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.

CNVR-MVS		98.46 1	98.38 1	98.72 3	99.80 4	96.19 9	99.80 7	97.99 48	97.05 3	99.41 1	99.59 2	92.89 10	100.00 1	98.99 4	99.90 4	99.96 4

MCST-MVS		98.18 2	97.95 4	98.86 1	99.85 3	96.60 5	99.70 10	97.98 49	97.18 2	95.96 60	99.33 6	92.62 11	100.00 1	98.99 4	99.93 1	99.98 2

NCCC		98.12 3	98.11 3	98.13 14	99.76 6	94.46 37	99.81 5	97.88 54	96.54 4	98.84 6	99.46 3	92.55 12	99.98 8	98.25 20	99.93 1	99.94 6

HSP-MVS		97.73 4	98.15 2	96.44 89	99.54 27	90.14 123	99.41 36	97.47 113	95.46 14	98.60 8	99.19 16	95.71 4	99.49 84	98.15 21	99.85 9	99.69 45

HPM-MVS++		97.72 5	97.59 6	98.14 13	99.53 32	94.76 28	99.19 51	97.75 70	95.66 11	98.21 15	99.29 7	91.10 18	99.99 4	97.68 26	99.87 5	99.68 46

APDe-MVS		97.53 6	97.47 7	97.70 24	99.58 19	93.63 49	99.56 21	97.52 105	93.59 32	98.01 23	99.12 29	90.80 29	99.55 76	99.26 2	99.79 16	99.93 7

SD-MVS		97.51 7	97.40 10	97.81 22	99.01 57	93.79 48	99.33 47	97.38 125	93.73 29	98.83 7	99.02 39	90.87 27	99.88 32	98.69 8	99.74 19	99.77 33

MSLP-MVS++		97.50 8	97.45 9	97.63 26	99.65 13	93.21 56	99.70 10	98.13 42	94.61 16	97.78 29	99.46 3	89.85 37	99.81 50	97.97 22	99.91 3	99.88 14

TSAR-MVS + MP.		97.44 9	97.46 8	97.39 38	99.12 51	93.49 54	98.52 132	97.50 110	94.46 17	98.99 2	98.64 73	91.58 15	99.08 112	98.49 15	99.83 12	99.60 57

SteuartSystems-ACMMP		97.25 10	97.34 11	97.01 49	97.38 104	91.46 88	99.75 8	97.66 80	94.14 21	98.13 16	99.26 8	92.16 13	99.66 63	97.91 24	99.64 29	99.90 9
Skip Steuart: Steuart Systems R&D Blog.
MG-MVS		97.24 11	96.83 19	98.47 9	99.79 5	95.71 12	99.07 69	99.06 14	94.45 18	96.42 55	98.70 70	88.81 48	99.74 58	95.35 62	99.86 8	99.97 3

train_agg		97.20 12	97.08 13	97.57 30	99.57 23	93.17 57	99.38 38	97.66 80	90.18 91	98.39 11	99.18 18	90.94 24	99.66 63	98.58 12	99.85 9	99.88 14

DeepC-MVS_fast	93.52 2	97.16 13	96.84 18	98.13 14	99.61 17	94.45 38	98.85 94	97.64 85	96.51 6	95.88 61	99.39 5	87.35 75	99.99 4	96.61 39	99.69 26	99.96 4
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
agg_prior1		97.12 14	97.03 14	97.38 39	99.54 27	92.66 69	99.35 44	97.64 85	90.38 86	97.98 24	99.17 20	90.84 28	99.61 72	98.57 14	99.78 18	99.87 18

DELS-MVS		97.12 14	96.60 25	98.68 5	98.03 84	96.57 6	99.84 3	97.84 58	96.36 7	95.20 74	98.24 90	88.17 58	99.83 45	96.11 50	99.60 36	99.64 51
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
agg_prior3		97.09 16	96.97 15	97.45 33	99.56 25	92.79 68	99.36 42	97.67 79	89.59 101	98.36 13	99.16 22	90.57 31	99.68 60	98.58 12	99.85 9	99.88 14

test_prior3		97.07 17	97.09 12	97.01 49	99.58 19	91.77 79	99.57 19	97.57 98	91.43 68	98.12 18	98.97 45	90.43 33	99.49 84	98.33 17	99.81 14	99.79 24

CANet		97.00 18	96.49 26	98.55 6	98.86 66	96.10 10	99.83 4	97.52 105	95.90 8	97.21 36	98.90 55	82.66 138	99.93 22	98.71 7	98.80 72	99.63 53

Regformer-1		96.97 19	96.80 20	97.47 32	99.46 36	93.11 59	98.89 91	97.94 50	92.89 41	96.90 41	99.02 39	89.78 38	99.53 78	97.06 30	99.26 55	99.75 34

TSAR-MVS + GP.		96.95 20	96.91 16	97.07 46	98.88 64	91.62 84	99.58 18	96.54 175	95.09 15	96.84 48	98.63 74	91.16 16	99.77 55	99.04 3	96.42 107	99.81 21

APD-MVS		96.95 20	96.72 22	97.63 26	99.51 33	93.58 50	99.16 56	97.44 118	90.08 96	98.59 9	99.07 33	89.06 44	99.42 92	97.92 23	99.66 27	99.88 14
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
Regformer-2		96.94 22	96.78 21	97.42 35	99.46 36	92.97 64	98.89 91	97.93 51	92.86 43	96.88 42	99.02 39	89.74 39	99.53 78	97.03 31	99.26 55	99.75 34

PS-MVSNAJ		96.87 23	96.40 28	98.29 10	97.35 105	97.29 1	99.03 73	97.11 144	95.83 9	98.97 3	99.14 26	82.48 141	99.60 74	98.60 9	99.08 58	98.00 150

EPNet		96.82 24	96.68 24	97.25 42	98.65 71	93.10 60	99.48 26	98.76 17	96.54 4	97.84 28	98.22 91	87.49 68	99.66 63	95.35 62	97.78 90	99.00 92
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 280x420		96.80 25	96.85 17	96.66 77	97.85 86	94.42 40	94.76 275	98.36 25	92.50 46	95.62 68	97.52 108	97.92 1	97.38 189	98.31 19	98.80 72	98.20 145

MVS_111021_HR		96.69 26	96.69 23	96.72 73	98.58 74	91.00 106	99.14 63	99.45 1	93.86 26	95.15 75	98.73 66	88.48 53	99.76 56	97.23 29	99.56 39	99.40 68

xiu_mvs_v2_base		96.66 27	96.17 36	98.11 16	97.11 113	96.96 2	99.01 76	97.04 152	95.51 13	98.86 5	99.11 32	82.19 147	99.36 97	98.59 11	98.14 84	98.00 150

PHI-MVS		96.65 28	96.46 27	97.21 43	99.34 39	91.77 79	99.70 10	98.05 44	86.48 182	98.05 20	99.20 15	89.33 42	99.96 15	98.38 16	99.62 33	99.90 9

ACMMP_Plus		96.59 29	96.18 34	97.81 22	98.82 67	93.55 51	98.88 93	97.59 93	90.66 78	97.98 24	99.14 26	86.59 86	100.00 1	96.47 42	99.46 43	99.89 13

CDPH-MVS		96.56 30	96.18 34	97.70 24	99.59 18	93.92 46	99.13 66	97.44 118	89.02 117	97.90 27	99.22 13	88.90 47	99.49 84	94.63 75	99.79 16	99.68 46

DeepPCF-MVS	93.56 1	96.55 31	97.84 5	92.68 188	98.71 70	78.11 297	99.70 10	97.71 75	98.18 1	97.36 35	99.76 1	90.37 35	99.94 20	99.27 1	99.54 40	99.99 1

Regformer-3		96.50 32	96.36 30	96.91 59	99.34 39	91.72 82	98.71 105	97.90 53	92.48 47	96.00 57	98.95 50	88.60 50	99.52 81	96.44 43	98.83 69	99.49 64

#test#		96.48 33	96.34 31	96.90 60	99.69 8	90.96 107	99.53 24	97.81 63	90.94 76	96.88 42	99.05 36	87.57 65	99.96 15	95.87 54	99.72 21	99.78 28

XVS		96.47 34	96.37 29	96.77 67	99.62 15	90.66 116	99.43 33	97.58 95	92.41 52	96.86 45	98.96 48	87.37 71	99.87 35	95.65 55	99.43 46	99.78 28

Regformer-4		96.45 35	96.33 32	96.81 66	99.34 39	91.44 89	98.71 105	97.88 54	92.43 48	95.97 59	98.95 50	88.42 54	99.51 82	96.40 44	98.83 69	99.49 64

HFP-MVS		96.42 36	96.26 33	96.90 60	99.69 8	90.96 107	99.47 27	97.81 63	90.54 83	96.88 42	99.05 36	87.57 65	99.96 15	95.65 55	99.72 21	99.78 28

PAPR		96.35 37	95.82 44	97.94 19	99.63 14	94.19 44	99.42 35	97.55 101	92.43 48	93.82 96	99.12 29	87.30 76	99.91 26	94.02 79	99.06 59	99.74 37

PAPM		96.35 37	95.94 41	97.58 28	94.10 193	95.25 15	98.93 82	98.17 38	94.26 19	93.94 92	98.72 68	89.68 40	97.88 154	96.36 45	99.29 53	99.62 55

lupinMVS		96.32 39	95.94 41	97.44 34	95.05 177	94.87 21	99.86 2	96.50 176	93.82 27	98.04 21	98.77 62	85.52 99	98.09 143	96.98 35	98.97 63	99.37 69

region2R		96.30 40	96.17 36	96.70 74	99.70 7	90.31 120	99.46 30	97.66 80	90.55 82	97.07 39	99.07 33	86.85 83	99.97 13	95.43 60	99.74 19	99.81 21

ACMMPR		96.28 41	96.14 39	96.73 71	99.68 10	90.47 118	99.47 27	97.80 65	90.54 83	96.83 49	99.03 38	86.51 89	99.95 18	95.65 55	99.72 21	99.75 34

CP-MVS		96.22 42	96.15 38	96.42 90	99.67 11	89.62 138	99.70 10	97.61 91	90.07 97	96.00 57	99.16 22	87.43 69	99.92 24	96.03 52	99.72 21	99.70 43

MPTG		96.21 43	95.96 40	96.96 57	99.29 43	91.19 97	98.69 109	97.45 115	92.58 44	94.39 84	99.24 11	86.43 91	99.99 4	96.22 46	99.40 49	99.71 41

MVS_0304		96.12 44	95.26 54	98.69 4	98.44 76	96.54 7	99.70 10	96.89 161	95.76 10	97.53 31	99.12 29	72.42 226	99.93 22	98.75 6	98.69 75	99.61 56

MTAPA		96.09 45	95.80 46	96.96 57	99.29 43	91.19 97	97.23 209	97.45 115	92.58 44	94.39 84	99.24 11	86.43 91	99.99 4	96.22 46	99.40 49	99.71 41

MP-MVS		96.00 46	95.82 44	96.54 85	99.47 35	90.13 125	99.36 42	97.41 122	90.64 81	95.49 69	98.95 50	85.51 101	99.98 8	96.00 53	99.59 38	99.52 61

WTY-MVS		95.97 47	95.11 57	98.54 7	97.62 92	96.65 4	99.44 31	98.74 18	92.25 55	95.21 73	98.46 87	86.56 87	99.46 91	95.00 68	92.69 145	99.50 63

PVSNet_Blended		95.94 48	95.66 48	96.75 69	98.77 68	91.61 85	99.88 1	98.04 45	93.64 31	94.21 88	97.76 101	83.50 120	99.87 35	97.41 27	97.75 91	98.79 110

mPP-MVS		95.90 49	95.75 47	96.38 92	99.58 19	89.41 143	99.26 49	97.41 122	90.66 78	94.82 79	98.95 50	86.15 95	99.98 8	95.24 65	99.64 29	99.74 37

PGM-MVS		95.85 50	95.65 49	96.45 88	99.50 34	89.77 135	98.22 167	98.90 16	89.19 111	96.74 51	98.95 50	85.91 97	99.92 24	93.94 80	99.46 43	99.66 49

DP-MVS Recon		95.85 50	95.15 56	97.95 18	99.87 2	94.38 41	99.60 17	97.48 112	86.58 180	94.42 83	99.13 28	87.36 74	99.98 8	93.64 87	98.33 83	99.48 66

MP-MVS-pluss		95.80 52	95.30 52	97.29 41	98.95 61	92.66 69	98.59 126	97.14 141	88.95 120	93.12 100	99.25 9	85.62 98	99.94 20	96.56 41	99.48 42	99.28 78
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MVS_111021_LR		95.78 53	95.94 41	95.28 128	98.19 81	87.69 168	98.80 99	99.26 12	93.39 34	95.04 77	98.69 71	84.09 116	99.76 56	96.96 36	99.06 59	98.38 135

alignmvs		95.77 54	95.00 59	98.06 17	97.35 105	95.68 13	99.71 9	97.50 110	91.50 66	96.16 56	98.61 75	86.28 93	99.00 114	96.19 48	91.74 159	99.51 62

EI-MVSNet-Vis-set		95.76 55	95.63 51	96.17 99	99.14 50	90.33 119	98.49 138	97.82 60	91.92 59	94.75 80	98.88 57	87.06 79	99.48 89	95.40 61	97.17 100	98.70 118

APD-MVS_3200maxsize		95.64 56	95.65 49	95.62 115	99.24 47	87.80 167	98.42 146	97.22 135	88.93 122	96.64 54	98.98 44	85.49 102	99.36 97	96.68 38	99.27 54	99.70 43

EI-MVSNet-UG-set		95.43 57	95.29 53	95.86 110	99.07 55	89.87 132	98.43 145	97.80 65	91.78 62	94.11 90	98.77 62	86.25 94	99.48 89	94.95 70	96.45 106	98.22 143

PAPM_NR		95.43 57	95.05 58	96.57 84	99.42 38	90.14 123	98.58 127	97.51 107	90.65 80	92.44 107	98.90 55	87.77 64	99.90 28	90.88 115	99.32 52	99.68 46

HPM-MVS		95.41 59	95.22 55	95.99 104	99.29 43	89.14 144	99.17 55	97.09 148	87.28 169	95.40 70	98.48 84	84.93 108	99.38 95	95.64 59	99.65 28	99.47 67

jason		95.40 60	94.86 60	97.03 48	92.91 222	94.23 43	99.70 10	96.30 187	93.56 33	96.73 52	98.52 79	81.46 152	97.91 151	96.08 51	98.47 81	98.96 97
jason: jason.
HY-MVS	88.56 7	95.29 61	94.23 68	98.48 8	97.72 89	96.41 8	94.03 283	98.74 18	92.42 51	95.65 67	94.76 176	86.52 88	99.49 84	95.29 64	92.97 141	99.53 60

1121		95.19 62	94.45 64	97.42 35	98.88 64	92.58 73	96.22 245	97.75 70	85.50 193	96.86 45	99.01 43	88.59 52	99.90 28	87.64 148	99.60 36	99.79 24

VNet		95.08 63	94.26 67	97.55 31	98.07 83	93.88 47	98.68 112	98.73 20	90.33 88	97.16 38	97.43 112	79.19 163	99.53 78	96.91 37	91.85 157	99.24 81

canonicalmvs		95.02 64	93.96 77	98.20 11	97.53 98	95.92 11	98.71 105	96.19 196	91.78 62	95.86 63	98.49 83	79.53 160	99.03 113	96.12 49	91.42 165	99.66 49

HPM-MVS_fast		94.89 65	94.62 62	95.70 114	99.11 52	88.44 158	99.14 63	97.11 144	85.82 188	95.69 66	98.47 85	83.46 122	99.32 101	93.16 95	99.63 32	99.35 70

CSCG		94.87 66	94.71 61	95.36 125	99.54 27	86.49 201	99.34 46	98.15 40	82.71 247	90.15 140	99.25 9	89.48 41	99.86 40	94.97 69	98.82 71	99.72 40

sss		94.85 67	93.94 79	97.58 28	96.43 135	94.09 45	98.93 82	99.16 13	89.50 105	95.27 72	97.85 97	81.50 151	99.65 67	92.79 101	94.02 135	98.99 94

API-MVS		94.78 68	94.18 69	96.59 83	99.21 48	90.06 129	98.80 99	97.78 68	83.59 230	93.85 94	99.21 14	83.79 118	99.97 13	92.37 103	99.00 62	99.74 37

xiu_mvs_v1_base_debu		94.73 69	93.98 74	96.99 52	95.19 167	95.24 16	98.62 120	96.50 176	92.99 37	97.52 32	98.83 59	72.37 227	99.15 106	97.03 31	96.74 102	96.58 185

xiu_mvs_v1_base		94.73 69	93.98 74	96.99 52	95.19 167	95.24 16	98.62 120	96.50 176	92.99 37	97.52 32	98.83 59	72.37 227	99.15 106	97.03 31	96.74 102	96.58 185

xiu_mvs_v1_base_debi		94.73 69	93.98 74	96.99 52	95.19 167	95.24 16	98.62 120	96.50 176	92.99 37	97.52 32	98.83 59	72.37 227	99.15 106	97.03 31	96.74 102	96.58 185

MVSFormer		94.71 72	94.08 72	96.61 82	95.05 177	94.87 21	97.77 193	96.17 197	86.84 176	98.04 21	98.52 79	85.52 99	95.99 255	89.83 123	98.97 63	98.96 97

PVSNet_Blended_VisFu		94.67 73	94.11 70	96.34 94	97.14 112	91.10 102	99.32 48	97.43 120	92.10 58	91.53 117	96.38 157	83.29 126	99.68 60	93.42 92	96.37 108	98.25 142

ACMMP		94.67 73	94.30 66	95.79 111	99.25 46	88.13 161	98.41 148	98.67 22	90.38 86	91.43 119	98.72 68	82.22 146	99.95 18	93.83 84	95.76 121	99.29 76
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
abl_6		94.63 75	94.48 63	95.09 131	98.61 73	86.96 188	98.06 182	96.97 158	89.31 107	95.86 63	98.56 77	79.82 158	99.64 69	94.53 77	98.65 78	98.66 120

CPTT-MVS		94.60 76	94.43 65	95.09 131	99.66 12	86.85 191	99.44 31	97.47 113	83.22 238	94.34 86	98.96 48	82.50 139	99.55 76	94.81 71	99.50 41	98.88 105

DeepC-MVS	91.02 4	94.56 77	93.92 80	96.46 87	97.16 111	90.76 112	98.39 152	97.11 144	93.92 22	88.66 158	98.33 88	78.14 172	99.85 42	95.02 67	98.57 79	98.78 113
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MAR-MVS		94.43 78	94.09 71	95.45 124	99.10 53	87.47 174	98.39 152	97.79 67	88.37 138	94.02 91	99.17 20	78.64 170	99.91 26	92.48 102	98.85 68	98.96 97
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
DWT-MVSNet_test		94.36 79	93.95 78	95.62 115	96.99 117	89.47 141	96.62 230	97.38 125	90.96 75	93.07 102	97.27 118	93.73 7	98.09 143	85.86 165	93.65 137	99.29 76

CHOSEN 1792x2688		94.35 80	93.82 82	95.95 107	97.40 103	88.74 152	98.41 148	98.27 27	92.18 57	91.43 119	96.40 154	78.88 164	99.81 50	93.59 88	97.81 87	99.30 75

CANet_DTU		94.31 81	93.35 86	97.20 44	97.03 116	94.71 30	98.62 120	95.54 239	95.61 12	97.21 36	98.47 85	71.88 232	99.84 43	88.38 141	97.46 96	97.04 174

PLC	91.07 3	94.23 82	94.01 73	94.87 138	99.17 49	87.49 173	99.25 50	96.55 174	88.43 136	91.26 122	98.21 93	85.92 96	99.86 40	89.77 126	97.57 92	97.24 168
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PatchFormer-LS_test		94.08 83	93.60 85	95.53 122	96.92 118	89.57 139	96.51 233	97.34 129	91.29 72	92.22 110	97.18 124	91.66 14	98.02 148	87.05 152	92.21 152	99.00 92

114514_t		94.06 84	93.05 92	97.06 47	99.08 54	92.26 77	98.97 80	97.01 156	82.58 249	92.57 105	98.22 91	80.68 156	99.30 102	89.34 132	99.02 61	99.63 53

MVS		93.92 85	92.28 106	98.83 2	95.69 155	96.82 3	96.22 245	98.17 38	84.89 205	84.34 191	98.61 75	79.32 162	99.83 45	93.88 82	99.43 46	99.86 19

OMC-MVS		93.90 86	93.62 84	94.73 142	98.63 72	87.00 187	98.04 183	96.56 173	92.19 56	92.46 106	98.73 66	79.49 161	99.14 109	92.16 106	94.34 133	98.03 149

Effi-MVS+		93.87 87	93.15 90	96.02 103	95.79 151	90.76 112	96.70 227	95.78 221	86.98 173	95.71 65	97.17 126	79.58 159	98.01 149	94.57 76	96.09 115	99.31 74

TESTMET0.1,1		93.82 88	93.26 88	95.49 123	95.21 166	90.25 121	99.15 60	97.54 104	89.18 113	91.79 112	94.87 174	89.13 43	97.63 173	86.21 159	96.29 112	98.60 121

AdaColmap		93.82 88	93.06 91	96.10 102	99.88 1	89.07 145	98.33 154	97.55 101	86.81 178	90.39 137	98.65 72	75.09 186	99.98 8	93.32 93	97.53 94	99.26 80

EPP-MVSNet		93.75 90	93.67 83	94.01 162	95.86 150	85.70 229	98.67 114	97.66 80	84.46 210	91.36 121	97.18 124	91.16 16	97.79 160	92.93 98	93.75 136	98.53 126

thres200		93.69 91	92.59 101	96.97 56	97.76 87	94.74 29	99.35 44	99.36 2	89.23 110	91.21 124	96.97 136	83.42 123	98.77 119	85.08 169	90.96 168	97.39 165

PVSNet	87.13 12	93.69 91	92.83 96	96.28 95	97.99 85	90.22 122	99.38 38	98.93 15	91.42 70	93.66 97	97.68 104	71.29 238	99.64 69	87.94 145	97.20 99	98.98 95

HyFIR lowres test		93.68 93	93.29 87	94.87 138	97.57 97	88.04 163	98.18 172	98.47 23	87.57 161	91.24 123	95.05 172	85.49 102	97.46 182	93.22 94	92.82 142	99.10 88

MVS_Test		93.67 94	92.67 99	96.69 75	96.72 129	92.66 69	97.22 210	96.03 202	87.69 159	95.12 76	94.03 183	81.55 150	98.28 138	89.17 136	96.46 105	99.14 86

CNLPA		93.64 95	92.74 97	96.36 93	98.96 60	90.01 131	99.19 51	95.89 218	86.22 185	89.40 153	98.85 58	80.66 157	99.84 43	88.57 140	96.92 101	99.24 81

PMMVS		93.62 96	93.90 81	92.79 184	96.79 127	81.40 270	98.85 94	96.81 162	91.25 73	96.82 50	98.15 95	77.02 178	98.13 142	93.15 96	96.30 111	98.83 107

CDS-MVSNet		93.47 97	93.04 93	94.76 140	94.75 185	89.45 142	98.82 97	97.03 154	87.91 151	90.97 126	96.48 152	89.06 44	96.36 232	89.50 127	92.81 144	98.49 128
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
1314		93.44 98	91.98 116	97.84 20	95.24 164	94.38 41	96.22 245	97.92 52	90.18 91	82.28 220	97.71 103	77.63 175	99.80 52	91.94 108	98.67 77	99.34 72

tfpn200view9		93.43 99	92.27 107	96.90 60	97.68 90	94.84 23	99.18 53	99.36 2	88.45 133	90.79 127	96.90 138	83.31 124	98.75 121	84.11 180	90.69 170	97.12 169

3Dnovator+	87.72 8	93.43 99	91.84 118	98.17 12	95.73 154	95.08 19	98.92 84	97.04 152	91.42 70	81.48 233	97.60 106	74.60 193	99.79 53	90.84 116	98.97 63	99.64 51

thres400		93.39 101	92.27 107	96.73 71	97.68 90	94.84 23	99.18 53	99.36 2	88.45 133	90.79 127	96.90 138	83.31 124	98.75 121	84.11 180	90.69 170	96.61 179

PVSNet_BlendedMVS		93.36 102	93.20 89	93.84 167	98.77 68	91.61 85	99.47 27	98.04 45	91.44 67	94.21 88	92.63 215	83.50 120	99.87 35	97.41 27	83.37 222	90.05 278

thres100view900		93.34 103	92.15 111	96.90 60	97.62 92	94.84 23	99.06 71	99.36 2	87.96 148	90.47 134	96.78 140	83.29 126	98.75 121	84.11 180	90.69 170	97.12 169

conf200view11		93.32 104	92.15 111	96.84 65	97.62 92	94.84 23	99.06 71	99.36 2	87.96 148	90.47 134	96.78 140	83.29 126	98.75 121	84.11 180	90.69 170	96.94 176

UA-Net		93.30 105	92.62 100	95.34 126	96.27 139	88.53 157	95.88 259	96.97 158	90.90 77	95.37 71	97.07 131	82.38 144	99.10 111	83.91 184	94.86 130	98.38 135

tfpn_ndepth		93.28 106	92.32 104	96.16 100	97.74 88	92.86 67	99.01 76	98.19 36	85.50 193	89.84 145	97.12 128	93.57 8	97.58 176	79.39 225	90.50 176	98.04 148

test-mter		93.27 107	92.89 95	94.40 150	94.94 181	87.27 184	99.15 60	97.25 131	88.95 120	91.57 114	94.04 181	88.03 62	97.58 176	85.94 162	96.13 113	98.36 138

Vis-MVSNet (Re-imp)		93.26 108	93.00 94	94.06 160	96.14 145	86.71 197	98.68 112	96.70 165	88.30 140	89.71 148	97.64 105	85.43 105	96.39 230	88.06 144	96.32 109	99.08 89

thres600view7		93.18 109	92.00 115	96.75 69	97.62 92	94.92 20	99.07 69	99.36 2	87.96 148	90.47 134	96.78 140	83.29 126	98.71 126	82.93 192	90.47 177	96.61 179

3Dnovator	87.35 11	93.17 110	91.77 120	97.37 40	95.41 162	93.07 61	98.82 97	97.85 57	91.53 65	82.56 215	97.58 107	71.97 231	99.82 48	91.01 113	99.23 57	99.22 83

test-LLR		93.11 111	92.68 98	94.40 150	94.94 181	87.27 184	99.15 60	97.25 131	90.21 89	91.57 114	94.04 181	84.89 109	97.58 176	85.94 162	96.13 113	98.36 138

IS-MVSNet		93.00 112	92.51 102	94.49 147	96.14 145	87.36 181	98.31 157	95.70 227	88.58 129	90.17 139	97.50 109	83.02 134	97.22 192	87.06 151	96.07 117	98.90 104

CostFormer		92.89 113	92.48 103	94.12 158	94.99 179	85.89 223	92.89 293	97.00 157	86.98 173	95.00 78	90.78 239	90.05 36	97.51 181	92.92 99	91.73 160	98.96 97

view600		92.78 114	91.50 126	96.63 78	97.51 99	94.66 32	98.91 85	99.36 2	87.31 165	89.64 149	96.59 146	83.26 130	98.63 129	80.76 214	90.15 179	96.61 179

view800		92.78 114	91.50 126	96.63 78	97.51 99	94.66 32	98.91 85	99.36 2	87.31 165	89.64 149	96.59 146	83.26 130	98.63 129	80.76 214	90.15 179	96.61 179

conf0.05thres1000		92.78 114	91.50 126	96.63 78	97.51 99	94.66 32	98.91 85	99.36 2	87.31 165	89.64 149	96.59 146	83.26 130	98.63 129	80.76 214	90.15 179	96.61 179

tfpn		92.78 114	91.50 126	96.63 78	97.51 99	94.66 32	98.91 85	99.36 2	87.31 165	89.64 149	96.59 146	83.26 130	98.63 129	80.76 214	90.15 179	96.61 179

tpmrst		92.78 114	92.16 110	94.65 144	96.27 139	87.45 175	91.83 302	97.10 147	89.10 116	94.68 82	90.69 244	88.22 57	97.73 169	89.78 125	91.80 158	98.77 114

MVSTER		92.71 119	92.32 104	93.86 166	97.29 107	92.95 65	99.01 76	96.59 169	90.09 95	85.51 183	94.00 185	94.61 5	96.56 213	90.77 118	83.03 225	92.08 221

1112_ss		92.71 119	91.55 125	96.20 96	95.56 158	91.12 100	98.48 139	94.69 269	88.29 141	86.89 176	98.50 81	87.02 80	98.66 127	84.75 172	89.77 185	98.81 108

tfpn1000		92.67 121	91.64 123	95.78 112	97.61 96	92.34 76	98.69 109	98.18 37	84.15 215	88.80 157	96.99 135	93.56 9	97.21 193	76.56 250	90.19 178	97.77 157

Vis-MVSNet		92.64 122	91.85 117	95.03 136	95.12 173	88.23 159	98.48 139	96.81 162	91.61 64	92.16 111	97.22 122	71.58 236	98.00 150	85.85 166	97.81 87	98.88 105
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
TAMVS		92.62 123	92.09 114	94.20 156	94.10 193	87.68 169	98.41 148	96.97 158	87.53 162	89.74 146	96.04 161	84.77 112	96.49 221	88.97 138	92.31 149	98.42 130

EPMVS		92.59 124	91.59 124	95.59 117	97.22 109	90.03 130	91.78 303	98.04 45	90.42 85	91.66 113	90.65 250	86.49 90	97.46 182	81.78 205	96.31 110	99.28 78

mvs_anonymous		92.50 125	91.65 122	95.06 134	96.60 131	89.64 137	97.06 215	96.44 180	86.64 179	84.14 192	93.93 187	82.49 140	96.17 249	91.47 109	96.08 116	99.35 70

BH-w/o		92.32 126	91.79 119	93.91 165	96.85 120	86.18 213	99.11 67	95.74 223	88.13 145	84.81 186	97.00 134	77.26 177	97.91 151	89.16 137	98.03 85	97.64 158

EPNet_dtu		92.28 127	92.15 111	92.70 187	97.29 107	84.84 239	98.64 118	97.82 60	92.91 40	93.02 103	97.02 133	85.48 104	95.70 265	72.25 291	94.89 129	97.55 163
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test_1112_low_res		92.27 128	90.97 137	96.18 97	95.53 159	91.10 102	98.47 141	94.66 270	88.28 142	86.83 177	93.50 200	87.00 81	98.65 128	84.69 173	89.74 186	98.80 109

LFMVS		92.23 129	90.84 141	96.42 90	98.24 78	91.08 104	98.24 165	96.22 194	83.39 236	94.74 81	98.31 89	61.12 295	98.85 116	94.45 78	92.82 142	99.32 73

thresconf0.02		92.14 130	90.99 133	95.58 118	96.84 121	91.39 90	98.31 157	98.20 31	83.57 231	88.08 161	97.34 114	91.05 19	97.40 185	75.80 256	89.74 186	97.94 152

tfpn_n400		92.14 130	90.99 133	95.58 118	96.84 121	91.39 90	98.31 157	98.20 31	83.57 231	88.08 161	97.34 114	91.05 19	97.40 185	75.80 256	89.74 186	97.94 152

tfpnconf		92.14 130	90.99 133	95.58 118	96.84 121	91.39 90	98.31 157	98.20 31	83.57 231	88.08 161	97.34 114	91.05 19	97.40 185	75.80 256	89.74 186	97.94 152

tfpnview11		92.14 130	90.99 133	95.58 118	96.84 121	91.39 90	98.31 157	98.20 31	83.57 231	88.08 161	97.34 114	91.05 19	97.40 185	75.80 256	89.74 186	97.94 152

IB-MVS	89.43 6	92.12 134	90.83 143	95.98 105	95.40 163	90.78 111	99.81 5	98.06 43	91.23 74	85.63 182	93.66 195	90.63 30	98.78 118	91.22 110	71.85 293	98.36 138
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
diffmvs		92.07 135	90.77 145	95.97 106	96.41 136	91.32 95	96.46 234	95.98 203	81.73 260	94.33 87	93.36 201	78.72 168	98.20 139	84.28 176	95.66 123	98.41 131

F-COLMAP		92.07 135	91.75 121	93.02 180	98.16 82	82.89 259	98.79 102	95.97 205	86.54 181	87.92 165	97.80 99	78.69 169	99.65 67	85.97 161	95.93 119	96.53 188

PatchmatchNet		92.05 137	91.04 132	95.06 134	96.17 143	89.04 146	91.26 307	97.26 130	89.56 104	90.64 131	90.56 256	88.35 56	97.11 196	79.53 222	96.07 117	99.03 91
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
UGNet		91.91 138	90.85 140	95.10 130	97.06 115	88.69 153	98.01 184	98.24 29	92.41 52	92.39 108	93.61 196	60.52 296	99.68 60	88.14 143	97.25 98	96.92 177
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
tpm2		91.77 139	91.09 131	93.82 168	94.83 183	85.56 232	92.51 296	97.16 140	84.00 217	93.83 95	90.66 249	87.54 67	97.17 194	87.73 147	91.55 163	98.72 116

Fast-Effi-MVS+		91.72 140	90.79 144	94.49 147	95.89 149	87.40 178	99.54 23	95.70 227	85.01 203	89.28 154	95.68 164	77.75 174	97.57 180	83.22 188	95.06 127	98.51 127

mvs-test1		91.57 141	92.20 109	89.70 245	95.15 171	74.34 306	99.51 25	95.40 250	91.92 59	91.02 125	97.25 119	74.27 203	98.08 146	89.45 128	95.83 120	96.67 178

HQP-MVS		91.50 142	91.23 130	92.29 192	93.95 197	86.39 205	99.16 56	96.37 182	93.92 22	87.57 167	96.67 144	73.34 216	97.77 162	93.82 85	86.29 199	92.72 202

PatchMatch-RL		91.47 143	90.54 149	94.26 154	98.20 79	86.36 207	96.94 217	97.14 141	87.75 155	88.98 155	95.75 163	71.80 234	99.40 94	80.92 211	97.39 97	97.02 175

BH-untuned		91.46 144	90.84 141	93.33 174	96.51 134	84.83 240	98.84 96	95.50 242	86.44 184	83.50 196	96.70 143	75.49 185	97.77 162	86.78 158	97.81 87	97.40 164

QAPM		91.41 145	89.49 157	97.17 45	95.66 157	93.42 55	98.60 124	97.51 107	80.92 268	81.39 234	97.41 113	72.89 223	99.87 35	82.33 196	98.68 76	98.21 144

HQP_MVS		91.26 146	90.95 138	92.16 194	93.84 204	86.07 218	99.02 74	96.30 187	93.38 35	86.99 173	96.52 150	72.92 221	97.75 167	93.46 90	86.17 202	92.67 204

PCF-MVS	89.78 5	91.26 146	89.63 156	96.16 100	95.44 161	91.58 87	95.29 271	96.10 200	85.07 201	82.75 211	97.45 111	78.28 171	99.78 54	80.60 218	95.65 124	97.12 169
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
BH-RMVSNet		91.25 148	89.99 154	95.03 136	96.75 128	88.55 155	98.65 116	94.95 263	87.74 156	87.74 166	97.80 99	68.27 256	98.14 141	80.53 219	97.49 95	98.41 131

VDD-MVS		91.24 149	90.18 152	94.45 149	97.08 114	85.84 227	98.40 151	96.10 200	86.99 171	93.36 98	98.16 94	54.27 313	99.20 103	96.59 40	90.63 174	98.31 141

CLD-MVS		91.06 150	90.71 146	92.10 195	94.05 196	86.10 216	99.55 22	96.29 190	94.16 20	84.70 187	97.17 126	69.62 246	97.82 158	94.74 73	86.08 204	92.39 207
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
tpmp4_e23		91.05 151	90.07 153	93.97 164	95.77 153	85.30 234	92.64 294	97.09 148	84.42 212	91.53 117	90.31 261	87.38 70	97.82 158	80.86 213	90.62 175	98.79 110

ab-mvs		91.05 151	89.17 162	96.69 75	95.96 148	91.72 82	92.62 295	97.23 134	85.61 190	89.74 146	93.89 189	68.55 254	99.42 92	91.09 111	87.84 194	98.92 103

XVG-OURS-SEG-HR		90.95 153	90.66 148	91.83 199	95.18 170	81.14 276	95.92 256	95.92 212	88.40 137	90.33 138	97.85 97	70.66 241	99.38 95	92.83 100	88.83 191	94.98 193

cascas		90.93 154	89.33 161	95.76 113	95.69 155	93.03 63	98.99 79	96.59 169	80.49 270	86.79 178	94.45 179	65.23 278	98.60 133	93.52 89	92.18 153	95.66 192

XVG-OURS		90.83 155	90.49 150	91.86 198	95.23 165	81.25 274	95.79 264	95.92 212	88.96 119	90.02 142	98.03 96	71.60 235	99.35 99	91.06 112	87.78 195	94.98 193

TR-MVS		90.77 156	89.44 158	94.76 140	96.31 138	88.02 164	97.92 186	95.96 207	85.52 191	88.22 160	97.23 121	66.80 268	98.09 143	84.58 174	92.38 147	98.17 146

OpenMVS	85.28 14	90.75 157	88.84 168	96.48 86	93.58 210	93.51 53	98.80 99	97.41 122	82.59 248	78.62 257	97.49 110	68.00 259	99.82 48	84.52 175	98.55 80	96.11 190

FIs		90.70 158	89.87 155	93.18 176	92.29 227	91.12 100	98.17 175	98.25 28	89.11 115	83.44 197	94.82 175	82.26 145	96.17 249	87.76 146	82.76 227	92.25 212

X-MVStestdata		90.69 159	88.66 172	96.77 67	99.62 15	90.66 116	99.43 33	97.58 95	92.41 52	96.86 45	29.59 350	87.37 71	99.87 35	95.65 55	99.43 46	99.78 28

TAPA-MVS	87.50 9	90.35 160	89.05 164	94.25 155	98.48 75	85.17 237	98.42 146	96.58 172	82.44 253	87.24 172	98.53 78	82.77 137	98.84 117	59.09 321	97.88 86	98.72 116
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CVMVSNet		90.30 161	90.91 139	88.46 268	94.32 190	73.58 310	97.61 198	97.59 93	90.16 94	88.43 159	97.10 129	76.83 179	92.86 299	82.64 194	93.54 138	98.93 102

nrg030		90.23 162	88.87 167	94.32 153	91.53 240	93.54 52	98.79 102	95.89 218	88.12 146	84.55 189	94.61 178	78.80 167	96.88 204	92.35 104	75.21 258	92.53 206

FC-MVSNet-test		90.22 163	89.40 159	92.67 189	91.78 237	89.86 133	97.89 187	98.22 30	88.81 125	82.96 206	94.66 177	81.90 148	95.96 257	85.89 164	82.52 230	92.20 217

LS3D		90.19 164	88.72 170	94.59 145	98.97 58	86.33 208	96.90 219	96.60 168	74.96 302	84.06 194	98.74 65	75.78 183	99.83 45	74.93 265	97.57 92	97.62 161

dp		90.16 165	88.83 169	94.14 157	96.38 137	86.42 203	91.57 304	97.06 151	84.76 207	88.81 156	90.19 269	84.29 115	97.43 184	75.05 264	91.35 167	98.56 125

Patchmatch-test1		90.10 166	88.61 173	94.57 146	94.95 180	88.83 148	96.26 241	97.21 136	90.06 98	90.03 141	90.68 246	66.61 270	95.83 262	77.31 240	94.36 132	99.05 90

GA-MVS		90.10 166	88.69 171	94.33 152	92.44 226	87.97 165	99.08 68	96.26 192	89.65 100	86.92 175	93.11 208	68.09 257	96.96 201	82.54 195	90.15 179	98.05 147

VDDNet		90.08 168	88.54 178	94.69 143	94.41 189	87.68 169	98.21 170	96.40 181	76.21 298	93.33 99	97.75 102	54.93 311	98.77 119	94.71 74	90.96 168	97.61 162

gg-mvs-nofinetune		90.00 169	87.71 185	96.89 64	96.15 144	94.69 31	85.15 323	97.74 72	68.32 322	92.97 104	60.16 336	96.10 3	96.84 205	93.89 81	98.87 67	99.14 86

Effi-MVS+-dtu		89.97 170	90.68 147	87.81 281	95.15 171	71.98 315	97.87 190	95.40 250	91.92 59	87.57 167	91.44 228	74.27 203	96.84 205	89.45 128	93.10 140	94.60 195

EI-MVSNet		89.87 171	89.38 160	91.36 214	94.32 190	85.87 224	97.61 198	96.59 169	85.10 199	85.51 183	97.10 129	81.30 154	96.56 213	83.85 186	83.03 225	91.64 229

OPM-MVS		89.76 172	89.15 163	91.57 209	90.53 251	85.58 231	98.11 177	95.93 211	92.88 42	86.05 179	96.47 153	67.06 267	97.87 155	89.29 135	86.08 204	91.26 242

tpm		89.67 173	88.95 166	91.82 200	92.54 225	81.43 269	92.95 292	95.92 212	87.81 153	90.50 133	89.44 276	84.99 107	95.65 266	83.67 187	82.71 228	98.38 135

UniMVSNet_NR-MVSNet		89.60 174	88.55 177	92.75 186	92.17 230	90.07 127	98.74 104	98.15 40	88.37 138	83.21 199	93.98 186	82.86 136	95.93 259	86.95 154	72.47 285	92.25 212

PS-MVSNAJss		89.54 175	89.05 164	91.00 219	88.77 288	84.36 244	97.39 201	95.97 205	88.47 130	81.88 229	93.80 191	82.48 141	96.50 220	89.34 132	83.34 223	92.15 218

UniMVSNet (Re)		89.50 176	88.32 180	93.03 179	92.21 229	90.96 107	98.90 90	98.39 24	89.13 114	83.22 198	92.03 218	81.69 149	96.34 238	86.79 157	72.53 284	91.81 226

DI_MVS_plusplus_test		89.41 177	87.24 192	95.92 109	89.06 285	90.75 114	98.18 172	96.63 166	89.29 109	70.54 295	90.31 261	63.50 285	98.40 134	92.25 105	95.44 125	98.60 121

test_normal		89.37 178	87.18 194	95.93 108	88.94 287	90.83 110	98.24 165	96.62 167	89.31 107	70.38 297	90.20 268	63.50 285	98.37 135	92.06 107	95.41 126	98.59 124

tpmvs		89.16 179	87.76 183	93.35 173	97.19 110	84.75 241	90.58 313	97.36 127	81.99 256	84.56 188	89.31 279	83.98 117	98.17 140	74.85 267	90.00 184	97.12 169

VPA-MVSNet		89.10 180	87.66 186	93.45 172	92.56 224	91.02 105	97.97 185	98.32 26	86.92 175	86.03 180	92.01 220	68.84 253	97.10 198	90.92 114	75.34 257	92.23 214

ADS-MVSNet		88.99 181	87.30 190	94.07 159	96.21 141	87.56 172	87.15 318	96.78 164	83.01 242	89.91 143	87.27 294	78.87 165	97.01 200	74.20 272	92.27 150	97.64 158

test0.0.03 1		88.96 182	88.61 173	90.03 239	91.09 245	84.43 243	98.97 80	97.02 155	90.21 89	80.29 240	96.31 158	84.89 109	91.93 319	72.98 287	85.70 207	93.73 197

tpm cat1		88.89 183	87.27 191	93.76 169	95.79 151	85.32 233	90.76 311	97.09 148	76.14 299	85.72 181	88.59 284	82.92 135	98.04 147	76.96 244	91.43 164	97.90 156

LPG-MVS_test		88.86 184	88.47 179	90.06 237	93.35 217	80.95 278	98.22 167	95.94 209	87.73 157	83.17 201	96.11 159	66.28 272	97.77 162	90.19 121	85.19 208	91.46 236

Fast-Effi-MVS+-dtu		88.84 185	88.59 176	89.58 248	93.44 215	78.18 295	98.65 116	94.62 271	88.46 132	84.12 193	95.37 170	68.91 251	96.52 219	82.06 199	91.70 161	94.06 196

DU-MVS		88.83 186	87.51 187	92.79 184	91.46 241	90.07 127	98.71 105	97.62 90	88.87 124	83.21 199	93.68 193	74.63 191	95.93 259	86.95 154	72.47 285	92.36 208

CR-MVSNet		88.83 186	87.38 189	93.16 177	93.47 212	86.24 210	84.97 325	94.20 280	88.92 123	90.76 129	86.88 298	84.43 113	94.82 285	70.64 296	92.17 154	98.41 131

FMVSNet3		88.81 188	87.08 195	93.99 163	96.52 133	94.59 36	98.08 180	96.20 195	85.85 187	82.12 223	91.60 227	74.05 208	95.40 273	79.04 227	80.24 236	91.99 224

ACMM	86.95 13	88.77 189	88.22 182	90.43 230	93.61 209	81.34 272	98.50 136	95.92 212	87.88 152	83.85 195	95.20 171	67.20 265	97.89 153	86.90 156	84.90 211	92.06 222
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
DP-MVS		88.75 190	86.56 198	95.34 126	98.92 62	87.45 175	97.64 197	93.52 289	70.55 313	81.49 232	97.25 119	74.43 200	99.88 32	71.14 295	94.09 134	98.67 119

ACMP	87.39 10	88.71 191	88.24 181	90.12 236	93.91 202	81.06 277	98.50 136	95.67 229	89.43 106	80.37 239	95.55 165	65.67 275	97.83 157	90.55 119	84.51 213	91.47 235
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
LCM-MVSNet-Re		88.59 192	88.61 173	88.51 267	95.53 159	72.68 313	96.85 220	88.43 337	88.45 133	73.14 286	90.63 251	75.82 182	94.38 289	92.95 97	95.71 122	98.48 129

WR-MVS		88.54 193	87.22 193	92.52 190	91.93 235	89.50 140	98.56 128	97.84 58	86.99 171	81.87 230	93.81 190	74.25 205	95.92 261	85.29 167	74.43 265	92.12 219

IterMVS-LS		88.34 194	87.44 188	91.04 218	94.10 193	85.85 226	98.10 178	95.48 244	85.12 198	82.03 227	91.21 230	81.35 153	95.63 267	83.86 185	75.73 255	91.63 230
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
VPNet		88.30 195	86.57 197	93.49 171	91.95 233	91.35 94	98.18 172	97.20 137	88.61 128	84.52 190	94.89 173	62.21 290	96.76 209	89.34 132	72.26 289	92.36 208

MSDG		88.29 196	86.37 200	94.04 161	96.90 119	86.15 215	96.52 232	94.36 277	77.89 295	79.22 253	96.95 137	69.72 245	99.59 75	73.20 284	92.58 146	96.37 189

test_djsdf		88.26 197	87.73 184	89.84 242	88.05 297	82.21 264	97.77 193	96.17 197	86.84 176	82.41 219	91.95 223	72.07 230	95.99 255	89.83 123	84.50 214	91.32 240

TranMVSNet+NR-MVSNet		87.75 198	86.31 201	92.07 196	90.81 248	88.56 154	98.33 154	97.18 138	87.76 154	81.87 230	93.90 188	72.45 225	95.43 271	83.13 190	71.30 297	92.23 214

XXY-MVS		87.75 198	86.02 204	92.95 182	90.46 252	89.70 136	97.71 195	95.90 216	84.02 216	80.95 235	94.05 180	67.51 263	97.10 198	85.16 168	78.41 245	92.04 223

NR-MVSNet		87.74 200	86.00 205	92.96 181	91.46 241	90.68 115	96.65 229	97.42 121	88.02 147	73.42 284	93.68 193	77.31 176	95.83 262	84.26 177	71.82 294	92.36 208

ADS-MVSNet2		87.62 201	86.88 196	89.86 241	96.21 141	79.14 286	87.15 318	92.99 295	83.01 242	89.91 143	87.27 294	78.87 165	92.80 303	74.20 272	92.27 150	97.64 158

pmmvs4		87.58 202	86.17 203	91.80 201	89.58 277	88.92 147	97.25 207	95.28 256	82.54 250	80.49 238	93.17 207	75.62 184	96.05 254	82.75 193	78.90 243	90.42 270

jajsoiax		87.35 203	86.51 199	89.87 240	87.75 302	81.74 267	97.03 216	95.98 203	88.47 130	80.15 242	93.80 191	61.47 292	96.36 232	89.44 130	84.47 215	91.50 234

PVSNet_0	83.28 16	87.31 204	85.16 222	93.74 170	94.78 184	84.59 242	98.91 85	98.69 21	89.81 99	78.59 259	93.23 205	61.95 291	99.34 100	94.75 72	55.72 332	97.30 167

v1neww		87.29 205	85.88 207	91.50 210	90.07 253	86.87 189	98.45 142	95.66 232	83.84 223	83.07 204	90.99 233	74.58 195	96.56 213	81.96 202	74.33 267	91.07 249

v7new		87.29 205	85.88 207	91.50 210	90.07 253	86.87 189	98.45 142	95.66 232	83.84 223	83.07 204	90.99 233	74.58 195	96.56 213	81.96 202	74.33 267	91.07 249

v6		87.27 207	85.86 209	91.50 210	89.97 260	86.84 193	98.45 142	95.67 229	83.85 222	83.11 203	90.97 235	74.46 198	96.58 211	81.97 201	74.34 266	91.09 246

v2v482		87.27 207	85.76 211	91.78 205	89.59 276	87.58 171	98.56 128	95.54 239	84.53 209	82.51 216	91.78 224	73.11 220	96.47 224	82.07 198	74.14 272	91.30 241

v1141		87.23 209	85.75 213	91.67 206	89.88 265	87.43 177	98.52 132	95.62 235	83.91 219	82.83 210	90.69 244	74.70 188	96.49 221	81.53 208	74.08 273	91.07 249

divwei89l23v2f112		87.23 209	85.75 213	91.66 207	89.88 265	87.40 178	98.53 131	95.62 235	83.91 219	82.84 209	90.67 247	74.75 187	96.49 221	81.55 206	74.05 275	91.08 247

v1		87.23 209	85.76 211	91.66 207	89.88 265	87.37 180	98.54 130	95.64 234	83.91 219	82.88 208	90.70 242	74.64 189	96.53 217	81.54 207	74.08 273	91.08 247

mvs_tets		87.09 212	86.22 202	89.71 244	87.87 298	81.39 271	96.73 226	95.90 216	88.19 144	79.99 243	93.61 196	59.96 298	96.31 242	89.40 131	84.34 216	91.43 238

V42		87.00 213	85.68 216	90.98 220	89.91 261	86.08 217	98.32 156	95.61 237	83.67 229	82.72 212	90.67 247	74.00 209	96.53 217	81.94 204	74.28 270	90.32 272

v7		86.91 214	85.45 219	91.29 215	90.06 255	86.73 195	98.26 163	95.49 243	83.08 241	82.95 207	90.96 236	73.37 214	96.42 227	79.90 221	74.97 259	90.71 264

FMVSNet2		86.90 215	84.79 230	93.24 175	95.11 174	92.54 74	97.67 196	95.86 220	82.94 244	80.55 237	91.17 231	62.89 287	95.29 275	77.23 241	79.71 242	91.90 225

v1144		86.83 216	85.31 221	91.40 213	89.75 270	87.21 186	98.31 157	95.45 247	83.22 238	82.70 213	90.78 239	73.36 215	96.36 232	79.49 223	74.69 263	90.63 267

MS-PatchMatch		86.75 217	85.92 206	89.22 254	91.97 232	82.47 263	96.91 218	96.14 199	83.74 226	77.73 265	93.53 199	58.19 300	97.37 191	76.75 248	98.35 82	87.84 296

anonymousdsp		86.69 218	85.75 213	89.53 249	86.46 311	82.94 256	96.39 236	95.71 226	83.97 218	79.63 248	90.70 242	68.85 252	95.94 258	86.01 160	84.02 217	89.72 284

GBi-Net		86.67 219	84.96 224	91.80 201	95.11 174	88.81 149	96.77 222	95.25 257	82.94 244	82.12 223	90.25 263	62.89 287	94.97 280	79.04 227	80.24 236	91.62 231

test1		86.67 219	84.96 224	91.80 201	95.11 174	88.81 149	96.77 222	95.25 257	82.94 244	82.12 223	90.25 263	62.89 287	94.97 280	79.04 227	80.24 236	91.62 231

MVP-Stereo		86.61 221	85.83 210	88.93 260	88.70 290	83.85 249	96.07 252	94.41 276	82.15 255	75.64 276	91.96 222	67.65 262	96.45 226	77.20 243	98.72 74	86.51 309
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CP-MVSNet		86.54 222	85.45 219	89.79 243	91.02 247	82.78 262	97.38 203	97.56 100	85.37 195	79.53 250	93.03 209	71.86 233	95.25 276	79.92 220	73.43 279	91.34 239

WR-MVS_H		86.53 223	85.49 218	89.66 247	91.04 246	83.31 253	97.53 200	98.20 31	84.95 204	79.64 247	90.90 238	78.01 173	95.33 274	76.29 252	72.81 281	90.35 271

v144192		86.40 224	84.89 227	90.91 221	89.48 281	85.59 230	98.21 170	95.43 249	82.45 252	82.62 214	90.58 255	72.79 224	96.36 232	78.45 233	74.04 276	90.79 259

v148		86.38 225	85.06 223	90.37 232	89.47 282	84.10 246	98.52 132	95.48 244	83.80 225	80.93 236	90.22 266	74.60 193	96.31 242	80.92 211	71.55 295	90.69 265

v1192		86.32 226	84.71 231	91.17 216	89.53 279	86.40 204	98.13 176	95.44 248	82.52 251	82.42 218	90.62 252	71.58 236	96.33 239	77.23 241	74.88 260	90.79 259

Patchmatch-test		86.25 227	84.06 239	92.82 183	94.42 188	82.88 260	82.88 333	94.23 279	71.58 309	79.39 251	90.62 252	89.00 46	96.42 227	63.03 311	91.37 166	99.16 85

v8		86.11 228	84.45 234	91.10 217	89.99 259	86.85 191	97.24 208	95.36 252	81.99 256	79.89 245	89.86 272	74.53 197	96.39 230	78.83 231	72.32 287	90.05 278

v1921920		86.02 229	84.44 235	90.77 223	89.32 283	85.20 235	98.10 178	95.35 254	82.19 254	82.25 221	90.71 241	70.73 239	96.30 245	76.85 247	74.49 264	90.80 258

JIA-IIPM		85.97 230	84.85 228	89.33 253	93.23 219	73.68 309	85.05 324	97.13 143	69.62 318	91.56 116	68.03 334	88.03 62	96.96 201	77.89 238	93.12 139	97.34 166

pmmvs5		85.87 231	84.40 237	90.30 233	88.53 292	84.23 245	98.60 124	93.71 286	81.53 262	80.29 240	92.02 219	64.51 280	95.52 269	82.04 200	78.34 246	91.15 244

XVG-ACMP-BASELINE		85.86 232	84.95 226	88.57 265	89.90 263	77.12 300	94.30 279	95.60 238	87.40 164	82.12 223	92.99 211	53.42 316	97.66 171	85.02 170	83.83 218	90.92 255

Baseline_NR-MVSNet		85.83 233	84.82 229	88.87 261	88.73 289	83.34 252	98.63 119	91.66 318	80.41 271	82.44 217	91.35 229	74.63 191	95.42 272	84.13 179	71.39 296	87.84 296

PS-CasMVS		85.81 234	84.58 233	89.49 251	90.77 249	82.11 265	97.20 211	97.36 127	84.83 206	79.12 254	92.84 212	67.42 264	95.16 278	78.39 234	73.25 280	91.21 243

IterMVS		85.81 234	84.67 232	89.22 254	93.51 211	83.67 250	96.32 239	94.80 265	85.09 200	78.69 255	90.17 270	66.57 271	93.17 295	79.48 224	77.42 251	90.81 257
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v1240		85.77 236	84.11 238	90.73 224	89.26 284	85.15 238	97.88 189	95.23 261	81.89 259	82.16 222	90.55 257	69.60 247	96.31 242	75.59 262	74.87 261	90.72 263

v10		85.73 237	84.01 240	90.87 222	90.03 256	86.73 195	97.20 211	95.22 262	81.25 264	79.85 246	89.75 273	73.30 219	96.28 246	76.87 245	72.64 283	89.61 285

Test4		85.71 238	82.59 254	95.07 133	84.45 315	89.84 134	97.20 211	95.73 224	89.19 111	64.59 320	87.58 290	40.59 334	96.77 208	88.95 139	95.01 128	98.60 121

PatchT		85.44 239	83.19 243	92.22 193	93.13 221	83.00 255	83.80 331	96.37 182	70.62 312	90.55 132	79.63 325	84.81 111	94.87 283	58.18 323	91.59 162	98.79 110

RPSCF		85.33 240	85.55 217	84.67 301	94.63 187	62.28 327	93.73 286	93.76 284	74.38 305	85.23 185	97.06 132	64.09 281	98.31 136	80.98 209	86.08 204	93.41 201

PEN-MVS		85.21 241	83.93 241	89.07 258	89.89 264	81.31 273	97.09 214	97.24 133	84.45 211	78.66 256	92.68 214	68.44 255	94.87 283	75.98 254	70.92 298	91.04 252

AllTest		84.97 242	83.12 244	90.52 228	96.82 125	78.84 290	95.89 257	92.17 311	77.96 292	75.94 273	95.50 166	55.48 308	99.18 104	71.15 293	87.14 196	93.55 199

USDC		84.74 243	82.93 245	90.16 235	91.73 238	83.54 251	95.00 273	93.30 291	88.77 126	73.19 285	93.30 203	53.62 315	97.65 172	75.88 255	81.54 234	89.30 287

pm-mvs1		84.68 244	82.78 250	90.40 231	89.58 277	85.18 236	97.31 204	94.73 267	81.93 258	76.05 272	92.01 220	65.48 277	96.11 252	78.75 232	69.14 301	89.91 281

RPMNet		84.62 245	81.78 258	93.16 177	93.47 212	86.24 210	84.97 325	96.28 191	64.85 328	90.76 129	78.80 327	80.95 155	94.82 285	53.76 326	92.17 154	98.41 131

ACMH	83.09 17	84.60 246	82.61 253	90.57 226	93.18 220	82.94 256	96.27 240	94.92 264	81.01 266	72.61 292	93.61 196	56.54 304	97.79 160	74.31 270	81.07 235	90.99 253
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LTVRE_ROB	81.71 19	84.59 247	82.72 252	90.18 234	92.89 223	83.18 254	93.15 291	94.74 266	78.99 279	75.14 278	92.69 213	65.64 276	97.63 173	69.46 297	81.82 233	89.74 283
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
COLMAP_ROB	82.69 18	84.54 248	82.82 248	89.70 245	96.72 129	78.85 289	95.89 257	92.83 304	71.55 310	77.54 268	95.89 162	59.40 299	99.14 109	67.26 302	88.26 192	91.11 245
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
MIMVSNet		84.48 249	81.83 257	92.42 191	91.73 238	87.36 181	85.52 321	94.42 275	81.40 263	81.91 228	87.58 290	51.92 318	92.81 302	73.84 277	88.15 193	97.08 173

v7n		84.42 250	82.75 251	89.43 252	88.15 295	81.86 266	96.75 225	95.67 229	80.53 269	78.38 263	89.43 277	69.89 243	96.35 237	73.83 278	72.13 291	90.07 277

ACMH+	83.78 15	84.21 251	82.56 255	89.15 256	93.73 208	79.16 285	96.43 235	94.28 278	81.09 265	74.00 283	94.03 183	54.58 312	97.67 170	76.10 253	78.81 244	90.63 267

V4		84.20 252	82.92 246	88.02 276	87.59 305	79.91 283	96.21 248	95.36 252	79.88 273	78.51 260	89.00 281	69.52 248	96.32 240	77.96 236	72.29 288	87.83 298

v52		84.19 253	82.92 246	88.01 277	87.64 304	79.92 282	96.23 243	95.32 255	79.87 274	78.51 260	89.05 280	69.50 249	96.32 240	77.95 237	72.24 290	87.79 299

EU-MVSNet		84.19 253	84.42 236	83.52 304	88.64 291	67.37 324	96.04 253	95.76 222	85.29 196	78.44 262	93.18 206	70.67 240	91.48 322	75.79 260	75.98 253	91.70 228

DTE-MVSNet		84.14 255	82.80 249	88.14 275	88.95 286	79.87 284	96.81 221	96.24 193	83.50 235	77.60 267	92.52 216	67.89 261	94.24 290	72.64 290	69.05 302	90.32 272

OurMVSNet-221017-0		84.13 256	83.59 242	85.77 295	87.81 299	70.24 319	94.89 274	93.65 288	86.08 186	76.53 270	93.28 204	61.41 293	96.14 251	80.95 210	77.69 250	90.93 254

FMVSNet1		83.94 257	81.32 264	91.80 201	91.94 234	88.81 149	96.77 222	95.25 257	77.98 290	78.25 264	90.25 263	50.37 322	94.97 280	73.27 283	77.81 249	91.62 231

v748		83.84 258	82.31 256	88.41 270	87.65 303	79.10 287	96.66 228	95.51 241	80.09 272	77.65 266	88.53 285	69.81 244	96.23 247	75.67 261	69.25 300	89.91 281

tfpnnormal		83.65 259	81.35 263	90.56 227	91.37 243	88.06 162	97.29 205	97.87 56	78.51 284	76.20 271	90.91 237	64.78 279	96.47 224	61.71 314	73.50 277	87.13 306

Patchmtry		83.61 260	81.64 260	89.50 250	93.36 216	82.84 261	84.10 328	94.20 280	69.47 319	79.57 249	86.88 298	84.43 113	94.78 287	68.48 300	74.30 269	90.88 256

SixPastTwentyTwo		82.63 261	81.58 261	85.79 294	88.12 296	71.01 318	95.17 272	92.54 307	84.33 213	72.93 289	92.08 217	60.41 297	95.61 268	74.47 269	74.15 271	90.75 262

testgi		82.29 262	81.00 266	86.17 292	87.24 307	74.84 305	97.39 201	91.62 319	88.63 127	75.85 275	95.42 169	46.07 327	91.55 321	66.87 305	79.94 239	92.12 219

FMVSNet5		82.29 262	80.54 267	87.52 283	93.79 207	84.01 247	93.73 286	92.47 308	76.92 297	74.27 281	86.15 302	63.69 284	89.24 325	69.07 298	74.79 262	89.29 288

v18		82.00 264	79.76 272	88.72 262	90.03 256	86.81 194	96.17 250	93.12 292	78.70 281	68.39 301	82.10 307	74.64 189	93.00 296	74.21 271	60.45 320	86.35 310

TransMVSNet (Re)		81.97 265	79.61 274	89.08 257	89.70 272	84.01 247	97.26 206	91.85 317	78.84 280	73.07 288	91.62 226	67.17 266	95.21 277	67.50 301	59.46 327	88.02 295

LF4IMVS		81.94 266	81.17 265	84.25 302	87.23 308	68.87 323	93.35 290	91.93 316	83.35 237	75.40 277	93.00 210	49.25 324	96.65 210	78.88 230	78.11 247	87.22 305

Patchmatch-RL test		81.90 267	80.13 268	87.23 286	80.71 324	70.12 321	84.07 329	88.19 338	83.16 240	70.57 294	82.18 306	87.18 77	92.59 311	82.28 197	62.78 313	98.98 95

v16		81.90 267	79.65 273	88.65 263	90.02 258	86.66 198	96.01 254	93.07 294	78.53 283	68.27 303	82.05 308	74.39 201	92.96 297	74.02 275	60.48 319	86.33 312

v17		81.87 269	79.61 274	88.64 264	89.91 261	86.64 199	96.01 254	93.08 293	78.54 282	68.27 303	81.96 309	74.44 199	92.95 298	74.03 274	60.22 322	86.34 311

v15		81.62 270	79.32 277	88.52 266	89.80 268	86.56 200	95.83 263	92.96 297	78.50 285	67.88 307	81.68 311	74.22 206	92.82 301	73.46 281	59.55 323	86.18 315

DSMNet-mixed		81.60 271	81.43 262	82.10 307	84.36 316	60.79 328	93.63 288	86.74 339	79.00 278	79.32 252	87.15 296	63.87 283	89.78 324	66.89 304	91.92 156	95.73 191

V14		81.55 272	79.26 278	88.42 269	89.80 268	86.33 208	95.72 266	92.96 297	78.35 286	67.82 308	81.70 310	74.13 207	92.78 305	73.32 282	59.50 325	86.16 317

V9		81.46 273	79.15 279	88.39 272	89.75 270	86.17 214	95.62 267	92.92 299	78.22 287	67.65 312	81.64 312	73.95 210	92.80 303	73.15 285	59.43 328	86.21 314

v11		81.38 274	79.03 281	88.41 270	89.68 273	86.43 202	95.74 265	92.82 306	78.03 289	67.74 309	81.45 315	73.33 218	92.69 309	72.23 292	60.27 321	86.11 319

v12		81.37 275	79.05 280	88.33 273	89.68 273	86.05 220	95.48 269	92.92 299	78.08 288	67.55 313	81.58 313	73.75 211	92.75 306	73.05 286	59.37 329	86.18 315

v13		81.30 276	78.99 282	88.25 274	89.61 275	85.87 224	95.39 270	92.90 301	77.93 294	67.45 316	81.52 314	73.66 212	92.75 306	72.91 288	59.53 324	86.14 318

K. test v3		81.04 277	79.77 271	84.83 299	87.41 306	70.23 320	95.60 268	93.93 283	83.70 228	67.51 314	89.35 278	55.76 306	93.58 293	76.67 249	68.03 305	90.67 266

test2356		80.96 278	81.77 259	78.52 315	81.02 323	62.33 326	98.22 167	94.49 272	79.38 277	74.56 279	90.34 260	70.65 242	85.10 333	60.83 315	86.42 198	88.14 293

testing_2		80.92 279	77.24 287	91.98 197	78.88 329	87.83 166	93.96 284	95.72 225	84.27 214	56.20 330	80.42 320	38.64 336	96.40 229	87.20 150	79.85 240	91.72 227

Anonymous20231206		80.76 280	79.42 276	84.79 300	84.78 314	72.98 311	96.53 231	92.97 296	79.56 276	74.33 280	88.83 282	61.27 294	92.15 316	60.59 317	75.92 254	89.24 289

testpf		80.59 281	80.13 268	81.97 309	94.25 192	71.65 316	60.37 343	95.46 246	70.99 311	76.97 269	87.74 288	73.58 213	91.67 320	76.86 246	84.97 210	82.60 330

CMPMVS	58.40 21	80.48 282	80.11 270	81.59 311	85.10 313	59.56 330	94.14 282	95.95 208	68.54 321	60.71 324	93.31 202	55.35 310	97.87 155	83.06 191	84.85 212	87.33 302
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
TinyColmap		80.42 283	77.94 283	87.85 280	92.09 231	78.58 292	93.74 285	89.94 331	74.99 301	69.77 298	91.78 224	46.09 326	97.58 176	65.17 309	77.89 248	87.38 301

EG-PatchMatch MVS		79.92 284	77.59 284	86.90 288	87.06 309	77.90 299	96.20 249	94.06 282	74.61 303	66.53 318	88.76 283	40.40 335	96.20 248	67.02 303	83.66 221	86.61 307

pmmvs6		79.90 285	77.31 286	87.67 282	84.17 317	78.13 296	95.86 261	93.68 287	67.94 323	72.67 291	89.62 275	50.98 321	95.75 264	74.80 268	66.04 308	89.14 290

MDA-MVSNet_test_wron		79.65 286	77.05 288	87.45 284	87.79 301	80.13 280	96.25 242	94.44 273	73.87 306	51.80 333	87.47 293	68.04 258	92.12 317	66.02 306	67.79 306	90.09 275

YYNet1		79.64 287	77.04 289	87.43 285	87.80 300	79.98 281	96.23 243	94.44 273	73.83 307	51.83 332	87.53 292	67.96 260	92.07 318	66.00 307	67.75 307	90.23 274

MVS-HIRNet		79.01 288	75.13 295	90.66 225	93.82 206	81.69 268	85.16 322	93.75 285	54.54 334	74.17 282	59.15 338	57.46 302	96.58 211	63.74 310	94.38 131	93.72 198

UnsupCasMVSNet_eth		78.90 289	76.67 291	85.58 296	82.81 321	74.94 304	91.98 301	96.31 186	84.64 208	65.84 319	87.71 289	51.33 319	92.23 315	72.89 289	56.50 331	89.56 286

test_0402		78.81 290	76.33 292	86.26 291	91.18 244	78.44 294	95.88 259	91.34 322	68.55 320	70.51 296	89.91 271	52.65 317	94.99 279	47.14 331	79.78 241	85.34 323

pmmvs-eth3d		78.71 291	76.16 293	86.38 290	80.25 325	81.19 275	94.17 281	92.13 313	77.97 291	66.90 317	82.31 305	55.76 306	92.56 312	73.63 280	62.31 316	85.38 321

test20.03		78.51 292	77.48 285	81.62 310	83.07 320	71.03 317	96.11 251	92.83 304	81.66 261	69.31 299	89.68 274	57.53 301	87.29 329	58.65 322	68.47 303	86.53 308

TDRefinement		78.01 293	75.31 294	86.10 293	70.06 337	73.84 308	93.59 289	91.58 320	74.51 304	73.08 287	91.04 232	49.63 323	97.12 195	74.88 266	59.47 326	87.33 302

OpenMVS_ROB	73.86 20	77.99 294	75.06 296	86.77 289	83.81 319	77.94 298	96.38 237	91.53 321	67.54 324	68.38 302	87.13 297	43.94 328	96.08 253	55.03 325	81.83 232	86.29 313

MDA-MVSNet-bldmvs		77.82 295	74.75 297	87.03 287	88.33 293	78.52 293	96.34 238	92.85 303	75.57 300	48.87 335	87.89 287	57.32 303	92.49 313	60.79 316	64.80 311	90.08 276

LP		77.80 296	74.39 298	88.01 277	91.93 235	79.02 288	80.88 335	92.90 301	65.43 326	72.00 293	81.29 317	65.78 274	92.73 308	43.76 336	75.58 256	92.27 211

testus		77.11 297	76.95 290	77.58 316	80.02 326	58.93 332	97.78 191	90.48 327	79.68 275	72.84 290	90.61 254	37.72 337	86.57 332	60.28 319	83.18 224	87.23 304

new_pmnet		76.02 298	73.71 299	82.95 305	83.88 318	72.85 312	91.26 307	92.26 310	70.44 314	62.60 322	81.37 316	47.64 325	92.32 314	61.85 313	72.10 292	83.68 327

MIMVSNet1		75.92 299	73.30 300	83.81 303	81.29 322	75.57 303	92.26 299	92.05 314	73.09 308	67.48 315	86.18 301	40.87 333	87.64 328	55.78 324	70.68 299	88.21 292

PM-MVS		74.88 300	72.85 301	80.98 312	78.98 328	64.75 325	90.81 310	85.77 341	80.95 267	68.23 306	82.81 304	29.08 340	92.84 300	76.54 251	62.46 315	85.36 322

new-patchmatchnet		74.80 301	72.40 302	81.99 308	78.36 330	72.20 314	94.44 276	92.36 309	77.06 296	63.47 321	79.98 324	51.04 320	88.85 326	60.53 318	54.35 333	84.92 324

UnsupCasMVSNet_bld		73.85 302	70.14 304	84.99 298	79.44 327	75.73 302	88.53 316	95.24 260	70.12 317	61.94 323	74.81 330	41.41 332	93.62 292	68.65 299	51.13 338	85.62 320

pmmvs3		72.86 303	69.76 306	82.17 306	73.86 332	74.19 307	94.20 280	89.01 334	64.23 329	67.72 310	80.91 319	41.48 331	88.65 327	62.40 312	54.02 334	83.68 327

1111		72.28 304	71.36 303	75.02 319	73.04 333	57.38 334	92.30 297	90.22 329	62.27 330	59.46 325	80.36 321	76.23 180	87.07 330	44.29 334	64.08 312	80.59 331

test1235678		71.07 305	69.53 307	75.71 318	71.87 336	55.27 338	94.32 277	90.76 325	70.23 315	57.61 329	79.06 326	43.13 329	83.72 335	50.48 328	68.30 304	88.14 293

N_pmnet		70.19 306	69.87 305	71.12 321	88.24 294	30.63 352	95.85 262	28.70 354	70.18 316	68.73 300	86.55 300	64.04 282	93.81 291	53.12 327	73.46 278	88.94 291

Anonymous20231211		67.10 307	63.29 310	78.54 314	75.68 331	60.00 329	92.05 300	88.86 335	49.84 335	59.35 327	78.48 328	26.15 341	90.76 323	45.96 333	53.24 335	84.88 325

test12356		66.36 308	65.12 308	70.08 324	66.92 338	50.46 341	89.96 314	88.58 336	66.00 325	53.38 331	78.13 329	32.89 339	82.87 336	48.36 330	61.87 317	76.92 332

FPMVS		61.57 309	60.32 311	65.34 326	60.14 343	42.44 346	91.02 309	89.72 332	44.15 337	42.63 338	80.93 318	19.02 344	80.59 340	42.50 337	72.76 282	73.00 335

.test1245		61.50 310	64.44 309	52.65 334	73.04 333	57.38 334	92.30 297	90.22 329	62.27 330	59.46 325	80.36 321	76.23 180	87.07 330	44.29 334	1.80 349	13.50 347

testmv		60.41 311	57.98 312	67.69 325	58.16 346	47.14 343	89.09 315	86.74 339	61.52 333	44.30 337	68.44 332	20.98 343	79.92 341	40.94 338	51.67 336	76.01 333

LCM-MVSNet		60.07 312	56.37 313	71.18 320	54.81 347	48.67 342	82.17 334	89.48 333	37.95 338	49.13 334	69.12 331	13.75 351	81.76 337	59.28 320	51.63 337	83.10 329

PMMVS2		58.97 313	55.07 314	70.69 323	62.72 339	55.37 337	85.97 320	80.52 345	49.48 336	45.94 336	68.31 333	15.73 349	80.78 339	49.79 329	37.12 339	75.91 334

no-one		56.69 314	51.89 317	71.08 322	59.35 345	58.65 333	83.78 332	84.81 344	61.73 332	36.46 341	56.52 340	18.15 347	84.78 334	47.03 332	19.19 343	69.81 337

Gipuma		54.77 315	52.22 316	62.40 328	86.50 310	59.37 331	50.20 344	90.35 328	36.52 340	41.20 339	49.49 342	18.33 346	81.29 338	32.10 342	65.34 309	46.54 343
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
tmp_tt		53.66 316	52.86 315	56.05 331	32.75 352	41.97 348	73.42 339	76.12 348	21.91 346	39.68 340	96.39 156	42.59 330	65.10 346	78.00 235	14.92 347	61.08 340

ANet_high		50.71 317	46.17 318	64.33 327	44.27 350	52.30 339	76.13 338	78.73 346	64.95 327	27.37 344	55.23 341	14.61 350	67.74 345	36.01 341	18.23 345	72.95 336

PNet_i23d		48.05 318	44.98 319	57.28 330	60.15 341	42.39 347	80.85 336	73.14 350	36.78 339	27.46 343	56.66 339	6.38 352	68.34 344	36.65 340	26.72 341	61.10 339

PMVS	41.42 23	45.67 319	42.50 320	55.17 332	34.28 351	32.37 350	66.24 341	78.71 347	30.72 342	22.04 347	59.59 337	4.59 353	77.85 342	27.49 343	58.84 330	55.29 341
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
wuykxyi23d		43.53 320	37.95 323	60.27 329	45.36 349	44.79 344	68.27 340	74.26 349	33.48 341	18.21 349	40.16 349	3.64 354	71.01 343	38.85 339	19.31 342	65.02 338

MVE	44.00 22	41.70 321	37.64 324	53.90 333	49.46 348	43.37 345	65.09 342	66.66 351	26.19 345	25.77 346	48.53 343	3.58 356	63.35 347	26.15 344	27.28 340	54.97 342
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN		41.02 322	40.93 321	41.29 335	61.97 340	33.83 349	84.00 330	65.17 352	27.17 343	27.56 342	46.72 344	17.63 348	60.41 348	19.32 345	18.82 344	29.61 344

EMVS		39.96 323	39.88 322	40.18 336	59.57 344	32.12 351	84.79 327	64.57 353	26.27 344	26.14 345	44.18 347	18.73 345	59.29 349	17.03 346	17.67 346	29.12 345

pcd1.5k->3k		35.91 324	37.64 324	30.74 337	89.49 280	0.00 356	0.00 346	96.36 185	0.00 350	0.00 352	0.00 352	69.17 250	0.00 353	0.00 350	83.71 220	92.21 216

cdsmvs_eth3d_5k		22.52 325	30.03 326	0.00 341	0.00 355	0.00 356	0.00 346	97.17 139	0.00 350	0.00 352	98.77 62	74.35 202	0.00 353	0.00 350	0.00 352	0.00 350

testmvs		18.81 326	23.05 327	6.10 340	4.48 353	2.29 355	97.78 191	3.00 356	3.27 348	18.60 348	62.71 335	1.53 358	2.49 352	14.26 348	1.80 349	13.50 347

wuyk23d		16.71 327	16.73 329	16.65 338	60.15 341	25.22 353	41.24 345	5.17 355	6.56 347	5.48 351	3.61 351	3.64 354	22.72 350	15.20 347	9.52 348	1.99 349

test123		16.58 328	19.47 328	7.91 339	3.59 354	5.37 354	94.32 277	1.39 357	2.49 349	13.98 350	44.60 346	2.91 357	2.65 351	11.35 349	0.57 351	15.70 346

ab-mvs-re		8.21 329	10.94 330	0.00 341	0.00 355	0.00 356	0.00 346	0.00 358	0.00 350	0.00 352	98.50 81	0.00 359	0.00 353	0.00 350	0.00 352	0.00 350

pcd_1.5k_mvsjas		6.87 330	9.16 331	0.00 341	0.00 355	0.00 356	0.00 346	0.00 358	0.00 350	0.00 352	0.00 352	82.48 141	0.00 353	0.00 350	0.00 352	0.00 350

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

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

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

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

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

ESAPD_part2					99.54 27	95.42 14				98.13 16

ESAPD_part1								97.69 77				93.96 6			99.83 12	99.90 9

ESAPD								97.71 75

sam_mvs1												88.39 55

sam_mvs												87.08 78

semantic-postprocess				89.00 259	93.46 214	82.90 258		94.70 268	85.02 202	78.62 257	90.35 259	66.63 269	93.33 294	79.38 226	77.36 252	90.76 261

ambc				79.60 313	72.76 335	56.61 336	76.20 337	92.01 315		68.25 305	80.23 323	23.34 342	94.73 288	73.78 279	60.81 318	87.48 300

MTGPA								97.45 115

test_post1							90.74 312				41.37 348	85.38 106	96.36 232	83.16 189

test_post											46.00 345	87.37 71	97.11 196

patchmatchnet-post											84.86 303	88.73 49	96.81 207

GG-mvs-BLEND				96.98 55	96.53 132	94.81 27	87.20 317	97.74 72		93.91 93	96.40 154	96.56 2	96.94 203	95.08 66	98.95 66	99.20 84

MTMP								91.09 323

gm-plane-assit					94.69 186	88.14 160			88.22 143		97.20 123		98.29 137	90.79 117

test9_res														98.60 9	99.87 5	99.90 9

TEST9					99.57 23	93.17 57	99.38 38	97.66 80	89.57 103	98.39 11	99.18 18	90.88 26	99.66 63

test_8					99.55 26	93.07 61	99.37 41	97.64 85	90.18 91	98.36 13	99.19 16	90.94 24	99.64 69

agg_prior2														97.84 25	99.87 5	99.91 8

agg_prior					99.54 27	92.66 69		97.64 85		97.98 24			99.61 72

TestCases				90.52 228	96.82 125	78.84 290		92.17 311	77.96 292	75.94 273	95.50 166	55.48 308	99.18 104	71.15 293	87.14 196	93.55 199

test_prior4						92.00 78	99.41 36

test_prior2							99.57 19		91.43 68	98.12 18	98.97 45	90.43 33		98.33 17	99.81 14

test_prior				97.01 49	99.58 19	91.77 79		97.57 98					99.49 84			99.79 24

旧先验2							98.67 114		85.75 189	98.96 4			98.97 115	93.84 83

新几何2							98.26 163

新几何1				97.40 37	98.92 62	92.51 75		97.77 69	85.52 191	96.69 53	99.06 35	88.08 61	99.89 31	84.88 171	99.62 33	99.79 24

旧先验1					98.97 58	92.90 66		97.74 72			99.15 24	91.05 19			99.33 51	99.60 57

无先验							98.52 132	97.82 60	87.20 170				99.90 28	87.64 148		99.85 20

原ACMM2							98.69 109

原ACMM1				96.18 97	99.03 56	90.08 126		97.63 89	88.98 118	97.00 40	98.97 45	88.14 60	99.71 59	88.23 142	99.62 33	98.76 115

test222					98.32 77	91.21 96	98.08 180	97.58 95	83.74 226	95.87 62	99.02 39	86.74 84			99.64 29	99.81 21

testdata2													99.88 32	84.16 178

segment_acmp												90.56 32

testdata				95.26 129	98.20 79	87.28 183		97.60 92	85.21 197	98.48 10	99.15 24	88.15 59	98.72 125	90.29 120	99.45 45	99.78 28

testdata1							97.89 187		92.43 48

test12				97.83 21	99.33 42	94.45 38		97.55 101		97.56 30		88.60 50	99.50 83		99.71 25	99.55 59

plane_prior7					93.84 204	85.73 228

plane_prior6					93.92 201	86.02 221						72.92 221

plane_prior5								96.30 187					97.75 167	93.46 90	86.17 202	92.67 204

plane_prior4											96.52 150

plane_prior3						85.91 222			93.65 30	86.99 173

plane_prior2							99.02 74		93.38 35

plane_prior1					93.90 203

plane_prior						86.07 218	99.14 63		93.81 28						86.26 201

n2								0.00 358

nn								0.00 358

door-mid								84.90 343

lessismore_v0				85.08 297	85.59 312	69.28 322		90.56 326		67.68 311	90.21 267	54.21 314	95.46 270	73.88 276	62.64 314	90.50 269

LGP-MVS_train				90.06 237	93.35 217	80.95 278		95.94 209	87.73 157	83.17 201	96.11 159	66.28 272	97.77 162	90.19 121	85.19 208	91.46 236

test11								97.68 78

door								85.30 342

HQP5-MVS						86.39 205

HQP-NCC					93.95 197		99.16 56		93.92 22	87.57 167

ACMP_Plane					93.95 197		99.16 56		93.92 22	87.57 167

BP-MVS														93.82 85

HQP4-MVS										87.57 167			97.77 162			92.72 202

HQP3-MVS								96.37 182							86.29 199

HQP2-MVS												73.34 216

NP-MVS					93.94 200	86.22 212					96.67 144

MDTV_nov1_ep13_2view						91.17 99	91.38 305		87.45 163	93.08 101		86.67 85		87.02 153		98.95 101

MDTV_nov1_ep13			90.47 151		96.14 145	88.55 155	91.34 306	97.51 107	89.58 102	92.24 109	90.50 258	86.99 82	97.61 175	77.64 239	92.34 148

ACMMP++_ref															82.64 229

ACMMP++															83.83 218

Test By Simon												83.62 119

ITE_SJBPF				87.93 279	92.26 228	76.44 301		93.47 290	87.67 160	79.95 244	95.49 168	56.50 305	97.38 189	75.24 263	82.33 231	89.98 280

DeepMVS_CX				76.08 317	90.74 250	51.65 340		90.84 324	86.47 183	57.89 328	87.98 286	35.88 338	92.60 310	65.77 308	65.06 310	83.97 326

High-resolution multi-view benchmark