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.

DeepPCF-MVS	81.17 1	89.72 5	91.38 3	84.72 104	93.00 54	58.16 258	96.72 3	94.41 36	86.50 5	90.25 5	97.83 1	75.46 7	98.67 13	92.78 2	95.49 7	97.32 1

ESAPD		89.08 8	89.53 8	87.72 20	96.29 7	68.16 60	94.96 31	94.26 40	68.52 211	90.78 3	97.23 2	77.03 4	98.90 7	91.52 6	95.18 8	96.11 19

CNVR-MVS		90.32 3	90.89 4	88.61 11	96.76 4	70.65 18	96.47 6	94.83 23	84.83 9	89.07 9	96.80 3	70.86 16	99.06 3	92.64 4	95.71 5	96.12 18

PHI-MVS		86.83 30	86.85 29	86.78 41	93.47 45	65.55 137	95.39 20	95.10 19	71.77 164	85.69 27	96.52 4	62.07 83	98.77 11	86.06 35	95.60 6	96.03 23

MSLP-MVS++		86.27 35	85.91 36	87.35 28	92.01 75	68.97 43	95.04 29	92.70 97	79.04 46	81.50 56	96.50 5	58.98 111	96.78 82	83.49 51	93.93 26	96.29 16

HPM-MVS++		89.37 7	89.95 7	87.64 21	95.10 19	68.23 59	95.24 22	94.49 33	82.43 17	88.90 10	96.35 6	71.89 15	98.63 14	88.76 19	96.40 2	96.06 21

APDe-MVS		87.54 18	87.84 15	86.65 43	96.07 11	66.30 123	94.84 33	93.78 46	69.35 199	88.39 12	96.34 7	67.74 30	97.66 37	90.62 10	93.44 36	96.01 24

MCST-MVS		91.08 1	91.46 2	89.94 2	97.66 2	73.37 7	97.13 1	95.58 12	89.33 1	85.77 25	96.26 8	72.84 11	99.38 1	92.64 4	95.93 4	97.08 4

NCCC		89.07 9	89.46 9	87.91 16	96.60 5	69.05 40	96.38 7	94.64 30	84.42 10	86.74 20	96.20 9	66.56 39	98.76 12	89.03 17	94.56 20	95.92 27

DeepC-MVS_fast	79.48 2	87.95 14	88.00 14	87.79 19	95.86 14	68.32 55	95.74 12	94.11 42	83.82 12	83.49 46	96.19 10	64.53 62	98.44 18	83.42 52	94.88 14	96.61 9
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
HSP-MVS		90.38 2	91.89 1	85.84 69	92.83 57	64.03 170	93.06 75	94.52 31	82.19 19	93.65 1	96.15 11	85.89 1	97.19 58	91.02 9	97.75 1	96.29 16

PS-MVSNAJ		88.14 11	87.61 18	89.71 4	92.06 74	76.72 1	95.75 11	93.26 75	83.86 11	89.55 7	96.06 12	53.55 178	97.89 31	91.10 7	93.31 37	94.54 70

xiu_mvs_v2_base		87.92 15	87.38 23	89.55 7	91.41 99	76.43 2	95.74 12	93.12 84	83.53 13	89.55 7	95.95 13	53.45 183	97.68 33	91.07 8	92.62 44	94.54 70

MVS_0304		88.39 10	88.35 13	88.50 12	93.01 53	70.11 23	95.90 10	92.20 117	86.27 6	88.70 11	95.92 14	56.76 130	99.02 4	92.68 3	93.76 30	96.37 15

APD-MVS		85.93 39	85.99 34	85.76 74	95.98 13	65.21 142	93.59 62	92.58 104	66.54 228	86.17 21	95.88 15	63.83 67	97.00 68	86.39 33	92.94 40	95.06 51
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
CANet		89.61 6	89.99 6	88.46 13	94.39 26	69.71 32	96.53 5	93.78 46	86.89 4	89.68 6	95.78 16	65.94 44	99.10 2	92.99 1	93.91 27	96.58 11

SD-MVS		87.49 19	87.49 20	87.50 25	93.60 41	68.82 46	93.90 54	92.63 102	76.86 71	87.90 14	95.76 17	66.17 40	97.63 39	89.06 16	91.48 60	96.05 22

Regformer-1		87.24 22	87.60 19	86.15 63	95.14 17	65.83 133	93.95 50	95.12 17	82.11 21	84.25 39	95.73 18	67.88 29	98.35 20	85.60 37	88.64 80	94.26 77

Regformer-2		87.00 26	87.43 21	85.71 77	95.14 17	64.73 152	93.95 50	94.95 20	81.69 26	84.03 43	95.73 18	67.35 33	98.19 24	85.40 39	88.64 80	94.20 79

SteuartSystems-ACMMP		86.82 31	86.90 27	86.58 47	90.42 111	66.38 120	96.09 9	93.87 44	77.73 60	84.01 44	95.66 20	63.39 73	97.94 28	87.40 26	93.55 35	95.42 34
Skip Steuart: Steuart Systems R&D Blog.
MP-MVS-pluss		85.24 45	85.13 45	85.56 78	91.42 97	65.59 136	91.54 139	92.51 106	74.56 99	80.62 61	95.64 21	59.15 108	97.00 68	86.94 30	93.80 28	94.07 90
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
test_prior3		87.38 20	87.70 17	86.42 54	94.71 23	67.35 77	95.10 27	93.10 85	75.40 89	85.25 32	95.61 22	67.94 26	96.84 80	87.47 24	94.77 15	95.05 52

test_prior2							95.10 27		75.40 89	85.25 32	95.61 22	67.94 26		87.47 24	94.77 15

MAR-MVS		84.18 57	83.43 58	86.44 53	96.25 9	65.93 130	94.28 36	94.27 39	74.41 100	79.16 76	95.61 22	53.99 173	98.88 10	69.62 145	93.26 38	94.50 73
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
agg_prior1		87.02 25	87.26 24	86.28 61	94.16 33	66.97 88	94.08 43	93.31 73	71.85 159	84.49 37	95.39 25	68.91 19	96.75 84	88.84 18	94.32 22	95.13 49

test_8					94.19 28	67.19 81	94.15 39	93.42 68	71.87 157	85.38 30	95.35 26	68.19 23	96.95 75

TEST9					94.18 29	67.28 79	94.16 37	93.51 58	71.75 165	85.52 28	95.33 27	68.01 25	97.27 55

train_agg		87.21 23	87.42 22	86.60 45	94.18 29	67.28 79	94.16 37	93.51 58	71.87 157	85.52 28	95.33 27	68.19 23	97.27 55	89.09 14	94.90 12	95.25 45

ACMMP_Plus		86.05 38	85.80 38	86.80 40	91.58 88	67.53 74	91.79 127	93.49 60	74.93 96	84.61 35	95.30 29	59.42 105	97.92 29	86.13 34	94.92 11	94.94 58

CDPH-MVS		85.71 42	85.46 42	86.46 52	94.75 22	67.19 81	93.89 55	92.83 94	70.90 178	83.09 48	95.28 30	63.62 70	97.36 49	80.63 69	94.18 23	94.84 60

cdsmvs_eth3d_5k		19.86 327	26.47 323	0.00 343	0.00 357	0.00 358	0.00 348	93.45 61	0.00 352	0.00 354	95.27 31	49.56 212	0.00 355	0.00 352	0.00 353	0.00 354

lupinMVS		87.74 17	87.77 16	87.63 23	89.24 139	71.18 14	96.57 4	92.90 92	82.70 16	87.13 17	95.27 31	64.99 58	95.80 107	89.34 13	91.80 54	95.93 26

canonicalmvs		86.85 29	86.25 32	88.66 10	91.80 84	71.92 10	93.54 64	91.71 135	80.26 31	87.55 15	95.25 33	63.59 72	96.93 78	88.18 20	84.34 113	97.11 3

alignmvs		87.28 21	86.97 26	88.24 15	91.30 100	71.14 16	95.61 16	93.56 56	79.30 38	87.07 19	95.25 33	68.43 21	96.93 78	87.87 22	84.33 114	96.65 8

MPTG		84.73 50	84.47 48	85.50 79	91.89 80	65.16 143	91.55 138	92.23 112	75.32 91	80.53 62	95.21 35	56.06 142	97.16 60	84.86 43	92.55 46	94.18 80

MTAPA		83.91 62	83.38 61	85.50 79	91.89 80	65.16 143	81.75 277	92.23 112	75.32 91	80.53 62	95.21 35	56.06 142	97.16 60	84.86 43	92.55 46	94.18 80

agg_prior3		86.93 27	87.08 25	86.48 51	94.21 27	66.95 90	94.14 40	93.40 69	71.80 162	84.86 34	95.13 37	66.16 41	97.25 57	89.09 14	94.90 12	95.25 45

Regformer-3		85.80 41	85.92 35	85.46 81	94.17 31	65.09 148	92.95 79	95.11 18	81.13 27	81.68 55	95.04 38	65.82 46	98.32 21	83.02 53	84.36 111	92.97 120

Regformer-4		85.45 44	85.69 40	84.73 102	94.17 31	63.23 185	92.95 79	94.83 23	80.66 29	81.29 57	95.04 38	65.12 51	98.08 27	82.74 54	84.36 111	92.88 124

PAPR		85.15 46	84.47 48	87.18 31	96.02 12	68.29 56	91.85 125	93.00 89	76.59 76	79.03 77	95.00 40	61.59 86	97.61 41	78.16 85	89.00 78	95.63 30

1112_ss		80.56 104	79.83 101	82.77 138	88.65 150	60.78 221	92.29 99	88.36 242	72.58 139	72.46 138	94.95 41	65.09 52	93.42 198	66.38 171	77.71 153	94.10 87

ab-mvs-re		7.91 329	10.55 330	0.00 343	0.00 357	0.00 358	0.00 348	0.00 359	0.00 352	0.00 354	94.95 41	0.00 361	0.00 355	0.00 352	0.00 353	0.00 354

HFP-MVS		84.73 50	84.40 50	85.72 75	93.75 39	65.01 149	93.50 65	93.19 80	72.19 149	79.22 74	94.93 43	59.04 109	97.67 34	81.55 63	92.21 48	94.49 74

#test#		84.98 48	84.74 47	85.72 75	93.75 39	65.01 149	94.09 42	93.19 80	73.55 124	79.22 74	94.93 43	59.04 109	97.67 34	82.66 55	92.21 48	94.49 74

CP-MVS		83.71 67	83.40 60	84.65 105	93.14 51	63.84 171	94.59 34	92.28 110	71.03 176	77.41 93	94.92 45	55.21 150	96.19 94	81.32 67	90.70 68	93.91 97

DELS-MVS		90.05 4	90.09 5	89.94 2	93.14 51	73.88 6	97.01 2	94.40 37	88.32 2	85.71 26	94.91 46	74.11 9	98.91 6	87.26 27	95.94 3	97.03 5
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
ACMMPR		84.37 53	84.06 51	85.28 89	93.56 42	64.37 162	93.50 65	93.15 83	72.19 149	78.85 80	94.86 47	56.69 134	97.45 45	81.55 63	92.20 50	94.02 93

region2R		84.36 54	84.03 52	85.36 87	93.54 43	64.31 164	93.43 68	92.95 90	72.16 152	78.86 79	94.84 48	56.97 127	97.53 43	81.38 66	92.11 52	94.24 78

TSAR-MVS + GP.		87.96 13	88.37 12	86.70 42	93.51 44	65.32 140	95.15 25	93.84 45	78.17 55	85.93 24	94.80 49	75.80 6	98.21 22	89.38 12	88.78 79	96.59 10

WTY-MVS		86.32 34	85.81 37	87.85 17	92.82 59	69.37 37	95.20 23	95.25 15	82.71 15	81.91 53	94.73 50	67.93 28	97.63 39	79.55 74	82.25 126	96.54 12

MVS		84.66 52	82.86 67	90.06 1	90.93 105	74.56 5	87.91 221	95.54 13	68.55 210	72.35 141	94.71 51	59.78 102	98.90 7	81.29 68	94.69 19	96.74 7

APD-MVS_3200maxsize		81.64 92	81.32 84	82.59 145	92.36 65	58.74 255	91.39 142	91.01 161	63.35 256	79.72 70	94.62 52	51.82 194	96.14 96	79.71 72	87.93 85	92.89 123

EPNet		87.84 16	88.38 11	86.23 62	93.30 46	66.05 127	95.26 21	94.84 22	87.09 3	88.06 13	94.53 53	66.79 36	97.34 51	83.89 49	91.68 56	95.29 40
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MP-MVS		85.02 47	84.97 46	85.17 93	92.60 63	64.27 167	93.24 70	92.27 111	73.13 130	79.63 71	94.43 54	61.90 84	97.17 59	85.00 41	92.56 45	94.06 91

PGM-MVS		83.25 69	82.70 71	84.92 97	92.81 60	64.07 169	90.44 171	92.20 117	71.28 174	77.23 96	94.43 54	55.17 151	97.31 52	79.33 76	91.38 61	93.37 106

xiu_mvs_v1_base_debu		82.16 85	81.12 86	85.26 90	86.42 183	68.72 47	92.59 94	90.44 172	73.12 131	84.20 40	94.36 56	38.04 277	95.73 111	84.12 46	86.81 91	91.33 146

xiu_mvs_v1_base		82.16 85	81.12 86	85.26 90	86.42 183	68.72 47	92.59 94	90.44 172	73.12 131	84.20 40	94.36 56	38.04 277	95.73 111	84.12 46	86.81 91	91.33 146

xiu_mvs_v1_base_debi		82.16 85	81.12 86	85.26 90	86.42 183	68.72 47	92.59 94	90.44 172	73.12 131	84.20 40	94.36 56	38.04 277	95.73 111	84.12 46	86.81 91	91.33 146

旧先验1					91.94 76	60.74 224		91.50 143			94.36 56	65.23 50			91.84 53	94.55 68

CSCG		86.87 28	86.26 31	88.72 9	95.05 20	70.79 17	93.83 57	95.33 14	68.48 213	77.63 90	94.35 60	73.04 10	98.45 17	84.92 42	93.71 32	96.92 6

MVSFormer		83.75 66	82.88 66	86.37 57	89.24 139	71.18 14	89.07 202	90.69 167	65.80 234	87.13 17	94.34 61	64.99 58	92.67 217	72.83 114	91.80 54	95.27 42

jason		86.40 33	86.17 33	87.11 34	86.16 189	70.54 20	95.71 15	92.19 119	82.00 24	84.58 36	94.34 61	61.86 85	95.53 123	87.76 23	90.89 66	95.27 42
jason: jason.
XVS		83.87 63	83.47 56	85.05 95	93.22 47	63.78 173	92.92 81	92.66 100	73.99 111	78.18 84	94.31 63	55.25 147	97.41 46	79.16 77	91.58 58	93.95 95

mPP-MVS		82.96 75	82.44 72	84.52 109	92.83 57	62.92 193	92.76 84	91.85 130	71.52 171	75.61 108	94.24 64	53.48 182	96.99 71	78.97 80	90.73 67	93.64 102

EI-MVSNet-Vis-set		83.77 65	83.67 53	84.06 116	92.79 61	63.56 182	91.76 130	94.81 25	79.65 36	77.87 86	94.09 65	63.35 74	97.90 30	79.35 75	79.36 140	90.74 154

testdata				81.34 182	89.02 143	57.72 262		89.84 199	58.65 286	85.32 31	94.09 65	57.03 125	93.28 199	69.34 148	90.56 71	93.03 118

MVS_111021_HR		86.19 37	85.80 38	87.37 27	93.17 50	69.79 30	93.99 48	93.76 49	79.08 45	78.88 78	93.99 67	62.25 82	98.15 25	85.93 36	91.15 64	94.15 84

HPM-MVS		83.25 69	82.95 65	84.17 114	92.25 70	62.88 195	90.91 160	91.86 129	70.30 191	77.12 97	93.96 68	56.75 132	96.28 92	82.04 59	91.34 63	93.34 107

DP-MVS Recon		82.73 76	81.65 81	85.98 65	97.31 3	67.06 85	95.15 25	91.99 124	69.08 202	76.50 103	93.89 69	54.48 167	98.20 23	70.76 137	85.66 103	92.69 125

EI-MVSNet-UG-set		83.14 71	82.96 64	83.67 126	92.28 69	63.19 188	91.38 144	94.68 28	79.22 40	76.60 101	93.75 70	62.64 80	97.76 32	78.07 86	78.01 151	90.05 161

CANet_DTU		84.09 59	83.52 54	85.81 70	90.30 114	66.82 95	91.87 123	89.01 229	85.27 7	86.09 22	93.74 71	47.71 230	96.98 72	77.90 88	89.78 75	93.65 101

DeepC-MVS	77.85 3	85.52 43	85.24 44	86.37 57	88.80 148	66.64 110	92.15 102	93.68 52	81.07 28	76.91 100	93.64 72	62.59 81	98.44 18	85.50 38	92.84 42	94.03 92
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PAPM_NR		82.97 74	81.84 78	86.37 57	94.10 35	66.76 102	87.66 231	92.84 93	69.96 194	74.07 121	93.57 73	63.10 78	97.50 44	70.66 138	90.58 70	94.85 59

PMMVS		81.98 90	82.04 76	81.78 174	89.76 124	56.17 278	91.13 157	90.69 167	77.96 57	80.09 66	93.57 73	46.33 240	94.99 132	81.41 65	87.46 88	94.17 82

LFMVS		84.34 55	82.73 70	89.18 8	94.76 21	73.25 8	94.99 30	91.89 128	71.90 155	82.16 52	93.49 75	47.98 227	97.05 63	82.55 56	84.82 107	97.25 2

ACMMP		81.49 93	80.67 91	83.93 118	91.71 86	62.90 194	92.13 103	92.22 116	71.79 163	71.68 149	93.49 75	50.32 204	96.96 74	78.47 82	84.22 118	91.93 140
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
CPTT-MVS		79.59 124	79.16 115	80.89 197	91.54 91	59.80 241	92.10 105	88.54 240	60.42 276	72.96 127	93.28 77	48.27 223	92.80 212	78.89 81	86.50 98	90.06 160

MVS_111021_LR		82.02 89	81.52 82	83.51 129	88.42 157	62.88 195	89.77 190	88.93 231	76.78 73	75.55 109	93.10 78	50.31 205	95.38 125	83.82 50	87.02 90	92.26 137

1314		80.70 102	78.95 117	85.94 67	87.77 169	67.56 73	87.91 221	92.55 105	72.17 151	67.44 203	93.09 79	50.27 206	97.04 65	71.68 126	87.64 87	93.23 112

abl_6		79.82 119	79.20 114	81.70 178	89.85 121	58.34 257	88.47 211	90.07 192	62.56 263	77.71 88	93.08 80	47.65 231	96.78 82	77.94 87	85.45 105	89.99 162

PVSNet_Blended		86.73 32	86.86 28	86.31 60	93.76 37	67.53 74	96.33 8	93.61 54	82.34 18	81.00 59	93.08 80	63.19 76	97.29 53	87.08 28	91.38 61	94.13 85

VNet		86.20 36	85.65 41	87.84 18	93.92 36	69.99 26	95.73 14	95.94 11	78.43 53	86.00 23	93.07 82	58.22 114	97.00 68	85.22 40	84.33 114	96.52 13

HPM-MVS_fast		80.25 109	79.55 107	82.33 157	91.55 90	59.95 239	91.32 148	89.16 222	65.23 240	74.71 115	93.07 82	47.81 229	95.74 110	74.87 109	88.23 82	91.31 150

PAPM		85.89 40	85.46 42	87.18 31	88.20 161	72.42 9	92.41 98	92.77 95	82.11 21	80.34 64	93.07 82	68.27 22	95.02 131	78.39 84	93.59 34	94.09 88

MG-MVS		87.11 24	86.27 30	89.62 5	97.79 1	76.27 3	94.96 31	94.49 33	78.74 51	83.87 45	92.94 85	64.34 63	96.94 76	75.19 101	94.09 24	95.66 29

1121		81.25 96	80.05 96	84.87 99	92.30 68	64.31 164	87.91 221	91.39 147	59.44 282	79.94 67	92.91 86	57.09 123	97.01 66	66.63 167	92.81 43	93.29 110

新几何1				84.73 102	92.32 67	64.28 166		91.46 145	59.56 281	79.77 69	92.90 87	56.95 128	96.57 89	63.40 196	92.91 41	93.34 107

TSAR-MVS + MP.		88.11 12	88.64 10	86.54 48	91.73 85	68.04 63	90.36 174	93.55 57	82.89 14	91.29 2	92.89 88	72.27 12	96.03 101	87.99 21	94.77 15	95.54 33

API-MVS		82.28 83	80.53 94	87.54 24	96.13 10	70.59 19	93.63 60	91.04 160	65.72 236	75.45 110	92.83 89	56.11 141	98.89 9	64.10 192	89.75 76	93.15 114

Effi-MVS+		83.82 64	82.76 69	86.99 38	89.56 132	69.40 36	91.35 146	86.12 276	72.59 138	83.22 47	92.81 90	59.60 104	96.01 103	81.76 61	87.80 86	95.56 32

TAPA-MVS	70.22 12	74.94 204	73.53 201	79.17 232	90.40 112	52.07 296	89.19 199	89.61 208	62.69 262	70.07 162	92.67 91	48.89 221	94.32 161	38.26 304	79.97 136	91.12 151
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
原ACMM1				84.42 111	93.21 49	64.27 167		93.40 69	65.39 237	79.51 72	92.50 92	58.11 116	96.69 86	65.27 183	93.96 25	92.32 134

3Dnovator+	73.60 7	82.10 88	80.60 93	86.60 45	90.89 107	66.80 101	95.20 23	93.44 67	74.05 110	67.42 204	92.49 93	49.46 213	97.65 38	70.80 136	91.68 56	95.33 37

3Dnovator	73.91 6	82.69 79	80.82 89	88.31 14	89.57 131	71.26 13	92.60 92	94.39 38	78.84 48	67.89 199	92.48 94	48.42 222	98.52 16	68.80 153	94.40 21	95.15 48

test222					89.77 123	61.60 213	89.55 192	89.42 213	56.83 295	77.28 95	92.43 95	52.76 187			91.14 65	93.09 116

sss		82.71 78	82.38 73	83.73 123	89.25 137	59.58 244	92.24 101	94.89 21	77.96 57	79.86 68	92.38 96	56.70 133	97.05 63	77.26 91	80.86 134	94.55 68

AdaColmap		78.94 134	77.00 147	84.76 101	96.34 6	65.86 131	92.66 91	87.97 250	62.18 265	70.56 153	92.37 97	43.53 254	97.35 50	64.50 189	82.86 122	91.05 152

VDD-MVS		83.06 73	81.81 79	86.81 39	90.86 108	67.70 69	95.40 19	91.50 143	75.46 86	81.78 54	92.34 98	40.09 267	97.13 62	86.85 31	82.04 128	95.60 31

CLD-MVS		82.73 76	82.35 74	83.86 119	87.90 167	67.65 71	95.45 18	92.18 120	85.06 8	72.58 134	92.27 99	52.46 191	95.78 108	84.18 45	79.06 143	88.16 185
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
OMC-MVS		78.67 143	77.91 131	80.95 196	85.76 196	57.40 267	88.49 210	88.67 235	73.85 116	72.43 139	92.10 100	49.29 215	94.55 147	72.73 116	77.89 152	90.91 153

OpenMVS	70.45 11	78.54 145	75.92 159	86.41 56	85.93 195	71.68 11	92.74 85	92.51 106	66.49 229	64.56 227	91.96 101	43.88 253	98.10 26	54.61 240	90.65 69	89.44 168

Vis-MVSNet (Re-imp)		79.24 129	79.57 104	78.24 249	88.46 155	52.29 295	90.41 173	89.12 224	74.24 106	69.13 178	91.91 102	65.77 47	90.09 270	59.00 227	88.09 84	92.33 133

gm-plane-assit					88.42 157	67.04 87			78.62 52		91.83 103		97.37 48	76.57 94

DWT-MVSNet_test		83.95 61	82.80 68	87.41 26	92.90 56	70.07 25	89.12 201	94.42 35	82.15 20	77.64 89	91.77 104	70.81 17	96.22 93	65.03 184	81.36 130	95.94 25

Vis-MVSNet		80.92 101	79.98 99	83.74 121	88.48 154	61.80 211	93.44 67	88.26 246	73.96 114	77.73 87	91.76 105	49.94 209	94.76 139	65.84 178	90.37 72	94.65 66
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
QAPM		79.95 117	77.39 140	87.64 21	89.63 130	71.41 12	93.30 69	93.70 51	65.34 239	67.39 206	91.75 106	47.83 228	98.96 5	57.71 232	89.81 74	92.54 130

IS-MVSNet		80.14 112	79.41 109	82.33 157	87.91 166	60.08 238	91.97 114	88.27 245	72.90 135	71.44 151	91.73 107	61.44 87	93.66 193	62.47 209	86.53 97	93.24 111

PatchFormer-LS_test		83.14 71	81.81 79	87.12 33	92.34 66	69.92 28	88.64 208	93.32 72	82.07 23	74.87 114	91.62 108	68.91 19	96.08 100	66.07 175	78.45 150	95.37 35

TR-MVS		78.77 139	77.37 141	82.95 135	90.49 110	60.88 219	93.67 59	90.07 192	70.08 193	74.51 116	91.37 109	45.69 243	95.70 116	60.12 221	80.32 135	92.29 135

EPNet_dtu		78.80 137	79.26 113	77.43 259	88.06 163	49.71 308	91.96 115	91.95 127	77.67 61	76.56 102	91.28 110	58.51 113	90.20 265	56.37 235	80.95 133	92.39 132
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
BH-RMVSNet		79.46 127	77.65 133	84.89 98	91.68 87	65.66 135	93.55 63	88.09 247	72.93 134	73.37 125	91.12 111	46.20 242	96.12 97	56.28 236	85.61 104	92.91 122

VDDNet		80.50 105	78.26 124	87.21 30	86.19 188	69.79 30	94.48 35	91.31 150	60.42 276	79.34 73	90.91 112	38.48 273	96.56 90	82.16 57	81.05 132	95.27 42

GG-mvs-BLEND				86.53 50	91.91 79	69.67 34	75.02 311	94.75 26		78.67 83	90.85 113	77.91 2	94.56 146	72.25 120	93.74 31	95.36 36

mvs-test1		78.74 140	77.95 129	81.14 189	83.22 224	57.13 269	93.96 49	87.78 251	75.42 87	72.68 131	90.80 114	45.08 247	94.54 148	75.08 103	77.49 160	91.74 142

CNLPA		74.31 212	72.30 215	80.32 201	91.49 92	61.66 212	90.85 161	80.72 309	56.67 296	63.85 234	90.64 115	46.75 235	90.84 257	53.79 244	75.99 170	88.47 179

PCF-MVS	73.15 9	79.29 128	77.63 134	84.29 113	86.06 190	65.96 129	87.03 239	91.10 157	69.86 195	69.79 168	90.64 115	57.54 121	96.59 87	64.37 191	82.29 125	90.32 158
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
114514_t		79.17 130	77.67 132	83.68 125	95.32 16	65.53 138	92.85 83	91.60 139	63.49 255	67.92 198	90.63 117	46.65 237	95.72 115	67.01 165	83.54 119	89.79 163

PLC	68.80 14	75.23 198	73.68 195	79.86 213	92.93 55	58.68 256	90.64 168	88.30 243	60.90 273	64.43 230	90.53 118	42.38 258	94.57 145	56.52 234	76.54 167	86.33 220
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
tfpn_ndepth		76.45 181	75.22 175	80.14 204	90.97 104	58.92 252	90.11 179	93.24 76	65.96 233	67.37 207	90.52 119	66.67 37	92.29 229	37.71 305	74.44 179	89.21 169

PVSNet	73.49 8	80.05 114	78.63 119	84.31 112	90.92 106	64.97 151	92.47 97	91.05 159	79.18 41	72.43 139	90.51 120	37.05 289	94.06 176	68.06 155	86.00 101	93.90 98

EPP-MVSNet		81.79 91	81.52 82	82.61 144	88.77 149	60.21 234	93.02 77	93.66 53	68.52 211	72.90 129	90.39 121	72.19 13	94.96 133	74.93 106	79.29 142	92.67 126

NP-MVS					87.41 173	63.04 189					90.30 122

HQP-MVS		81.14 97	80.64 92	82.64 143	87.54 170	63.66 180	94.06 44	91.70 136	79.80 33	74.18 117	90.30 122	51.63 198	95.61 117	77.63 89	78.90 144	88.63 175

BH-w/o		80.49 106	79.30 112	84.05 117	90.83 109	64.36 163	93.60 61	89.42 213	74.35 105	69.09 179	90.15 124	55.23 149	95.61 117	64.61 187	86.43 99	92.17 138

EI-MVSNet		78.97 133	78.22 125	81.25 183	85.33 197	62.73 198	89.53 194	93.21 77	72.39 143	72.14 142	90.13 125	60.99 88	94.72 142	67.73 159	72.49 194	86.29 221

CVMVSNet		74.04 214	74.27 186	73.33 285	85.33 197	43.94 322	89.53 194	88.39 241	54.33 302	70.37 158	90.13 125	49.17 217	84.05 306	61.83 213	79.36 140	91.99 139

XVG-OURS-SEG-HR		74.70 210	73.08 206	79.57 219	78.25 290	57.33 268	80.49 287	87.32 257	63.22 258	68.76 185	90.12 127	44.89 250	91.59 247	70.55 139	74.09 182	89.79 163

conf0.002		74.95 203	73.61 196	78.96 236	89.65 125	56.94 272	87.72 225	93.45 61	65.14 241	65.68 215	89.99 128	65.09 52	91.67 241	35.16 312	70.61 205	88.27 183

thresconf0.02		74.92 205	73.61 196	78.85 238	89.65 125	56.94 272	87.72 225	93.45 61	65.14 241	65.68 215	89.99 128	65.09 52	91.67 241	35.16 312	70.61 205	87.94 188

tfpn_n400		74.92 205	73.61 196	78.85 238	89.65 125	56.94 272	87.72 225	93.45 61	65.14 241	65.68 215	89.99 128	65.09 52	91.67 241	35.16 312	70.61 205	87.94 188

tfpnconf		74.92 205	73.61 196	78.85 238	89.65 125	56.94 272	87.72 225	93.45 61	65.14 241	65.68 215	89.99 128	65.09 52	91.67 241	35.16 312	70.61 205	87.94 188

tfpnview11		74.92 205	73.61 196	78.85 238	89.65 125	56.94 272	87.72 225	93.45 61	65.14 241	65.68 215	89.99 128	65.09 52	91.67 241	35.16 312	70.61 205	87.94 188

OPM-MVS		79.00 132	78.09 126	81.73 175	83.52 222	63.83 172	91.64 137	90.30 182	76.36 79	71.97 144	89.93 133	46.30 241	95.17 130	75.10 102	77.70 154	86.19 223

PVSNet_Blended_VisFu		83.97 60	83.50 55	85.39 86	90.02 118	66.59 113	93.77 58	91.73 133	77.43 66	77.08 99	89.81 134	63.77 69	96.97 73	79.67 73	88.21 83	92.60 128

CDS-MVSNet		81.43 94	80.74 90	83.52 128	86.26 187	64.45 157	92.09 106	90.65 170	75.83 83	73.95 123	89.81 134	63.97 65	92.91 209	71.27 130	82.82 123	93.20 113
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
tfpn1000		75.25 197	74.00 191	79.03 235	90.30 114	57.56 266	88.55 209	93.36 71	64.14 252	65.17 222	89.76 136	67.06 34	91.46 254	34.54 319	73.09 189	88.06 187

XVG-OURS		74.25 213	72.46 214	79.63 217	78.45 289	57.59 265	80.33 289	87.39 254	63.86 254	68.76 185	89.62 137	40.50 266	91.72 240	69.00 150	74.25 180	89.58 166

UA-Net		80.02 115	79.65 103	81.11 190	89.33 135	57.72 262	86.33 249	89.00 230	77.44 65	81.01 58	89.15 138	59.33 106	95.90 104	61.01 216	84.28 116	89.73 165

HQP_MVS		80.34 108	79.75 102	82.12 167	86.94 178	62.42 200	93.13 73	91.31 150	78.81 49	72.53 135	89.14 139	50.66 202	95.55 121	76.74 92	78.53 148	88.39 180

plane_prior4											89.14 139

thres200		79.66 122	78.33 122	83.66 127	92.54 64	65.82 134	93.06 75	96.31 8	74.90 97	73.30 126	88.66 141	59.67 103	95.61 117	47.84 265	78.67 147	89.56 167

BH-untuned		78.68 141	77.08 143	83.48 130	89.84 122	63.74 175	92.70 87	88.59 238	71.57 169	66.83 212	88.65 142	51.75 196	95.39 124	59.03 226	84.77 108	91.32 149

TAMVS		80.37 107	79.45 108	83.13 134	85.14 200	63.37 183	91.23 151	90.76 166	74.81 98	72.65 132	88.49 143	60.63 95	92.95 205	69.41 147	81.95 129	93.08 117

LPG-MVS_test		75.82 190	74.58 181	79.56 220	84.31 212	59.37 247	90.44 171	89.73 204	69.49 197	64.86 224	88.42 144	38.65 271	94.30 162	72.56 117	72.76 191	85.01 248

LGP-MVS_train				79.56 220	84.31 212	59.37 247		89.73 204	69.49 197	64.86 224	88.42 144	38.65 271	94.30 162	72.56 117	72.76 191	85.01 248

VPNet		78.82 136	77.53 136	82.70 140	84.52 207	66.44 119	93.93 52	92.23 112	80.46 30	72.60 133	88.38 146	49.18 216	93.13 201	72.47 119	63.97 258	88.55 177

FIs		79.47 126	79.41 109	79.67 216	85.95 192	59.40 246	91.68 134	93.94 43	78.06 56	68.96 182	88.28 147	66.61 38	91.77 239	66.20 174	74.99 177	87.82 192

CHOSEN 1792x2688		84.98 48	83.45 57	89.57 6	89.94 120	75.14 4	92.07 108	92.32 109	81.87 25	75.68 105	88.27 148	60.18 99	98.60 15	80.46 71	90.27 73	94.96 57

tfpn200view9		78.79 138	77.43 138	82.88 136	92.21 72	64.49 154	92.05 109	96.28 9	73.48 125	71.75 147	88.26 149	60.07 100	95.32 126	45.16 274	77.58 156	88.83 171

Fast-Effi-MVS+		81.14 97	80.01 97	84.51 110	90.24 116	65.86 131	94.12 41	89.15 223	73.81 118	75.37 111	88.26 149	57.26 122	94.53 149	66.97 166	84.92 106	93.15 114

thres400		78.68 141	77.43 138	82.43 150	92.21 72	64.49 154	92.05 109	96.28 9	73.48 125	71.75 147	88.26 149	60.07 100	95.32 126	45.16 274	77.58 156	87.48 196

nrg030		80.93 100	79.86 100	84.13 115	83.69 219	68.83 45	93.23 71	91.20 153	75.55 85	75.06 113	88.22 152	63.04 79	94.74 141	81.88 60	66.88 232	88.82 173

F-COLMAP		70.66 243	68.44 242	77.32 261	86.37 186	55.91 280	88.00 217	86.32 271	56.94 294	57.28 271	88.07 153	33.58 298	92.49 222	51.02 253	68.37 223	83.55 259

HY-MVS	76.49 5	84.28 56	83.36 62	87.02 37	92.22 71	67.74 68	84.65 256	94.50 32	79.15 42	82.23 51	87.93 154	66.88 35	96.94 76	80.53 70	82.20 127	96.39 14

conf200view11		78.32 149	77.01 145	82.27 160	91.89 80	63.21 186	91.19 155	96.33 5	72.28 145	70.45 156	87.89 155	60.31 96	95.32 126	45.16 274	77.58 156	88.27 183

thres100view900		78.37 147	77.01 145	82.46 146	91.89 80	63.21 186	91.19 155	96.33 5	72.28 145	70.45 156	87.89 155	60.31 96	95.32 126	45.16 274	77.58 156	88.83 171

thres600view7		78.00 152	76.66 150	82.03 172	91.93 77	63.69 178	91.30 149	96.33 5	72.43 141	70.46 155	87.89 155	60.31 96	94.92 136	42.64 286	76.64 166	87.48 196

test0.0.03 1		72.76 224	72.71 210	72.88 289	80.25 267	47.99 313	91.22 152	89.45 211	71.51 172	62.51 246	87.66 158	53.83 174	85.06 302	50.16 256	67.84 229	85.58 240

FC-MVSNet-test		77.99 153	78.08 127	77.70 254	84.89 203	55.51 282	90.27 176	93.75 50	76.87 70	66.80 213	87.59 159	65.71 48	90.23 264	62.89 204	73.94 183	87.37 203

TESTMET0.1,1		82.41 81	81.98 77	83.72 124	88.08 162	63.74 175	92.70 87	93.77 48	79.30 38	77.61 91	87.57 160	58.19 115	94.08 175	73.91 110	86.68 94	93.33 109

LS3D		69.17 256	66.40 256	77.50 257	91.92 78	56.12 279	85.12 253	80.37 310	46.96 318	56.50 274	87.51 161	37.25 284	93.71 191	32.52 326	79.40 139	82.68 275

Test_1112_low_res		79.56 125	78.60 120	82.43 150	88.24 160	60.39 230	92.09 106	87.99 249	72.10 153	71.84 145	87.42 162	64.62 61	93.04 202	65.80 179	77.30 163	93.85 99

view600		76.93 170	75.50 170	81.23 184	91.44 93	62.00 206	89.94 184	96.56 1	70.68 182	68.54 189	87.31 163	60.79 90	94.19 167	38.90 299	75.31 173	87.48 196

view800		76.93 170	75.50 170	81.23 184	91.44 93	62.00 206	89.94 184	96.56 1	70.68 182	68.54 189	87.31 163	60.79 90	94.19 167	38.90 299	75.31 173	87.48 196

conf0.05thres1000		76.93 170	75.50 170	81.23 184	91.44 93	62.00 206	89.94 184	96.56 1	70.68 182	68.54 189	87.31 163	60.79 90	94.19 167	38.90 299	75.31 173	87.48 196

tfpn		76.93 170	75.50 170	81.23 184	91.44 93	62.00 206	89.94 184	96.56 1	70.68 182	68.54 189	87.31 163	60.79 90	94.19 167	38.90 299	75.31 173	87.48 196

ACMP	71.68 10	75.58 194	74.23 187	79.62 218	84.97 202	59.64 242	90.80 163	89.07 227	70.39 190	62.95 241	87.30 167	38.28 274	93.87 187	72.89 113	71.45 201	85.36 245
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
CHOSEN 280x420		77.35 163	76.95 148	78.55 243	87.07 177	62.68 199	69.71 320	82.95 302	68.80 205	71.48 150	87.27 168	66.03 43	84.00 309	76.47 95	82.81 124	88.95 170

test-LLR		80.10 113	79.56 105	81.72 176	86.93 180	61.17 216	92.70 87	91.54 140	71.51 172	75.62 106	86.94 169	53.83 174	92.38 225	72.21 121	84.76 109	91.60 143

test-mter		79.96 116	79.38 111	81.72 176	86.93 180	61.17 216	92.70 87	91.54 140	73.85 116	75.62 106	86.94 169	49.84 211	92.38 225	72.21 121	84.76 109	91.60 143

UniMVSNet_NR-MVSNet		78.15 151	77.55 135	79.98 209	84.46 209	60.26 232	92.25 100	93.20 79	77.50 64	68.88 183	86.61 171	66.10 42	92.13 232	66.38 171	62.55 261	87.54 194

MVS_Test		84.16 58	83.20 63	87.05 36	91.56 89	69.82 29	89.99 183	92.05 122	77.77 59	82.84 49	86.57 172	63.93 66	96.09 98	74.91 107	89.18 77	95.25 45

DU-MVS		76.86 174	75.84 160	79.91 211	82.96 228	60.26 232	91.26 150	91.54 140	76.46 78	68.88 183	86.35 173	56.16 139	92.13 232	66.38 171	62.55 261	87.35 205

NR-MVSNet		76.05 186	74.59 180	80.44 199	82.96 228	62.18 205	90.83 162	91.73 133	77.12 67	60.96 249	86.35 173	59.28 107	91.80 238	60.74 217	61.34 274	87.35 205

UGNet		79.87 118	78.68 118	83.45 131	89.96 119	61.51 214	92.13 103	90.79 164	76.83 72	78.85 80	86.33 175	38.16 275	96.17 95	67.93 157	87.17 89	92.67 126
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
TranMVSNet+NR-MVSNet		75.86 189	74.52 183	79.89 212	82.44 231	60.64 227	91.37 145	91.37 149	76.63 75	67.65 202	86.21 176	52.37 192	91.55 248	61.84 212	60.81 277	87.48 196

cascas		78.18 150	75.77 161	85.41 85	87.14 176	69.11 39	92.96 78	91.15 155	66.71 227	70.47 154	86.07 177	37.49 283	96.48 91	70.15 141	79.80 137	90.65 155

HyFIR lowres test		81.03 99	79.56 105	85.43 84	87.81 168	68.11 62	90.18 178	90.01 195	70.65 186	72.95 128	86.06 178	63.61 71	94.50 150	75.01 105	79.75 138	93.67 100

ACMM	69.62 13	74.34 211	72.73 209	79.17 232	84.25 214	57.87 260	90.36 174	89.93 197	63.17 259	65.64 220	86.04 179	37.79 281	94.10 173	65.89 177	71.52 200	85.55 242
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
XXY-MVS		77.94 154	76.44 153	82.43 150	82.60 230	64.44 158	92.01 111	91.83 131	73.59 123	70.00 164	85.82 180	54.43 168	94.76 139	69.63 144	68.02 226	88.10 186

IB-MVS	77.80 4	82.18 84	80.46 95	87.35 28	89.14 141	70.28 22	95.59 17	95.17 16	78.85 47	70.19 161	85.82 180	70.66 18	97.67 34	72.19 123	66.52 235	94.09 88
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
MVSTER		82.47 80	82.05 75	83.74 121	92.68 62	69.01 41	91.90 122	93.21 77	79.83 32	72.14 142	85.71 182	74.72 8	94.72 142	75.72 97	72.49 194	87.50 195

WR-MVS		76.76 177	75.74 162	79.82 214	84.60 205	62.27 204	92.60 92	92.51 106	76.06 80	67.87 200	85.34 183	56.76 130	90.24 263	62.20 210	63.69 260	86.94 213

diffmvs		80.18 110	78.55 121	85.07 94	88.56 151	66.93 91	86.70 247	88.62 237	70.42 188	78.69 82	85.26 184	56.93 129	94.77 138	68.68 154	83.09 120	93.51 104

DP-MVS		69.90 249	66.48 255	80.14 204	95.36 15	62.93 191	89.56 191	76.11 317	50.27 311	57.69 269	85.23 185	39.68 268	95.73 111	33.35 321	71.05 204	81.78 280

PVSNet_BlendedMVS		83.38 68	83.43 58	83.22 132	93.76 37	67.53 74	94.06 44	93.61 54	79.13 43	81.00 59	85.14 186	63.19 76	97.29 53	87.08 28	73.91 184	84.83 250

ab-mvs		80.18 110	78.31 123	85.80 71	88.44 156	65.49 139	83.00 271	92.67 99	71.82 161	77.36 94	85.01 187	54.50 165	96.59 87	76.35 96	75.63 171	95.32 39

VPA-MVSNet		79.03 131	78.00 128	82.11 170	85.95 192	64.48 156	93.22 72	94.66 29	75.05 95	74.04 122	84.95 188	52.17 193	93.52 195	74.90 108	67.04 231	88.32 182

Fast-Effi-MVS+-dtu		75.04 200	73.37 204	80.07 207	80.86 243	59.52 245	91.20 154	85.38 283	71.90 155	65.20 221	84.84 189	41.46 263	92.97 204	66.50 170	72.96 190	87.73 193

UniMVSNet (Re)		77.58 157	76.78 149	79.98 209	84.11 215	60.80 220	91.76 130	93.17 82	76.56 77	69.93 167	84.78 190	63.32 75	92.36 227	64.89 185	62.51 263	86.78 215

mvs_anonymous		81.36 95	79.99 98	85.46 81	90.39 113	68.40 52	86.88 244	90.61 171	74.41 100	70.31 160	84.67 191	63.79 68	92.32 228	73.13 111	85.70 102	95.67 28

RPSCF		64.24 282	61.98 283	71.01 301	76.10 302	45.00 319	75.83 310	75.94 319	46.94 319	58.96 260	84.59 192	31.40 308	82.00 322	47.76 266	60.33 280	86.04 231

PS-MVSNAJss		77.26 167	76.31 154	80.13 206	80.64 253	59.16 250	90.63 170	91.06 158	72.80 136	68.58 188	84.57 193	53.55 178	93.96 183	72.97 112	71.96 197	87.27 208

MS-PatchMatch		77.90 155	76.50 152	82.12 167	85.99 191	69.95 27	91.75 132	92.70 97	73.97 113	62.58 245	84.44 194	41.11 264	95.78 108	63.76 193	92.17 51	80.62 299

MSDG		69.54 254	65.73 258	80.96 195	85.11 201	63.71 177	84.19 258	83.28 299	56.95 293	54.50 280	84.03 195	31.50 307	96.03 101	42.87 284	69.13 218	83.14 269

GA-MVS		78.33 148	76.23 155	84.65 105	83.65 220	66.30 123	91.44 140	90.14 190	76.01 81	70.32 159	84.02 196	42.50 257	94.72 142	70.98 134	77.00 165	92.94 121

pmmvs4		73.92 216	71.81 219	80.25 203	79.17 281	65.24 141	87.43 234	87.26 259	67.64 222	63.46 237	83.91 197	48.96 220	91.53 252	62.94 203	65.49 241	83.96 255

pmmvs5		73.35 219	71.52 221	78.86 237	78.64 288	60.61 228	91.08 158	86.90 260	67.69 219	63.32 238	83.64 198	44.33 252	90.53 258	62.04 211	66.02 236	85.46 243

ITE_SJBPF				70.43 302	74.44 307	47.06 317		77.32 315	60.16 278	54.04 286	83.53 199	23.30 326	84.01 308	43.07 281	61.58 273	80.21 304

jajsoiax		73.05 220	71.51 222	77.67 255	77.46 295	54.83 285	88.81 205	90.04 194	69.13 201	62.85 243	83.51 200	31.16 309	92.75 214	70.83 135	69.80 211	85.43 244

testgi		64.48 281	62.87 278	69.31 304	71.24 315	40.62 329	85.49 252	79.92 311	65.36 238	54.18 285	83.49 201	23.74 325	84.55 303	41.60 288	60.79 278	82.77 272

v2v482		77.42 159	75.65 166	82.73 139	80.38 260	67.13 84	91.85 125	90.23 184	75.09 94	69.37 175	83.39 202	53.79 176	94.44 151	71.77 124	65.00 249	86.63 219

mvs_tets		72.71 225	71.11 223	77.52 256	77.41 296	54.52 287	88.45 212	89.76 200	68.76 206	62.70 244	83.26 203	29.49 313	92.71 215	70.51 140	69.62 213	85.34 246

FMVSNet3		77.73 156	76.04 157	82.80 137	91.20 102	68.99 42	91.87 123	91.99 124	73.35 128	67.04 209	83.19 204	56.62 135	92.14 231	59.80 223	69.34 215	87.28 207

MVP-Stereo		77.12 169	76.23 155	79.79 215	81.72 236	66.34 122	89.29 196	90.88 162	70.56 187	62.01 248	82.88 205	49.34 214	94.13 172	65.55 181	93.80 28	78.88 312
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
PatchMatch-RL		72.06 228	69.98 227	78.28 246	89.51 134	55.70 281	83.49 263	83.39 298	61.24 272	63.72 235	82.76 206	34.77 296	93.03 203	53.37 248	77.59 155	86.12 225

CP-MVSNet		70.50 246	69.91 229	72.26 294	80.71 247	51.00 302	87.23 237	90.30 182	67.84 218	59.64 254	82.69 207	50.23 207	82.30 320	51.28 252	59.28 281	83.46 263

v1neww		77.39 160	75.71 163	82.44 147	80.69 248	66.83 93	91.94 119	90.18 187	74.19 107	69.60 169	82.51 208	54.99 158	94.44 151	71.68 126	65.60 238	86.05 228

v7new		77.39 160	75.71 163	82.44 147	80.69 248	66.83 93	91.94 119	90.18 187	74.19 107	69.60 169	82.51 208	54.99 158	94.44 151	71.68 126	65.60 238	86.05 228

PEN-MVS		69.46 255	68.56 240	72.17 296	79.27 279	49.71 308	86.90 243	89.24 219	67.24 226	59.08 258	82.51 208	47.23 233	83.54 312	48.42 263	57.12 289	83.25 266

v6		77.39 160	75.71 163	82.44 147	80.67 250	66.82 95	91.94 119	90.18 187	74.19 107	69.60 169	82.50 211	55.00 157	94.44 151	71.68 126	65.60 238	86.05 228

DI_MVS_plusplus_test		79.78 121	77.50 137	86.62 44	80.90 242	69.46 35	90.69 166	91.97 126	77.00 68	59.07 259	82.34 212	46.82 234	95.88 105	82.14 58	86.59 96	94.53 72

PS-CasMVS		69.86 250	69.13 236	72.07 297	80.35 261	50.57 304	87.02 240	89.75 201	67.27 225	59.19 257	82.28 213	46.58 238	82.24 321	50.69 254	59.02 284	83.39 265

FMVSNet2		76.07 185	74.01 190	82.26 163	88.85 145	67.66 70	91.33 147	91.61 138	70.84 179	65.98 214	82.25 214	48.03 224	92.00 236	58.46 229	68.73 221	87.10 209

v7		76.83 176	75.01 177	82.29 159	80.35 261	66.70 107	91.68 134	89.97 196	73.47 127	69.22 177	82.22 215	52.52 189	94.43 155	69.73 143	65.96 237	85.74 239

DTE-MVSNet		68.46 261	67.33 251	71.87 300	77.94 293	49.00 311	86.16 251	88.58 239	66.36 230	58.19 264	82.21 216	46.36 239	83.87 310	44.97 278	55.17 296	82.73 273

CMPMVS	48.56 21	66.77 271	64.41 269	73.84 282	70.65 319	50.31 305	77.79 307	85.73 282	45.54 323	44.76 319	82.14 217	35.40 293	90.14 267	63.18 199	74.54 178	81.07 294
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
v1141		77.28 165	75.57 167	82.42 153	80.63 254	66.73 103	91.96 115	90.42 175	74.41 100	69.46 172	82.12 218	55.09 154	94.40 156	70.99 133	65.05 245	86.12 225

divwei89l23v2f112		77.28 165	75.57 167	82.42 153	80.62 255	66.72 105	91.96 115	90.42 175	74.41 100	69.46 172	82.12 218	55.11 153	94.40 156	71.00 131	65.04 246	86.12 225

v1		77.29 164	75.57 167	82.42 153	80.61 258	66.73 103	91.96 115	90.42 175	74.41 100	69.46 172	82.12 218	55.14 152	94.40 156	71.00 131	65.04 246	86.13 224

test_normal		79.66 122	77.36 142	86.54 48	80.72 246	69.21 38	90.68 167	92.16 121	76.99 69	58.63 263	82.03 221	46.70 236	95.86 106	81.74 62	86.63 95	94.56 67

test_djsdf		73.76 218	72.56 212	77.39 260	77.00 298	53.93 289	89.07 202	90.69 167	65.80 234	63.92 232	82.03 221	43.14 256	92.67 217	72.83 114	68.53 222	85.57 241

v1144		76.73 178	74.88 178	82.27 160	80.23 268	66.60 111	91.68 134	90.21 186	73.69 120	69.06 180	81.89 223	52.73 188	94.40 156	69.21 149	65.23 242	85.80 235

V42		76.46 180	74.55 182	82.19 165	79.14 282	67.82 66	90.26 177	89.42 213	73.75 119	68.63 187	81.89 223	51.31 200	94.09 174	71.69 125	64.84 250	84.66 251

pm-mvs1		72.89 222	71.09 224	78.26 248	79.10 284	57.62 264	90.80 163	89.30 216	67.66 220	62.91 242	81.78 225	49.11 219	92.95 205	60.29 220	58.89 286	84.22 254

IterMVS-LS		76.49 179	75.18 176	80.43 200	84.49 208	62.74 197	90.64 168	88.80 233	72.40 142	65.16 223	81.72 226	60.98 89	92.27 230	67.74 158	64.65 253	86.29 221
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CostFormer		82.33 82	81.15 85	85.86 68	89.01 144	68.46 51	82.39 274	93.01 87	75.59 84	80.25 65	81.57 227	72.03 14	94.96 133	79.06 79	77.48 161	94.16 83

Effi-MVS+-dtu		76.14 184	75.28 174	78.72 242	83.22 224	55.17 284	89.87 188	87.78 251	75.42 87	67.98 197	81.43 228	45.08 247	92.52 221	75.08 103	71.63 198	88.48 178

v1192		75.98 188	73.92 192	82.15 166	79.73 273	66.24 125	91.22 152	89.75 201	72.67 137	68.49 193	81.42 229	49.86 210	94.27 164	67.08 164	65.02 248	85.95 232

COLMAP_ROB	57.96 20	62.98 289	59.65 289	72.98 288	81.44 239	53.00 293	83.75 260	75.53 323	48.34 316	48.81 307	81.40 230	24.14 323	90.30 260	32.95 323	60.52 279	75.65 323
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
v144192		76.05 186	74.03 189	82.12 167	79.50 277	66.55 115	91.39 142	89.71 207	72.30 144	68.17 195	81.33 231	51.75 196	94.03 180	67.94 156	64.19 255	85.77 236

AllTest		61.66 290	58.06 291	72.46 292	79.57 274	51.42 300	80.17 292	68.61 336	51.25 308	45.88 313	81.23 232	19.86 331	86.58 298	38.98 297	57.01 291	79.39 309

TestCases				72.46 292	79.57 274	51.42 300		68.61 336	51.25 308	45.88 313	81.23 232	19.86 331	86.58 298	38.98 297	57.01 291	79.39 309

v1921920		75.63 193	73.49 202	82.06 171	79.38 278	66.35 121	91.07 159	89.48 210	71.98 154	67.99 196	81.22 234	49.16 218	93.90 186	66.56 169	64.56 254	85.92 234

v1240		75.21 199	72.98 207	81.88 173	79.20 280	66.00 128	90.75 165	89.11 225	71.63 167	67.41 205	81.22 234	47.36 232	93.87 187	65.46 182	64.72 252	85.77 236

XVG-ACMP-BASELINE		68.04 263	65.53 260	75.56 272	74.06 309	52.37 294	78.43 302	85.88 280	62.03 266	58.91 261	81.21 236	20.38 330	91.15 256	60.69 218	68.18 224	83.16 268

EU-MVSNet		64.01 284	63.01 276	67.02 310	74.40 308	38.86 334	83.27 267	86.19 274	45.11 324	54.27 283	81.15 237	36.91 290	80.01 326	48.79 262	57.02 290	82.19 278

ACMH+	65.35 16	67.65 265	64.55 266	76.96 264	84.59 206	57.10 270	88.08 216	80.79 308	58.59 287	53.00 293	81.09 238	26.63 321	92.95 205	46.51 269	61.69 272	80.82 296

v148		76.19 183	74.47 184	81.36 181	80.05 272	64.44 158	91.75 132	90.23 184	73.68 121	67.13 208	80.84 239	55.92 145	93.86 189	68.95 151	61.73 270	85.76 238

WR-MVS_H		70.59 244	69.94 228	72.53 291	81.03 241	51.43 299	87.35 236	92.03 123	67.38 224	60.23 252	80.70 240	55.84 146	83.45 313	46.33 270	58.58 287	82.72 274

Baseline_NR-MVSNet		73.99 215	72.83 208	77.48 258	80.78 244	59.29 249	91.79 127	84.55 287	68.85 204	68.99 181	80.70 240	56.16 139	92.04 235	62.67 207	60.98 276	81.11 293

PVSNet_0	68.08 15	71.81 230	68.32 244	82.27 160	84.68 204	62.31 203	88.68 207	90.31 181	75.84 82	57.93 266	80.65 242	37.85 280	94.19 167	69.94 142	29.05 339	90.31 159

tpm2		79.80 120	77.95 129	85.34 88	88.28 159	68.26 58	81.56 282	91.42 146	70.11 192	77.59 92	80.50 243	67.40 31	94.26 166	67.34 162	77.35 162	93.51 104

TransMVSNet (Re)		70.07 248	67.66 249	77.31 262	80.62 255	59.13 251	91.78 129	84.94 285	65.97 232	60.08 253	80.44 244	50.78 201	91.87 237	48.84 261	45.46 323	80.94 295

USDC		67.43 269	64.51 267	76.19 269	77.94 293	55.29 283	78.38 303	85.00 284	73.17 129	48.36 308	80.37 245	21.23 329	92.48 223	52.15 250	64.02 257	80.81 297

LTVRE_ROB	59.60 19	66.27 273	63.54 272	74.45 278	84.00 217	51.55 298	67.08 327	83.53 295	58.78 285	54.94 278	80.31 246	34.54 297	93.23 200	40.64 293	68.03 225	78.58 315
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
v8		75.35 195	73.26 205	81.61 179	80.67 250	66.82 95	89.54 193	89.27 217	71.65 166	63.30 239	80.30 247	54.99 158	94.06 176	67.33 163	62.33 264	83.94 256

GBi-Net		75.65 191	73.83 193	81.10 191	88.85 145	65.11 145	90.01 180	90.32 178	70.84 179	67.04 209	80.25 248	48.03 224	91.54 249	59.80 223	69.34 215	86.64 216

test1		75.65 191	73.83 193	81.10 191	88.85 145	65.11 145	90.01 180	90.32 178	70.84 179	67.04 209	80.25 248	48.03 224	91.54 249	59.80 223	69.34 215	86.64 216

FMVSNet1		72.71 225	69.91 229	81.10 191	83.60 221	65.11 145	90.01 180	90.32 178	63.92 253	63.56 236	80.25 248	36.35 291	91.54 249	54.46 241	66.75 233	86.64 216

LCM-MVSNet-Re		72.93 221	71.84 218	76.18 270	88.49 153	48.02 312	80.07 294	70.17 334	73.96 114	52.25 295	80.09 251	49.98 208	88.24 289	67.35 161	84.23 117	92.28 136

v10		74.77 209	72.54 213	81.46 180	80.33 265	66.71 106	89.15 200	89.08 226	70.94 177	63.08 240	79.86 252	52.52 189	94.04 179	65.70 180	62.17 265	83.64 258

anonymousdsp		71.14 238	69.37 233	76.45 267	72.95 310	54.71 286	84.19 258	88.88 232	61.92 268	62.15 247	79.77 253	38.14 276	91.44 255	68.90 152	67.45 230	83.21 267

tpm		78.58 144	77.03 144	83.22 132	85.94 194	64.56 153	83.21 269	91.14 156	78.31 54	73.67 124	79.68 254	64.01 64	92.09 234	66.07 175	71.26 203	93.03 118

OurMVSNet-221017-0		64.68 279	62.17 282	72.21 295	76.08 303	47.35 316	80.67 286	81.02 307	56.19 297	51.60 297	79.66 255	27.05 320	88.56 286	53.60 246	53.63 301	80.71 298

Test4		76.45 181	73.45 203	85.45 83	76.07 304	67.61 72	88.38 213	90.83 163	76.71 74	53.06 292	79.65 256	31.61 306	94.35 160	78.47 82	86.22 100	94.40 76

tpmrst		80.57 103	79.14 116	84.84 100	90.10 117	68.28 57	81.70 278	89.72 206	77.63 62	75.96 104	79.54 257	64.94 60	92.71 215	75.43 99	77.28 164	93.55 103

ACMH	63.93 17	68.62 258	64.81 264	80.03 208	85.22 199	63.25 184	87.72 225	84.66 286	60.83 274	51.57 298	79.43 258	27.29 319	94.96 133	41.76 287	64.84 250	81.88 279
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
tpmp4_e23		78.85 135	76.55 151	85.77 73	89.25 137	68.39 53	81.63 281	91.38 148	70.40 189	75.21 112	79.22 259	67.37 32	94.79 137	58.98 228	75.51 172	94.13 85

semantic-postprocess				76.32 268	81.48 237	60.67 226		85.99 278	66.17 231	59.50 255	78.88 260	45.51 245	83.65 311	62.58 208	61.93 266	84.63 253

IterMVS		72.65 227	70.83 225	78.09 252	82.17 232	62.96 190	87.64 232	86.28 272	71.56 170	60.44 251	78.85 261	45.42 246	86.66 297	63.30 197	61.83 267	84.65 252
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
tfpnnormal		70.10 247	67.36 250	78.32 245	83.45 223	60.97 218	88.85 204	92.77 95	64.85 247	60.83 250	78.53 262	43.52 255	93.48 196	31.73 327	61.70 271	80.52 300

v7n		71.31 235	68.65 238	79.28 227	76.40 300	60.77 222	86.71 246	89.45 211	64.17 251	58.77 262	78.24 263	44.59 251	93.54 194	57.76 231	61.75 269	83.52 261

EPMVS		78.49 146	75.98 158	86.02 64	91.21 101	69.68 33	80.23 291	91.20 153	75.25 93	72.48 137	78.11 264	54.65 164	93.69 192	57.66 233	83.04 121	94.69 63

pmmvs6		67.57 266	64.76 265	76.00 271	72.82 312	53.37 291	88.71 206	86.78 261	53.19 303	57.58 270	78.03 265	35.33 294	92.41 224	55.56 238	54.88 298	82.21 277

OpenMVS_ROB	61.12 18	66.39 272	62.92 277	76.80 266	76.51 299	57.77 261	89.22 197	83.41 297	55.48 300	53.86 288	77.84 266	26.28 322	93.95 184	34.90 318	68.76 220	78.68 314

EG-PatchMatch MVS		68.55 259	65.41 261	77.96 253	78.69 287	62.93 191	89.86 189	89.17 221	60.55 275	50.27 303	77.73 267	22.60 327	94.06 176	47.18 268	72.65 193	76.88 320

SixPastTwentyTwo		64.92 278	61.78 284	74.34 280	78.74 286	49.76 307	83.42 266	79.51 313	62.86 261	50.27 303	77.35 268	30.92 311	90.49 259	45.89 272	47.06 320	82.78 271

test20.03		63.83 285	62.65 279	67.38 309	70.58 320	39.94 330	86.57 248	84.17 289	63.29 257	51.86 296	77.30 269	37.09 288	82.47 318	38.87 303	54.13 300	79.73 307

Anonymous20231206		67.53 267	65.78 257	72.79 290	74.95 306	47.59 315	88.23 214	87.32 257	61.75 271	58.07 265	77.29 270	37.79 281	87.29 295	42.91 282	63.71 259	83.48 262

test_0402		64.54 280	61.09 285	74.92 275	84.10 216	60.75 223	87.95 218	79.71 312	52.03 306	52.41 294	77.20 271	32.21 304	91.64 246	23.14 337	61.03 275	72.36 327

dp		75.01 201	72.09 217	83.76 120	89.28 136	66.22 126	79.96 296	89.75 201	71.16 175	67.80 201	77.19 272	51.81 195	92.54 220	50.39 255	71.44 202	92.51 131

v748		70.55 245	67.97 248	78.27 247	75.75 305	58.78 254	86.29 250	89.25 218	65.12 246	56.66 273	77.17 273	45.05 249	92.95 205	58.13 230	58.33 288	83.10 270

Patchmatch-test1		75.00 202	71.80 220	84.58 107	86.63 182	70.08 24	81.06 284	89.19 220	71.60 168	70.01 163	77.16 274	45.53 244	88.63 283	51.79 251	73.27 186	95.02 56

Patchmatch-test		65.86 275	60.94 286	80.62 198	83.75 218	58.83 253	58.91 337	75.26 324	44.50 327	50.95 302	77.09 275	58.81 112	87.90 291	35.13 317	64.03 256	95.12 50

PatchmatchNet		77.46 158	74.63 179	85.96 66	89.55 133	70.35 21	79.97 295	89.55 209	72.23 147	70.94 152	76.91 276	57.03 125	92.79 213	54.27 242	81.17 131	94.74 62
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tpm cat1		75.30 196	72.21 216	84.58 107	88.52 152	67.77 67	78.16 306	88.02 248	61.88 269	68.45 194	76.37 277	60.65 94	94.03 180	53.77 245	74.11 181	91.93 140

TDRefinement		55.28 305	51.58 306	66.39 312	59.53 337	46.15 318	76.23 309	72.80 328	44.60 326	42.49 325	76.28 278	15.29 336	82.39 319	33.20 322	43.75 325	70.62 331

V4		69.80 251	67.02 253	78.15 250	71.86 313	60.10 236	82.02 275	87.39 254	64.48 248	57.78 268	75.98 279	41.49 261	92.90 210	63.00 201	59.16 282	81.44 285

v52		69.80 251	67.01 254	78.15 250	71.84 314	60.10 236	82.02 275	87.39 254	64.48 248	57.80 267	75.97 280	41.47 262	92.90 210	63.00 201	59.13 283	81.45 284

MDTV_nov1_ep13			72.61 211		89.06 142	68.48 50	80.33 289	90.11 191	71.84 160	71.81 146	75.92 281	53.01 185	93.92 185	48.04 264	73.38 185

TinyColmap		60.32 293	56.42 299	72.00 298	78.78 285	53.18 292	78.36 304	75.64 320	52.30 305	41.59 329	75.82 282	14.76 338	88.35 288	35.84 309	54.71 299	74.46 324

LF4IMVS		54.01 306	52.12 304	59.69 319	62.41 332	39.91 331	68.59 322	68.28 338	42.96 330	44.55 321	75.18 283	14.09 339	68.39 339	41.36 290	51.68 306	70.78 330

tpmvs		72.88 223	69.76 231	82.22 164	90.98 103	67.05 86	78.22 305	88.30 243	63.10 260	64.35 231	74.98 284	55.09 154	94.27 164	43.25 280	69.57 214	85.34 246

MIMVSNet		71.64 233	68.44 242	81.23 184	81.97 235	64.44 158	73.05 313	88.80 233	69.67 196	64.59 226	74.79 285	32.79 300	87.82 292	53.99 243	76.35 168	91.42 145

UnsupCasMVSNet_eth		65.79 276	63.10 275	73.88 281	70.71 318	50.29 306	81.09 283	89.88 198	72.58 139	49.25 306	74.77 286	32.57 302	87.43 294	55.96 237	41.04 329	83.90 257

lessismore_v0				73.72 283	72.93 311	47.83 314		61.72 344		45.86 315	73.76 287	28.63 316	89.81 277	47.75 267	31.37 338	83.53 260

FMVSNet5		68.04 263	65.66 259	75.18 274	84.43 210	57.89 259	83.54 262	86.26 273	61.83 270	53.64 290	73.30 288	37.15 287	85.08 301	48.99 260	61.77 268	82.56 276

test2356		64.16 283	63.28 274	66.81 311	69.37 324	39.86 332	87.76 224	86.02 277	59.83 280	53.54 291	73.23 289	34.94 295	80.67 325	39.66 295	65.20 243	79.89 305

testus		59.36 297	57.51 294	64.90 314	66.72 326	37.56 335	84.98 254	81.09 306	57.46 291	47.72 310	72.76 290	11.43 342	78.78 332	36.56 306	58.91 285	78.36 317

v18		71.94 229	69.43 232	79.50 222	80.74 245	66.82 95	88.16 215	86.66 262	68.95 203	55.55 275	72.66 291	55.03 156	90.15 266	64.78 186	52.30 303	81.54 281

v16		71.81 230	69.26 234	79.47 223	80.66 252	66.81 99	87.93 219	86.63 264	68.70 208	55.35 276	72.51 292	54.75 162	90.12 268	64.51 188	52.28 304	81.47 282

pmmvs-eth3d		65.53 277	62.32 281	75.19 273	69.39 323	59.59 243	82.80 272	83.43 296	62.52 264	51.30 300	72.49 293	32.86 299	87.16 296	55.32 239	50.73 309	78.83 313

v17		71.77 232	69.20 235	79.46 224	80.62 255	66.81 99	87.93 219	86.63 264	68.71 207	55.25 277	72.49 293	54.72 163	90.11 269	64.50 189	51.97 305	81.47 282

MDA-MVSNet-bldmvs		61.54 292	57.70 293	73.05 287	79.53 276	57.00 271	83.08 270	81.23 305	57.57 288	34.91 334	72.45 295	32.79 300	86.26 300	35.81 310	41.95 327	75.89 322

CR-MVSNet		73.79 217	70.82 226	82.70 140	83.15 226	67.96 64	70.25 317	84.00 292	73.67 122	69.97 165	72.41 296	57.82 118	89.48 279	52.99 249	73.13 187	90.64 156

Patchmtry		67.53 267	63.93 271	78.34 244	82.12 233	64.38 161	68.72 321	84.00 292	48.23 317	59.24 256	72.41 296	57.82 118	89.27 281	46.10 271	56.68 293	81.36 287

K. test v3		63.09 288	59.61 290	73.53 284	76.26 301	49.38 310	83.27 267	77.15 316	64.35 250	47.77 309	72.32 298	28.73 314	87.79 293	49.93 258	36.69 334	83.41 264

PM-MVS		59.40 296	56.59 297	67.84 306	63.63 329	41.86 326	76.76 308	63.22 342	59.01 284	51.07 301	72.27 299	11.72 340	83.25 315	61.34 214	50.28 315	78.39 316

v15		71.40 234	68.75 237	79.35 225	80.39 259	66.70 107	87.57 233	86.64 263	68.66 209	54.68 279	72.00 300	54.50 165	89.98 271	63.69 194	50.66 310	81.38 286

V14		71.29 236	68.61 239	79.31 226	80.34 263	66.65 109	87.39 235	86.61 266	68.41 214	54.49 281	71.91 301	54.25 170	89.96 272	63.50 195	50.62 311	81.33 288

MIMVSNet1		60.16 295	57.33 295	68.67 305	69.71 322	44.13 321	78.92 300	84.21 288	55.05 301	44.63 320	71.85 302	23.91 324	81.54 324	32.63 325	55.03 297	80.35 301

V9		71.16 237	68.46 241	79.27 228	80.26 266	66.60 111	87.21 238	86.56 267	68.17 215	54.26 284	71.81 303	54.00 172	89.93 273	63.28 198	50.57 312	81.27 289

v12		71.02 241	68.29 246	79.22 230	80.18 269	66.53 116	87.01 241	86.54 269	67.90 217	54.00 287	71.70 304	53.66 177	89.91 274	63.09 200	50.51 313	81.21 290

v11		71.05 240	68.32 244	79.23 229	80.34 263	66.57 114	87.01 241	86.55 268	68.11 216	54.40 282	71.66 305	52.94 186	89.91 274	62.71 206	51.12 308	81.21 290

v13		70.90 242	68.15 247	79.15 234	80.08 270	66.45 118	86.83 245	86.50 270	67.62 223	53.78 289	71.61 306	53.51 181	89.87 276	62.89 204	50.50 314	81.14 292

DSMNet-mixed		56.78 300	54.44 302	63.79 316	63.21 330	29.44 343	64.43 330	64.10 341	42.12 332	51.32 299	71.60 307	31.76 305	75.04 335	36.23 308	65.20 243	86.87 214

MDA-MVSNet_test_wron		63.78 286	60.16 287	74.64 276	78.15 291	60.41 229	83.49 263	84.03 290	56.17 299	39.17 331	71.59 308	37.22 285	83.24 316	42.87 284	48.73 317	80.26 303

YYNet1		63.76 287	60.14 288	74.62 277	78.06 292	60.19 235	83.46 265	83.99 294	56.18 298	39.25 330	71.56 309	37.18 286	83.34 314	42.90 283	48.70 318	80.32 302

testing_2		71.09 239	67.32 252	82.40 156	69.82 321	66.52 117	83.64 261	90.77 165	72.21 148	45.12 318	71.07 310	27.60 318	93.74 190	75.71 98	69.96 210	86.95 212

ADS-MVSNet2		66.90 270	63.44 273	77.26 263	88.06 163	60.70 225	68.01 324	75.56 322	57.57 288	64.48 228	69.87 311	38.68 269	84.10 305	40.87 291	67.89 227	86.97 210

ADS-MVSNet		68.54 260	64.38 270	81.03 194	88.06 163	66.90 92	68.01 324	84.02 291	57.57 288	64.48 228	69.87 311	38.68 269	89.21 282	40.87 291	67.89 227	86.97 210

N_pmnet		50.55 308	49.11 310	54.88 325	77.17 297	4.02 355	84.36 257	2.00 355	48.59 314	45.86 315	68.82 313	32.22 303	82.80 317	31.58 328	51.38 307	77.81 318

patchmatchnet-post											67.62 314	57.62 120	90.25 261

testpf		57.17 299	56.93 296	57.88 321	79.13 283	42.40 323	34.23 344	85.97 279	52.64 304	47.66 311	66.50 315	36.33 292	79.65 328	53.60 246	56.31 294	51.60 340

ambc				69.61 303	61.38 335	41.35 327	49.07 341	85.86 281		50.18 305	66.40 316	10.16 343	88.14 290	45.73 273	44.20 324	79.32 311

new-patchmatchnet		59.30 298	56.48 298	67.79 307	65.86 327	44.19 320	82.47 273	81.77 303	59.94 279	43.65 324	66.20 317	27.67 317	81.68 323	39.34 296	41.40 328	77.50 319

1111		56.66 302	54.98 301	61.69 317	61.99 333	31.38 339	79.81 297	83.17 300	45.66 321	41.94 326	65.44 318	41.50 259	79.56 329	27.64 331	47.68 319	74.14 325

.test1245		46.52 312	49.68 308	37.02 334	61.99 333	31.38 339	79.81 297	83.17 300	45.66 321	41.94 326	65.44 318	41.50 259	79.56 329	27.64 331	0.01 351	0.13 352

PatchT		69.11 257	65.37 262	80.32 201	82.07 234	63.68 179	67.96 326	87.62 253	50.86 310	69.37 175	65.18 320	57.09 123	88.53 287	41.59 289	66.60 234	88.74 174

RPMNet		69.58 253	65.21 263	82.70 140	83.15 226	67.96 64	70.25 317	86.15 275	46.83 320	69.97 165	65.10 321	56.48 138	89.48 279	35.79 311	73.13 187	90.64 156

pmmvs3		55.51 304	51.50 307	67.53 308	57.90 338	50.93 303	80.37 288	73.66 327	40.63 333	44.15 322	64.75 322	16.30 334	78.97 331	44.77 279	40.98 330	72.69 326

Anonymous20231211		53.57 307	49.43 309	66.00 313	65.01 328	42.08 324	80.95 285	72.60 329	38.46 334	41.65 328	64.48 323	15.72 335	84.23 304	25.78 334	40.24 331	71.68 328

Patchmatch-RL test		68.17 262	64.49 268	79.19 231	71.22 316	53.93 289	70.07 319	71.54 333	69.22 200	56.79 272	62.89 324	56.58 136	88.61 284	69.53 146	52.61 302	95.03 55

test1235678		55.73 303	52.74 303	64.68 315	60.16 336	35.56 337	81.65 279	81.46 304	51.27 307	38.93 332	62.82 325	17.44 333	78.58 333	30.87 329	50.09 316	79.89 305

UnsupCasMVSNet_bld		61.60 291	57.71 292	73.29 286	68.73 325	51.64 297	78.61 301	89.05 228	57.20 292	46.11 312	61.96 326	28.70 315	88.60 285	50.08 257	38.90 332	79.63 308

FPMVS		45.64 313	43.10 314	53.23 327	51.42 341	36.46 336	64.97 329	71.91 331	29.13 338	27.53 337	61.55 327	9.83 344	65.01 343	16.00 343	55.58 295	58.22 339

LP		56.71 301	51.64 305	71.91 299	80.08 270	60.33 231	61.72 332	75.61 321	43.87 329	43.76 323	60.30 328	30.46 312	84.05 306	22.94 338	46.06 322	71.34 329

test12356		47.51 310	44.82 312	55.56 323	52.53 339	21.09 350	71.45 316	76.03 318	44.14 328	30.69 335	58.18 329	9.01 346	76.14 334	26.95 333	34.43 337	69.46 333

new_pmnet		49.31 309	46.44 311	57.93 320	62.84 331	40.74 328	68.47 323	62.96 343	36.48 335	35.09 333	57.81 330	14.97 337	72.18 336	32.86 324	46.44 321	60.88 338

testmv		46.98 311	43.53 313	57.35 322	47.75 344	30.41 342	74.99 312	77.69 314	42.84 331	28.03 336	53.36 331	8.18 347	71.18 337	24.36 336	34.55 335	70.46 332

DeepMVS_CX				34.71 335	51.45 340	24.73 349		28.48 354	31.46 337	17.49 343	52.75 332	5.80 350	42.60 350	18.18 342	19.42 340	36.81 344

PMMVS2		37.93 317	33.61 318	50.92 328	46.31 345	24.76 348	60.55 336	50.05 346	28.94 339	20.93 339	47.59 333	4.41 353	65.13 342	25.14 335	18.55 341	62.87 336

JIA-IIPM		66.06 274	62.45 280	76.88 265	81.42 240	54.45 288	57.49 338	88.67 235	49.36 313	63.86 233	46.86 334	56.06 142	90.25 261	49.53 259	68.83 219	85.95 232

gg-mvs-nofinetune		77.18 168	74.31 185	85.80 71	91.42 97	68.36 54	71.78 314	94.72 27	49.61 312	77.12 97	45.92 335	77.41 3	93.98 182	67.62 160	93.16 39	95.05 52

LCM-MVSNet		40.54 315	35.79 316	54.76 326	36.92 349	30.81 341	51.41 339	69.02 335	22.07 340	24.63 338	45.37 336	4.56 352	65.81 341	33.67 320	34.50 336	67.67 334

tmp_tt		22.26 326	23.75 325	17.80 339	5.23 354	12.06 354	35.26 343	39.48 350	2.82 349	18.94 341	44.20 337	22.23 328	24.64 351	36.30 307	9.31 348	16.69 347

MVS-HIRNet		60.25 294	55.55 300	74.35 279	84.37 211	56.57 277	71.64 315	74.11 326	34.44 336	45.54 317	42.24 338	31.11 310	89.81 277	40.36 294	76.10 169	76.67 321

ANet_high		40.27 316	35.20 317	55.47 324	34.74 350	34.47 338	63.84 331	71.56 332	48.42 315	18.80 342	41.08 339	9.52 345	64.45 344	20.18 340	8.66 349	67.49 335

PMVS	26.43 22	31.84 320	28.16 322	42.89 331	25.87 353	27.58 346	50.92 340	49.78 348	21.37 342	14.17 346	40.81 340	2.01 354	66.62 340	9.61 346	38.88 333	34.49 345
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
no-one		44.13 314	38.39 315	61.34 318	45.91 346	41.94 325	61.67 333	75.07 325	45.05 325	20.07 340	40.68 341	11.58 341	79.82 327	30.18 330	15.30 342	62.26 337

PNet_i23d		32.77 319	29.98 321	41.11 332	48.05 342	29.17 344	65.82 328	50.02 347	21.42 341	14.74 345	37.19 342	1.11 356	55.11 346	19.75 341	11.77 344	39.06 342

MVE	24.84 23	24.35 324	19.77 328	38.09 333	34.56 351	26.92 347	26.57 345	38.87 351	11.73 347	11.37 347	27.44 343	1.37 355	50.42 347	11.41 345	14.60 343	36.93 343
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
test_post											23.01 344	56.49 137	92.67 217

E-PMN		24.61 323	24.00 324	26.45 337	43.74 347	18.44 352	60.86 334	39.66 349	15.11 344	9.53 348	22.10 345	6.52 349	46.94 348	8.31 347	10.14 345	13.98 348

Gipuma		34.91 318	31.44 320	45.30 330	70.99 317	39.64 333	19.85 347	72.56 330	20.10 343	16.16 344	21.47 346	5.08 351	71.16 338	13.07 344	43.70 326	25.08 346
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
wuykxyi23d		29.03 322	23.09 327	46.84 329	31.67 352	28.82 345	43.46 342	57.72 345	14.39 346	7.52 350	20.84 347	0.64 357	60.29 345	21.57 339	10.04 346	51.40 341

test_post1							78.95 299				20.70 348	53.05 184	91.50 253	60.43 219

EMVS		23.76 325	23.20 326	25.46 338	41.52 348	16.90 353	60.56 335	38.79 352	14.62 345	8.99 349	20.24 349	7.35 348	45.82 349	7.25 348	9.46 347	13.64 349

X-MVStestdata		76.86 174	74.13 188	85.05 95	93.22 47	63.78 173	92.92 81	92.66 100	73.99 111	78.18 84	10.19 350	55.25 147	97.41 46	79.16 77	91.58 58	93.95 95

wuyk23d		11.30 328	10.95 329	12.33 340	48.05 342	19.89 351	25.89 346	1.92 356	3.58 348	3.12 351	1.37 351	0.64 357	15.77 352	6.23 349	7.77 350	1.35 350

testmvs		7.23 330	9.62 331	0.06 342	0.04 355	0.02 357	84.98 254	0.02 357	0.03 350	0.18 352	1.21 352	0.01 360	0.02 353	0.14 350	0.01 351	0.13 352

test123		6.92 331	9.21 332	0.08 341	0.03 356	0.05 356	81.65 279	0.01 358	0.02 351	0.14 353	0.85 353	0.03 359	0.02 353	0.12 351	0.00 353	0.16 351

pcd_1.5k_mvsjas		4.46 332	5.95 333	0.00 343	0.00 357	0.00 358	0.00 348	0.00 359	0.00 352	0.00 354	0.00 354	53.55 178	0.00 355	0.00 352	0.00 353	0.00 354

pcd1.5k->3k		31.17 321	31.85 319	29.12 336	81.48 237	0.00 358	0.00 348	91.79 132	0.00 352	0.00 354	0.00 354	41.05 265	0.00 355	0.00 352	72.34 196	87.36 204

sosnet-low-res		0.00 333	0.00 334	0.00 343	0.00 357	0.00 358	0.00 348	0.00 359	0.00 352	0.00 354	0.00 354	0.00 361	0.00 355	0.00 352	0.00 353	0.00 354

sosnet		0.00 333	0.00 334	0.00 343	0.00 357	0.00 358	0.00 348	0.00 359	0.00 352	0.00 354	0.00 354	0.00 361	0.00 355	0.00 352	0.00 353	0.00 354

uncertanet		0.00 333	0.00 334	0.00 343	0.00 357	0.00 358	0.00 348	0.00 359	0.00 352	0.00 354	0.00 354	0.00 361	0.00 355	0.00 352	0.00 353	0.00 354

Regformer		0.00 333	0.00 334	0.00 343	0.00 357	0.00 358	0.00 348	0.00 359	0.00 352	0.00 354	0.00 354	0.00 361	0.00 355	0.00 352	0.00 353	0.00 354

uanet		0.00 333	0.00 334	0.00 343	0.00 357	0.00 358	0.00 348	0.00 359	0.00 352	0.00 354	0.00 354	0.00 361	0.00 355	0.00 352	0.00 353	0.00 354

GSMVS																94.68 64

test_part2					96.29 7	68.16 60				90.78 3

test_part1								94.26 40				77.03 4			95.18 8	96.11 19

sam_mvs1												57.85 117				94.68 64

sam_mvs												54.91 161

MTGPA								92.23 112

MTMP								32.52 353

test9_res														89.41 11	94.96 10	95.29 40

agg_prior2														86.41 32	94.75 18	95.33 37

agg_prior					94.16 33	66.97 88		93.31 73		84.49 37			96.75 84

test_prior4						67.18 83	93.92 53

test_prior				86.42 54	94.71 23	67.35 77		93.10 85					96.84 80			95.05 52

旧先验2							92.00 113		59.37 283	87.54 16			93.47 197	75.39 100

新几何2							91.41 141

无先验							92.71 86	92.61 103	62.03 266				97.01 66	66.63 167		93.97 94

原ACMM2							92.01 111

testdata2													96.09 98	61.26 215

segment_acmp												65.94 44

testdata1							89.21 198		77.55 63

test12				87.09 35	94.60 25	68.86 44		92.91 91		82.67 50		65.44 49	97.55 42		93.69 33	94.84 60

plane_prior7					86.94 178	61.51 214

plane_prior6					87.23 174	62.32 202						50.66 202

plane_prior5								91.31 150					95.55 121	76.74 92	78.53 148	88.39 180

plane_prior3						61.95 210			79.09 44	72.53 135

plane_prior2							93.13 73		78.81 49

plane_prior1					87.15 175

plane_prior						62.42 200	93.85 56		79.38 37						78.80 146

n2								0.00 359

nn								0.00 359

door-mid								66.01 340

test11								93.01 87

door								66.57 339

HQP5-MVS						63.66 180

HQP-NCC					87.54 170		94.06 44		79.80 33	74.18 117

ACMP_Plane					87.54 170		94.06 44		79.80 33	74.18 117

BP-MVS														77.63 89

HQP4-MVS										74.18 117			95.61 117			88.63 175

HQP3-MVS								91.70 136							78.90 144

HQP2-MVS												51.63 198

MDTV_nov1_ep13_2view						59.90 240	80.13 293		67.65 221	72.79 130		54.33 169		59.83 222		92.58 129

ACMMP++_ref															71.63 198

ACMMP++															69.72 212

Test By Simon												54.21 171

High-resolution multi-view benchmark