9.09 352	36.67 344	46.65 320	33.65 322	44.39 341	60.94 334	17.56 351	39.23 343	16.01 347	53.03 343	44.72 342

PMMVS2		37.74 321	40.87 318	28.36 337	42.41 352	5.35 354	24.61 346	27.75 351	32.15 328	47.85 332	70.27 307	35.85 285	29.51 349	19.08 345	67.85 312	50.22 336

new_pmnet		37.55 322	39.80 324	30.79 335	56.83 332	16.46 348	39.35 338	30.65 350	25.59 344	45.26 337	61.60 333	24.54 341	28.02 350	21.60 341	52.80 344	47.90 338

PNet_i23d		36.76 323	36.63 326	37.12 331	58.19 328	33.00 314	39.86 336	32.55 349	48.44 238	39.64 345	51.31 344	6.89 358	41.83 339	22.29 339	30.55 348	36.54 347

MVE	27.91 23	36.69 324	35.64 327	39.84 329	43.37 351	35.85 291	19.49 347	24.61 353	24.68 345	39.05 347	62.63 332	38.67 274	27.10 351	21.04 342	47.25 346	56.56 329
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
pcd1.5k->3k		35.00 325	36.93 325	29.21 336	84.62 65	0.00 358	0.00 349	78.90 137	0.00 353	0.00 354	0.00 355	78.26 15	0.00 356	0.00 353	90.55 100	87.62 65

.test1245		34.47 326	40.38 322	16.73 338	59.56 319	14.82 349	43.56 329	45.65 325	45.60 256	60.04 286	75.47 263	9.31 356	34.46 345	23.66 336	0.55 352	0.90 351

cdsmvs_eth3d_5k		17.71 327	23.62 328	0.00 343	0.00 357	0.00 358	0.00 349	70.17 221	0.00 353	0.00 354	74.25 277	68.16 82	0.00 356	0.00 353	0.00 354	0.00 354

tmp_tt		11.98 328	14.73 329	3.72 340	2.28 354	4.62 355	19.44 348	14.50 355	0.47 350	21.55 350	9.58 350	25.78 339	4.57 353	11.61 349	27.37 349	1.96 350

ab-mvs-re		5.62 329	7.50 330	0.00 343	0.00 357	0.00 358	0.00 349	0.00 359	0.00 353	0.00 354	67.46 321	0.00 361	0.00 356	0.00 353	0.00 354	0.00 354

pcd_1.5k_mvsjas		5.20 330	6.93 331	0.00 343	0.00 357	0.00 358	0.00 349	0.00 359	0.00 353	0.00 354	0.00 355	62.39 123	0.00 356	0.00 353	0.00 354	0.00 354

test123		4.43 331	5.78 332	0.39 342	0.97 355	0.28 356	46.33 326	0.45 357	0.31 351	0.62 352	1.50 353	0.61 360	0.11 355	0.56 351	0.63 351	0.77 353

testmvs		4.06 332	5.28 333	0.41 341	0.64 356	0.16 357	42.54 331	0.31 358	0.26 352	0.50 353	1.40 354	0.77 359	0.17 354	0.56 351	0.55 352	0.90 351

sosnet-low-res		0.00 333	0.00 334	0.00 343	0.00 357	0.00 358	0.00 349	0.00 359	0.00 353	0.00 354	0.00 355	0.00 361	0.00 356	0.00 353	0.00 354	0.00 354

sosnet		0.00 333	0.00 334	0.00 343	0.00 357	0.00 358	0.00 349	0.00 359	0.00 353	0.00 354	0.00 355	0.00 361	0.00 356	0.00 353	0.00 354	0.00 354

uncertanet		0.00 333	0.00 334	0.00 343	0.00 357	0.00 358	0.00 349	0.00 359	0.00 353	0.00 354	0.00 355	0.00 361	0.00 356	0.00 353	0.00 354	0.00 354

Regformer		0.00 333	0.00 334	0.00 343	0.00 357	0.00 358	0.00 349	0.00 359	0.00 353	0.00 354	0.00 355	0.00 361	0.00 356	0.00 353	0.00 354	0.00 354

uanet		0.00 333	0.00 334	0.00 343	0.00 357	0.00 358	0.00 349	0.00 359	0.00 353	0.00 354	0.00 355	0.00 361	0.00 356	0.00 353	0.00 354	0.00 354

GSMVS																70.05 269

test_part3							83.39 33		73.27 20		89.25 80		86.96 9	72.56 45

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

sam_mvs1												31.41 308				70.05 269

sam_mvs												31.21 312

semantic-postprocess				72.49 141	73.34 213	58.20 139		65.55 238	48.10 240	76.91 146	82.64 190	42.25 258	78.84 150	61.20 133	77.89 263	80.44 185

ambc				70.10 171	77.74 145	50.21 174	74.28 135	77.93 156		79.26 120	88.29 102	54.11 209	79.77 140	64.43 117	91.10 86	80.30 186

MTGPA								80.63 106

test_post1							66.63 228				2.08 351	30.66 317	59.33 297	40.34 271

test_post											1.99 352	30.91 315	54.76 304

patchmatchnet-post											68.99 312	31.32 309	69.38 247

GG-mvs-BLEND				52.24 292	60.64 312	29.21 330	69.73 191	42.41 333		45.47 336	52.33 343	20.43 347	68.16 260	25.52 333	65.42 318	59.36 325

MTMP								19.26 354

gm-plane-assit					62.51 301	33.91 304			37.25 301		62.71 331		72.74 218	38.70 276

test9_res														72.12 53	91.37 79	77.40 214

TEST9					85.47 52	69.32 64	76.42 98	78.69 140	53.73 189	76.97 142	86.74 123	66.84 92	81.10 111

test_8					85.09 57	67.89 73	76.26 103	78.66 142	54.00 184	76.89 147	86.72 125	66.60 94	80.89 122

agg_prior2														70.70 61	90.93 91	78.55 203

agg_prior					84.44 70	66.02 83		78.62 143		76.95 144			80.34 131

TestCases				78.35 59	79.19 126	70.81 51		88.64 2	65.37 65	80.09 112	88.17 103	70.33 64	78.43 162	55.60 170	90.90 93	85.81 83

test_prior4						70.14 58	77.57 82

test_prior2							75.57 115		58.92 127	76.53 154	86.78 120	67.83 86		69.81 69	92.76 60

test_prior				75.27 90	82.15 96	59.85 125		84.33 38					83.39 66			82.58 141

旧先验2							71.17 175		45.11 263	78.54 127			61.28 293	59.19 145

新几何2							71.33 172

新几何1				69.99 173	88.37 30	71.34 47		62.08 250	43.85 269	74.99 170	86.11 146	52.85 213	70.57 241	50.99 200	83.23 202	68.05 288

旧先验1					84.55 67	60.36 121		63.69 244			87.05 113	54.65 207			83.34 200	69.66 277

无先验							74.82 126	70.94 215	47.75 246				76.85 183	54.47 180		72.09 253

原ACMM2							74.78 130

原ACMM1				73.90 102	85.90 45	65.15 91		81.67 80	50.97 221	74.25 180	86.16 144	61.60 131	83.54 62	56.75 158	91.08 87	73.00 242

test222					87.30 34	69.15 67	67.85 213	59.59 261	41.06 285	73.05 193	85.72 152	48.03 234			80.65 235	66.92 294

testdata2													67.30 268	48.34 220

segment_acmp												68.30 81

testdata				64.13 223	85.87 48	63.34 103		61.80 254	47.83 244	76.42 158	86.60 132	48.83 230	62.31 290	54.46 182	81.26 227	66.74 298

testdata1							68.34 210		57.24 140

test12				76.51 72	82.28 94	60.94 118		81.64 81		73.60 186		64.88 107	85.19 40		90.42 102	83.38 126

plane_prior7					85.18 54	66.21 82

plane_prior6					84.18 74	65.31 88						60.83 141

plane_prior5								85.49 21					86.15 21	71.09 55	90.94 89	84.82 94

plane_prior4											89.11 86

plane_prior3						65.67 85			63.82 85	78.23 132

plane_prior2							82.74 37		65.45 62

plane_prior1					84.46 69

plane_prior						65.18 89	80.06 60		61.88 102						89.91 112

n2								0.00 359

nn								0.00 359

door-mid								55.02 283

lessismore_v0				72.75 136	79.60 118	56.83 143		57.37 271		83.80 69	89.01 89	47.45 236	78.74 153	64.39 118	86.49 159	82.69 140

LGP-MVS_train				80.90 32	87.00 36	70.41 56		86.35 12	69.77 40	87.75 18	91.13 35	81.83 3	86.20 18	77.13 26	95.96 7	86.08 77

test11								82.71 67

door								52.91 298

HQP5-MVS						58.80 134

HQP-NCC					82.37 91		77.32 86		59.08 123	71.58 208

ACMP_Plane					82.37 91		77.32 86		59.08 123	71.58 208

BP-MVS														67.38 94

HQP4-MVS										71.59 207			85.31 34			83.74 118

HQP3-MVS								84.12 45							89.16 119

HQP2-MVS												58.09 175

NP-MVS					83.34 81	63.07 106					85.97 149

MDTV_nov1_ep13_2view						18.41 346	53.74 307		31.57 333	44.89 338		29.90 323		32.93 309		71.48 257

MDTV_nov1_ep13			54.05 282		65.54 288	29.30 329	59.00 292	55.22 281	35.96 307	52.44 320	75.98 251	30.77 316	59.62 296	38.21 281	73.33 285

ACMMP++_ref															89.47 117

ACMMP++															91.96 69

Test By Simon												62.56 119

ITE_SJBPF				80.35 37	76.94 154	73.60 38		80.48 110	66.87 50	83.64 71	86.18 142	70.25 66	79.90 139	61.12 134	88.95 123	87.56 67

DeepMVS_CX				11.83 339	15.51 353	13.86 351		11.25 356	5.76 349	20.85 351	26.46 348	17.06 352	9.22 352	9.69 350	13.82 350	12.42 349

High-resolution multi-view benchmark