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	63.30 105	84.80 26	87.77 7	86.18 1	96.26 2	96.06 1	90.32 1	84.49 49	68.08 83	97.05 3	96.93 1

TDRefinement		86.32 2	86.33 2	86.29 1	88.64 29	81.19 6	88.84 2	90.72 1	78.27 7	87.95 17	92.53 13	79.37 11	84.79 46	74.51 36	96.15 4	92.88 9

abl_6		84.92 3	85.70 3	82.57 14	86.72 40	79.27 8	87.56 5	86.08 16	77.48 9	88.12 16	91.53 31	81.18 6	84.31 54	78.12 22	94.47 35	84.15 116

HPM-MVS_fast		84.59 4	85.10 4	83.06 4	88.60 30	75.83 23	86.27 19	86.89 11	73.69 17	86.17 39	91.70 26	78.23 15	85.20 39	79.45 12	94.91 26	88.15 62

ACMMP		84.22 5	84.84 6	82.35 17	89.23 22	76.66 22	87.65 4	85.89 18	71.03 31	85.85 44	90.58 52	78.77 13	85.78 29	79.37 15	95.17 18	84.62 103
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 62	75.40 26	91.60 1	87.80 5	73.52 18	88.90 13	93.06 6	71.39 58	81.53 92	81.53 3	92.15 69	88.91 48
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 33	74.40 31	85.24 22	87.21 9	70.69 34	85.14 53	90.42 61	78.99 12	86.62 11	80.83 6	94.93 25	86.79 74
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CP-MVS		84.12 7	84.55 8	82.80 9	89.42 18	79.74 7	88.19 3	84.43 39	71.96 28	84.70 61	90.56 53	77.12 17	86.18 20	79.24 17	95.36 14	82.49 151

mPP-MVS		84.01 9	84.39 9	82.88 5	90.65 4	81.38 5	87.08 9	82.79 67	72.41 24	85.11 55	90.85 45	76.65 20	84.89 43	79.30 16	94.63 32	82.35 153

COLMAP_ROB	72.78 3	83.75 10	84.11 13	82.68 11	82.97 87	74.39 32	87.18 7	88.18 4	78.98 5	86.11 41	91.47 33	79.70 10	85.76 30	66.91 100	95.46 13	87.89 64
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 46	70.23 35	84.49 64	90.67 51	75.15 31	86.37 14	79.58 10	94.26 42	84.18 115

APD-MVS_3200maxsize		83.57 12	84.33 10	81.31 26	82.83 89	73.53 40	85.50 21	87.45 8	74.11 15	86.45 35	90.52 56	80.02 9	84.48 50	77.73 24	94.34 40	85.93 83

region2R		83.54 13	83.86 17	82.58 13	89.82 10	77.53 16	87.06 10	84.23 45	70.19 37	83.86 70	90.72 50	75.20 30	86.27 17	79.41 14	94.25 43	83.95 120

XVS		83.51 14	83.73 18	82.85 7	89.43 16	77.61 14	86.80 13	84.66 35	72.71 22	82.87 78	90.39 63	73.86 41	86.31 15	78.84 18	94.03 46	84.64 101

LPG-MVS_test		83.47 15	84.33 10	80.90 32	87.00 37	70.41 56	82.04 44	86.35 12	69.77 39	87.75 18	91.13 37	81.83 3	86.20 18	77.13 27	95.96 7	86.08 79

HFP-MVS		83.39 16	84.03 14	81.48 22	89.25 20	75.69 24	87.01 11	84.27 42	70.23 35	84.47 65	90.43 58	76.79 18	85.94 26	79.58 10	94.23 44	82.82 142

MTAPA		83.19 17	83.87 16	81.13 29	91.16 2	78.16 12	84.87 24	80.63 110	72.08 25	84.93 56	90.79 46	74.65 35	84.42 51	80.98 4	94.75 28	80.82 182

MP-MVS		83.19 17	83.54 21	82.14 18	90.54 5	79.00 9	86.42 18	83.59 56	71.31 29	81.26 97	90.96 42	74.57 37	84.69 47	78.41 20	94.78 27	82.74 145
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
PGM-MVS		83.07 19	83.25 26	82.54 15	89.57 14	77.21 20	82.04 44	85.40 23	67.96 47	84.91 58	90.88 43	75.59 27	86.57 12	78.16 21	94.71 30	83.82 121

SteuartSystems-ACMMP		83.07 19	83.64 19	81.35 25	85.14 58	71.00 50	85.53 20	84.78 32	70.91 32	85.64 45	90.41 62	75.55 28	87.69 3	79.75 7	95.08 21	85.36 90
Skip Steuart: Steuart Systems R&D Blog.
zzz-MVS		83.01 21	83.63 20	81.13 29	91.16 2	78.16 12	82.72 40	80.63 110	72.08 25	84.93 56	90.79 46	74.65 35	84.42 51	80.98 4	94.75 28	80.82 182

APDe-MVS		82.88 22	84.14 12	79.08 50	84.80 64	66.72 79	86.54 16	85.11 26	72.00 27	86.65 33	91.75 25	78.20 16	87.04 8	77.93 23	94.32 41	83.47 129

ACMP	69.50 8	82.64 23	83.38 23	80.40 37	86.50 42	69.44 63	82.30 41	86.08 16	66.80 53	86.70 32	89.99 73	81.64 5	85.95 25	74.35 37	96.11 5	85.81 85
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 41	88.88 28	68.44 71	81.57 47	86.33 14	63.17 96	85.38 52	91.26 36	76.33 22	84.67 48	83.30 1	94.96 24	86.17 78
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
#test#		82.40 25	82.71 32	81.48 22	89.25 20	75.69 24	84.47 28	84.27 42	64.45 78	84.47 65	90.43 58	76.79 18	85.94 26	76.01 31	94.23 44	82.82 142

ACMMP_Plus		82.33 26	83.28 25	79.46 46	89.28 19	69.09 69	83.62 33	84.98 27	64.77 75	83.97 69	91.02 40	75.53 29	85.93 28	82.00 2	94.36 38	83.35 135

SMA-MVS		82.12 27	82.68 33	80.43 36	88.90 27	69.52 61	85.12 23	84.76 33	63.53 91	84.23 68	91.47 33	72.02 52	87.16 6	79.74 9	94.36 38	84.61 104

ACMM	69.25 9	82.11 28	83.31 24	78.49 58	88.17 34	73.96 34	83.11 36	84.52 38	66.40 57	87.45 23	89.16 87	81.02 7	80.52 131	74.27 38	95.73 9	80.98 179
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ESAPD		82.00 29	83.02 28	78.95 53	85.36 55	67.25 78	82.91 37	84.98 27	73.52 18	85.43 51	90.03 72	76.37 21	86.97 10	74.56 35	94.02 48	82.62 147

PMVS	70.70 6	81.70 30	83.15 27	77.36 70	90.35 6	82.82 3	82.15 42	79.22 134	74.08 16	87.16 27	91.97 19	84.80 2	76.97 183	64.98 117	93.61 50	72.28 261
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
UA-Net		81.56 31	82.28 35	79.40 47	88.91 26	69.16 67	84.67 27	80.01 126	75.34 12	79.80 117	94.91 2	69.79 68	80.25 135	72.63 45	94.46 36	88.78 52

CPTT-MVS		81.51 32	81.76 37	80.76 34	89.20 23	78.75 10	86.48 17	82.03 77	68.80 42	80.92 105	88.52 100	72.00 53	82.39 79	74.80 32	93.04 56	81.14 175

ACMH+	66.64 10	81.20 33	82.48 34	77.35 71	81.16 109	62.39 109	80.51 53	87.80 5	73.02 21	87.57 21	91.08 39	80.28 8	82.44 78	64.82 118	96.10 6	87.21 71

APD-MVS		81.13 34	81.73 38	79.36 48	84.47 70	70.53 55	83.85 32	83.70 53	69.43 41	83.67 72	88.96 95	75.89 26	86.41 13	72.62 46	92.95 57	81.14 175
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
3Dnovator+	73.19 2	81.08 35	80.48 45	82.87 6	81.41 106	72.03 42	84.38 29	86.23 15	77.28 11	80.65 108	90.18 70	59.80 156	87.58 4	73.06 43	91.34 81	89.01 43

DeepC-MVS	72.44 4	81.00 36	80.83 44	81.50 21	86.70 41	70.03 60	82.06 43	87.00 10	59.89 124	80.91 106	90.53 54	72.19 48	88.56 1	73.67 41	94.52 34	85.92 84
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 37	81.63 40	79.07 51	86.86 39	69.39 64	79.41 68	84.00 51	65.64 62	85.54 49	89.28 81	76.32 23	83.47 64	74.03 39	93.57 51	84.35 114

LS3D		80.99 37	80.85 43	81.41 24	78.37 137	71.37 46	87.45 6	85.87 19	77.48 9	81.98 85	89.95 74	69.14 71	85.26 36	66.15 107	91.24 83	87.61 67

XVG-ACMP-BASELINE		80.54 39	81.06 42	78.98 52	87.01 36	72.91 41	80.23 59	85.56 20	66.56 56	85.64 45	89.57 78	69.12 72	80.55 130	72.51 47	93.37 52	83.48 128

PEN-MVS		80.46 40	82.91 29	73.11 128	89.83 9	39.02 276	77.06 95	82.61 70	80.04 3	90.60 8	92.85 9	74.93 34	85.21 38	63.15 127	95.15 19	95.09 2

PS-CasMVS		80.41 41	82.86 31	73.07 129	89.93 7	39.21 273	77.15 93	81.28 93	79.74 4	90.87 6	92.73 11	75.03 33	84.93 42	63.83 124	95.19 17	95.07 3

DTE-MVSNet		80.35 42	82.89 30	72.74 140	89.84 8	37.34 291	77.16 92	81.81 81	80.45 2	90.92 5	92.95 7	74.57 37	86.12 24	63.65 125	94.68 31	94.76 6

SD-MVS		80.28 43	81.55 41	76.47 75	83.57 79	67.83 75	83.39 35	85.35 25	64.42 81	86.14 40	87.07 118	74.02 40	80.97 117	77.70 25	92.32 68	80.62 187

WR-MVS_H		80.22 44	82.17 36	74.39 97	89.46 15	42.69 250	78.24 80	82.24 74	78.21 8	89.57 11	92.10 18	68.05 82	85.59 31	66.04 109	95.62 11	94.88 5

HPM-MVS++		79.89 45	79.80 50	80.18 39	89.02 24	78.44 11	83.49 34	80.18 123	64.71 77	78.11 137	88.39 103	65.46 105	83.14 69	77.64 26	91.20 84	78.94 208

HSP-MVS		79.69 46	79.17 55	81.27 28	89.70 12	77.46 19	87.16 8	80.58 113	64.94 74	81.05 102	88.38 104	57.10 201	87.10 7	79.75 7	83.87 200	79.24 205

XVG-OURS-SEG-HR		79.62 47	79.99 48	78.49 58	86.46 43	74.79 30	77.15 93	85.39 24	66.73 54	80.39 112	88.85 97	74.43 39	78.33 170	74.73 34	85.79 167	82.35 153

XVG-OURS		79.51 48	79.82 49	78.58 57	86.11 45	74.96 29	76.33 105	84.95 29	66.89 50	82.75 80	88.99 93	66.82 92	78.37 169	74.80 32	90.76 98	82.40 152

CP-MVSNet		79.48 49	81.65 39	72.98 133	89.66 13	39.06 275	76.76 97	80.46 115	78.91 6	90.32 9	91.70 26	68.49 77	84.89 43	63.40 126	95.12 20	95.01 4

OMC-MVS		79.41 50	78.79 57	81.28 27	80.62 111	70.71 54	80.91 50	84.76 33	62.54 101	81.77 87	86.65 135	71.46 56	83.53 63	67.95 90	92.44 65	89.60 35

v7n		79.37 51	80.41 46	76.28 79	78.67 136	55.81 147	79.22 69	82.51 73	70.72 33	87.54 22	92.44 14	68.00 84	81.34 102	72.84 44	91.72 71	91.69 12

TSAR-MVS + MP.		79.05 52	78.81 56	79.74 42	88.94 25	67.52 76	86.61 15	81.38 92	51.71 215	77.15 144	91.42 35	65.49 104	87.20 5	79.44 13	87.17 155	84.51 109

v52		78.96 53	79.79 51	76.46 76	73.03 232	54.90 150	78.48 75	83.48 57	64.43 79	91.19 4	91.54 29	72.08 49	81.11 110	76.45 29	87.47 144	93.38 7

V4		78.96 53	79.79 51	76.46 76	73.02 233	54.90 150	78.48 75	83.47 58	64.43 79	91.20 3	91.54 29	72.08 49	81.11 110	76.45 29	87.46 146	93.38 7

mvs_tets		78.93 55	78.67 59	79.72 43	84.81 63	73.93 35	80.65 52	76.50 176	51.98 213	87.40 24	91.86 22	76.09 25	78.53 160	68.58 78	90.20 105	86.69 76

test_djsdf		78.88 56	78.27 62	80.70 35	81.42 105	71.24 48	83.98 30	75.72 182	52.27 208	87.37 25	92.25 16	68.04 83	80.56 128	72.28 51	91.15 85	90.32 32

HQP_MVS		78.77 57	78.78 58	78.72 55	85.18 56	65.18 90	82.74 38	85.49 21	65.45 64	78.23 135	89.11 89	60.83 146	86.15 21	71.09 55	90.94 90	84.82 98

anonymousdsp		78.60 58	77.80 66	81.00 31	78.01 142	74.34 33	80.09 60	76.12 178	50.51 233	89.19 12	90.88 43	71.45 57	77.78 178	73.38 42	90.60 100	90.90 26

OurMVSNet-221017-0		78.57 59	78.53 61	78.67 56	80.48 112	64.16 97	80.24 58	82.06 76	61.89 105	88.77 14	93.32 4	57.15 199	82.60 77	70.08 67	92.80 58	89.25 38

jajsoiax		78.51 60	78.16 63	79.59 45	84.65 66	73.83 37	80.42 55	76.12 178	51.33 220	87.19 26	91.51 32	73.79 43	78.44 164	68.27 81	90.13 109	86.49 77

CNVR-MVS		78.49 61	78.59 60	78.16 62	85.86 50	67.40 77	78.12 83	81.50 85	63.92 85	77.51 142	86.56 139	68.43 79	84.82 45	73.83 40	91.61 74	82.26 156

DeepPCF-MVS	71.07 5	78.48 62	77.14 72	82.52 16	84.39 74	77.04 21	76.35 103	84.05 49	56.66 156	80.27 113	85.31 162	68.56 76	87.03 9	67.39 95	91.26 82	83.50 127

DP-MVS		78.44 63	79.29 54	75.90 84	81.86 101	65.33 88	79.05 70	84.63 37	74.83 14	80.41 111	86.27 146	71.68 54	83.45 65	62.45 131	92.40 66	78.92 209

NCCC		78.25 64	78.04 64	78.89 54	85.61 52	69.45 62	79.80 64	80.99 106	65.77 61	75.55 168	86.25 148	67.42 87	85.42 32	70.10 66	90.88 96	81.81 165

test_0402		78.17 65	79.48 53	74.24 99	83.50 80	59.15 133	72.52 150	74.60 192	75.34 12	88.69 15	91.81 23	75.06 32	82.37 80	65.10 115	88.68 128	81.20 172

AllTest		77.66 66	77.43 68	78.35 60	79.19 127	70.81 51	78.60 73	88.64 2	65.37 67	80.09 115	88.17 107	70.33 63	78.43 165	55.60 175	90.90 94	85.81 85

PS-MVSNAJss		77.54 67	77.35 69	78.13 64	84.88 61	66.37 82	78.55 74	79.59 131	53.48 199	86.29 38	92.43 15	62.39 126	80.25 135	67.90 91	90.61 99	87.77 65

ACMH	63.62 14	77.50 68	80.11 47	69.68 179	79.61 118	56.28 145	78.81 71	83.62 55	63.41 94	87.14 28	90.23 69	76.11 24	73.32 217	67.58 92	94.44 37	79.44 203
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CDPH-MVS		77.33 69	77.06 73	78.14 63	84.21 75	63.98 99	76.07 110	83.45 59	54.20 188	77.68 141	87.18 115	69.98 66	85.37 33	68.01 86	92.72 63	85.08 95

DeepC-MVS_fast	69.89 7	77.17 70	76.33 82	79.70 44	83.90 78	67.94 73	80.06 62	83.75 52	56.73 155	74.88 176	85.32 161	65.54 103	87.79 2	65.61 113	91.14 86	83.35 135
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	73.87 104	73.94 206	52.44 168	75.90 113	79.98 127	65.34 69	86.97 30	91.77 24	67.40 88	78.40 167	70.23 64	90.01 110	90.76 30

X-MVStestdata		76.81 72	74.79 99	82.85 7	89.43 16	77.61 14	86.80 13	84.66 35	72.71 22	82.87 78	9.95 361	73.86 41	86.31 15	78.84 18	94.03 46	84.64 101

test_prior3		76.71 73	77.19 70	75.27 91	82.15 97	59.85 126	75.57 117	84.33 40	58.92 131	76.53 158	86.78 126	67.83 85	83.39 66	69.81 69	92.76 60	82.58 148

train_agg		76.38 74	76.55 77	75.86 85	85.47 53	69.32 65	76.42 101	78.69 145	54.00 192	76.97 145	86.74 129	66.60 93	81.10 112	72.50 48	91.56 75	77.15 225

agg_prior3		76.32 75	76.33 82	76.28 79	85.86 50	70.13 59	76.50 99	78.26 155	53.41 201	75.78 164	86.49 141	66.58 95	81.57 91	72.50 48	91.56 75	77.15 225

v13		76.23 76	77.02 74	73.86 106	74.61 191	48.80 187	76.91 96	81.10 100	62.66 99	87.02 29	91.01 41	59.76 157	81.41 97	71.29 54	88.78 127	91.38 13

TranMVSNet+NR-MVSNet		76.13 77	77.66 67	71.56 158	84.61 68	42.57 251	70.98 183	78.29 154	68.67 45	83.04 76	89.26 82	72.99 46	80.75 127	55.58 178	95.47 12	91.35 14

v12		76.03 78	76.79 75	73.76 108	74.45 193	48.60 193	76.59 98	81.11 97	62.22 104	86.79 31	90.74 49	59.51 158	81.40 99	71.01 57	88.67 129	91.29 15

agg_prior1		75.89 79	76.41 80	74.31 98	84.44 72	66.02 84	76.12 109	78.62 148	54.40 186	76.95 147	86.85 123	66.44 97	80.34 133	72.45 50	91.42 79	76.57 230

V9		75.82 80	76.53 78	73.66 109	74.28 197	48.37 194	76.26 106	81.10 100	61.73 107	86.59 34	90.43 58	59.16 164	81.42 96	70.71 60	88.56 130	91.21 18

SixPastTwentyTwo		75.77 81	76.34 81	74.06 102	81.69 103	54.84 152	76.47 100	75.49 184	64.10 84	87.73 20	92.24 17	50.45 230	81.30 104	67.41 94	91.46 78	86.04 81

v11		75.76 82	76.51 79	73.48 116	74.28 197	47.81 206	76.16 108	81.28 93	61.56 108	86.39 36	90.38 64	59.32 162	81.41 97	70.85 58	88.41 132	91.23 16

RPSCF		75.76 82	74.37 105	79.93 40	74.81 182	77.53 16	77.53 87	79.30 133	59.44 126	78.88 126	89.80 76	71.26 59	73.09 219	57.45 158	80.89 242	89.17 41

v10		75.69 84	76.20 86	74.16 100	74.44 195	48.69 189	75.84 115	82.93 66	59.02 130	85.92 43	89.17 86	58.56 173	82.74 75	70.73 59	89.14 123	91.05 20

V14		75.58 85	76.26 84	73.55 114	74.10 205	48.13 199	75.91 112	81.07 103	61.19 111	86.34 37	90.11 71	58.80 168	81.40 99	70.40 62	88.43 131	91.12 19

Anonymous20231211		75.54 86	77.19 70	70.59 166	77.67 150	45.70 235	74.73 134	80.19 122	68.80 42	82.95 77	92.91 8	66.26 98	76.76 188	58.41 154	92.77 59	89.30 37

Effi-MVS+-dtu		75.43 87	72.28 147	84.91 2	77.05 154	83.58 2	78.47 77	77.70 163	57.68 139	74.89 175	78.13 248	64.80 110	84.26 55	56.46 168	85.32 182	86.88 73

v15		75.37 88	76.01 87	73.44 118	73.91 209	47.87 205	75.55 119	81.04 104	60.76 116	86.11 41	89.76 77	58.53 174	81.40 99	70.11 65	88.32 133	91.04 22

wuykxyi23d		75.33 89	76.75 76	71.04 162	78.83 134	85.01 1	71.78 166	61.00 265	53.47 200	96.33 1	93.38 3	73.07 44	68.04 271	65.65 112	97.28 2	60.07 332

Regformer-2		75.32 90	74.47 103	77.88 65	74.22 200	66.65 80	72.77 147	77.54 165	68.47 46	80.44 110	72.08 301	70.60 62	80.97 117	70.08 67	84.02 198	86.01 82

F-COLMAP		75.29 91	73.99 110	79.18 49	81.73 102	71.90 43	81.86 46	82.98 64	59.86 125	72.27 209	84.00 180	64.56 113	83.07 71	51.48 200	87.19 154	82.56 150

HQP-MVS		75.24 92	75.01 98	75.94 83	82.37 92	58.80 135	77.32 89	84.12 47	59.08 127	71.58 214	85.96 157	58.09 181	85.30 35	67.38 96	89.16 121	83.73 124

TAPA-MVS	65.27 12	75.16 93	74.29 107	77.77 67	74.86 181	68.08 72	77.89 84	84.04 50	55.15 171	76.19 163	83.39 185	66.91 90	80.11 139	60.04 143	90.14 108	85.13 93
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
IS-MVSNet		75.10 94	75.42 95	74.15 101	79.23 125	48.05 202	79.43 66	78.04 160	70.09 38	79.17 124	88.02 111	53.04 216	83.60 61	58.05 155	93.76 49	90.79 28

v8		75.07 95	75.64 91	73.35 120	73.42 215	47.46 215	75.20 125	81.45 88	60.05 122	85.64 45	89.26 82	58.08 183	81.80 89	69.71 71	87.97 139	90.79 28

v17		75.03 96	75.59 92	73.36 119	73.56 211	47.66 210	75.48 120	81.45 88	60.58 118	85.55 48	89.02 91	58.36 176	81.47 93	69.69 72	86.59 161	90.96 23

UniMVSNet (Re)		75.00 97	75.48 94	73.56 113	83.14 84	47.92 204	70.41 189	81.04 104	63.67 88	79.54 119	86.37 145	62.83 120	81.82 88	57.10 162	95.25 16	90.94 25

Anonymous20240521		74.99 98	76.21 85	71.33 161	77.99 143	44.41 242	75.24 124	77.16 172	65.86 60	84.89 59	91.96 20	60.23 150	79.31 147	59.86 145	92.75 62	90.27 33

PHI-MVS		74.92 99	74.36 106	76.61 72	76.40 163	62.32 110	80.38 56	83.15 62	54.16 190	73.23 196	80.75 218	62.19 129	83.86 57	68.02 85	90.92 93	83.65 125

DU-MVS		74.91 100	75.57 93	72.93 135	83.50 80	45.79 233	69.47 199	80.14 124	65.22 70	81.74 89	87.08 116	61.82 132	81.07 114	56.21 171	94.98 22	91.93 10

UniMVSNet_NR-MVSNet		74.90 101	75.65 90	72.64 142	83.04 85	45.79 233	69.26 201	78.81 143	66.66 55	81.74 89	86.88 122	63.26 118	81.07 114	56.21 171	94.98 22	91.05 20

v16		74.89 102	75.41 96	73.35 120	73.54 212	47.62 211	75.47 121	81.45 88	60.58 118	85.46 50	88.97 94	58.27 177	81.47 93	69.66 73	85.25 183	90.95 24

nrg030		74.87 103	75.99 88	71.52 159	74.90 180	49.88 182	74.10 140	82.58 72	54.55 185	83.50 74	89.21 85	71.51 55	75.74 197	61.24 136	92.34 67	88.94 47

Vis-MVSNet		74.85 104	74.56 101	75.72 86	81.63 104	64.64 94	76.35 103	79.06 139	62.85 98	73.33 194	88.41 102	62.54 124	79.59 145	63.94 123	82.92 209	82.94 139
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Regformer-4		74.64 105	73.67 114	77.55 68	74.74 184	64.49 96	72.91 144	75.42 187	67.45 48	80.24 114	72.07 304	68.98 73	80.19 138	70.29 63	80.91 240	87.98 63

v18		74.60 106	75.06 97	73.22 125	73.29 221	47.36 219	75.02 126	81.47 87	60.01 123	85.13 54	88.44 101	57.93 190	81.47 93	69.26 75	85.02 187	90.84 27

MVS_0304		74.55 107	73.47 118	77.80 66	77.41 153	63.88 100	75.75 116	83.67 54	63.55 90	66.12 266	82.16 205	60.20 151	86.15 21	65.37 114	86.98 157	83.38 132

MSLP-MVS++		74.48 108	75.78 89	70.59 166	84.66 65	62.40 108	78.65 72	84.24 44	60.55 120	77.71 140	81.98 207	63.12 119	77.64 179	62.95 128	88.14 135	71.73 266

Regformer-1		74.28 109	73.63 116	76.21 82	74.22 200	64.12 98	72.77 147	75.46 186	66.86 52	79.27 122	72.08 301	69.29 70	78.74 156	68.73 77	84.02 198	85.77 88

AdaColmap		74.22 110	74.56 101	73.20 126	81.95 99	60.97 118	79.43 66	80.90 107	65.57 63	72.54 206	81.76 211	70.98 61	85.26 36	47.88 229	90.00 111	73.37 249

CSCG		74.12 111	74.39 104	73.33 122	79.35 122	61.66 115	77.45 88	81.98 78	62.47 103	79.06 125	80.19 224	61.83 131	78.79 155	59.83 146	87.35 149	79.54 202

PAPM_NR		73.91 112	74.16 108	73.16 127	81.90 100	53.50 162	81.28 48	81.40 91	66.17 58	73.30 195	83.31 189	59.96 152	83.10 70	58.45 153	81.66 227	82.87 140

EPP-MVSNet		73.86 113	73.38 121	75.31 90	78.19 139	53.35 165	80.45 54	77.32 169	65.11 72	76.47 160	86.80 124	49.47 232	83.77 58	53.89 190	92.72 63	88.81 51

mvs-test1		73.81 114	70.69 168	83.18 3	77.05 154	81.39 4	75.39 122	77.70 163	57.68 139	71.19 223	74.72 280	64.80 110	83.66 60	56.46 168	81.19 238	84.50 110

K. test v3		73.67 115	73.61 117	73.87 104	79.78 116	55.62 148	74.69 136	62.04 262	66.16 59	84.76 60	93.23 5	49.47 232	80.97 117	65.66 111	86.67 160	85.02 96

NR-MVSNet		73.62 116	74.05 109	72.33 151	83.50 80	43.71 244	65.65 248	77.32 169	64.32 82	75.59 167	87.08 116	62.45 125	81.34 102	54.90 181	95.63 10	91.93 10

v7		73.59 117	73.69 113	73.28 124	74.42 196	48.68 190	72.74 149	81.98 78	54.76 181	82.07 84	85.05 167	58.53 174	82.22 85	67.99 87	85.66 171	88.95 46

DP-MVS Recon		73.57 118	72.69 141	76.23 81	82.85 88	63.39 103	74.32 138	82.96 65	57.75 138	70.35 233	81.98 207	64.34 114	84.41 53	49.69 214	89.95 113	80.89 180

CNLPA		73.44 119	73.03 133	74.66 93	78.27 138	75.29 27	75.99 111	78.49 150	65.39 66	75.67 166	83.22 194	61.23 141	66.77 283	53.70 192	85.33 181	81.92 164

MCST-MVS		73.42 120	73.34 123	73.63 112	81.28 107	59.17 132	74.80 132	83.13 63	45.50 267	72.84 199	83.78 183	65.15 107	80.99 116	64.54 119	89.09 124	80.73 185

v1192		73.40 121	73.42 119	73.32 123	74.65 190	48.67 191	72.21 153	81.73 82	52.76 206	81.85 86	84.56 174	57.12 200	82.24 84	68.58 78	87.33 150	89.06 42

114514_t		73.40 121	73.33 124	73.64 111	84.15 77	57.11 142	78.20 81	80.02 125	43.76 281	72.55 205	86.07 155	64.00 115	83.35 68	60.14 142	91.03 89	80.45 190

FC-MVSNet-test		73.32 123	74.78 100	68.93 190	79.21 126	36.57 293	71.82 165	79.54 132	57.63 143	82.57 81	90.38 64	59.38 161	78.99 150	57.91 156	94.56 33	91.23 16

v1144		73.29 124	73.39 120	73.01 131	74.12 204	48.11 200	72.01 158	81.08 102	53.83 196	81.77 87	84.68 172	58.07 184	81.91 87	68.10 82	86.86 158	88.99 45

TSAR-MVS + GP.		73.08 125	71.60 158	77.54 69	78.99 133	70.73 53	74.96 127	69.38 231	60.73 117	74.39 183	78.44 245	57.72 193	82.78 74	60.16 141	89.60 116	79.11 207

v1240		73.06 126	73.14 126	72.84 137	74.74 184	47.27 221	71.88 164	81.11 97	51.80 214	82.28 83	84.21 177	56.22 207	82.34 81	68.82 76	87.17 155	88.91 48

IterMVS-LS		73.01 127	73.12 128	72.66 141	73.79 210	49.90 179	71.63 168	78.44 151	58.22 134	80.51 109	86.63 136	58.15 180	79.62 143	62.51 129	88.20 134	88.48 60
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CANet		73.00 128	71.84 151	76.48 74	75.82 171	61.28 116	74.81 130	80.37 117	63.17 96	62.43 285	80.50 221	61.10 143	85.16 41	64.00 122	84.34 194	83.01 138

v144192		72.99 129	73.06 132	72.77 138	74.58 192	47.48 213	71.90 163	80.44 116	51.57 217	81.46 96	84.11 179	58.04 185	82.12 86	67.98 88	87.47 144	88.70 53

MVS_111021_HR		72.98 130	72.97 135	72.99 132	80.82 110	65.47 87	68.81 206	72.77 202	57.67 141	75.76 165	82.38 202	71.01 60	77.17 181	61.38 135	86.15 163	76.32 231

v1921920		72.96 131	72.98 134	72.89 136	74.67 187	47.58 212	71.92 162	80.69 109	51.70 216	81.69 91	83.89 181	56.58 205	82.25 83	68.34 80	87.36 148	88.82 50

v1neww		72.93 132	73.07 130	72.48 145	73.41 217	47.46 215	72.17 154	80.26 119	55.63 163	81.63 93	85.07 165	57.97 187	81.28 105	66.55 105	84.98 189	88.70 53

v7new		72.93 132	73.07 130	72.48 145	73.41 217	47.46 215	72.17 154	80.26 119	55.63 163	81.63 93	85.07 165	57.97 187	81.28 105	66.55 105	84.98 189	88.70 53

v6		72.93 132	73.08 129	72.48 145	73.42 215	47.47 214	72.17 154	80.25 121	55.63 163	81.65 92	85.04 168	57.95 189	81.28 105	66.56 104	85.01 188	88.70 53

casdiffmvs1		72.89 135	72.85 136	73.04 130	77.69 149	53.36 164	80.89 51	80.76 108	44.66 276	72.86 198	88.56 99	66.45 96	80.91 122	61.58 133	82.17 215	84.84 97

CLD-MVS		72.88 136	72.36 145	74.43 96	77.03 156	54.30 157	68.77 209	83.43 60	52.12 210	76.79 153	74.44 284	69.54 69	83.91 56	55.88 174	93.25 55	85.09 94
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
Regformer-3		72.86 137	72.28 147	74.62 94	74.74 184	60.18 123	72.91 144	71.76 210	64.74 76	78.42 131	72.07 304	67.00 89	76.28 192	67.97 89	80.91 240	87.39 69

EI-MVSNet-Vis-set		72.78 138	71.87 150	75.54 88	74.77 183	59.02 134	72.24 152	71.56 213	63.92 85	78.59 127	71.59 311	66.22 99	78.60 158	67.58 92	80.32 248	89.00 44

PCF-MVS	63.80 13	72.70 139	71.69 154	75.72 86	78.10 140	60.01 125	73.04 143	81.50 85	45.34 270	79.66 118	84.35 176	65.15 107	82.65 76	48.70 221	89.38 120	84.50 110
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
EI-MVSNet-UG-set		72.63 140	71.68 155	75.47 89	74.67 187	58.64 138	72.02 157	71.50 214	63.53 91	78.58 129	71.39 314	65.98 100	78.53 160	67.30 98	80.18 249	89.23 39

divwei89l23v2f112		72.60 141	72.73 138	72.19 152	73.10 228	47.00 225	71.48 169	79.11 136	55.01 172	81.23 99	84.95 169	57.45 196	80.89 124	66.58 102	85.67 169	88.68 57

v1		72.60 141	72.73 138	72.19 152	73.12 227	47.01 224	71.48 169	79.10 138	55.01 172	81.24 98	84.92 171	57.46 195	80.90 123	66.59 101	85.67 169	88.68 57

v1141		72.59 143	72.73 138	72.19 152	73.10 228	47.00 225	71.48 169	79.11 136	55.01 172	81.23 99	84.94 170	57.45 196	80.89 124	66.58 102	85.65 172	88.68 57

Anonymous20240529		72.56 144	73.79 112	68.86 194	76.89 160	45.21 238	68.80 208	77.25 171	67.16 49	76.89 150	90.44 57	65.95 101	74.19 212	50.75 206	90.00 111	87.18 72

FIs		72.56 144	73.80 111	68.84 195	78.74 135	37.74 287	71.02 182	79.83 128	56.12 158	80.88 107	89.45 79	58.18 178	78.28 171	56.63 164	93.36 53	90.51 31

v2v482		72.55 146	72.58 142	72.43 148	72.92 238	46.72 229	71.41 174	79.13 135	55.27 167	81.17 101	85.25 163	55.41 209	81.13 109	67.25 99	85.46 177	89.43 36

canonicalmvs		72.29 147	73.38 121	69.04 187	74.23 199	47.37 218	73.93 141	83.18 61	54.36 187	76.61 155	81.64 213	72.03 51	75.34 200	57.12 161	87.28 152	84.40 112

casdiffmvs		72.24 148	71.83 152	73.47 117	75.01 177	54.46 156	79.73 65	82.60 71	45.66 264	70.90 226	87.73 113	63.41 117	82.32 82	65.09 116	76.36 277	83.64 126

Effi-MVS+		72.10 149	72.28 147	71.58 157	74.21 203	50.33 175	74.72 135	82.73 68	62.62 100	70.77 227	76.83 255	69.96 67	80.97 117	60.20 140	78.43 267	83.45 131

MVS_111021_LR		72.10 149	71.82 153	72.95 134	79.53 120	73.90 36	70.45 188	66.64 241	56.87 152	76.81 152	81.76 211	68.78 74	71.76 241	61.81 132	83.74 202	73.18 251

testing_2		72.01 151	72.36 145	70.95 163	70.79 250	48.70 188	72.81 146	78.09 159	48.79 243	84.46 67	89.15 88	57.90 191	78.55 159	61.55 134	87.74 140	85.61 89

pmmvs6		71.82 152	73.66 115	66.31 218	75.94 170	42.01 253	66.99 230	72.53 205	63.45 93	76.43 161	92.78 10	72.95 47	69.69 254	51.41 201	90.46 102	87.22 70

PLC	62.01 16	71.79 153	70.28 170	76.33 78	80.31 114	68.63 70	78.18 82	81.24 95	54.57 184	67.09 263	80.63 219	59.44 159	81.74 90	46.91 236	84.17 195	78.63 210
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
VDDNet		71.60 154	73.13 127	67.02 211	86.29 44	41.11 259	69.97 192	66.50 242	68.72 44	74.74 178	91.70 26	59.90 153	75.81 195	48.58 223	91.72 71	84.15 116

3Dnovator	65.95 11	71.50 155	71.22 163	72.34 150	73.16 223	63.09 106	78.37 78	78.32 152	57.67 141	72.22 211	84.61 173	54.77 210	78.47 162	60.82 139	81.07 239	75.45 236

WR-MVS		71.20 156	72.48 143	67.36 208	84.98 60	35.70 302	64.43 261	68.66 234	65.05 73	81.49 95	86.43 143	57.57 194	76.48 190	50.36 210	93.32 54	89.90 34

V42		71.06 157	70.83 166	71.72 156	67.25 288	47.14 222	65.94 244	80.35 118	51.35 219	83.40 75	83.23 192	59.25 163	78.80 154	65.91 110	80.81 244	89.23 39

FMVSNet1		71.06 157	72.48 143	66.81 212	77.65 151	40.68 262	71.96 159	73.03 198	61.14 112	79.45 121	90.36 66	60.44 148	75.20 202	50.20 211	88.05 136	84.54 106

API-MVS		70.97 159	71.51 160	69.37 180	75.20 175	55.94 146	80.99 49	76.84 173	62.48 102	71.24 221	77.51 251	61.51 136	80.96 121	52.04 196	85.76 168	71.22 270

diffmvs1		70.85 160	71.63 156	68.50 199	64.78 305	46.14 232	71.03 181	77.76 162	57.00 151	72.44 207	87.61 114	61.32 137	74.11 213	69.58 74	83.16 208	85.26 91

VDD-MVS		70.81 161	71.44 161	68.91 192	79.07 132	46.51 230	67.82 220	70.83 225	61.23 110	74.07 187	88.69 98	59.86 154	75.62 198	51.11 203	90.28 104	84.61 104

EG-PatchMatch MVS		70.70 162	70.88 165	70.16 173	82.64 91	58.80 135	71.48 169	73.64 196	54.98 175	76.55 156	81.77 210	61.10 143	78.94 151	54.87 182	80.84 243	72.74 256

Baseline_NR-MVSNet		70.62 163	73.19 125	62.92 243	76.97 157	34.44 312	68.84 204	70.88 224	60.25 121	79.50 120	90.53 54	61.82 132	69.11 256	54.67 184	95.27 15	85.22 92

alignmvs		70.54 164	71.00 164	69.15 186	73.50 213	48.04 203	69.85 195	79.62 129	53.94 195	76.54 157	82.00 206	59.00 166	74.68 207	57.32 159	87.21 153	84.72 100

MG-MVS		70.47 165	71.34 162	67.85 203	79.26 124	40.42 267	74.67 137	75.15 190	58.41 133	68.74 246	88.14 110	56.08 208	83.69 59	59.90 144	81.71 226	79.43 204

UGNet		70.20 166	69.05 179	73.65 110	76.24 165	63.64 101	75.87 114	72.53 205	61.48 109	60.93 296	86.14 152	52.37 220	77.12 182	50.67 207	85.21 184	80.17 198
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		70.04 167	68.88 184	73.53 115	82.71 90	63.62 102	74.81 130	81.95 80	48.53 245	67.16 262	79.18 240	51.42 227	78.38 168	54.39 188	79.72 257	78.60 211

Fast-Effi-MVS+-dtu		70.00 168	68.74 189	73.77 107	73.47 214	64.53 95	71.36 175	78.14 158	55.81 161	68.84 245	74.71 281	65.36 106	75.75 196	52.00 197	79.00 261	81.03 177

MVSFormer		69.93 169	69.03 181	72.63 143	74.93 178	59.19 130	83.98 30	75.72 182	52.27 208	63.53 281	76.74 256	43.19 259	80.56 128	72.28 51	78.67 265	78.14 217

MVS_Test		69.84 170	70.71 167	67.24 209	67.49 287	43.25 246	69.87 194	81.22 96	52.69 207	71.57 217	86.68 132	62.09 130	74.51 209	66.05 108	78.74 263	83.96 119

TransMVSNet (Re)		69.62 171	71.63 156	63.57 236	76.51 162	35.93 300	65.75 247	71.29 218	61.05 113	75.02 173	89.90 75	65.88 102	70.41 252	49.79 213	89.48 118	84.38 113

EI-MVSNet		69.61 172	69.01 182	71.41 160	73.94 206	49.90 179	71.31 177	71.32 216	58.22 134	75.40 171	70.44 315	58.16 179	75.85 193	62.51 129	79.81 254	88.48 60

diffmvs		69.55 173	70.18 171	67.66 206	63.63 310	45.24 237	71.26 179	76.21 177	55.79 162	67.89 249	86.41 144	61.00 145	73.76 216	68.03 84	81.40 230	83.98 118

Gipuma		69.55 173	72.83 137	59.70 274	63.63 310	53.97 159	80.08 61	75.93 180	64.24 83	73.49 192	88.93 96	57.89 192	62.46 298	59.75 147	91.55 77	62.67 326
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
BH-untuned		69.39 175	69.46 174	69.18 185	77.96 144	56.88 143	68.47 215	77.53 166	56.77 154	77.79 139	79.63 232	60.30 149	80.20 137	46.04 241	80.65 245	70.47 276

v148		69.38 176	69.39 175	69.36 181	69.14 267	44.56 240	68.83 205	72.70 203	54.79 179	78.59 127	84.12 178	54.69 211	76.74 189	59.40 148	82.20 214	86.79 74

1121		69.23 177	68.26 193	72.12 155	88.36 32	71.40 45	68.59 210	62.06 260	43.80 280	74.75 177	86.18 149	52.92 217	76.85 186	54.47 185	83.27 206	68.12 298

PAPR		69.20 178	68.66 190	70.82 164	75.15 176	47.77 207	75.31 123	81.11 97	49.62 239	66.33 265	79.27 237	61.53 135	82.96 72	48.12 227	81.50 229	81.74 166

QAPM		69.18 179	69.26 177	68.94 189	71.61 248	52.58 167	80.37 57	78.79 144	49.63 238	73.51 191	85.14 164	53.66 215	79.12 148	55.11 180	75.54 283	75.11 240

LCM-MVSNet-Re		69.10 180	71.57 159	61.70 256	70.37 257	34.30 313	61.45 287	79.62 129	56.81 153	89.59 10	88.16 109	68.44 78	72.94 220	42.30 267	87.33 150	77.85 222

EPNet		69.10 180	67.32 200	74.46 95	68.33 278	61.27 117	77.56 86	63.57 254	60.95 114	56.62 317	82.75 196	51.53 226	81.24 108	54.36 189	90.20 105	80.88 181
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test4		69.04 182	68.95 183	69.32 184	69.52 263	48.10 201	70.69 187	78.25 156	45.90 263	80.99 103	82.24 203	51.91 221	78.11 176	58.46 152	82.58 212	81.74 166

DI_MVS_plusplus_test		69.01 183	69.04 180	68.93 190	69.54 262	46.74 228	70.14 190	75.49 184	46.64 259	78.30 133	83.18 195	58.80 168	78.86 152	57.14 160	82.15 216	81.18 173

test_normal		68.88 184	68.88 184	68.88 193	69.43 265	47.03 223	69.85 195	74.83 191	46.06 262	78.30 133	83.29 190	58.76 172	78.23 172	57.51 157	81.90 220	81.36 171

DELS-MVS		68.83 185	68.31 191	70.38 168	70.55 256	48.31 195	63.78 266	82.13 75	54.00 192	68.96 243	75.17 276	58.95 167	80.06 140	58.55 151	82.74 210	82.76 144
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+		68.81 186	68.30 192	70.35 169	74.66 189	48.61 192	66.06 243	78.32 152	50.62 232	71.48 220	75.54 270	68.75 75	79.59 145	50.55 209	78.73 264	82.86 141

OpenMVS	62.51 15	68.76 187	68.75 188	68.78 196	70.56 255	53.91 160	78.29 79	77.35 168	48.85 242	70.22 235	83.52 184	52.65 219	76.93 184	55.31 179	81.99 218	75.49 235

VPA-MVSNet		68.71 188	70.37 169	63.72 235	76.13 167	38.06 285	64.10 263	71.48 215	56.60 157	74.10 186	88.31 105	64.78 112	69.72 253	47.69 231	90.15 107	83.37 134

BH-RMVSNet		68.69 189	68.20 195	70.14 174	76.40 163	53.90 161	64.62 258	73.48 197	58.01 136	73.91 189	81.78 209	59.09 165	78.22 173	48.59 222	77.96 272	78.31 214

pm-mvs1		68.40 190	69.85 173	64.04 232	73.10 228	39.94 269	64.61 259	70.50 226	55.52 166	73.97 188	89.33 80	63.91 116	68.38 268	49.68 215	88.02 137	83.81 122

GBi-Net		68.30 191	68.79 186	66.81 212	73.14 224	40.68 262	71.96 159	73.03 198	54.81 176	74.72 179	90.36 66	48.63 237	75.20 202	47.12 233	85.37 178	84.54 106

test1		68.30 191	68.79 186	66.81 212	73.14 224	40.68 262	71.96 159	73.03 198	54.81 176	74.72 179	90.36 66	48.63 237	75.20 202	47.12 233	85.37 178	84.54 106

TinyColmap		67.98 193	69.28 176	64.08 231	67.98 282	46.82 227	70.04 191	75.26 188	53.05 203	77.36 143	86.79 125	59.39 160	72.59 231	45.64 243	88.01 138	72.83 254

xiu_mvs_v1_base_debu		67.87 194	67.07 202	70.26 170	79.13 129	61.90 112	67.34 225	71.25 219	47.98 249	67.70 251	74.19 289	61.31 138	72.62 228	56.51 165	78.26 269	76.27 232

xiu_mvs_v1_base		67.87 194	67.07 202	70.26 170	79.13 129	61.90 112	67.34 225	71.25 219	47.98 249	67.70 251	74.19 289	61.31 138	72.62 228	56.51 165	78.26 269	76.27 232

xiu_mvs_v1_base_debi		67.87 194	67.07 202	70.26 170	79.13 129	61.90 112	67.34 225	71.25 219	47.98 249	67.70 251	74.19 289	61.31 138	72.62 228	56.51 165	78.26 269	76.27 232

MAR-MVS		67.72 197	66.16 207	72.40 149	74.45 193	64.99 93	74.87 128	77.50 167	48.67 244	65.78 270	68.58 330	57.01 203	77.79 177	46.68 239	81.92 219	74.42 244
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		67.50 198	67.31 201	68.08 201	58.86 335	61.93 111	71.43 173	75.90 181	44.67 275	72.42 208	80.20 223	57.16 198	70.44 250	58.99 150	86.12 164	71.88 264

FMVSNet2		67.48 199	68.21 194	65.29 223	73.14 224	38.94 277	68.81 206	71.21 222	54.81 176	76.73 154	86.48 142	48.63 237	74.60 208	47.98 228	86.11 165	82.35 153

MSDG		67.47 200	67.48 199	67.46 207	70.70 253	54.69 154	66.90 232	78.17 157	60.88 115	70.41 232	74.76 278	61.22 142	73.18 218	47.38 232	76.87 275	74.49 243

ANet_high		67.08 201	69.94 172	58.51 281	57.55 343	27.09 346	58.43 305	76.80 174	63.56 89	82.40 82	91.93 21	59.82 155	64.98 290	50.10 212	88.86 126	83.46 130

LFMVS		67.06 202	67.89 197	64.56 227	78.02 141	38.25 282	70.81 186	59.60 270	65.18 71	71.06 224	86.56 139	43.85 255	75.22 201	46.35 240	89.63 115	80.21 193

MIMVSNet1		66.57 203	69.23 178	58.59 280	81.26 108	37.73 288	64.06 264	57.62 278	57.02 150	78.40 132	90.75 48	62.65 121	58.10 311	41.77 273	89.58 117	79.95 199

tfpnnormal		66.48 204	67.93 196	62.16 254	73.40 219	36.65 292	63.45 268	64.99 250	55.97 159	72.82 200	87.80 112	57.06 202	69.10 257	48.31 226	87.54 142	80.72 186

Anonymous202405211		66.02 205	66.89 205	63.43 239	74.22 200	38.14 283	59.00 301	66.13 243	63.33 95	69.76 238	85.95 158	51.88 222	70.50 249	44.23 248	87.52 143	81.64 168

VPNet		65.58 206	67.56 198	59.65 275	79.72 117	30.17 339	60.27 295	62.14 258	54.19 189	71.24 221	86.63 136	58.80 168	67.62 274	44.17 249	90.87 97	81.18 173

PVSNet_BlendedMVS		65.38 207	64.30 213	68.61 197	69.81 259	49.36 183	65.60 250	78.96 140	45.50 267	59.98 301	78.61 244	51.82 223	78.20 174	44.30 246	84.11 196	78.27 215

TAMVS		65.31 208	63.75 217	69.97 178	82.23 96	59.76 128	66.78 233	63.37 255	45.20 271	69.79 237	79.37 236	47.42 243	72.17 233	34.48 313	85.15 186	77.99 221

0601test		65.11 209	65.09 212	65.18 224	70.59 254	40.86 261	63.22 273	72.79 201	57.91 137	68.88 244	79.07 243	42.85 262	74.89 206	45.50 244	84.97 191	79.81 200

mvs_anonymous		65.08 210	65.49 208	63.83 234	63.79 308	37.60 289	66.52 236	69.82 230	43.44 285	73.46 193	86.08 154	58.79 171	71.75 242	51.90 198	75.63 282	82.15 157

FMVSNet3		65.00 211	65.16 209	64.52 228	69.47 264	37.56 290	66.63 234	70.38 227	51.55 218	74.72 179	83.27 191	37.89 289	74.44 210	47.12 233	85.37 178	81.57 169

BH-w/o		64.81 212	64.29 214	66.36 217	76.08 169	54.71 153	65.61 249	75.23 189	50.10 236	71.05 225	71.86 310	54.33 213	79.02 149	38.20 293	76.14 279	65.36 314

cascas		64.59 213	62.77 231	70.05 176	75.27 174	50.02 178	61.79 284	71.61 211	42.46 289	63.68 280	68.89 327	49.33 234	80.35 132	47.82 230	84.05 197	79.78 201

TR-MVS		64.59 213	63.54 220	67.73 205	75.75 173	50.83 174	63.39 269	70.29 228	49.33 240	71.55 218	74.55 282	50.94 228	78.46 163	40.43 280	75.69 281	73.89 247

PM-MVS		64.49 215	63.61 219	67.14 210	76.68 161	75.15 28	68.49 214	42.85 345	51.17 223	77.85 138	80.51 220	45.76 244	66.31 286	52.83 195	76.35 278	59.96 334

jason		64.47 216	62.84 230	69.34 183	76.91 159	59.20 129	67.15 229	65.67 244	35.29 322	65.16 272	76.74 256	44.67 250	70.68 246	54.74 183	79.28 260	78.14 217
jason: jason.
xiu_mvs_v2_base		64.43 217	63.96 215	65.85 222	77.72 148	51.32 172	63.63 267	72.31 208	45.06 274	61.70 286	69.66 321	62.56 122	73.93 215	49.06 219	73.91 293	72.31 260

pmmvs-eth3d		64.41 218	63.27 222	67.82 204	75.81 172	60.18 123	69.49 198	62.05 261	38.81 305	74.13 185	82.23 204	43.76 256	68.65 266	42.53 266	80.63 247	74.63 242

CDS-MVSNet		64.33 219	62.66 232	69.35 182	80.44 113	58.28 139	65.26 254	65.66 245	44.36 277	67.30 261	75.54 270	43.27 258	71.77 240	37.68 296	84.44 193	78.01 220
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PS-MVSNAJ		64.27 220	63.73 218	65.90 221	77.82 146	51.42 171	63.33 270	72.33 207	45.09 273	61.60 287	68.04 331	62.39 126	73.95 214	49.07 218	73.87 294	72.34 259

ab-mvs		64.11 221	65.13 211	61.05 263	71.99 246	38.03 286	67.59 221	68.79 233	49.08 241	65.32 271	86.26 147	58.02 186	66.85 281	39.33 282	79.79 256	78.27 215

CANet_DTU		64.04 222	63.83 216	64.66 226	68.39 275	42.97 248	73.45 142	74.50 193	52.05 212	54.78 325	75.44 275	43.99 254	70.42 251	53.49 194	78.41 268	80.59 188

VNet		64.01 223	65.15 210	60.57 267	73.28 222	35.61 303	57.60 308	67.08 239	54.61 183	66.76 264	83.37 187	56.28 206	66.87 279	42.19 268	85.20 185	79.23 206

lupinMVS		63.36 224	61.49 240	68.97 188	74.93 178	59.19 130	65.80 246	64.52 252	34.68 327	63.53 281	74.25 287	43.19 259	70.62 247	53.88 191	78.67 265	77.10 227

MVSTER		63.29 225	61.60 238	68.36 200	59.77 330	46.21 231	60.62 293	71.32 216	41.83 292	75.40 171	79.12 241	30.25 329	75.85 193	56.30 170	79.81 254	83.03 137

OpenMVS_ROB	54.93 17	63.23 226	63.28 221	63.07 242	69.81 259	45.34 236	68.52 213	67.14 238	43.74 282	70.61 231	79.22 238	47.90 241	72.66 227	48.75 220	73.84 295	71.21 271

IterMVS		63.12 227	62.48 233	65.02 225	66.34 295	52.86 166	63.81 265	62.25 257	46.57 260	71.51 219	80.40 222	44.60 251	66.82 282	51.38 202	75.47 284	75.38 238
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
HyFIR lowres test		63.01 228	60.47 246	70.61 165	83.04 85	54.10 158	59.93 297	72.24 209	33.67 333	69.00 242	75.63 269	38.69 282	76.93 184	36.60 303	75.45 285	80.81 184

GA-MVS		62.91 229	61.66 235	66.66 216	67.09 290	44.49 241	61.18 291	69.36 232	51.33 220	69.33 240	74.47 283	36.83 290	74.94 205	50.60 208	74.72 290	80.57 189

PVSNet_Blended		62.90 230	61.64 237	66.69 215	69.81 259	49.36 183	61.23 290	78.96 140	42.04 291	59.98 301	68.86 328	51.82 223	78.20 174	44.30 246	77.77 274	72.52 257

view600		62.88 231	62.90 226	62.82 244	72.97 234	33.66 318	66.10 239	55.01 295	57.05 146	72.66 201	82.56 198	31.60 314	72.78 222	42.64 262	85.55 173	82.02 158

view800		62.88 231	62.90 226	62.82 244	72.97 234	33.66 318	66.10 239	55.01 295	57.05 146	72.66 201	82.56 198	31.60 314	72.78 222	42.64 262	85.55 173	82.02 158

conf0.05thres1000		62.88 231	62.90 226	62.82 244	72.97 234	33.66 318	66.10 239	55.01 295	57.05 146	72.66 201	82.56 198	31.60 314	72.78 222	42.64 262	85.55 173	82.02 158

tfpn		62.88 231	62.90 226	62.82 244	72.97 234	33.66 318	66.10 239	55.01 295	57.05 146	72.66 201	82.56 198	31.60 314	72.78 222	42.64 262	85.55 173	82.02 158

USDC		62.80 235	63.10 224	61.89 255	65.19 301	43.30 245	67.42 224	74.20 194	35.80 320	72.25 210	84.48 175	45.67 245	71.95 239	37.95 295	84.97 191	70.42 278

Vis-MVSNet (Re-imp)		62.74 236	63.21 223	61.34 261	72.19 241	31.56 337	67.31 228	53.87 302	53.60 198	69.88 236	83.37 187	40.52 275	70.98 245	41.40 274	86.78 159	81.48 170

MDA-MVSNet-bldmvs		62.34 237	61.73 234	64.16 229	61.64 319	49.90 179	48.11 332	57.24 284	53.31 202	80.95 104	79.39 235	49.00 235	61.55 302	45.92 242	80.05 251	81.03 177

wuyk23d		61.97 238	66.25 206	49.12 314	58.19 341	60.77 120	66.32 237	52.97 308	55.93 160	90.62 7	86.91 121	73.07 44	35.98 355	20.63 354	91.63 73	50.62 346

tfpn111		61.91 239	61.65 236	62.68 249	72.14 242	35.01 306	65.42 251	56.99 285	55.23 168	70.71 228	79.90 226	32.07 309	72.85 221	38.80 286	83.61 203	80.18 194

thres600view7		61.82 240	61.38 241	63.12 241	71.81 247	34.93 309	64.64 257	56.99 285	54.78 180	70.33 234	79.74 231	32.07 309	72.42 232	38.61 289	83.46 204	82.02 158

PAPM		61.79 241	60.37 247	66.05 219	76.09 168	41.87 254	69.30 200	76.79 175	40.64 299	53.80 331	79.62 233	44.38 252	82.92 73	29.64 333	73.11 297	73.36 250

MVP-Stereo		61.56 242	59.22 253	68.58 198	79.28 123	60.44 121	69.20 202	71.57 212	43.58 284	56.42 318	78.37 246	39.57 279	76.46 191	34.86 312	60.16 339	68.86 296
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CMPMVS	48.73 20	61.54 243	60.89 244	63.52 237	61.08 322	51.55 170	68.07 218	68.00 237	33.88 329	65.87 268	81.25 215	37.91 288	67.71 272	49.32 217	82.60 211	71.31 269
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
conf200view11		61.42 244	61.09 242	62.43 252	72.14 242	35.01 306	65.42 251	56.99 285	55.23 168	70.71 228	79.90 226	32.07 309	72.09 234	35.61 308	81.73 222	80.18 194

RPMNet		61.25 245	61.55 239	60.36 271	66.37 293	48.24 197	70.93 184	54.45 300	54.66 182	61.35 289	86.77 128	33.29 300	63.22 295	55.93 173	70.17 311	69.62 289

thres100view900		61.17 246	61.09 242	61.39 260	72.14 242	35.01 306	65.42 251	56.99 285	55.23 168	70.71 228	79.90 226	32.07 309	72.09 234	35.61 308	81.73 222	77.08 228

Patchmtry		60.91 247	63.01 225	54.62 299	66.10 297	26.27 350	67.47 223	56.40 290	54.05 191	72.04 212	86.66 133	33.19 301	60.17 305	43.69 250	87.45 147	77.42 223

EU-MVSNet		60.82 248	60.80 245	60.86 266	68.37 276	41.16 258	72.27 151	68.27 236	26.96 354	69.08 241	75.71 268	32.09 308	67.44 275	55.59 177	78.90 262	73.97 245

pmmvs4		60.78 249	59.04 255	66.00 220	73.06 231	57.67 141	64.53 260	60.22 268	36.91 315	65.96 267	77.27 252	39.66 278	68.54 267	38.87 285	74.89 289	71.80 265

thres400		60.77 250	59.97 249	63.15 240	70.78 251	35.35 304	63.27 271	57.47 279	53.00 204	68.31 247	77.09 253	32.45 306	72.09 234	35.61 308	81.73 222	82.02 158

MVS		60.62 251	59.97 249	62.58 250	68.13 280	47.28 220	68.59 210	73.96 195	32.19 338	59.94 303	68.86 328	50.48 229	77.64 179	41.85 271	75.74 280	62.83 324

tfpn200view9		60.35 252	59.97 249	61.51 258	70.78 251	35.35 304	63.27 271	57.47 279	53.00 204	68.31 247	77.09 253	32.45 306	72.09 234	35.61 308	81.73 222	77.08 228

ppachtmachnet_test		60.26 253	59.61 252	62.20 253	67.70 285	44.33 243	58.18 306	60.96 266	40.75 297	65.80 269	72.57 299	41.23 269	63.92 293	46.87 237	82.42 213	78.33 213

Patchmatch-RL test		59.95 254	59.12 254	62.44 251	72.46 240	54.61 155	59.63 298	47.51 332	41.05 296	74.58 182	74.30 286	31.06 323	65.31 287	51.61 199	79.85 253	67.39 302

1314		59.83 255	58.86 263	62.74 248	65.71 299	44.78 239	68.59 210	72.63 204	33.54 336	61.05 293	67.29 335	43.62 257	71.26 244	49.49 216	67.84 324	72.19 262

IB-MVS	49.67 18	59.69 256	56.96 276	67.90 202	68.19 279	50.30 176	61.42 288	65.18 249	47.57 255	55.83 321	67.15 336	23.77 354	79.60 144	43.56 252	79.97 252	73.79 248
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		59.48 257	58.99 256	60.96 265	77.84 145	42.39 252	61.42 288	68.45 235	37.96 310	59.93 304	67.46 333	45.11 248	65.07 289	40.89 277	71.81 302	75.41 237

FPMVS		59.43 258	60.07 248	57.51 286	77.62 152	71.52 44	62.33 275	50.92 320	57.40 144	69.40 239	80.00 225	39.14 280	61.92 301	37.47 299	66.36 327	39.09 356

conf0.01		59.26 259	58.88 257	60.40 269	68.66 268	31.96 331	62.04 277	51.95 312	50.99 224	67.57 254	75.91 262	28.59 339	69.07 258	42.77 256	81.40 230	80.18 194

conf0.002		59.26 259	58.88 257	60.40 269	68.66 268	31.96 331	62.04 277	51.95 312	50.99 224	67.57 254	75.91 262	28.59 339	69.07 258	42.77 256	81.40 230	80.18 194

CVMVSNet		59.21 261	58.44 268	61.51 258	73.94 206	47.76 208	71.31 177	64.56 251	26.91 355	60.34 298	70.44 315	36.24 292	67.65 273	53.57 193	68.66 321	69.12 294

CR-MVSNet		58.96 262	58.49 267	60.36 271	66.37 293	48.24 197	70.93 184	56.40 290	32.87 337	61.35 289	86.66 133	33.19 301	63.22 295	48.50 224	70.17 311	69.62 289

EPNet_dtu		58.93 263	58.52 266	60.16 273	67.91 283	47.70 209	69.97 192	58.02 275	49.73 237	47.28 346	73.02 298	38.14 285	62.34 299	36.57 304	85.99 166	70.43 277
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test_1112_low_res		58.78 264	58.69 265	59.04 278	79.41 121	38.13 284	57.62 307	66.98 240	34.74 325	59.62 305	77.56 250	42.92 261	63.65 294	38.66 288	70.73 308	75.35 239

PatchMatch-RL		58.68 265	57.72 270	61.57 257	76.21 166	73.59 39	61.83 283	49.00 327	47.30 257	61.08 291	68.97 325	50.16 231	59.01 308	36.06 307	68.84 319	52.10 345

thresconf0.02		58.38 266	58.88 257	56.91 289	68.66 268	31.96 331	62.04 277	51.95 312	50.99 224	67.57 254	75.91 262	28.59 339	69.07 258	42.77 256	81.40 230	69.70 284

tfpn_n400		58.38 266	58.88 257	56.91 289	68.66 268	31.96 331	62.04 277	51.95 312	50.99 224	67.57 254	75.91 262	28.59 339	69.07 258	42.77 256	81.40 230	69.70 284

tfpnconf		58.38 266	58.88 257	56.91 289	68.66 268	31.96 331	62.04 277	51.95 312	50.99 224	67.57 254	75.91 262	28.59 339	69.07 258	42.77 256	81.40 230	69.70 284

tfpnview11		58.38 266	58.88 257	56.91 289	68.66 268	31.96 331	62.04 277	51.95 312	50.99 224	67.57 254	75.91 262	28.59 339	69.07 258	42.77 256	81.40 230	69.70 284

tfpn1000		58.28 270	58.86 263	56.53 293	68.05 281	32.26 328	62.58 274	51.67 319	51.25 222	67.38 260	75.95 261	27.24 346	68.83 264	43.51 253	82.11 217	68.49 297

CHOSEN 1792x2688		58.09 271	56.30 281	63.45 238	79.95 115	50.93 173	54.07 318	65.59 246	28.56 351	61.53 288	74.33 285	41.09 271	66.52 285	33.91 317	67.69 325	72.92 253

HY-MVS	49.31 19	57.96 272	57.59 271	59.10 277	66.85 291	36.17 297	65.13 256	65.39 248	39.24 303	54.69 327	78.14 247	44.28 253	67.18 278	33.75 318	70.79 307	73.95 246

Patchmatch-test1		57.81 273	58.04 269	57.13 287	70.17 258	41.07 260	65.19 255	53.38 306	43.34 288	61.00 294	71.94 308	45.20 247	62.69 297	41.81 272	70.31 310	67.63 301

tpmp4_e23		57.57 274	55.46 288	63.93 233	66.48 292	41.56 257	71.68 167	60.65 267	35.64 321	55.35 324	76.25 259	29.53 335	75.41 199	34.40 314	69.12 318	74.83 241

thres200		57.55 275	57.02 275	59.17 276	67.89 284	34.93 309	58.91 303	57.25 283	50.24 234	64.01 277	71.46 313	32.49 305	71.39 243	31.31 324	79.57 258	71.19 272

CostFormer		57.35 276	56.14 282	60.97 264	63.76 309	38.43 279	67.50 222	60.22 268	37.14 314	59.12 306	76.34 258	32.78 303	71.99 238	39.12 284	69.27 317	72.47 258

tfpn_ndepth		56.91 277	57.30 274	55.71 295	67.22 289	33.26 323	61.72 285	53.98 301	48.49 246	64.16 276	71.94 308	27.65 345	68.71 265	40.49 279	80.08 250	65.17 316

our_test_3		56.46 278	56.51 279	56.30 294	67.70 285	39.66 271	55.36 315	52.34 311	40.57 300	63.85 278	69.91 320	40.04 277	58.22 310	43.49 254	75.29 288	71.03 275

tpm2		56.12 279	54.64 291	60.55 268	66.24 296	36.01 298	68.14 217	56.77 289	33.60 335	58.25 310	75.52 272	30.25 329	74.33 211	33.27 319	69.76 316	71.32 268

no-one		56.11 280	55.62 286	57.60 285	62.68 313	49.23 185	39.12 351	58.99 273	33.72 331	60.98 295	80.90 217	36.07 293	60.36 304	30.68 326	97.40 1	63.22 323

tpmvs		55.84 281	55.45 289	57.01 288	60.33 326	33.20 324	65.89 245	59.29 272	47.52 256	56.04 319	73.60 292	31.05 324	68.06 270	40.64 278	64.64 330	69.77 283

gg-mvs-nofinetune		55.75 282	56.75 278	52.72 303	62.87 312	28.04 345	68.92 203	41.36 353	71.09 30	50.80 337	92.63 12	20.74 357	66.86 280	29.97 331	72.41 299	63.25 322

test20.03		55.74 283	57.51 272	50.42 307	59.89 329	32.09 329	50.63 325	49.01 326	50.11 235	65.07 273	83.23 192	45.61 246	48.11 326	30.22 329	83.82 201	71.07 274

MS-PatchMatch		55.59 284	54.89 290	57.68 284	69.18 266	49.05 186	61.00 292	62.93 256	35.98 318	58.36 309	68.93 326	36.71 291	66.59 284	37.62 298	63.30 333	57.39 338

XXY-MVS		55.19 285	57.40 273	48.56 317	64.45 306	34.84 311	51.54 324	53.59 304	38.99 304	63.79 279	79.43 234	56.59 204	45.57 331	36.92 302	71.29 304	65.25 315

FMVSNet5		55.08 286	55.54 287	53.71 300	65.80 298	33.50 322	56.22 310	52.50 310	43.72 283	61.06 292	83.38 186	25.46 351	54.87 314	30.11 330	81.64 228	72.75 255

PatchmatchNet		54.60 287	54.27 293	55.59 296	65.17 303	39.08 274	66.92 231	51.80 318	39.89 301	58.39 308	73.12 297	31.69 313	58.33 309	43.01 255	58.38 348	69.38 292
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MIMVSNet		54.39 288	56.12 283	49.20 312	72.57 239	30.91 338	59.98 296	48.43 329	41.66 293	55.94 320	83.86 182	41.19 270	50.42 320	26.05 340	75.38 286	66.27 310

Anonymous20231206		54.13 289	55.82 284	49.04 315	70.89 249	35.96 299	51.73 323	50.87 321	34.86 323	62.49 284	79.22 238	42.52 264	44.29 340	27.95 338	81.88 221	66.88 306

JIA-IIPM		54.03 290	51.62 303	61.25 262	59.14 334	55.21 149	59.10 300	47.72 331	50.85 231	50.31 341	85.81 159	20.10 359	63.97 292	36.16 306	55.41 353	64.55 320

tpm cat1		54.02 291	52.63 299	58.19 282	64.85 304	39.86 270	66.26 238	57.28 282	32.16 339	56.90 315	70.39 317	32.75 304	65.30 288	34.29 315	58.79 344	69.41 291

testgi		54.00 292	56.86 277	45.45 325	58.20 340	25.81 351	49.05 328	49.50 325	45.43 269	67.84 250	81.17 216	51.81 225	43.20 344	29.30 334	79.41 259	67.34 304

PatchFormer-LS_test		53.94 293	52.64 298	57.85 283	61.87 317	39.59 272	61.60 286	57.63 277	40.65 298	54.52 328	58.64 350	29.07 338	64.18 291	46.78 238	62.98 335	69.78 282

PatchT		53.35 294	56.47 280	43.99 332	64.19 307	17.46 359	59.15 299	43.10 343	52.11 211	54.74 326	86.95 120	29.97 332	49.98 323	43.62 251	74.40 291	64.53 321

DWT-MVSNet_test		53.04 295	51.12 306	58.77 279	61.23 320	38.67 278	62.16 276	57.74 276	38.24 307	51.76 335	59.07 349	21.36 356	67.40 276	44.80 245	63.76 332	70.25 279

LP		53.02 296	52.27 302	55.27 297	55.76 352	40.55 265	55.64 313	55.07 293	42.46 289	56.95 314	73.21 296	33.67 299	54.18 318	38.41 291	59.29 343	71.08 273

testmv		52.91 297	54.31 292	48.71 316	72.13 245	36.18 296	50.26 326	47.78 330	44.15 278	64.61 274	79.78 230	38.18 284	50.20 322	21.96 351	69.93 313	59.75 335

new-patchmatchnet		52.89 298	55.76 285	44.26 331	59.94 328	6.31 365	37.36 355	50.76 322	41.10 294	64.28 275	79.82 229	44.77 249	48.43 325	36.24 305	87.61 141	78.03 219

YYNet1		52.58 299	53.50 295	49.85 308	54.15 358	36.45 295	40.53 346	46.55 335	38.09 309	75.52 169	73.31 295	41.08 272	43.88 341	41.10 275	71.14 306	69.21 293

MDA-MVSNet_test_wron		52.57 300	53.49 296	49.81 309	54.24 357	36.47 294	40.48 347	46.58 334	38.13 308	75.47 170	73.32 294	41.05 273	43.85 342	40.98 276	71.20 305	69.10 295

pmmvs5		52.49 301	52.58 300	52.21 305	54.99 355	32.38 327	55.45 314	53.84 303	32.15 340	55.49 323	74.81 277	38.08 286	57.37 312	34.02 316	74.40 291	66.88 306

UnsupCasMVSNet_eth		52.26 302	53.29 297	49.16 313	55.08 354	33.67 317	50.03 327	58.79 274	37.67 311	63.43 283	74.75 279	41.82 267	45.83 330	38.59 290	59.42 342	67.98 300

N_pmnet		52.06 303	51.11 307	54.92 298	59.64 331	71.03 49	37.42 354	61.62 264	33.68 332	57.12 312	72.10 300	37.94 287	31.03 359	29.13 337	71.35 303	62.70 325

PVSNet	43.83 21	51.56 304	51.17 305	52.73 302	68.34 277	38.27 281	48.22 331	53.56 305	36.41 316	54.29 329	64.94 339	34.60 296	54.20 317	30.34 328	69.87 314	65.71 313

tpm		50.60 305	52.42 301	45.14 327	65.18 302	26.29 349	60.30 294	43.50 342	37.41 312	57.01 313	79.09 242	30.20 331	42.32 346	32.77 321	66.36 327	66.81 308

test-LLR		50.43 306	50.69 309	49.64 310	60.76 323	41.87 254	53.18 320	45.48 340	43.41 286	49.41 342	60.47 347	29.22 336	44.73 337	42.09 269	72.14 300	62.33 328

tpmrst		50.15 307	51.38 304	46.45 322	56.05 348	24.77 353	64.40 262	49.98 323	36.14 317	53.32 332	69.59 322	35.16 295	48.69 324	39.24 283	58.51 347	65.89 311

UnsupCasMVSNet_bld		50.01 308	51.03 308	46.95 318	58.61 337	32.64 326	48.31 330	53.27 307	34.27 328	60.47 297	71.53 312	41.40 268	47.07 328	30.68 326	60.78 338	61.13 330

WTY-MVS		49.39 309	50.31 310	46.62 321	61.22 321	32.00 330	46.61 336	49.77 324	33.87 330	54.12 330	69.55 323	41.96 266	45.40 333	31.28 325	64.42 331	62.47 327

ADS-MVSNet2		48.76 310	47.25 319	53.29 301	55.90 350	40.54 266	47.34 334	54.99 299	31.41 346	50.48 338	72.06 306	31.23 320	54.26 316	25.93 341	55.93 350	65.07 317

test-mter		48.56 311	48.20 316	49.64 310	60.76 323	41.87 254	53.18 320	45.48 340	31.91 344	49.41 342	60.47 347	18.34 360	44.73 337	42.09 269	72.14 300	62.33 328

test1235678		48.41 312	49.60 312	44.83 329	68.52 274	33.81 316	46.33 338	45.89 337	38.72 306	58.46 307	72.08 301	29.85 334	47.82 327	19.67 355	66.91 326	52.88 343

Patchmatch-test		47.93 313	49.96 311	41.84 336	57.42 344	24.26 354	48.75 329	41.49 352	39.30 302	56.79 316	73.48 293	30.48 328	33.87 358	29.29 335	72.61 298	67.39 302

test0.0.03 1		47.72 314	48.31 315	45.93 323	55.53 353	29.39 340	46.40 337	41.21 354	43.41 286	55.81 322	67.65 332	29.22 336	43.77 343	25.73 343	69.87 314	64.62 319

sss		47.59 315	48.32 314	45.40 326	56.73 347	33.96 314	45.17 340	48.51 328	32.11 342	52.37 334	65.79 337	40.39 276	41.91 349	31.85 322	61.97 336	60.35 331

pmmvs3		46.71 316	45.09 325	51.55 306	56.76 346	48.25 196	55.78 312	39.53 358	24.13 358	50.35 340	63.40 341	15.90 364	51.08 319	29.29 335	70.69 309	55.33 341

EPMVS		45.74 317	46.53 320	43.39 333	54.14 359	22.33 356	55.02 316	35.00 361	34.69 326	51.09 336	70.20 319	25.92 349	42.04 348	37.19 300	55.50 352	65.78 312

MVS-HIRNet		45.53 318	47.29 318	40.24 340	62.29 316	26.82 348	56.02 311	37.41 359	29.74 350	43.69 357	81.27 214	33.96 298	55.48 313	24.46 346	56.79 349	38.43 357

testpf		45.32 319	48.47 313	35.88 345	53.56 360	26.84 347	58.86 304	42.95 344	47.78 253	46.18 348	63.70 340	13.73 365	50.29 321	50.81 205	58.61 346	30.51 359

TESTMET0.1,1		45.17 320	44.93 326	45.89 324	56.02 349	38.31 280	53.18 320	41.94 351	27.85 352	44.86 352	56.47 352	17.93 361	41.50 351	38.08 294	68.06 322	57.85 337

E-PMN		45.17 320	45.36 324	44.60 330	50.07 361	42.75 249	38.66 352	42.29 349	46.39 261	39.55 359	51.15 357	26.00 348	45.37 334	37.68 296	76.41 276	45.69 352

1111		45.08 322	47.96 317	36.43 344	59.56 332	14.82 361	43.56 341	45.65 338	45.60 265	60.04 299	75.47 273	9.31 367	34.46 356	23.66 347	68.76 320	60.02 333

testus		45.03 323	46.49 321	40.65 339	62.53 314	25.24 352	42.54 343	46.23 336	31.16 348	57.69 311	62.90 342	34.60 296	42.33 345	17.72 357	63.01 334	54.37 342

PMMVS		44.69 324	43.95 330	46.92 319	50.05 362	53.47 163	48.08 333	42.40 347	22.36 359	44.01 356	53.05 354	42.60 263	45.49 332	31.69 323	61.36 337	41.79 354

ADS-MVSNet		44.62 325	45.58 323	41.73 337	55.90 350	20.83 357	47.34 334	39.94 357	31.41 346	50.48 338	72.06 306	31.23 320	39.31 352	25.93 341	55.93 350	65.07 317

EMVS		44.61 326	44.45 329	45.10 328	48.91 363	43.00 247	37.92 353	41.10 355	46.75 258	38.00 361	48.43 359	26.42 347	46.27 329	37.11 301	75.38 286	46.03 351

dp		44.09 327	44.88 327	41.72 338	58.53 338	23.18 355	54.70 317	42.38 348	34.80 324	44.25 355	65.61 338	24.48 353	44.80 336	29.77 332	49.42 356	57.18 339

DSMNet-mixed		43.18 328	44.66 328	38.75 342	54.75 356	28.88 343	57.06 309	27.42 365	13.47 360	47.27 347	77.67 249	38.83 281	39.29 353	25.32 345	60.12 340	48.08 348

CHOSEN 280x420		41.62 329	39.89 336	46.80 320	61.81 318	51.59 169	33.56 357	35.74 360	27.48 353	37.64 362	53.53 353	23.24 355	42.09 347	27.39 339	58.64 345	46.72 350

PVSNet_0	36.71 22	41.12 330	40.78 333	42.14 334	59.97 327	40.13 268	40.97 345	42.24 350	30.81 349	44.86 352	49.41 358	40.70 274	45.12 335	23.15 349	34.96 358	41.16 355

test2356		40.85 331	40.47 334	41.98 335	58.78 336	28.65 344	39.45 349	40.98 356	31.95 343	48.47 344	56.63 351	12.54 366	44.41 339	15.84 359	59.58 341	52.88 343

test12356		38.35 332	40.80 332	31.01 346	58.31 339	9.09 364	36.67 356	46.65 333	33.65 334	44.39 354	60.94 346	17.56 362	39.23 354	16.01 358	53.03 354	44.72 353

PMMVS2		37.74 333	40.87 331	28.36 349	42.41 365	5.35 366	24.61 358	27.75 364	32.15 340	47.85 345	70.27 318	35.85 294	29.51 360	19.08 356	67.85 323	50.22 347

new_pmnet		37.55 334	39.80 337	30.79 347	56.83 345	16.46 360	39.35 350	30.65 363	25.59 356	45.26 350	61.60 345	24.54 352	28.02 361	21.60 352	52.80 355	47.90 349

PNet_i23d		36.76 335	36.63 339	37.12 343	58.19 341	33.00 325	39.86 348	32.55 362	48.44 247	39.64 358	51.31 356	6.89 369	41.83 350	22.29 350	30.55 359	36.54 358

MVE	27.91 23	36.69 336	35.64 340	39.84 341	43.37 364	35.85 301	19.49 359	24.61 366	24.68 357	39.05 360	62.63 344	38.67 283	27.10 362	21.04 353	47.25 357	56.56 340
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
pcd1.5k->3k		35.00 337	36.93 338	29.21 348	84.62 67	0.00 370	0.00 361	78.90 142	0.00 365	0.00 367	0.00 367	78.26 14	0.00 367	0.00 364	90.55 101	87.62 66

v1.0		34.83 338	46.44 322	0.00 355	85.90 46	0.00 370	0.00 361	84.94 30	73.27 20	84.61 62	89.25 84	0.00 372	0.00 367	0.00 364	0.00 365	0.00 365

.test1245		34.47 339	40.38 335	16.73 350	59.56 332	14.82 361	43.56 341	45.65 338	45.60 265	60.04 299	75.47 273	9.31 367	34.46 356	23.66 347	0.55 363	0.90 362

cdsmvs_eth3d_5k		17.71 340	23.62 341	0.00 355	0.00 370	0.00 370	0.00 361	70.17 229	0.00 365	0.00 367	74.25 287	68.16 81	0.00 367	0.00 364	0.00 365	0.00 365

tmp_tt		11.98 341	14.73 342	3.72 352	2.28 367	4.62 367	19.44 360	14.50 368	0.47 362	21.55 363	9.58 362	25.78 350	4.57 364	11.61 360	27.37 360	1.96 361

ab-mvs-re		5.62 342	7.50 343	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	67.46 333	0.00 372	0.00 367	0.00 364	0.00 365	0.00 365

pcd_1.5k_mvsjas		5.20 343	6.93 344	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	62.39 126	0.00 367	0.00 364	0.00 365	0.00 365

test123		4.43 344	5.78 345	0.39 354	0.97 368	0.28 368	46.33 338	0.45 370	0.31 363	0.62 365	1.50 365	0.61 371	0.11 366	0.56 362	0.63 362	0.77 364

testmvs		4.06 345	5.28 346	0.41 353	0.64 369	0.16 369	42.54 343	0.31 371	0.26 364	0.50 366	1.40 366	0.77 370	0.17 365	0.56 362	0.55 363	0.90 362

sosnet-low-res		0.00 346	0.00 347	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	0.00 372	0.00 367	0.00 364	0.00 365	0.00 365

sosnet		0.00 346	0.00 347	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	0.00 372	0.00 367	0.00 364	0.00 365	0.00 365

uncertanet		0.00 346	0.00 347	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	0.00 372	0.00 367	0.00 364	0.00 365	0.00 365

Regformer		0.00 346	0.00 347	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	0.00 372	0.00 367	0.00 364	0.00 365	0.00 365

uanet		0.00 346	0.00 347	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	0.00 372	0.00 367	0.00 364	0.00 365	0.00 365

GSMVS																70.05 280

test_part2					85.90 46	66.44 81				84.61 62

test_part1				0.00 355		0.00 370	0.00 361	84.94 30				0.00 372	0.00 367	0.00 364	0.00 365	0.00 365

sam_mvs1												31.41 318				70.05 280

sam_mvs												31.21 322

semantic-postprocess				72.49 144	73.34 220	58.20 140		65.55 247	48.10 248	76.91 149	82.64 197	42.25 265	78.84 153	61.20 137	77.89 273	80.44 191

ambc				70.10 175	77.74 147	50.21 177	74.28 139	77.93 161		79.26 123	88.29 106	54.11 214	79.77 142	64.43 120	91.10 87	80.30 192

MTGPA								80.63 110

test_post1							66.63 234				2.08 363	30.66 327	59.33 307	40.34 281

test_post											1.99 364	30.91 325	54.76 315

patchmatchnet-post											68.99 324	31.32 319	69.38 255

GG-mvs-BLEND				52.24 304	60.64 325	29.21 342	69.73 197	42.41 346		45.47 349	52.33 355	20.43 358	68.16 269	25.52 344	65.42 329	59.36 336

MTMP							84.83 25	19.26 367

gm-plane-assit					62.51 315	33.91 315			37.25 313		62.71 343		72.74 226	38.70 287

test9_res														72.12 53	91.37 80	77.40 224

TEST9					85.47 53	69.32 65	76.42 101	78.69 145	53.73 197	76.97 145	86.74 129	66.84 91	81.10 112

test_8					85.09 59	67.89 74	76.26 106	78.66 147	54.00 192	76.89 150	86.72 131	66.60 93	80.89 124

agg_prior2														70.70 61	90.93 92	78.55 212

agg_prior					84.44 72	66.02 84		78.62 148		76.95 147			80.34 133

TestCases				78.35 60	79.19 127	70.81 51		88.64 2	65.37 67	80.09 115	88.17 107	70.33 63	78.43 165	55.60 175	90.90 94	85.81 85

test_prior4						70.14 58	77.57 85

test_prior2							75.57 117		58.92 131	76.53 158	86.78 126	67.83 85		69.81 69	92.76 60

test_prior				75.27 91	82.15 97	59.85 126		84.33 40					83.39 66			82.58 148

旧先验2							71.17 180		45.11 272	78.54 130			61.28 303	59.19 149

新几何2							71.33 176

新几何1				69.99 177	88.37 31	71.34 47		62.08 259	43.85 279	74.99 174	86.11 153	52.85 218	70.57 248	50.99 204	83.23 207	68.05 299

旧先验1					84.55 69	60.36 122		63.69 253			87.05 119	54.65 212			83.34 205	69.66 288

无先验							74.82 129	70.94 223	47.75 254				76.85 186	54.47 185		72.09 263

原ACMM2							74.78 133

原ACMM1				73.90 103	85.90 46	65.15 92		81.67 83	50.97 230	74.25 184	86.16 151	61.60 134	83.54 62	56.75 163	91.08 88	73.00 252

test222					87.30 35	69.15 68	67.85 219	59.59 271	41.06 295	73.05 197	85.72 160	48.03 240			80.65 245	66.92 305

testdata2													67.30 277	48.34 225

segment_acmp												68.30 80

testdata				64.13 230	85.87 49	63.34 104		61.80 263	47.83 252	76.42 162	86.60 138	48.83 236	62.31 300	54.46 187	81.26 237	66.74 309

testdata1							68.34 216		57.24 145

test12				76.51 73	82.28 95	60.94 119		81.64 84		73.60 190		64.88 109	85.19 40		90.42 103	83.38 132

plane_prior7					85.18 56	66.21 83

plane_prior6					84.18 76	65.31 89						60.83 146

plane_prior5								85.49 21					86.15 21	71.09 55	90.94 90	84.82 98

plane_prior4											89.11 89

plane_prior3						65.67 86			63.82 87	78.23 135

plane_prior2							82.74 38		65.45 64

plane_prior1					84.46 71

plane_prior						65.18 90	80.06 62		61.88 106						89.91 114

n2								0.00 372

nn								0.00 372

door-mid								55.02 294

lessismore_v0				72.75 139	79.60 119	56.83 144		57.37 281		83.80 71	89.01 92	47.45 242	78.74 156	64.39 121	86.49 162	82.69 146

LGP-MVS_train				80.90 32	87.00 37	70.41 56		86.35 12	69.77 39	87.75 18	91.13 37	81.83 3	86.20 18	77.13 27	95.96 7	86.08 79

test11								82.71 69

door								52.91 309

HQP5-MVS						58.80 135

HQP-NCC					82.37 92		77.32 89		59.08 127	71.58 214

ACMP_Plane					82.37 92		77.32 89		59.08 127	71.58 214

BP-MVS														67.38 96

HQP4-MVS										71.59 213			85.31 34			83.74 123

HQP3-MVS								84.12 47							89.16 121

HQP2-MVS												58.09 181

NP-MVS					83.34 83	63.07 107					85.97 156

MDTV_nov1_ep13_2view						18.41 358	53.74 319		31.57 345	44.89 351		29.90 333		32.93 320		71.48 267

MDTV_nov1_ep13			54.05 294		65.54 300	29.30 341	59.00 301	55.22 292	35.96 319	52.44 333	75.98 260	30.77 326	59.62 306	38.21 292	73.33 296

ACMMP++_ref															89.47 119

ACMMP++															91.96 70

Test By Simon												62.56 122

ITE_SJBPF				80.35 38	76.94 158	73.60 38		80.48 114	66.87 51	83.64 73	86.18 149	70.25 65	79.90 141	61.12 138	88.95 125	87.56 68

DeepMVS_CX				11.83 351	15.51 366	13.86 363		11.25 369	5.76 361	20.85 364	26.46 360	17.06 363	9.22 363	9.69 361	13.82 361	12.42 360

High-resolution multi-view benchmark