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.

MCST-MVS		91.08 1	91.46 2	89.94 2	97.66 2	73.37 7	97.13 1	95.58 5	89.33 1	85.77 23	96.26 7	72.84 9	99.38 1	92.64 4	95.93 4	97.08 4

HSP-MVS		90.38 2	91.89 1	85.84 68	92.83 55	64.03 165	93.06 74	94.52 24	82.19 19	93.65 1	96.15 10	85.89 1	97.19 57	91.02 8	97.75 1	96.29 16

CNVR-MVS		90.32 3	90.89 4	88.61 11	96.76 4	70.65 18	96.47 6	94.83 16	84.83 9	89.07 7	96.80 2	70.86 14	99.06 3	92.64 4	95.71 5	96.12 18

DELS-MVS		90.05 4	90.09 5	89.94 2	93.14 49	73.88 6	97.01 2	94.40 30	88.32 2	85.71 24	94.91 45	74.11 7	98.91 6	87.26 26	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
DeepPCF-MVS	81.17 1	89.72 5	91.38 3	84.72 103	93.00 52	58.16 247	96.72 3	94.41 29	86.50 5	90.25 3	97.83 1	75.46 5	98.67 12	92.78 2	95.49 7	97.32 1

CANet		89.61 6	89.99 6	88.46 13	94.39 24	69.71 32	96.53 5	93.78 37	86.89 4	89.68 4	95.78 15	65.94 40	99.10 2	92.99 1	93.91 25	96.58 11

HPM-MVS++		89.37 7	89.95 7	87.64 20	95.10 17	68.23 59	95.24 22	94.49 26	82.43 17	88.90 8	96.35 5	71.89 13	98.63 13	88.76 18	96.40 2	96.06 19

NCCC		89.07 8	89.46 8	87.91 16	96.60 5	69.05 40	96.38 7	94.64 23	84.42 10	86.74 18	96.20 8	66.56 35	98.76 11	89.03 16	94.56 18	95.92 25

MVS_0304		88.39 9	88.35 12	88.50 12	93.01 51	70.11 23	95.90 10	92.20 100	86.27 6	88.70 9	95.92 13	56.76 114	99.02 4	92.68 3	93.76 28	96.37 15

PS-MVSNAJ		88.14 10	87.61 17	89.71 4	92.06 69	76.72 1	95.75 11	93.26 60	83.86 11	89.55 5	96.06 11	53.55 162	97.89 30	91.10 6	93.31 35	94.54 66

TSAR-MVS + MP.		88.11 11	88.64 9	86.54 47	91.73 77	68.04 61	90.36 167	93.55 48	82.89 14	91.29 2	92.89 87	72.27 10	96.03 100	87.99 20	94.77 13	95.54 31

TSAR-MVS + GP.		87.96 12	88.37 11	86.70 41	93.51 42	65.32 137	95.15 25	93.84 36	78.17 55	85.93 22	94.80 48	75.80 4	98.21 21	89.38 11	88.78 77	96.59 10

DeepC-MVS_fast	79.48 2	87.95 13	88.00 13	87.79 19	95.86 12	68.32 55	95.74 12	94.11 33	83.82 12	83.49 44	96.19 9	64.53 53	98.44 17	83.42 51	94.88 12	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
xiu_mvs_v2_base		87.92 14	87.38 22	89.55 7	91.41 90	76.43 2	95.74 12	93.12 68	83.53 13	89.55 5	95.95 12	53.45 167	97.68 32	91.07 7	92.62 42	94.54 66

EPNet		87.84 15	88.38 10	86.23 61	93.30 44	66.05 125	95.26 21	94.84 15	87.09 3	88.06 11	94.53 52	66.79 33	97.34 50	83.89 48	91.68 54	95.29 38
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
lupinMVS		87.74 16	87.77 15	87.63 22	89.24 123	71.18 14	96.57 4	92.90 76	82.70 16	87.13 15	95.27 30	64.99 49	95.80 106	89.34 12	91.80 52	95.93 24

APDe-MVS		87.54 17	87.84 14	86.65 42	96.07 9	66.30 121	94.84 32	93.78 37	69.35 192	88.39 10	96.34 6	67.74 28	97.66 36	90.62 9	93.44 34	96.01 22

SD-MVS		87.49 18	87.49 19	87.50 24	93.60 39	68.82 46	93.90 53	92.63 85	76.86 71	87.90 12	95.76 16	66.17 36	97.63 38	89.06 15	91.48 58	96.05 20

test_prior3		87.38 19	87.70 16	86.42 53	94.71 21	67.35 75	95.10 27	93.10 69	75.40 89	85.25 30	95.61 21	67.94 24	96.84 79	87.47 23	94.77 13	95.05 50

alignmvs		87.28 20	86.97 25	88.24 15	91.30 91	71.14 16	95.61 16	93.56 47	79.30 38	87.07 17	95.25 32	68.43 19	96.93 77	87.87 21	84.33 112	96.65 8

Regformer-1		87.24 21	87.60 18	86.15 62	95.14 15	65.83 131	93.95 49	95.12 10	82.11 21	84.25 37	95.73 17	67.88 27	98.35 19	85.60 36	88.64 78	94.26 73

train_agg		87.21 22	87.42 21	86.60 44	94.18 27	67.28 77	94.16 36	93.51 49	71.87 151	85.52 26	95.33 26	68.19 21	97.27 54	89.09 13	94.90 10	95.25 43

MG-MVS		87.11 23	86.27 29	89.62 5	97.79 1	76.27 3	94.96 31	94.49 26	78.74 51	83.87 43	92.94 84	64.34 54	96.94 75	75.19 100	94.09 22	95.66 27

agg_prior1		87.02 24	87.26 23	86.28 60	94.16 31	66.97 86	94.08 42	93.31 58	71.85 153	84.49 35	95.39 24	68.91 17	96.75 83	88.84 17	94.32 20	95.13 47

Regformer-2		87.00 25	87.43 20	85.71 76	95.14 15	64.73 149	93.95 49	94.95 13	81.69 26	84.03 41	95.73 17	67.35 31	98.19 23	85.40 38	88.64 78	94.20 75

agg_prior3		86.93 26	87.08 24	86.48 50	94.21 25	66.95 88	94.14 39	93.40 55	71.80 156	84.86 32	95.13 36	66.16 37	97.25 56	89.09 13	94.90 10	95.25 43

CSCG		86.87 27	86.26 30	88.72 9	95.05 18	70.79 17	93.83 56	95.33 7	68.48 205	77.63 88	94.35 59	73.04 8	98.45 16	84.92 41	93.71 30	96.92 6

canonicalmvs		86.85 28	86.25 31	88.66 10	91.80 76	71.92 10	93.54 63	91.71 118	80.26 31	87.55 13	95.25 32	63.59 63	96.93 77	88.18 19	84.34 111	97.11 3

PHI-MVS		86.83 29	86.85 28	86.78 40	93.47 43	65.55 134	95.39 20	95.10 12	71.77 158	85.69 25	96.52 3	62.07 74	98.77 10	86.06 34	95.60 6	96.03 21

SteuartSystems-ACMMP		86.82 30	86.90 26	86.58 46	90.42 101	66.38 118	96.09 9	93.87 35	77.73 60	84.01 42	95.66 19	63.39 64	97.94 27	87.40 25	93.55 33	95.42 32
Skip Steuart: Steuart Systems R&D Blog.
PVSNet_Blended		86.73 31	86.86 27	86.31 59	93.76 35	67.53 72	96.33 8	93.61 45	82.34 18	81.00 57	93.08 79	63.19 67	97.29 52	87.08 27	91.38 59	94.13 81

jason		86.40 32	86.17 32	87.11 33	86.16 173	70.54 20	95.71 15	92.19 102	82.00 24	84.58 34	94.34 60	61.86 76	95.53 121	87.76 22	90.89 64	95.27 40
jason: jason.
WTY-MVS		86.32 33	85.81 36	87.85 17	92.82 57	69.37 37	95.20 23	95.25 8	82.71 15	81.91 51	94.73 49	67.93 26	97.63 38	79.55 73	82.25 124	96.54 12

MSLP-MVS++		86.27 34	85.91 35	87.35 27	92.01 70	68.97 43	95.04 29	92.70 80	79.04 46	81.50 54	96.50 4	58.98 95	96.78 81	83.49 50	93.93 24	96.29 16

VNet		86.20 35	85.65 40	87.84 18	93.92 34	69.99 26	95.73 14	95.94 4	78.43 53	86.00 21	93.07 81	58.22 98	97.00 67	85.22 39	84.33 112	96.52 13

MVS_111021_HR		86.19 36	85.80 37	87.37 26	93.17 48	69.79 30	93.99 47	93.76 40	79.08 45	78.88 76	93.99 66	62.25 73	98.15 24	85.93 35	91.15 62	94.15 80

ACMMP_Plus		86.05 37	85.80 37	86.80 39	91.58 80	67.53 72	91.79 123	93.49 51	74.93 96	84.61 33	95.30 28	59.42 89	97.92 28	86.13 33	94.92 9	94.94 56

APD-MVS		85.93 38	85.99 33	85.76 73	95.98 11	65.21 139	93.59 61	92.58 87	66.54 220	86.17 19	95.88 14	63.83 58	97.00 67	86.39 32	92.94 38	95.06 49
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
PAPM		85.89 39	85.46 41	87.18 30	88.20 145	72.42 9	92.41 96	92.77 79	82.11 21	80.34 62	93.07 81	68.27 20	95.02 125	78.39 83	93.59 32	94.09 84

Regformer-3		85.80 40	85.92 34	85.46 80	94.17 29	65.09 145	92.95 77	95.11 11	81.13 27	81.68 53	95.04 37	65.82 42	98.32 20	83.02 52	84.36 109	92.97 116

CDPH-MVS		85.71 41	85.46 41	86.46 51	94.75 20	67.19 79	93.89 54	92.83 78	70.90 172	83.09 46	95.28 29	63.62 61	97.36 48	80.63 68	94.18 21	94.84 58

DeepC-MVS	77.85 3	85.52 42	85.24 43	86.37 56	88.80 132	66.64 108	92.15 100	93.68 43	81.07 28	76.91 98	93.64 71	62.59 72	98.44 17	85.50 37	92.84 40	94.03 88
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
Regformer-4		85.45 43	85.69 39	84.73 101	94.17 29	63.23 179	92.95 77	94.83 16	80.66 29	81.29 55	95.04 37	65.12 47	98.08 26	82.74 53	84.36 109	92.88 120

MP-MVS-pluss		85.24 44	85.13 44	85.56 77	91.42 88	65.59 133	91.54 135	92.51 89	74.56 98	80.62 59	95.64 20	59.15 92	97.00 67	86.94 29	93.80 26	94.07 86
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
PAPR		85.15 45	84.47 47	87.18 30	96.02 10	68.29 56	91.85 121	93.00 73	76.59 76	79.03 75	95.00 39	61.59 77	97.61 40	78.16 84	89.00 76	95.63 28

MP-MVS		85.02 46	84.97 45	85.17 92	92.60 61	64.27 162	93.24 69	92.27 94	73.13 127	79.63 69	94.43 53	61.90 75	97.17 58	85.00 40	92.56 43	94.06 87

#test#		84.98 47	84.74 46	85.72 74	93.75 37	65.01 146	94.09 41	93.19 64	73.55 123	79.22 72	94.93 42	59.04 93	97.67 33	82.66 54	92.21 46	94.49 70

CHOSEN 1792x2688		84.98 47	83.45 56	89.57 6	89.94 109	75.14 4	92.07 106	92.32 92	81.87 25	75.68 103	88.27 139	60.18 86	98.60 14	80.46 70	90.27 71	94.96 55

MPTG		84.73 49	84.47 47	85.50 78	91.89 74	65.16 140	91.55 134	92.23 95	75.32 91	80.53 60	95.21 34	56.06 126	97.16 59	84.86 42	92.55 44	94.18 76

HFP-MVS		84.73 49	84.40 49	85.72 74	93.75 37	65.01 146	93.50 64	93.19 64	72.19 143	79.22 72	94.93 42	59.04 93	97.67 33	81.55 62	92.21 46	94.49 70

MVS		84.66 51	82.86 66	90.06 1	90.93 95	74.56 5	87.91 210	95.54 6	68.55 203	72.35 138	94.71 50	59.78 87	98.90 7	81.29 67	94.69 17	96.74 7

ACMMPR		84.37 52	84.06 50	85.28 88	93.56 40	64.37 157	93.50 64	93.15 67	72.19 143	78.85 78	94.86 46	56.69 118	97.45 44	81.55 62	92.20 48	94.02 89

region2R		84.36 53	84.03 51	85.36 86	93.54 41	64.31 159	93.43 67	92.95 74	72.16 146	78.86 77	94.84 47	56.97 111	97.53 42	81.38 65	92.11 50	94.24 74

LFMVS		84.34 54	82.73 69	89.18 8	94.76 19	73.25 8	94.99 30	91.89 111	71.90 149	82.16 50	93.49 74	47.98 211	97.05 62	82.55 55	84.82 105	97.25 2

HY-MVS	76.49 5	84.28 55	83.36 61	87.02 36	92.22 68	67.74 66	84.65 240	94.50 25	79.15 42	82.23 49	87.93 143	66.88 32	96.94 75	80.53 69	82.20 125	96.39 14

MAR-MVS		84.18 56	83.43 57	86.44 52	96.25 7	65.93 128	94.28 35	94.27 32	74.41 99	79.16 74	95.61 21	53.99 157	98.88 9	69.62 144	93.26 36	94.50 69
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
MVS_Test		84.16 57	83.20 62	87.05 35	91.56 81	69.82 29	89.99 175	92.05 105	77.77 59	82.84 47	86.57 157	63.93 57	96.09 97	74.91 106	89.18 75	95.25 43

CANet_DTU		84.09 58	83.52 53	85.81 69	90.30 104	66.82 93	91.87 119	89.01 212	85.27 7	86.09 20	93.74 70	47.71 214	96.98 71	77.90 87	89.78 73	93.65 97

PVSNet_Blended_VisFu		83.97 59	83.50 54	85.39 85	90.02 107	66.59 111	93.77 57	91.73 116	77.43 66	77.08 97	89.81 127	63.77 60	96.97 72	79.67 72	88.21 81	92.60 124

DWT-MVSNet_test		83.95 60	82.80 67	87.41 25	92.90 54	70.07 25	89.12 192	94.42 28	82.15 20	77.64 87	91.77 103	70.81 15	96.22 92	65.03 183	81.36 128	95.94 23

MTAPA		83.91 61	83.38 60	85.50 78	91.89 74	65.16 140	81.75 261	92.23 95	75.32 91	80.53 60	95.21 34	56.06 126	97.16 59	84.86 42	92.55 44	94.18 76

XVS		83.87 62	83.47 55	85.05 94	93.22 45	63.78 168	92.92 79	92.66 83	73.99 110	78.18 82	94.31 62	55.25 131	97.41 45	79.16 76	91.58 56	93.95 91

Effi-MVS+		83.82 63	82.76 68	86.99 37	89.56 116	69.40 36	91.35 142	86.12 259	72.59 135	83.22 45	92.81 89	59.60 88	96.01 102	81.76 60	87.80 84	95.56 30

EI-MVSNet-Vis-set		83.77 64	83.67 52	84.06 115	92.79 59	63.56 176	91.76 126	94.81 18	79.65 36	77.87 84	94.09 64	63.35 65	97.90 29	79.35 74	79.36 138	90.74 150

MVSFormer		83.75 65	82.88 65	86.37 56	89.24 123	71.18 14	89.07 193	90.69 150	65.80 225	87.13 15	94.34 60	64.99 49	92.67 208	72.83 113	91.80 52	95.27 40

CP-MVS		83.71 66	83.40 59	84.65 104	93.14 49	63.84 166	94.59 33	92.28 93	71.03 170	77.41 91	94.92 44	55.21 134	96.19 93	81.32 66	90.70 66	93.91 93

PVSNet_BlendedMVS		83.38 67	83.43 57	83.22 130	93.76 35	67.53 72	94.06 43	93.61 45	79.13 43	81.00 57	85.14 171	63.19 67	97.29 52	87.08 27	73.91 174	84.83 232

PGM-MVS		83.25 68	82.70 70	84.92 96	92.81 58	64.07 164	90.44 164	92.20 100	71.28 168	77.23 94	94.43 53	55.17 135	97.31 51	79.33 75	91.38 59	93.37 102

HPM-MVS		83.25 68	82.95 64	84.17 113	92.25 67	62.88 187	90.91 153	91.86 112	70.30 184	77.12 95	93.96 67	56.75 116	96.28 91	82.04 58	91.34 61	93.34 103

EI-MVSNet-UG-set		83.14 70	82.96 63	83.67 125	92.28 66	63.19 180	91.38 140	94.68 21	79.22 40	76.60 99	93.75 69	62.64 71	97.76 31	78.07 85	78.01 148	90.05 157

PatchFormer-LS_test		83.14 70	81.81 78	87.12 32	92.34 63	69.92 28	88.64 198	93.32 57	82.07 23	74.87 112	91.62 107	68.91 17	96.08 99	66.07 174	78.45 147	95.37 33

VDD-MVS		83.06 72	81.81 78	86.81 38	90.86 98	67.70 67	95.40 19	91.50 126	75.46 86	81.78 52	92.34 97	40.09 250	97.13 61	86.85 30	82.04 126	95.60 29

PAPM_NR		82.97 73	81.84 77	86.37 56	94.10 33	66.76 100	87.66 215	92.84 77	69.96 187	74.07 119	93.57 72	63.10 69	97.50 43	70.66 137	90.58 68	94.85 57

mPP-MVS		82.96 74	82.44 71	84.52 108	92.83 55	62.92 185	92.76 82	91.85 113	71.52 165	75.61 106	94.24 63	53.48 166	96.99 70	78.97 79	90.73 65	93.64 98

DP-MVS Recon		82.73 75	81.65 80	85.98 64	97.31 3	67.06 83	95.15 25	91.99 107	69.08 195	76.50 101	93.89 68	54.48 151	98.20 22	70.76 136	85.66 101	92.69 121

CLD-MVS		82.73 75	82.35 73	83.86 118	87.90 151	67.65 69	95.45 18	92.18 103	85.06 8	72.58 131	92.27 98	52.46 175	95.78 107	84.18 44	79.06 141	88.16 175
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
sss		82.71 77	82.38 72	83.73 122	89.25 121	59.58 234	92.24 99	94.89 14	77.96 57	79.86 66	92.38 95	56.70 117	97.05 62	77.26 90	80.86 132	94.55 64

3Dnovator	73.91 6	82.69 78	80.82 88	88.31 14	89.57 115	71.26 13	92.60 90	94.39 31	78.84 48	67.89 190	92.48 93	48.42 206	98.52 15	68.80 152	94.40 19	95.15 46

MVSTER		82.47 79	82.05 74	83.74 120	92.68 60	69.01 41	91.90 118	93.21 61	79.83 32	72.14 139	85.71 167	74.72 6	94.72 135	75.72 96	72.49 183	87.50 180

TESTMET0.1,1		82.41 80	81.98 76	83.72 123	88.08 146	63.74 170	92.70 85	93.77 39	79.30 38	77.61 89	87.57 146	58.19 99	94.08 167	73.91 109	86.68 92	93.33 105

CostFormer		82.33 81	81.15 84	85.86 67	89.01 128	68.46 51	82.39 258	93.01 71	75.59 84	80.25 63	81.57 212	72.03 12	94.96 127	79.06 78	77.48 154	94.16 79

API-MVS		82.28 82	80.53 93	87.54 23	96.13 8	70.59 19	93.63 59	91.04 143	65.72 227	75.45 108	92.83 88	56.11 125	98.89 8	64.10 191	89.75 74	93.15 110

IB-MVS	77.80 4	82.18 83	80.46 94	87.35 27	89.14 125	70.28 22	95.59 17	95.17 9	78.85 47	70.19 153	85.82 165	70.66 16	97.67 33	72.19 122	66.52 219	94.09 84
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
xiu_mvs_v1_base_debu		82.16 84	81.12 85	85.26 89	86.42 167	68.72 47	92.59 92	90.44 155	73.12 128	84.20 38	94.36 55	38.04 260	95.73 110	84.12 45	86.81 89	91.33 142

xiu_mvs_v1_base		82.16 84	81.12 85	85.26 89	86.42 167	68.72 47	92.59 92	90.44 155	73.12 128	84.20 38	94.36 55	38.04 260	95.73 110	84.12 45	86.81 89	91.33 142

xiu_mvs_v1_base_debi		82.16 84	81.12 85	85.26 89	86.42 167	68.72 47	92.59 92	90.44 155	73.12 128	84.20 38	94.36 55	38.04 260	95.73 110	84.12 45	86.81 89	91.33 142

3Dnovator+	73.60 7	82.10 87	80.60 92	86.60 44	90.89 97	66.80 99	95.20 23	93.44 53	74.05 109	67.42 195	92.49 92	49.46 197	97.65 37	70.80 135	91.68 54	95.33 35

MVS_111021_LR		82.02 88	81.52 81	83.51 127	88.42 141	62.88 187	89.77 181	88.93 214	76.78 73	75.55 107	93.10 77	50.31 189	95.38 123	83.82 49	87.02 88	92.26 133

PMMVS		81.98 89	82.04 75	81.78 167	89.76 113	56.17 261	91.13 150	90.69 150	77.96 57	80.09 64	93.57 72	46.33 224	94.99 126	81.41 64	87.46 86	94.17 78

EPP-MVSNet		81.79 90	81.52 81	82.61 141	88.77 133	60.21 224	93.02 75	93.66 44	68.52 204	72.90 126	90.39 119	72.19 11	94.96 127	74.93 105	79.29 140	92.67 122

APD-MVS_3200maxsize		81.64 91	81.32 83	82.59 142	92.36 62	58.74 244	91.39 138	91.01 144	63.35 240	79.72 68	94.62 51	51.82 178	96.14 95	79.71 71	87.93 83	92.89 119

ACMMP		81.49 92	80.67 90	83.93 117	91.71 78	62.90 186	92.13 101	92.22 99	71.79 157	71.68 144	93.49 74	50.32 188	96.96 73	78.47 81	84.22 116	91.93 136
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
CDS-MVSNet		81.43 93	80.74 89	83.52 126	86.26 171	64.45 152	92.09 104	90.65 153	75.83 83	73.95 121	89.81 127	63.97 56	92.91 200	71.27 129	82.82 121	93.20 109
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
mvs_anonymous		81.36 94	79.99 97	85.46 80	90.39 103	68.40 52	86.88 228	90.61 154	74.41 99	70.31 152	84.67 176	63.79 59	92.32 219	73.13 110	85.70 100	95.67 26

1121		81.25 95	80.05 95	84.87 98	92.30 65	64.31 159	87.91 210	91.39 130	59.44 266	79.94 65	92.91 85	57.09 107	97.01 65	66.63 166	92.81 41	93.29 106

Fast-Effi-MVS+		81.14 96	80.01 96	84.51 109	90.24 105	65.86 129	94.12 40	89.15 206	73.81 117	75.37 109	88.26 140	57.26 106	94.53 142	66.97 165	84.92 104	93.15 110

HQP-MVS		81.14 96	80.64 91	82.64 140	87.54 154	63.66 174	94.06 43	91.70 119	79.80 33	74.18 115	90.30 120	51.63 182	95.61 116	77.63 88	78.90 142	88.63 167

HyFIR lowres test		81.03 98	79.56 104	85.43 83	87.81 152	68.11 60	90.18 171	90.01 178	70.65 179	72.95 125	86.06 163	63.61 62	94.50 143	75.01 104	79.75 136	93.67 96

nrg030		80.93 99	79.86 99	84.13 114	83.69 203	68.83 45	93.23 70	91.20 136	75.55 85	75.06 111	88.22 141	63.04 70	94.74 134	81.88 59	66.88 216	88.82 165

Vis-MVSNet		80.92 100	79.98 98	83.74 120	88.48 138	61.80 202	93.44 66	88.26 229	73.96 113	77.73 85	91.76 104	49.94 193	94.76 132	65.84 177	90.37 70	94.65 62
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
1314		80.70 101	78.95 116	85.94 66	87.77 153	67.56 71	87.91 210	92.55 88	72.17 145	67.44 194	93.09 78	50.27 190	97.04 64	71.68 125	87.64 85	93.23 108

tpmrst		80.57 102	79.14 115	84.84 99	90.10 106	68.28 57	81.70 262	89.72 189	77.63 62	75.96 102	79.54 242	64.94 51	92.71 206	75.43 98	77.28 157	93.55 99

1112_ss		80.56 103	79.83 100	82.77 135	88.65 134	60.78 211	92.29 97	88.36 225	72.58 136	72.46 135	94.95 40	65.09 48	93.42 189	66.38 170	77.71 150	94.10 83

VDDNet		80.50 104	78.26 122	87.21 29	86.19 172	69.79 30	94.48 34	91.31 133	60.42 260	79.34 71	90.91 111	38.48 256	96.56 89	82.16 56	81.05 130	95.27 40

BH-w/o		80.49 105	79.30 111	84.05 116	90.83 99	64.36 158	93.60 60	89.42 196	74.35 104	69.09 171	90.15 122	55.23 133	95.61 116	64.61 186	86.43 97	92.17 134

TAMVS		80.37 106	79.45 107	83.13 132	85.14 184	63.37 177	91.23 146	90.76 149	74.81 97	72.65 129	88.49 134	60.63 85	92.95 196	69.41 146	81.95 127	93.08 113

HQP_MVS		80.34 107	79.75 101	82.12 161	86.94 162	62.42 192	93.13 72	91.31 133	78.81 49	72.53 132	89.14 131	50.66 186	95.55 119	76.74 91	78.53 145	88.39 172

HPM-MVS_fast		80.25 108	79.55 106	82.33 152	91.55 82	59.95 229	91.32 144	89.16 205	65.23 231	74.71 113	93.07 81	47.81 213	95.74 109	74.87 108	88.23 80	91.31 146

diffmvs		80.18 109	78.55 120	85.07 93	88.56 135	66.93 89	86.70 231	88.62 220	70.42 181	78.69 80	85.26 169	56.93 113	94.77 131	68.68 153	83.09 118	93.51 100

ab-mvs		80.18 109	78.31 121	85.80 70	88.44 140	65.49 136	83.00 255	92.67 82	71.82 155	77.36 92	85.01 172	54.50 149	96.59 86	76.35 95	75.63 163	95.32 37

IS-MVSNet		80.14 111	79.41 108	82.33 152	87.91 150	60.08 228	91.97 110	88.27 228	72.90 132	71.44 146	91.73 106	61.44 78	93.66 185	62.47 208	86.53 95	93.24 107

test-LLR		80.10 112	79.56 104	81.72 169	86.93 164	61.17 207	92.70 85	91.54 123	71.51 166	75.62 104	86.94 154	53.83 158	92.38 216	72.21 120	84.76 107	91.60 139

PVSNet	73.49 8	80.05 113	78.63 118	84.31 111	90.92 96	64.97 148	92.47 95	91.05 142	79.18 41	72.43 136	90.51 118	37.05 272	94.06 168	68.06 154	86.00 99	93.90 94

UA-Net		80.02 114	79.65 102	81.11 182	89.33 119	57.72 251	86.33 233	89.00 213	77.44 65	81.01 56	89.15 130	59.33 90	95.90 103	61.01 215	84.28 114	89.73 161

test-mter		79.96 115	79.38 110	81.72 169	86.93 164	61.17 207	92.70 85	91.54 123	73.85 115	75.62 104	86.94 154	49.84 195	92.38 216	72.21 120	84.76 107	91.60 139

QAPM		79.95 116	77.39 136	87.64 20	89.63 114	71.41 12	93.30 68	93.70 42	65.34 230	67.39 197	91.75 105	47.83 212	98.96 5	57.71 231	89.81 72	92.54 126

UGNet		79.87 117	78.68 117	83.45 129	89.96 108	61.51 205	92.13 101	90.79 147	76.83 72	78.85 78	86.33 160	38.16 258	96.17 94	67.93 156	87.17 87	92.67 122
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
abl_6		79.82 118	79.20 113	81.70 171	89.85 110	58.34 246	88.47 200	90.07 175	62.56 247	77.71 86	93.08 79	47.65 215	96.78 81	77.94 86	85.45 103	89.99 158

tpm2		79.80 119	77.95 127	85.34 87	88.28 143	68.26 58	81.56 266	91.42 129	70.11 185	77.59 90	80.50 228	67.40 29	94.26 159	67.34 161	77.35 155	93.51 100

DI_MVS_plusplus_test		79.78 120	77.50 135	86.62 43	80.90 225	69.46 35	90.69 159	91.97 109	77.00 68	59.07 242	82.34 197	46.82 218	95.88 104	82.14 57	86.59 94	94.53 68

test_normal		79.66 121	77.36 138	86.54 47	80.72 229	69.21 38	90.68 160	92.16 104	76.99 69	58.63 246	82.03 206	46.70 220	95.86 105	81.74 61	86.63 93	94.56 63

CPTT-MVS		79.59 122	79.16 114	80.89 189	91.54 83	59.80 231	92.10 103	88.54 223	60.42 260	72.96 124	93.28 76	48.27 207	92.80 203	78.89 80	86.50 96	90.06 156

Test_1112_low_res		79.56 123	78.60 119	82.43 146	88.24 144	60.39 220	92.09 104	87.99 232	72.10 147	71.84 142	87.42 148	64.62 52	93.04 193	65.80 178	77.30 156	93.85 95

FIs		79.47 124	79.41 108	79.67 207	85.95 176	59.40 236	91.68 130	93.94 34	78.06 56	68.96 174	88.28 138	66.61 34	91.77 229	66.20 173	74.99 168	87.82 177

BH-RMVSNet		79.46 125	77.65 131	84.89 97	91.68 79	65.66 132	93.55 62	88.09 230	72.93 131	73.37 123	91.12 110	46.20 226	96.12 96	56.28 235	85.61 102	92.91 118

PCF-MVS	73.15 9	79.29 126	77.63 132	84.29 112	86.06 174	65.96 127	87.03 223	91.10 140	69.86 188	69.79 160	90.64 114	57.54 105	96.59 86	64.37 190	82.29 123	90.32 154
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
Vis-MVSNet (Re-imp)		79.24 127	79.57 103	78.24 233	88.46 139	52.29 278	90.41 166	89.12 207	74.24 105	69.13 170	91.91 101	65.77 43	90.09 254	59.00 226	88.09 82	92.33 129

114514_t		79.17 128	77.67 130	83.68 124	95.32 14	65.53 135	92.85 81	91.60 122	63.49 239	67.92 189	90.63 116	46.65 221	95.72 114	67.01 164	83.54 117	89.79 159

VPA-MVSNet		79.03 129	78.00 126	82.11 164	85.95 176	64.48 151	93.22 71	94.66 22	75.05 95	74.04 120	84.95 173	52.17 177	93.52 187	74.90 107	67.04 215	88.32 174

OPM-MVS		79.00 130	78.09 124	81.73 168	83.52 206	63.83 167	91.64 133	90.30 165	76.36 79	71.97 141	89.93 126	46.30 225	95.17 124	75.10 101	77.70 151	86.19 205

EI-MVSNet		78.97 131	78.22 123	81.25 176	85.33 181	62.73 190	89.53 185	93.21 61	72.39 139	72.14 139	90.13 123	60.99 79	94.72 135	67.73 158	72.49 183	86.29 203

AdaColmap		78.94 132	77.00 141	84.76 100	96.34 6	65.86 129	92.66 89	87.97 233	62.18 249	70.56 148	92.37 96	43.53 238	97.35 49	64.50 188	82.86 120	91.05 148

tpmp4_e23		78.85 133	76.55 144	85.77 72	89.25 121	68.39 53	81.63 265	91.38 131	70.40 182	75.21 110	79.22 244	67.37 30	94.79 130	58.98 227	75.51 164	94.13 81

VPNet		78.82 134	77.53 134	82.70 137	84.52 191	66.44 117	93.93 51	92.23 95	80.46 30	72.60 130	88.38 137	49.18 200	93.13 192	72.47 118	63.97 242	88.55 169

EPNet_dtu		78.80 135	79.26 112	77.43 243	88.06 147	49.71 291	91.96 111	91.95 110	77.67 61	76.56 100	91.28 109	58.51 97	90.20 249	56.37 234	80.95 131	92.39 128
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
TR-MVS		78.77 136	77.37 137	82.95 133	90.49 100	60.88 209	93.67 58	90.07 175	70.08 186	74.51 114	91.37 108	45.69 227	95.70 115	60.12 220	80.32 133	92.29 131

mvs-test1		78.74 137	77.95 127	81.14 181	83.22 207	57.13 257	93.96 48	87.78 234	75.42 87	72.68 128	90.80 113	45.08 231	94.54 141	75.08 102	77.49 153	91.74 138

BH-untuned		78.68 138	77.08 139	83.48 128	89.84 111	63.74 170	92.70 85	88.59 221	71.57 163	66.83 202	88.65 133	51.75 180	95.39 122	59.03 225	84.77 106	91.32 145

OMC-MVS		78.67 139	77.91 129	80.95 188	85.76 180	57.40 255	88.49 199	88.67 218	73.85 115	72.43 136	92.10 99	49.29 199	94.55 140	72.73 115	77.89 149	90.91 149

tpm		78.58 140	77.03 140	83.22 130	85.94 178	64.56 150	83.21 253	91.14 139	78.31 54	73.67 122	79.68 239	64.01 55	92.09 224	66.07 174	71.26 192	93.03 114

OpenMVS	70.45 11	78.54 141	75.92 152	86.41 55	85.93 179	71.68 11	92.74 83	92.51 89	66.49 221	64.56 211	91.96 100	43.88 237	98.10 25	54.61 239	90.65 67	89.44 163

EPMVS		78.49 142	75.98 151	86.02 63	91.21 92	69.68 33	80.23 275	91.20 136	75.25 93	72.48 134	78.11 248	54.65 148	93.69 184	57.66 232	83.04 119	94.69 61

GA-MVS		78.33 143	76.23 148	84.65 104	83.65 204	66.30 121	91.44 136	90.14 173	76.01 81	70.32 151	84.02 181	42.50 240	94.72 135	70.98 133	77.00 158	92.94 117

cascas		78.18 144	75.77 154	85.41 84	87.14 160	69.11 39	92.96 76	91.15 138	66.71 219	70.47 149	86.07 162	37.49 266	96.48 90	70.15 140	79.80 135	90.65 151

UniMVSNet_NR-MVSNet		78.15 145	77.55 133	79.98 200	84.46 193	60.26 222	92.25 98	93.20 63	77.50 64	68.88 175	86.61 156	66.10 38	92.13 222	66.38 170	62.55 245	87.54 179

FC-MVSNet-test		77.99 146	78.08 125	77.70 238	84.89 187	55.51 265	90.27 169	93.75 41	76.87 70	66.80 203	87.59 145	65.71 44	90.23 248	62.89 203	73.94 173	87.37 185

XXY-MVS		77.94 147	76.44 146	82.43 146	82.60 213	64.44 153	92.01 107	91.83 114	73.59 122	70.00 156	85.82 165	54.43 152	94.76 132	69.63 143	68.02 210	88.10 176

MS-PatchMatch		77.90 148	76.50 145	82.12 161	85.99 175	69.95 27	91.75 128	92.70 80	73.97 112	62.58 229	84.44 179	41.11 247	95.78 107	63.76 192	92.17 49	80.62 281

FMVSNet3		77.73 149	76.04 150	82.80 134	91.20 93	68.99 42	91.87 119	91.99 107	73.35 125	67.04 199	83.19 189	56.62 119	92.14 221	59.80 222	69.34 199	87.28 189

UniMVSNet (Re)		77.58 150	76.78 143	79.98 200	84.11 199	60.80 210	91.76 126	93.17 66	76.56 77	69.93 159	84.78 175	63.32 66	92.36 218	64.89 184	62.51 247	86.78 197

PatchmatchNet		77.46 151	74.63 170	85.96 65	89.55 117	70.35 21	79.97 279	89.55 192	72.23 141	70.94 147	76.91 260	57.03 109	92.79 204	54.27 241	81.17 129	94.74 60
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
v2v482		77.42 152	75.65 159	82.73 136	80.38 243	67.13 82	91.85 121	90.23 167	75.09 94	69.37 167	83.39 187	53.79 160	94.44 144	71.77 123	65.00 233	86.63 201

v1neww		77.39 153	75.71 156	82.44 143	80.69 231	66.83 91	91.94 115	90.18 170	74.19 106	69.60 161	82.51 193	54.99 142	94.44 144	71.68 125	65.60 222	86.05 210

v7new		77.39 153	75.71 156	82.44 143	80.69 231	66.83 91	91.94 115	90.18 170	74.19 106	69.60 161	82.51 193	54.99 142	94.44 144	71.68 125	65.60 222	86.05 210

v6		77.39 153	75.71 156	82.44 143	80.67 233	66.82 93	91.94 115	90.18 170	74.19 106	69.60 161	82.50 196	55.00 141	94.44 144	71.68 125	65.60 222	86.05 210

CHOSEN 280x420		77.35 156	76.95 142	78.55 228	87.07 161	62.68 191	69.71 304	82.95 285	68.80 198	71.48 145	87.27 153	66.03 39	84.00 293	76.47 94	82.81 122	88.95 164

v1		77.29 157	75.57 160	82.42 148	80.61 241	66.73 101	91.96 111	90.42 158	74.41 99	69.46 164	82.12 203	55.14 136	94.40 149	71.00 130	65.04 230	86.13 206

v1141		77.28 158	75.57 160	82.42 148	80.63 237	66.73 101	91.96 111	90.42 158	74.41 99	69.46 164	82.12 203	55.09 138	94.40 149	70.99 132	65.05 229	86.12 207

divwei89l23v2f112		77.28 158	75.57 160	82.42 148	80.62 238	66.72 103	91.96 111	90.42 158	74.41 99	69.46 164	82.12 203	55.11 137	94.40 149	71.00 130	65.04 230	86.12 207

PS-MVSNAJss		77.26 160	76.31 147	80.13 197	80.64 236	59.16 240	90.63 163	91.06 141	72.80 133	68.58 180	84.57 178	53.55 162	93.96 175	72.97 111	71.96 186	87.27 190

gg-mvs-nofinetune		77.18 161	74.31 176	85.80 70	91.42 88	68.36 54	71.78 298	94.72 20	49.61 296	77.12 95	45.92 319	77.41 3	93.98 174	67.62 159	93.16 37	95.05 50

MVP-Stereo		77.12 162	76.23 148	79.79 206	81.72 219	66.34 120	89.29 187	90.88 145	70.56 180	62.01 232	82.88 190	49.34 198	94.13 164	65.55 180	93.80 26	78.88 293
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
view800		76.93 163	75.50 163	81.23 177	91.44 85	62.00 198	89.94 176	96.56 1	70.68 176	68.54 181	87.31 149	60.79 81	94.19 160	38.90 292	75.31 165	87.48 181

conf0.05thres1000		76.93 163	75.50 163	81.23 177	91.44 85	62.00 198	89.94 176	96.56 1	70.68 176	68.54 181	87.31 149	60.79 81	94.19 160	38.90 292	75.31 165	87.48 181

tfpn		76.93 163	75.50 163	81.23 177	91.44 85	62.00 198	89.94 176	96.56 1	70.68 176	68.54 181	87.31 149	60.79 81	94.19 160	38.90 292	75.31 165	87.48 181

X-MVStestdata		76.86 166	74.13 179	85.05 94	93.22 45	63.78 168	92.92 79	92.66 83	73.99 110	78.18 82	10.19 334	55.25 131	97.41 45	79.16 76	91.58 56	93.95 91

DU-MVS		76.86 166	75.84 153	79.91 202	82.96 211	60.26 222	91.26 145	91.54 123	76.46 78	68.88 175	86.35 158	56.16 123	92.13 222	66.38 170	62.55 245	87.35 187

v7		76.83 168	75.01 168	82.29 154	80.35 244	66.70 105	91.68 130	89.97 179	73.47 124	69.22 169	82.22 200	52.52 173	94.43 148	69.73 142	65.96 221	85.74 221

WR-MVS		76.76 169	75.74 155	79.82 205	84.60 189	62.27 196	92.60 90	92.51 89	76.06 80	67.87 191	85.34 168	56.76 114	90.24 247	62.20 209	63.69 244	86.94 195

v1144		76.73 170	74.88 169	82.27 155	80.23 251	66.60 109	91.68 130	90.21 169	73.69 119	69.06 172	81.89 208	52.73 172	94.40 149	69.21 148	65.23 226	85.80 217

IterMVS-LS		76.49 171	75.18 167	80.43 192	84.49 192	62.74 189	90.64 161	88.80 216	72.40 138	65.16 207	81.72 211	60.98 80	92.27 220	67.74 157	64.65 237	86.29 203
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
V42		76.46 172	74.55 173	82.19 159	79.14 265	67.82 64	90.26 170	89.42 196	73.75 118	68.63 179	81.89 208	51.31 184	94.09 166	71.69 124	64.84 234	84.66 233

Test4		76.45 173	73.45 188	85.45 82	76.07 287	67.61 70	88.38 202	90.83 146	76.71 74	53.06 275	79.65 241	31.61 289	94.35 153	78.47 81	86.22 98	94.40 72

v148		76.19 174	74.47 175	81.36 174	80.05 255	64.44 153	91.75 128	90.23 167	73.68 120	67.13 198	80.84 224	55.92 129	93.86 181	68.95 150	61.73 254	85.76 220

Effi-MVS+-dtu		76.14 175	75.28 166	78.72 227	83.22 207	55.17 267	89.87 179	87.78 234	75.42 87	67.98 188	81.43 213	45.08 231	92.52 212	75.08 102	71.63 187	88.48 170

FMVSNet2		76.07 176	74.01 181	82.26 157	88.85 129	67.66 68	91.33 143	91.61 121	70.84 173	65.98 204	82.25 199	48.03 208	92.00 226	58.46 228	68.73 205	87.10 191

v144192		76.05 177	74.03 180	82.12 161	79.50 260	66.55 113	91.39 138	89.71 190	72.30 140	68.17 186	81.33 216	51.75 180	94.03 172	67.94 155	64.19 239	85.77 218

NR-MVSNet		76.05 177	74.59 171	80.44 191	82.96 211	62.18 197	90.83 155	91.73 116	77.12 67	60.96 233	86.35 158	59.28 91	91.80 228	60.74 216	61.34 257	87.35 187

v1192		75.98 179	73.92 182	82.15 160	79.73 256	66.24 123	91.22 147	89.75 184	72.67 134	68.49 184	81.42 214	49.86 194	94.27 157	67.08 163	65.02 232	85.95 214

TranMVSNet+NR-MVSNet		75.86 180	74.52 174	79.89 203	82.44 214	60.64 217	91.37 141	91.37 132	76.63 75	67.65 193	86.21 161	52.37 176	91.55 233	61.84 211	60.81 260	87.48 181

LPG-MVS_test		75.82 181	74.58 172	79.56 211	84.31 196	59.37 237	90.44 164	89.73 187	69.49 190	64.86 208	88.42 135	38.65 254	94.30 155	72.56 116	72.76 180	85.01 230

GBi-Net		75.65 182	73.83 183	81.10 183	88.85 129	65.11 142	90.01 172	90.32 161	70.84 173	67.04 199	80.25 233	48.03 208	91.54 234	59.80 222	69.34 199	86.64 198

test1		75.65 182	73.83 183	81.10 183	88.85 129	65.11 142	90.01 172	90.32 161	70.84 173	67.04 199	80.25 233	48.03 208	91.54 234	59.80 222	69.34 199	86.64 198

v1921920		75.63 184	73.49 187	82.06 165	79.38 261	66.35 119	91.07 152	89.48 193	71.98 148	67.99 187	81.22 219	49.16 202	93.90 178	66.56 168	64.56 238	85.92 216

ACMP	71.68 10	75.58 185	74.23 178	79.62 209	84.97 186	59.64 232	90.80 156	89.07 210	70.39 183	62.95 225	87.30 152	38.28 257	93.87 179	72.89 112	71.45 190	85.36 227
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
v8		75.35 186	73.26 190	81.61 172	80.67 233	66.82 93	89.54 184	89.27 200	71.65 160	63.30 223	80.30 232	54.99 142	94.06 168	67.33 162	62.33 248	83.94 238

tpm cat1		75.30 187	72.21 201	84.58 106	88.52 136	67.77 65	78.16 290	88.02 231	61.88 253	68.45 185	76.37 261	60.65 84	94.03 172	53.77 244	74.11 171	91.93 136

PLC	68.80 14	75.23 188	73.68 185	79.86 204	92.93 53	58.68 245	90.64 161	88.30 226	60.90 257	64.43 214	90.53 117	42.38 241	94.57 138	56.52 233	76.54 159	86.33 202
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
v1240		75.21 189	72.98 192	81.88 166	79.20 263	66.00 126	90.75 158	89.11 208	71.63 161	67.41 196	81.22 219	47.36 216	93.87 179	65.46 181	64.72 236	85.77 218

Fast-Effi-MVS+-dtu		75.04 190	73.37 189	80.07 198	80.86 226	59.52 235	91.20 149	85.38 266	71.90 149	65.20 206	84.84 174	41.46 246	92.97 195	66.50 169	72.96 179	87.73 178

dp		75.01 191	72.09 202	83.76 119	89.28 120	66.22 124	79.96 280	89.75 184	71.16 169	67.80 192	77.19 256	51.81 179	92.54 211	50.39 254	71.44 191	92.51 127

Patchmatch-test1		75.00 192	71.80 205	84.58 106	86.63 166	70.08 24	81.06 268	89.19 203	71.60 162	70.01 155	77.16 258	45.53 228	88.63 267	51.79 250	73.27 176	95.02 54

TAPA-MVS	70.22 12	74.94 193	73.53 186	79.17 223	90.40 102	52.07 279	89.19 190	89.61 191	62.69 246	70.07 154	92.67 90	48.89 205	94.32 154	38.26 296	79.97 134	91.12 147
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
v10		74.77 194	72.54 198	81.46 173	80.33 248	66.71 104	89.15 191	89.08 209	70.94 171	63.08 224	79.86 237	52.52 173	94.04 171	65.70 179	62.17 249	83.64 240

XVG-OURS-SEG-HR		74.70 195	73.08 191	79.57 210	78.25 273	57.33 256	80.49 271	87.32 240	63.22 242	68.76 177	90.12 125	44.89 234	91.59 232	70.55 138	74.09 172	89.79 159

ACMM	69.62 13	74.34 196	72.73 194	79.17 223	84.25 198	57.87 249	90.36 167	89.93 180	63.17 243	65.64 205	86.04 164	37.79 264	94.10 165	65.89 176	71.52 189	85.55 224
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CNLPA		74.31 197	72.30 200	80.32 193	91.49 84	61.66 203	90.85 154	80.72 292	56.67 280	63.85 218	90.64 114	46.75 219	90.84 241	53.79 243	75.99 162	88.47 171

XVG-OURS		74.25 198	72.46 199	79.63 208	78.45 272	57.59 254	80.33 273	87.39 237	63.86 238	68.76 177	89.62 129	40.50 249	91.72 230	69.00 149	74.25 170	89.58 162

CVMVSNet		74.04 199	74.27 177	73.33 269	85.33 181	43.94 305	89.53 185	88.39 224	54.33 286	70.37 150	90.13 123	49.17 201	84.05 290	61.83 212	79.36 138	91.99 135

Baseline_NR-MVSNet		73.99 200	72.83 193	77.48 242	80.78 227	59.29 239	91.79 123	84.55 270	68.85 197	68.99 173	80.70 225	56.16 123	92.04 225	62.67 206	60.98 259	81.11 275

pmmvs4		73.92 201	71.81 204	80.25 195	79.17 264	65.24 138	87.43 218	87.26 242	67.64 214	63.46 221	83.91 182	48.96 204	91.53 237	62.94 202	65.49 225	83.96 237

CR-MVSNet		73.79 202	70.82 211	82.70 137	83.15 209	67.96 62	70.25 301	84.00 275	73.67 121	69.97 157	72.41 280	57.82 102	89.48 263	52.99 248	73.13 177	90.64 152

test_djsdf		73.76 203	72.56 197	77.39 244	77.00 281	53.93 272	89.07 193	90.69 150	65.80 225	63.92 216	82.03 206	43.14 239	92.67 208	72.83 113	68.53 206	85.57 223

pmmvs5		73.35 204	71.52 206	78.86 226	78.64 271	60.61 218	91.08 151	86.90 243	67.69 211	63.32 222	83.64 183	44.33 236	90.53 242	62.04 210	66.02 220	85.46 225

jajsoiax		73.05 205	71.51 207	77.67 239	77.46 278	54.83 268	88.81 195	90.04 177	69.13 194	62.85 227	83.51 185	31.16 292	92.75 205	70.83 134	69.80 195	85.43 226

LCM-MVSNet-Re		72.93 206	71.84 203	76.18 254	88.49 137	48.02 295	80.07 278	70.17 317	73.96 113	52.25 278	80.09 236	49.98 192	88.24 273	67.35 160	84.23 115	92.28 132

pm-mvs1		72.89 207	71.09 209	78.26 232	79.10 267	57.62 253	90.80 156	89.30 199	67.66 212	62.91 226	81.78 210	49.11 203	92.95 196	60.29 219	58.89 269	84.22 236

tpmvs		72.88 208	69.76 216	82.22 158	90.98 94	67.05 84	78.22 289	88.30 226	63.10 244	64.35 215	74.98 268	55.09 138	94.27 157	43.25 274	69.57 198	85.34 228

test0.0.03 1		72.76 209	72.71 195	72.88 273	80.25 250	47.99 296	91.22 147	89.45 194	71.51 166	62.51 230	87.66 144	53.83 158	85.06 286	50.16 255	67.84 213	85.58 222

mvs_tets		72.71 210	71.11 208	77.52 240	77.41 279	54.52 270	88.45 201	89.76 183	68.76 199	62.70 228	83.26 188	29.49 296	92.71 206	70.51 139	69.62 197	85.34 228

FMVSNet1		72.71 210	69.91 214	81.10 183	83.60 205	65.11 142	90.01 172	90.32 161	63.92 237	63.56 220	80.25 233	36.35 274	91.54 234	54.46 240	66.75 217	86.64 198

IterMVS		72.65 212	70.83 210	78.09 236	82.17 215	62.96 182	87.64 216	86.28 255	71.56 164	60.44 234	78.85 246	45.42 230	86.66 281	63.30 196	61.83 251	84.65 234
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
PatchMatch-RL		72.06 213	69.98 212	78.28 230	89.51 118	55.70 264	83.49 247	83.39 281	61.24 256	63.72 219	82.76 191	34.77 279	93.03 194	53.37 247	77.59 152	86.12 207

v18		71.94 214	69.43 217	79.50 213	80.74 228	66.82 93	88.16 204	86.66 245	68.95 196	55.55 258	72.66 275	55.03 140	90.15 250	64.78 185	52.30 286	81.54 263

v16		71.81 215	69.26 219	79.47 214	80.66 235	66.81 97	87.93 208	86.63 247	68.70 201	55.35 259	72.51 276	54.75 146	90.12 252	64.51 187	52.28 287	81.47 264

PVSNet_0	68.08 15	71.81 215	68.32 229	82.27 155	84.68 188	62.31 195	88.68 197	90.31 164	75.84 82	57.93 249	80.65 227	37.85 263	94.19 160	69.94 141	29.05 322	90.31 155

v17		71.77 217	69.20 220	79.46 215	80.62 238	66.81 97	87.93 208	86.63 247	68.71 200	55.25 260	72.49 277	54.72 147	90.11 253	64.50 188	51.97 288	81.47 264

MIMVSNet		71.64 218	68.44 227	81.23 177	81.97 218	64.44 153	73.05 297	88.80 216	69.67 189	64.59 210	74.79 269	32.79 283	87.82 276	53.99 242	76.35 160	91.42 141

v15		71.40 219	68.75 222	79.35 216	80.39 242	66.70 105	87.57 217	86.64 246	68.66 202	54.68 262	72.00 284	54.50 149	89.98 255	63.69 193	50.66 293	81.38 268

v7n		71.31 220	68.65 223	79.28 218	76.40 283	60.77 212	86.71 230	89.45 194	64.17 236	58.77 245	78.24 247	44.59 235	93.54 186	57.76 230	61.75 253	83.52 243

V14		71.29 221	68.61 224	79.31 217	80.34 246	66.65 107	87.39 219	86.61 249	68.41 206	54.49 264	71.91 285	54.25 154	89.96 256	63.50 194	50.62 294	81.33 270

V9		71.16 222	68.46 226	79.27 219	80.26 249	66.60 109	87.21 222	86.56 250	68.17 207	54.26 267	71.81 287	54.00 156	89.93 257	63.28 197	50.57 295	81.27 271

anonymousdsp		71.14 223	69.37 218	76.45 251	72.95 293	54.71 269	84.19 242	88.88 215	61.92 252	62.15 231	79.77 238	38.14 259	91.44 239	68.90 151	67.45 214	83.21 249

testing_2		71.09 224	67.32 236	82.40 151	69.82 304	66.52 115	83.64 245	90.77 148	72.21 142	45.12 301	71.07 294	27.60 301	93.74 182	75.71 97	69.96 194	86.95 194

v11		71.05 225	68.32 229	79.23 220	80.34 246	66.57 112	87.01 225	86.55 251	68.11 208	54.40 265	71.66 289	52.94 170	89.91 258	62.71 205	51.12 291	81.21 272

v12		71.02 226	68.29 231	79.22 221	80.18 252	66.53 114	87.01 225	86.54 252	67.90 209	54.00 270	71.70 288	53.66 161	89.91 258	63.09 199	50.51 296	81.21 272

v13		70.90 227	68.15 232	79.15 225	80.08 253	66.45 116	86.83 229	86.50 253	67.62 215	53.78 272	71.61 290	53.51 165	89.87 260	62.89 203	50.50 297	81.14 274

F-COLMAP		70.66 228	68.44 227	77.32 245	86.37 170	55.91 263	88.00 206	86.32 254	56.94 278	57.28 254	88.07 142	33.58 281	92.49 213	51.02 252	68.37 207	83.55 241

WR-MVS_H		70.59 229	69.94 213	72.53 275	81.03 224	51.43 282	87.35 220	92.03 106	67.38 216	60.23 235	80.70 225	55.84 130	83.45 297	46.33 268	58.58 270	82.72 256

v748		70.55 230	67.97 233	78.27 231	75.75 288	58.78 243	86.29 234	89.25 201	65.12 232	56.66 256	77.17 257	45.05 233	92.95 196	58.13 229	58.33 271	83.10 252

CP-MVSNet		70.50 231	69.91 214	72.26 278	80.71 230	51.00 285	87.23 221	90.30 165	67.84 210	59.64 237	82.69 192	50.23 191	82.30 304	51.28 251	59.28 264	83.46 245

TransMVSNet (Re)		70.07 232	67.66 234	77.31 246	80.62 238	59.13 241	91.78 125	84.94 268	65.97 224	60.08 236	80.44 229	50.78 185	91.87 227	48.84 260	45.46 306	80.94 277

DP-MVS		69.90 233	66.48 239	80.14 196	95.36 13	62.93 183	89.56 182	76.11 300	50.27 295	57.69 252	85.23 170	39.68 251	95.73 110	33.35 306	71.05 193	81.78 262

PS-CasMVS		69.86 234	69.13 221	72.07 281	80.35 244	50.57 287	87.02 224	89.75 184	67.27 217	59.19 240	82.28 198	46.58 222	82.24 305	50.69 253	59.02 267	83.39 247

v52		69.80 235	67.01 238	78.15 234	71.84 297	60.10 226	82.02 259	87.39 237	64.48 233	57.80 250	75.97 264	41.47 245	92.90 201	63.00 200	59.13 266	81.45 266

V4		69.80 235	67.02 237	78.15 234	71.86 296	60.10 226	82.02 259	87.39 237	64.48 233	57.78 251	75.98 263	41.49 244	92.90 201	63.00 200	59.16 265	81.44 267

RPMNet		69.58 237	65.21 247	82.70 137	83.15 209	67.96 62	70.25 301	86.15 258	46.83 304	69.97 157	65.10 305	56.48 122	89.48 263	35.79 302	73.13 177	90.64 152

MSDG		69.54 238	65.73 242	80.96 187	85.11 185	63.71 172	84.19 242	83.28 282	56.95 277	54.50 263	84.03 180	31.50 290	96.03 100	42.87 278	69.13 202	83.14 251

PEN-MVS		69.46 239	68.56 225	72.17 280	79.27 262	49.71 291	86.90 227	89.24 202	67.24 218	59.08 241	82.51 193	47.23 217	83.54 296	48.42 262	57.12 272	83.25 248

LS3D		69.17 240	66.40 240	77.50 241	91.92 72	56.12 262	85.12 237	80.37 293	46.96 302	56.50 257	87.51 147	37.25 267	93.71 183	32.52 311	79.40 137	82.68 257

PatchT		69.11 241	65.37 246	80.32 193	82.07 217	63.68 173	67.96 310	87.62 236	50.86 294	69.37 167	65.18 304	57.09 107	88.53 271	41.59 282	66.60 218	88.74 166

ACMH	63.93 17	68.62 242	64.81 248	80.03 199	85.22 183	63.25 178	87.72 214	84.66 269	60.83 258	51.57 281	79.43 243	27.29 302	94.96 127	41.76 280	64.84 234	81.88 261
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
EG-PatchMatch MVS		68.55 243	65.41 245	77.96 237	78.69 270	62.93 183	89.86 180	89.17 204	60.55 259	50.27 286	77.73 251	22.60 310	94.06 168	47.18 266	72.65 182	76.88 301

ADS-MVSNet		68.54 244	64.38 254	81.03 186	88.06 147	66.90 90	68.01 308	84.02 274	57.57 272	64.48 212	69.87 295	38.68 252	89.21 266	40.87 284	67.89 211	86.97 192

DTE-MVSNet		68.46 245	67.33 235	71.87 284	77.94 276	49.00 294	86.16 235	88.58 222	66.36 222	58.19 247	82.21 201	46.36 223	83.87 294	44.97 272	55.17 279	82.73 255

Patchmatch-RL test		68.17 246	64.49 252	79.19 222	71.22 299	53.93 272	70.07 303	71.54 316	69.22 193	56.79 255	62.89 308	56.58 120	88.61 268	69.53 145	52.61 285	95.03 53

XVG-ACMP-BASELINE		68.04 247	65.53 244	75.56 256	74.06 292	52.37 277	78.43 286	85.88 263	62.03 250	58.91 244	81.21 221	20.38 313	91.15 240	60.69 217	68.18 208	83.16 250

FMVSNet5		68.04 247	65.66 243	75.18 258	84.43 194	57.89 248	83.54 246	86.26 256	61.83 254	53.64 273	73.30 272	37.15 270	85.08 285	48.99 259	61.77 252	82.56 258

ACMH+	65.35 16	67.65 249	64.55 250	76.96 248	84.59 190	57.10 258	88.08 205	80.79 291	58.59 271	53.00 276	81.09 223	26.63 304	92.95 196	46.51 267	61.69 255	80.82 278

pmmvs6		67.57 250	64.76 249	76.00 255	72.82 295	53.37 274	88.71 196	86.78 244	53.19 287	57.58 253	78.03 249	35.33 277	92.41 215	55.56 237	54.88 281	82.21 259

Anonymous20231206		67.53 251	65.78 241	72.79 274	74.95 289	47.59 298	88.23 203	87.32 240	61.75 255	58.07 248	77.29 254	37.79 264	87.29 279	42.91 276	63.71 243	83.48 244

Patchmtry		67.53 251	63.93 255	78.34 229	82.12 216	64.38 156	68.72 305	84.00 275	48.23 301	59.24 239	72.41 280	57.82 102	89.27 265	46.10 269	56.68 276	81.36 269

USDC		67.43 253	64.51 251	76.19 253	77.94 276	55.29 266	78.38 287	85.00 267	73.17 126	48.36 291	80.37 230	21.23 312	92.48 214	52.15 249	64.02 241	80.81 279

ADS-MVSNet2		66.90 254	63.44 257	77.26 247	88.06 147	60.70 215	68.01 308	75.56 305	57.57 272	64.48 212	69.87 295	38.68 252	84.10 289	40.87 284	67.89 211	86.97 192

CMPMVS	48.56 21	66.77 255	64.41 253	73.84 266	70.65 302	50.31 288	77.79 291	85.73 265	45.54 307	44.76 302	82.14 202	35.40 276	90.14 251	63.18 198	74.54 169	81.07 276
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
OpenMVS_ROB	61.12 18	66.39 256	62.92 261	76.80 250	76.51 282	57.77 250	89.22 188	83.41 280	55.48 284	53.86 271	77.84 250	26.28 305	93.95 176	34.90 304	68.76 204	78.68 295

LTVRE_ROB	59.60 19	66.27 257	63.54 256	74.45 262	84.00 201	51.55 281	67.08 311	83.53 278	58.78 269	54.94 261	80.31 231	34.54 280	93.23 191	40.64 286	68.03 209	78.58 296
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
JIA-IIPM		66.06 258	62.45 264	76.88 249	81.42 223	54.45 271	57.49 322	88.67 218	49.36 297	63.86 217	46.86 318	56.06 126	90.25 245	49.53 258	68.83 203	85.95 214

Patchmatch-test		65.86 259	60.94 270	80.62 190	83.75 202	58.83 242	58.91 321	75.26 307	44.50 311	50.95 285	77.09 259	58.81 96	87.90 275	35.13 303	64.03 240	95.12 48

UnsupCasMVSNet_eth		65.79 260	63.10 259	73.88 265	70.71 301	50.29 289	81.09 267	89.88 181	72.58 136	49.25 289	74.77 270	32.57 285	87.43 278	55.96 236	41.04 312	83.90 239

pmmvs-eth3d		65.53 261	62.32 265	75.19 257	69.39 306	59.59 233	82.80 256	83.43 279	62.52 248	51.30 283	72.49 277	32.86 282	87.16 280	55.32 238	50.73 292	78.83 294

SixPastTwentyTwo		64.92 262	61.78 268	74.34 264	78.74 269	49.76 290	83.42 250	79.51 296	62.86 245	50.27 286	77.35 252	30.92 294	90.49 243	45.89 270	47.06 303	82.78 253

OurMVSNet-221017-0		64.68 263	62.17 266	72.21 279	76.08 286	47.35 299	80.67 270	81.02 290	56.19 281	51.60 280	79.66 240	27.05 303	88.56 270	53.60 245	53.63 284	80.71 280

test_0402		64.54 264	61.09 269	74.92 259	84.10 200	60.75 213	87.95 207	79.71 295	52.03 290	52.41 277	77.20 255	32.21 287	91.64 231	23.14 321	61.03 258	72.36 308

testgi		64.48 265	62.87 262	69.31 288	71.24 298	40.62 312	85.49 236	79.92 294	65.36 229	54.18 268	83.49 186	23.74 308	84.55 287	41.60 281	60.79 261	82.77 254

RPSCF		64.24 266	61.98 267	71.01 285	76.10 285	45.00 302	75.83 294	75.94 302	46.94 303	58.96 243	84.59 177	31.40 291	82.00 306	47.76 264	60.33 263	86.04 213

test2356		64.16 267	63.28 258	66.81 295	69.37 307	39.86 315	87.76 213	86.02 260	59.83 264	53.54 274	73.23 273	34.94 278	80.67 309	39.66 288	65.20 227	79.89 286

EU-MVSNet		64.01 268	63.01 260	67.02 294	74.40 291	38.86 317	83.27 251	86.19 257	45.11 308	54.27 266	81.15 222	36.91 273	80.01 310	48.79 261	57.02 273	82.19 260

test20.03		63.83 269	62.65 263	67.38 293	70.58 303	39.94 313	86.57 232	84.17 272	63.29 241	51.86 279	77.30 253	37.09 271	82.47 302	38.87 295	54.13 283	79.73 288

MDA-MVSNet_test_wron		63.78 270	60.16 271	74.64 260	78.15 274	60.41 219	83.49 247	84.03 273	56.17 283	39.17 314	71.59 292	37.22 268	83.24 300	42.87 278	48.73 300	80.26 284

YYNet1		63.76 271	60.14 272	74.62 261	78.06 275	60.19 225	83.46 249	83.99 277	56.18 282	39.25 313	71.56 293	37.18 269	83.34 298	42.90 277	48.70 301	80.32 283

K. test v3		63.09 272	59.61 274	73.53 268	76.26 284	49.38 293	83.27 251	77.15 299	64.35 235	47.77 292	72.32 282	28.73 297	87.79 277	49.93 257	36.69 317	83.41 246

COLMAP_ROB	57.96 20	62.98 273	59.65 273	72.98 272	81.44 222	53.00 276	83.75 244	75.53 306	48.34 300	48.81 290	81.40 215	24.14 306	90.30 244	32.95 308	60.52 262	75.65 304
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
AllTest		61.66 274	58.06 275	72.46 276	79.57 257	51.42 283	80.17 276	68.61 319	51.25 292	45.88 296	81.23 217	19.86 314	86.58 282	38.98 290	57.01 274	79.39 290

UnsupCasMVSNet_bld		61.60 275	57.71 276	73.29 270	68.73 308	51.64 280	78.61 285	89.05 211	57.20 276	46.11 295	61.96 310	28.70 298	88.60 269	50.08 256	38.90 315	79.63 289

MDA-MVSNet-bldmvs		61.54 276	57.70 277	73.05 271	79.53 259	57.00 259	83.08 254	81.23 288	57.57 272	34.91 317	72.45 279	32.79 283	86.26 284	35.81 301	41.95 310	75.89 303

TinyColmap		60.32 277	56.42 283	72.00 282	78.78 268	53.18 275	78.36 288	75.64 303	52.30 289	41.59 312	75.82 266	14.76 321	88.35 272	35.84 300	54.71 282	74.46 305

MVS-HIRNet		60.25 278	55.55 284	74.35 263	84.37 195	56.57 260	71.64 299	74.11 309	34.44 320	45.54 300	42.24 322	31.11 293	89.81 261	40.36 287	76.10 161	76.67 302

MIMVSNet1		60.16 279	57.33 279	68.67 289	69.71 305	44.13 304	78.92 284	84.21 271	55.05 285	44.63 303	71.85 286	23.91 307	81.54 308	32.63 310	55.03 280	80.35 282

PM-MVS		59.40 280	56.59 281	67.84 290	63.63 312	41.86 309	76.76 292	63.22 325	59.01 268	51.07 284	72.27 283	11.72 323	83.25 299	61.34 213	50.28 298	78.39 297

testus		59.36 281	57.51 278	64.90 298	66.72 309	37.56 318	84.98 238	81.09 289	57.46 275	47.72 293	72.76 274	11.43 325	78.78 316	36.56 297	58.91 268	78.36 298

new-patchmatchnet		59.30 282	56.48 282	67.79 291	65.86 310	44.19 303	82.47 257	81.77 286	59.94 263	43.65 307	66.20 301	27.67 300	81.68 307	39.34 289	41.40 311	77.50 300

testpf		57.17 283	56.93 280	57.88 305	79.13 266	42.40 306	34.23 328	85.97 262	52.64 288	47.66 294	66.50 299	36.33 275	79.65 312	53.60 245	56.31 277	51.60 321

DSMNet-mixed		56.78 284	54.44 286	63.79 300	63.21 313	29.44 326	64.43 314	64.10 324	42.12 316	51.32 282	71.60 291	31.76 288	75.04 319	36.23 299	65.20 227	86.87 196

LP		56.71 285	51.64 289	71.91 283	80.08 253	60.33 221	61.72 316	75.61 304	43.87 313	43.76 306	60.30 312	30.46 295	84.05 290	22.94 322	46.06 305	71.34 310

1111		56.66 286	54.98 285	61.69 301	61.99 316	31.38 322	79.81 281	83.17 283	45.66 305	41.94 309	65.44 302	41.50 242	79.56 313	27.64 315	47.68 302	74.14 306

test1235678		55.73 287	52.74 287	64.68 299	60.16 319	35.56 320	81.65 263	81.46 287	51.27 291	38.93 315	62.82 309	17.44 316	78.58 317	30.87 313	50.09 299	79.89 286

pmmvs3		55.51 288	51.50 291	67.53 292	57.90 321	50.93 286	80.37 272	73.66 310	40.63 317	44.15 305	64.75 306	16.30 317	78.97 315	44.77 273	40.98 313	72.69 307

TDRefinement		55.28 289	51.58 290	66.39 296	59.53 320	46.15 301	76.23 293	72.80 311	44.60 310	42.49 308	76.28 262	15.29 319	82.39 303	33.20 307	43.75 308	70.62 312

LF4IMVS		54.01 290	52.12 288	59.69 303	62.41 315	39.91 314	68.59 306	68.28 321	42.96 314	44.55 304	75.18 267	14.09 322	68.39 323	41.36 283	51.68 289	70.78 311

Anonymous20231211		53.57 291	49.43 293	66.00 297	65.01 311	42.08 307	80.95 269	72.60 312	38.46 318	41.65 311	64.48 307	15.72 318	84.23 288	25.78 318	40.24 314	71.68 309

N_pmnet		50.55 292	49.11 294	54.88 309	77.17 280	4.02 338	84.36 241	2.00 338	48.59 298	45.86 298	68.82 297	32.22 286	82.80 301	31.58 312	51.38 290	77.81 299

new_pmnet		49.31 293	46.44 295	57.93 304	62.84 314	40.74 311	68.47 307	62.96 326	36.48 319	35.09 316	57.81 314	14.97 320	72.18 320	32.86 309	46.44 304	60.88 319

test12356		47.51 294	44.82 296	55.56 307	52.53 322	21.09 333	71.45 300	76.03 301	44.14 312	30.69 318	58.18 313	9.01 329	76.14 318	26.95 317	34.43 320	69.46 314

testmv		46.98 295	43.53 297	57.35 306	47.75 327	30.41 325	74.99 296	77.69 297	42.84 315	28.03 319	53.36 315	8.18 330	71.18 321	24.36 320	34.55 318	70.46 313

.test1245		46.52 296	49.68 292	37.02 318	61.99 316	31.38 322	79.81 281	83.17 283	45.66 305	41.94 309	65.44 302	41.50 242	79.56 313	27.64 315	0.01 334	0.13 333

FPMVS		45.64 297	43.10 298	53.23 311	51.42 324	36.46 319	64.97 313	71.91 314	29.13 322	27.53 320	61.55 311	9.83 327	65.01 327	16.00 327	55.58 278	58.22 320

no-one		44.13 298	38.39 299	61.34 302	45.91 329	41.94 308	61.67 317	75.07 308	45.05 309	20.07 323	40.68 325	11.58 324	79.82 311	30.18 314	15.30 325	62.26 318

LCM-MVSNet		40.54 299	35.79 300	54.76 310	36.92 332	30.81 324	51.41 323	69.02 318	22.07 324	24.63 321	45.37 320	4.56 335	65.81 325	33.67 305	34.50 319	67.67 315

ANet_high		40.27 300	35.20 301	55.47 308	34.74 333	34.47 321	63.84 315	71.56 315	48.42 299	18.80 325	41.08 323	9.52 328	64.45 328	20.18 324	8.66 332	67.49 316

PMMVS2		37.93 301	33.61 302	50.92 312	46.31 328	24.76 331	60.55 320	50.05 329	28.94 323	20.93 322	47.59 317	4.41 336	65.13 326	25.14 319	18.55 324	62.87 317

Gipuma		34.91 302	31.44 304	45.30 314	70.99 300	39.64 316	19.85 331	72.56 313	20.10 327	16.16 327	21.47 330	5.08 334	71.16 322	13.07 328	43.70 309	25.08 327
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PNet_i23d		32.77 303	29.98 305	41.11 316	48.05 325	29.17 327	65.82 312	50.02 330	21.42 325	14.74 328	37.19 326	1.11 339	55.11 330	19.75 325	11.77 327	39.06 323

PMVS	26.43 22	31.84 304	28.16 306	42.89 315	25.87 336	27.58 329	50.92 324	49.78 331	21.37 326	14.17 329	40.81 324	2.01 337	66.62 324	9.61 330	38.88 316	34.49 326
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
pcd1.5k->3k		31.17 305	31.85 303	29.12 320	81.48 220	0.00 341	0.00 332	91.79 115	0.00 336	0.00 337	0.00 338	41.05 248	0.00 339	0.00 336	72.34 185	87.36 186

wuykxyi23d		29.03 306	23.09 311	46.84 313	31.67 335	28.82 328	43.46 326	57.72 328	14.39 330	7.52 333	20.84 331	0.64 340	60.29 329	21.57 323	10.04 329	51.40 322

E-PMN		24.61 307	24.00 308	26.45 321	43.74 330	18.44 335	60.86 318	39.66 332	15.11 328	9.53 331	22.10 329	6.52 332	46.94 332	8.31 331	10.14 328	13.98 329

MVE	24.84 23	24.35 308	19.77 312	38.09 317	34.56 334	26.92 330	26.57 329	38.87 334	11.73 331	11.37 330	27.44 327	1.37 338	50.42 331	11.41 329	14.60 326	36.93 324
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
EMVS		23.76 309	23.20 310	25.46 322	41.52 331	16.90 336	60.56 319	38.79 335	14.62 329	8.99 332	20.24 333	7.35 331	45.82 333	7.25 332	9.46 330	13.64 330

tmp_tt		22.26 310	23.75 309	17.80 323	5.23 337	12.06 337	35.26 327	39.48 333	2.82 333	18.94 324	44.20 321	22.23 311	24.64 335	36.30 298	9.31 331	16.69 328

cdsmvs_eth3d_5k		19.86 311	26.47 307	0.00 327	0.00 340	0.00 341	0.00 332	93.45 52	0.00 336	0.00 337	95.27 30	49.56 196	0.00 339	0.00 336	0.00 336	0.00 335

wuyk23d		11.30 312	10.95 313	12.33 324	48.05 325	19.89 334	25.89 330	1.92 339	3.58 332	3.12 334	1.37 335	0.64 340	15.77 336	6.23 333	7.77 333	1.35 331

ab-mvs-re		7.91 313	10.55 314	0.00 327	0.00 340	0.00 341	0.00 332	0.00 342	0.00 336	0.00 337	94.95 40	0.00 344	0.00 339	0.00 336	0.00 336	0.00 335

testmvs		7.23 314	9.62 315	0.06 326	0.04 338	0.02 340	84.98 238	0.02 340	0.03 334	0.18 335	1.21 336	0.01 343	0.02 337	0.14 334	0.01 334	0.13 333

test123		6.92 315	9.21 316	0.08 325	0.03 339	0.05 339	81.65 263	0.01 341	0.02 335	0.14 336	0.85 337	0.03 342	0.02 337	0.12 335	0.00 336	0.16 332

pcd_1.5k_mvsjas		4.46 316	5.95 317	0.00 327	0.00 340	0.00 341	0.00 332	0.00 342	0.00 336	0.00 337	0.00 338	53.55 162	0.00 339	0.00 336	0.00 336	0.00 335

sosnet-low-res		0.00 317	0.00 318	0.00 327	0.00 340	0.00 341	0.00 332	0.00 342	0.00 336	0.00 337	0.00 338	0.00 344	0.00 339	0.00 336	0.00 336	0.00 335

sosnet		0.00 317	0.00 318	0.00 327	0.00 340	0.00 341	0.00 332	0.00 342	0.00 336	0.00 337	0.00 338	0.00 344	0.00 339	0.00 336	0.00 336	0.00 335

uncertanet		0.00 317	0.00 318	0.00 327	0.00 340	0.00 341	0.00 332	0.00 342	0.00 336	0.00 337	0.00 338	0.00 344	0.00 339	0.00 336	0.00 336	0.00 335

Regformer		0.00 317	0.00 318	0.00 327	0.00 340	0.00 341	0.00 332	0.00 342	0.00 336	0.00 337	0.00 338	0.00 344	0.00 339	0.00 336	0.00 336	0.00 335

uanet		0.00 317	0.00 318	0.00 327	0.00 340	0.00 341	0.00 332	0.00 342	0.00 336	0.00 337	0.00 338	0.00 344	0.00 339	0.00 336	0.00 336	0.00 335

sam_mvs1												57.85 101

sam_mvs												54.91 145

semantic-postprocess				76.32 252	81.48 220	60.67 216		85.99 261	66.17 223	59.50 238	78.88 245	45.51 229	83.65 295	62.58 207	61.93 250	84.63 235

ambc				69.61 287	61.38 318	41.35 310	49.07 325	85.86 264		50.18 288	66.40 300	10.16 326	88.14 274	45.73 271	44.20 307	79.32 292

MTGPA								92.23 95

test_post1							78.95 283				20.70 332	53.05 168	91.50 238	60.43 218

test_post											23.01 328	56.49 121	92.67 208

patchmatchnet-post											67.62 298	57.62 104	90.25 245

GG-mvs-BLEND				86.53 49	91.91 73	69.67 34	75.02 295	94.75 19		78.67 81	90.85 112	77.91 2	94.56 139	72.25 119	93.74 29	95.36 34

MTMP								32.52 336

gm-plane-assit					88.42 141	67.04 85			78.62 52		91.83 102		97.37 47	76.57 93

test9_res														89.41 10	94.96 8	95.29 38

TEST9					94.18 27	67.28 77	94.16 36	93.51 49	71.75 159	85.52 26	95.33 26	68.01 23	97.27 54

test_8					94.19 26	67.19 79	94.15 38	93.42 54	71.87 151	85.38 28	95.35 25	68.19 21	96.95 74

agg_prior2														86.41 31	94.75 16	95.33 35

agg_prior					94.16 31	66.97 86		93.31 58		84.49 35			96.75 83

TestCases				72.46 276	79.57 257	51.42 283		68.61 319	51.25 292	45.88 296	81.23 217	19.86 314	86.58 282	38.98 290	57.01 274	79.39 290

test_prior4						67.18 81	93.92 52

test_prior2							95.10 27		75.40 89	85.25 30	95.61 21	67.94 24		87.47 23	94.77 13

test_prior				86.42 53	94.71 21	67.35 75		93.10 69					96.84 79			95.05 50

旧先验2							92.00 109		59.37 267	87.54 14			93.47 188	75.39 99

新几何2							91.41 137

新几何1				84.73 101	92.32 64	64.28 161		91.46 128	59.56 265	79.77 67	92.90 86	56.95 112	96.57 88	63.40 195	92.91 39	93.34 103

旧先验1					91.94 71	60.74 214		91.50 126			94.36 55	65.23 46			91.84 51	94.55 64

无先验							92.71 84	92.61 86	62.03 250				97.01 65	66.63 166		93.97 90

原ACMM2							92.01 107

原ACMM1				84.42 110	93.21 47	64.27 162		93.40 55	65.39 228	79.51 70	92.50 91	58.11 100	96.69 85	65.27 182	93.96 23	92.32 130

test222					89.77 112	61.60 204	89.55 183	89.42 196	56.83 279	77.28 93	92.43 94	52.76 171			91.14 63	93.09 112

testdata2													96.09 97	61.26 214

segment_acmp												65.94 40

testdata				81.34 175	89.02 127	57.72 251		89.84 182	58.65 270	85.32 29	94.09 64	57.03 109	93.28 190	69.34 147	90.56 69	93.03 114

testdata1							89.21 189		77.55 63

test12				87.09 34	94.60 23	68.86 44		92.91 75		82.67 48		65.44 45	97.55 41		93.69 31	94.84 58

plane_prior7					86.94 162	61.51 205

plane_prior6					87.23 158	62.32 194						50.66 186

plane_prior5								91.31 133					95.55 119	76.74 91	78.53 145	88.39 172

plane_prior4											89.14 131

plane_prior3						61.95 201			79.09 44	72.53 132

plane_prior2							93.13 72		78.81 49

plane_prior1					87.15 159

plane_prior						62.42 192	93.85 55		79.38 37						78.80 144

n2								0.00 342

nn								0.00 342

door-mid								66.01 323

lessismore_v0				73.72 267	72.93 294	47.83 297		61.72 327		45.86 298	73.76 271	28.63 299	89.81 261	47.75 265	31.37 321	83.53 242

LGP-MVS_train				79.56 211	84.31 196	59.37 237		89.73 187	69.49 190	64.86 208	88.42 135	38.65 254	94.30 155	72.56 116	72.76 180	85.01 230

test11								93.01 71

door								66.57 322

HQP5-MVS						63.66 174

HQP-NCC					87.54 154		94.06 43		79.80 33	74.18 115

ACMP_Plane					87.54 154		94.06 43		79.80 33	74.18 115

BP-MVS														77.63 88

HQP4-MVS										74.18 115			95.61 116			88.63 167

HQP3-MVS								91.70 119							78.90 142

HQP2-MVS												51.63 182

NP-MVS					87.41 157	63.04 181					90.30 120

MDTV_nov1_ep13_2view						59.90 230	80.13 277		67.65 213	72.79 127		54.33 153		59.83 221		92.58 125

MDTV_nov1_ep13			72.61 196		89.06 126	68.48 50	80.33 273	90.11 174	71.84 154	71.81 143	75.92 265	53.01 169	93.92 177	48.04 263	73.38 175

ACMMP++_ref															71.63 187

ACMMP++															69.72 196

Test By Simon												54.21 155

ITE_SJBPF				70.43 286	74.44 290	47.06 300		77.32 298	60.16 262	54.04 269	83.53 184	23.30 309	84.01 292	43.07 275	61.58 256	80.21 285

DeepMVS_CX				34.71 319	51.45 323	24.73 332		28.48 337	31.46 321	17.49 326	52.75 316	5.80 333	42.60 334	18.18 326	19.42 323	36.81 325

High-resolution multi-view benchmark