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.

TSAR-MVS + MP.		99.58 3	99.50 7	99.81 29	99.91 1	99.66 37	99.63 82	99.39 186	98.91 29	99.78 23	99.85 27	99.36 2	99.94 41	98.84 71	99.88 35	99.82 31

HPM-MVS_fast		99.51 12	99.40 14	99.85 18	99.91 1	99.79 19	99.76 28	99.56 49	97.72 138	99.76 30	99.75 96	99.13 7	99.92 65	99.07 48	99.92 12	99.85 9

MP-MVS-pluss		99.37 39	99.20 48	99.88 5	99.90 3	99.87 3	99.30 216	99.52 77	97.18 186	99.60 63	99.79 76	98.79 36	99.95 34	98.83 74	99.91 17	99.83 24
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
zzz-MVS		99.49 13	99.36 19	99.89 3	99.90 3	99.86 4	99.36 201	99.47 132	98.79 40	99.68 39	99.81 57	98.43 63	99.97 11	98.88 61	99.90 24	99.83 24

MTAPA		99.52 11	99.39 15	99.89 3	99.90 3	99.86 4	99.66 68	99.47 132	98.79 40	99.68 39	99.81 57	98.43 63	99.97 11	98.88 61	99.90 24	99.83 24

HPM-MVS		99.42 31	99.28 40	99.83 24	99.90 3	99.72 28	99.81 15	99.54 63	97.59 147	99.68 39	99.63 147	98.91 27	99.94 41	98.58 103	99.91 17	99.84 13
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
HyFIR lowres test		99.11 74	98.92 81	99.65 59	99.90 3	99.37 77	99.02 284	99.91 3	97.67 144	99.59 66	99.75 96	95.90 140	99.73 173	99.53 6	99.02 134	99.86 6

HSP-MVS		99.41 34	99.26 45	99.85 18	99.89 8	99.80 15	99.67 59	99.37 200	98.70 46	99.77 25	99.49 197	98.21 75	99.95 34	98.46 119	99.77 76	99.81 35

CHOSEN 1792x2688		99.19 58	99.10 58	99.45 99	99.89 8	98.52 197	99.39 190	99.94 1	98.73 44	99.11 180	99.89 10	95.50 150	99.94 41	99.50 8	99.97 3	99.89 2

ACMMP		99.45 23	99.32 26	99.82 26	99.89 8	99.67 35	99.62 85	99.69 18	98.12 86	99.63 55	99.84 36	98.73 47	99.96 19	98.55 111	99.83 63	99.81 35
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
region2R		99.48 17	99.35 22	99.87 7	99.88 11	99.80 15	99.65 78	99.66 25	98.13 84	99.66 50	99.68 125	98.96 21	99.96 19	98.62 97	99.87 39	99.84 13

MP-MVS		99.33 43	99.15 52	99.87 7	99.88 11	99.82 13	99.66 68	99.46 142	98.09 91	99.48 91	99.74 101	98.29 72	99.96 19	97.93 157	99.87 39	99.82 31
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
mPP-MVS		99.44 26	99.30 34	99.86 13	99.88 11	99.79 19	99.69 48	99.48 116	98.12 86	99.50 87	99.75 96	98.78 37	99.97 11	98.57 105	99.89 32	99.83 24

COLMAP_ROB	97.56 6	98.86 105	98.75 105	99.17 139	99.88 11	98.53 193	99.34 209	99.59 38	97.55 152	98.70 243	99.89 10	95.83 142	99.90 88	98.10 142	99.90 24	99.08 173
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ACMMP_Plus		99.47 20	99.34 24	99.88 5	99.87 15	99.86 4	99.47 157	99.48 116	98.05 100	99.76 30	99.86 23	98.82 33	99.93 56	98.82 78	99.91 17	99.84 13

HFP-MVS		99.49 13	99.37 17	99.86 13	99.87 15	99.80 15	99.66 68	99.67 22	98.15 82	99.68 39	99.69 120	99.06 9	99.96 19	98.69 89	99.87 39	99.84 13

#test#		99.43 29	99.29 38	99.86 13	99.87 15	99.80 15	99.55 121	99.67 22	97.83 125	99.68 39	99.69 120	99.06 9	99.96 19	98.39 122	99.87 39	99.84 13

ACMMPR		99.49 13	99.36 19	99.86 13	99.87 15	99.79 19	99.66 68	99.67 22	98.15 82	99.67 45	99.69 120	98.95 24	99.96 19	98.69 89	99.87 39	99.84 13

PGM-MVS		99.45 23	99.31 32	99.86 13	99.87 15	99.78 23	99.58 102	99.65 30	97.84 124	99.71 33	99.80 68	99.12 8	99.97 11	98.33 129	99.87 39	99.83 24

AllTest		98.87 102	98.72 106	99.31 116	99.86 20	98.48 202	99.56 115	99.61 32	97.85 122	99.36 116	99.85 27	95.95 136	99.85 115	96.66 254	99.83 63	99.59 111

TestCases				99.31 116	99.86 20	98.48 202		99.61 32	97.85 122	99.36 116	99.85 27	95.95 136	99.85 115	96.66 254	99.83 63	99.59 111

PVSNet_Blended_VisFu		99.36 40	99.28 40	99.61 68	99.86 20	99.07 109	99.47 157	99.93 2	97.66 145	99.71 33	99.86 23	97.73 88	99.96 19	99.47 13	99.82 67	99.79 45

XVS		99.53 9	99.42 11	99.87 7	99.85 23	99.83 8	99.69 48	99.68 19	98.98 19	99.37 113	99.74 101	98.81 34	99.94 41	98.79 79	99.86 50	99.84 13

X-MVStestdata		96.55 279	95.45 300	99.87 7	99.85 23	99.83 8	99.69 48	99.68 19	98.98 19	99.37 113	64.01 364	98.81 34	99.94 41	98.79 79	99.86 50	99.84 13

abl_6		99.44 26	99.31 32	99.83 24	99.85 23	99.75 24	99.66 68	99.59 38	98.13 84	99.82 15	99.81 57	98.60 56	99.96 19	98.46 119	99.88 35	99.79 45

114514_t		98.93 99	98.67 112	99.72 49	99.85 23	99.53 58	99.62 85	99.59 38	92.65 329	99.71 33	99.78 82	98.06 80	99.90 88	98.84 71	99.91 17	99.74 60

CSCG		99.32 44	99.32 26	99.32 115	99.85 23	98.29 209	99.71 44	99.66 25	98.11 88	99.41 104	99.80 68	98.37 69	99.96 19	98.99 54	99.96 5	99.72 71

CP-MVS		99.45 23	99.32 26	99.85 18	99.83 28	99.75 24	99.69 48	99.52 77	98.07 95	99.53 81	99.63 147	98.93 26	99.97 11	98.74 82	99.91 17	99.83 24

SteuartSystems-ACMMP		99.54 7	99.42 11	99.87 7	99.82 29	99.81 14	99.59 95	99.51 86	98.62 50	99.79 19	99.83 40	99.28 3	99.97 11	98.48 116	99.90 24	99.84 13
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RPSCF		98.22 155	98.62 121	96.99 311	99.82 29	91.58 339	99.72 42	99.44 163	96.61 232	99.66 50	99.89 10	95.92 139	99.82 138	97.46 203	99.10 128	99.57 115

DeepC-MVS	98.35 2	99.30 46	99.19 49	99.64 64	99.82 29	99.23 93	99.62 85	99.55 56	98.94 26	99.63 55	99.95 2	95.82 143	99.94 41	99.37 18	99.97 3	99.73 65
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
test_part2					99.81 32	99.83 8				99.77 25

v1.0		41.40 337	55.20 338	0.00 354	99.81 32	0.00 369	0.00 360	99.48 116	97.97 111	99.77 25	99.78 82	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

CPTT-MVS		99.11 74	98.90 84	99.74 45	99.80 34	99.46 68	99.59 95	99.49 106	97.03 207	99.63 55	99.69 120	97.27 100	99.96 19	97.82 165	99.84 59	99.81 35

MCST-MVS		99.43 29	99.30 34	99.82 26	99.79 35	99.74 27	99.29 220	99.40 183	98.79 40	99.52 83	99.62 152	98.91 27	99.90 88	98.64 94	99.75 79	99.82 31

ESAPD		99.46 21	99.32 26	99.91 2	99.78 36	99.88 2	99.36 201	99.51 86	98.73 44	99.88 3	99.84 36	98.72 48	99.96 19	98.16 138	99.87 39	99.88 4

tfpn1000		98.33 143	98.02 157	99.25 130	99.78 36	98.73 174	99.70 45	97.55 351	97.48 158	99.69 38	99.53 183	92.37 271	99.85 115	97.82 165	98.26 183	99.16 164

EI-MVSNet-UG-set		99.58 3	99.57 1	99.64 64	99.78 36	99.14 102	99.60 93	99.45 154	99.01 13	99.90 1	99.83 40	98.98 19	99.93 56	99.59 2	99.95 6	99.86 6

EI-MVSNet-Vis-set		99.58 3	99.56 3	99.64 64	99.78 36	99.15 101	99.61 91	99.45 154	99.01 13	99.89 2	99.82 47	99.01 12	99.92 65	99.56 5	99.95 6	99.85 9

Vis-MVSNet		99.12 70	98.97 74	99.56 77	99.78 36	99.10 105	99.68 57	99.66 25	98.49 57	99.86 8	99.87 20	94.77 191	99.84 121	99.19 36	99.41 109	99.74 60
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
F-COLMAP		99.19 58	99.04 64	99.64 64	99.78 36	99.27 89	99.42 177	99.54 63	97.29 177	99.41 104	99.59 161	98.42 66	99.93 56	98.19 135	99.69 92	99.73 65

APDe-MVS		99.66 1	99.57 1	99.92 1	99.77 42	99.89 1	99.75 36	99.56 49	99.02 10	99.88 3	99.85 27	99.18 5	99.96 19	99.22 34	99.92 12	99.90 1

MVS_111021_LR		99.41 34	99.33 25	99.65 59	99.77 42	99.51 63	98.94 305	99.85 6	98.82 35	99.65 53	99.74 101	98.51 58	99.80 146	98.83 74	99.89 32	99.64 98

DP-MVS		99.16 63	98.95 79	99.78 35	99.77 42	99.53 58	99.41 181	99.50 101	97.03 207	99.04 195	99.88 15	97.39 95	99.92 65	98.66 92	99.90 24	99.87 5

conf0.01		98.21 158	97.89 172	99.15 142	99.76 45	99.04 112	99.67 59	97.71 343	97.10 196	99.55 74	99.54 176	92.70 253	99.79 149	96.90 238	98.12 198	98.61 282

conf0.002		98.21 158	97.89 172	99.15 142	99.76 45	99.04 112	99.67 59	97.71 343	97.10 196	99.55 74	99.54 176	92.70 253	99.79 149	96.90 238	98.12 198	98.61 282

thresconf0.02		98.24 151	97.89 172	99.27 125	99.76 45	99.04 112	99.67 59	97.71 343	97.10 196	99.55 74	99.54 176	92.70 253	99.79 149	96.90 238	98.12 198	98.97 187

tfpn_n400		98.24 151	97.89 172	99.27 125	99.76 45	99.04 112	99.67 59	97.71 343	97.10 196	99.55 74	99.54 176	92.70 253	99.79 149	96.90 238	98.12 198	98.97 187

tfpnconf		98.24 151	97.89 172	99.27 125	99.76 45	99.04 112	99.67 59	97.71 343	97.10 196	99.55 74	99.54 176	92.70 253	99.79 149	96.90 238	98.12 198	98.97 187

tfpnview11		98.24 151	97.89 172	99.27 125	99.76 45	99.04 112	99.67 59	97.71 343	97.10 196	99.55 74	99.54 176	92.70 253	99.79 149	96.90 238	98.12 198	98.97 187

Regformer-3		99.57 6	99.53 5	99.68 52	99.76 45	99.29 86	99.58 102	99.44 163	99.01 13	99.87 7	99.80 68	98.97 20	99.91 75	99.44 16	99.92 12	99.83 24

Regformer-4		99.59 2	99.54 4	99.73 47	99.76 45	99.41 74	99.58 102	99.49 106	99.02 10	99.88 3	99.80 68	99.00 18	99.94 41	99.45 15	99.92 12	99.84 13

APD-MVS_3200maxsize		99.48 17	99.35 22	99.85 18	99.76 45	99.83 8	99.63 82	99.54 63	98.36 66	99.79 19	99.82 47	98.86 30	99.95 34	98.62 97	99.81 68	99.78 49

PVSNet_BlendedMVS		98.86 105	98.80 99	99.03 153	99.76 45	98.79 168	99.28 222	99.91 3	97.42 167	99.67 45	99.37 234	97.53 91	99.88 103	98.98 55	97.29 241	98.42 303

PVSNet_Blended		99.08 81	98.97 74	99.42 105	99.76 45	98.79 168	98.78 317	99.91 3	96.74 223	99.67 45	99.49 197	97.53 91	99.88 103	98.98 55	99.85 54	99.60 107

MSDG		98.98 95	98.80 99	99.53 83	99.76 45	99.19 95	98.75 320	99.55 56	97.25 180	99.47 92	99.77 88	97.82 85	99.87 105	96.93 235	99.90 24	99.54 118

tfpn_ndepth		98.17 162	97.84 180	99.15 142	99.75 57	98.76 172	99.61 91	97.39 353	96.92 214	99.61 60	99.38 230	92.19 273	99.86 109	97.57 190	98.13 196	98.82 204

view600		97.97 194	97.66 204	98.89 184	99.75 57	97.81 232	99.69 48	98.80 299	98.02 104	99.25 147	98.88 293	91.95 275	99.89 96	94.36 300	98.29 178	98.96 193

view800		97.97 194	97.66 204	98.89 184	99.75 57	97.81 232	99.69 48	98.80 299	98.02 104	99.25 147	98.88 293	91.95 275	99.89 96	94.36 300	98.29 178	98.96 193

conf0.05thres1000		97.97 194	97.66 204	98.89 184	99.75 57	97.81 232	99.69 48	98.80 299	98.02 104	99.25 147	98.88 293	91.95 275	99.89 96	94.36 300	98.29 178	98.96 193

tfpn		97.97 194	97.66 204	98.89 184	99.75 57	97.81 232	99.69 48	98.80 299	98.02 104	99.25 147	98.88 293	91.95 275	99.89 96	94.36 300	98.29 178	98.96 193

HPM-MVS++		99.39 38	99.23 47	99.87 7	99.75 57	99.84 7	99.43 170	99.51 86	98.68 48	99.27 139	99.53 183	98.64 54	99.96 19	98.44 121	99.80 70	99.79 45

新几何1				99.75 40	99.75 57	99.59 49		99.54 63	96.76 222	99.29 131	99.64 143	98.43 63	99.94 41	96.92 236	99.66 97	99.72 71

test222					99.75 57	99.49 64	98.91 308	99.49 106	96.42 249	99.34 122	99.65 136	98.28 73			99.69 92	99.72 71

testdata				99.54 78	99.75 57	98.95 134		99.51 86	97.07 203	99.43 99	99.70 114	98.87 29	99.94 41	97.76 172	99.64 100	99.72 71

CDPH-MVS		99.13 65	98.91 83	99.80 31	99.75 57	99.71 29	99.15 254	99.41 176	96.60 234	99.60 63	99.55 173	98.83 32	99.90 88	97.48 200	99.83 63	99.78 49

APD-MVS		99.27 51	99.08 59	99.84 23	99.75 57	99.79 19	99.50 138	99.50 101	97.16 188	99.77 25	99.82 47	98.78 37	99.94 41	97.56 192	99.86 50	99.80 40
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
旧先验1					99.74 68	99.59 49		99.54 63			99.69 120	98.47 60			99.68 95	99.73 65

1121		99.09 78	98.87 88	99.75 40	99.74 68	99.60 47	99.27 225	99.48 116	96.82 221	99.25 147	99.65 136	98.38 67	99.93 56	97.53 195	99.67 96	99.73 65

SD-MVS		99.41 34	99.52 6	99.05 152	99.74 68	99.68 33	99.46 160	99.52 77	99.11 7	99.88 3	99.91 5	99.43 1	97.70 337	98.72 86	99.93 11	99.77 51

DP-MVS Recon		99.12 70	98.95 79	99.65 59	99.74 68	99.70 31	99.27 225	99.57 44	96.40 252	99.42 102	99.68 125	98.75 45	99.80 146	97.98 153	99.72 85	99.44 146

PAPM_NR		99.04 86	98.84 95	99.66 55	99.74 68	99.44 71	99.39 190	99.38 192	97.70 141	99.28 135	99.28 260	98.34 70	99.85 115	96.96 232	99.45 106	99.69 80

原ACMM1				99.65 59	99.73 73	99.33 81		99.47 132	97.46 159	99.12 178	99.66 135	98.67 53	99.91 75	97.70 181	99.69 92	99.71 78

IS-MVSNet		99.05 85	98.87 88	99.57 75	99.73 73	99.32 82	99.75 36	99.20 255	98.02 104	99.56 71	99.86 23	96.54 122	99.67 194	98.09 143	99.13 125	99.73 65

PVSNet	96.02 17	98.85 112	98.84 95	98.89 184	99.73 73	97.28 244	98.32 339	99.60 35	97.86 119	99.50 87	99.57 168	96.75 117	99.86 109	98.56 108	99.70 91	99.54 118

tfpn111		97.81 218	97.49 224	98.78 211	99.72 76	97.86 228	99.59 95	98.74 307	97.93 114	99.26 143	98.62 308	91.75 282	99.86 109	93.57 314	98.18 188	98.61 282

conf200view11		97.78 225	97.45 230	98.77 212	99.72 76	97.86 228	99.59 95	98.74 307	97.93 114	99.26 143	98.62 308	91.75 282	99.83 129	93.22 318	98.18 188	98.61 282

thres100view900		97.76 227	97.45 230	98.69 218	99.72 76	97.86 228	99.59 95	98.74 307	97.93 114	99.26 143	98.62 308	91.75 282	99.83 129	93.22 318	98.18 188	98.37 307

thres600view7		97.86 209	97.51 220	98.92 173	99.72 76	97.95 225	99.59 95	98.74 307	97.94 113	99.27 139	98.62 308	91.75 282	99.86 109	93.73 313	98.19 187	98.96 193

DELS-MVS		99.48 17	99.42 11	99.65 59	99.72 76	99.40 76	99.05 275	99.66 25	99.14 6	99.57 70	99.80 68	98.46 61	99.94 41	99.57 4	99.84 59	99.60 107
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
MVS_111021_HR		99.41 34	99.32 26	99.66 55	99.72 76	99.47 67	98.95 303	99.85 6	98.82 35	99.54 80	99.73 105	98.51 58	99.74 166	98.91 60	99.88 35	99.77 51

Anonymous20231211		97.88 206	97.54 217	98.90 181	99.71 82	98.53 193	99.48 152	99.57 44	94.16 312	98.81 227	99.68 125	93.23 237	99.42 229	98.84 71	94.42 301	98.76 213

Regformer-1		99.53 9	99.47 8	99.72 49	99.71 82	99.44 71	99.49 147	99.46 142	98.95 24	99.83 12	99.76 91	99.01 12	99.93 56	99.17 39	99.87 39	99.80 40

Regformer-2		99.54 7	99.47 8	99.75 40	99.71 82	99.52 61	99.49 147	99.49 106	98.94 26	99.83 12	99.76 91	99.01 12	99.94 41	99.15 42	99.87 39	99.80 40

XVG-OURS-SEG-HR		98.69 125	98.62 121	98.89 184	99.71 82	97.74 238	99.12 258	99.54 63	98.44 63	99.42 102	99.71 111	94.20 214	99.92 65	98.54 113	98.90 146	99.00 183

Vis-MVSNet (Re-imp)		98.87 102	98.72 106	99.31 116	99.71 82	98.88 144	99.80 19	99.44 163	97.91 117	99.36 116	99.78 82	95.49 151	99.43 228	97.91 158	99.11 126	99.62 104

PatchMatch-RL		98.84 114	98.62 121	99.52 87	99.71 82	99.28 87	99.06 273	99.77 9	97.74 136	99.50 87	99.53 183	95.41 152	99.84 121	97.17 220	99.64 100	99.44 146

SMA-MVS		99.44 26	99.30 34	99.85 18	99.70 88	99.83 8	99.56 115	99.47 132	97.45 162	99.78 23	99.82 47	99.18 5	99.91 75	98.83 74	99.89 32	99.80 40

XVG-OURS		98.73 123	98.68 111	98.88 191	99.70 88	97.73 239	98.92 306	99.55 56	98.52 56	99.45 95	99.84 36	95.27 157	99.91 75	98.08 147	98.84 151	99.00 183

TAPA-MVS	97.07 15	97.74 233	97.34 251	98.94 165	99.70 88	97.53 241	99.25 235	99.51 86	91.90 333	99.30 127	99.63 147	98.78 37	99.64 200	88.09 338	99.87 39	99.65 92
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
tfpn200view9		97.72 236	97.38 244	98.72 216	99.69 91	97.96 223	99.50 138	98.73 316	97.83 125	99.17 172	98.45 317	91.67 288	99.83 129	93.22 318	98.18 188	98.37 307

thres400		97.77 226	97.38 244	98.92 173	99.69 91	97.96 223	99.50 138	98.73 316	97.83 125	99.17 172	98.45 317	91.67 288	99.83 129	93.22 318	98.18 188	98.96 193

Test_1112_low_res		98.89 101	98.66 115	99.57 75	99.69 91	98.95 134	99.03 281	99.47 132	96.98 209	99.15 174	99.23 267	96.77 116	99.89 96	98.83 74	98.78 156	99.86 6

1112_ss		98.98 95	98.77 102	99.59 70	99.68 94	99.02 120	99.25 235	99.48 116	97.23 183	99.13 175	99.58 164	96.93 111	99.90 88	98.87 65	98.78 156	99.84 13

TEST9					99.67 95	99.65 40	99.05 275	99.41 176	96.22 265	98.95 209	99.49 197	98.77 40	99.91 75

train_agg		99.02 89	98.77 102	99.77 37	99.67 95	99.65 40	99.05 275	99.41 176	96.28 258	98.95 209	99.49 197	98.76 42	99.91 75	97.63 185	99.72 85	99.75 55

test_8					99.67 95	99.61 45	99.03 281	99.41 176	96.28 258	98.93 212	99.48 203	98.76 42	99.91 75

agg_prior3		98.97 97	98.71 108	99.75 40	99.67 95	99.60 47	99.04 280	99.41 176	95.93 282	98.87 219	99.48 203	98.61 55	99.91 75	97.63 185	99.72 85	99.75 55

agg_prior1		99.01 92	98.76 104	99.76 39	99.67 95	99.62 43	98.99 290	99.40 183	96.26 261	98.87 219	99.49 197	98.77 40	99.91 75	97.69 182	99.72 85	99.75 55

agg_prior					99.67 95	99.62 43		99.40 183		98.87 219			99.91 75

test_prior3		99.21 57	99.05 61	99.68 52	99.67 95	99.48 65	98.96 299	99.56 49	98.34 67	99.01 198	99.52 188	98.68 51	99.83 129	97.96 154	99.74 81	99.74 60

test_prior				99.68 52	99.67 95	99.48 65		99.56 49					99.83 129			99.74 60

TSAR-MVS + GP.		99.36 40	99.36 19	99.36 108	99.67 95	98.61 189	99.07 269	99.33 221	99.00 17	99.82 15	99.81 57	99.06 9	99.84 121	99.09 46	99.42 108	99.65 92

OMC-MVS		99.08 81	99.04 64	99.20 137	99.67 95	98.22 212	99.28 222	99.52 77	98.07 95	99.66 50	99.81 57	97.79 86	99.78 157	97.79 168	99.81 68	99.60 107

Anonymous20240529		98.09 172	97.68 202	99.34 110	99.66 105	98.44 204	99.40 188	99.43 171	93.67 318	99.22 159	99.89 10	90.23 305	99.93 56	99.26 31	98.33 174	99.66 88

CHOSEN 280x420		99.12 70	99.13 54	99.08 148	99.66 105	97.89 226	98.43 335	99.71 13	98.88 30	99.62 58	99.76 91	96.63 120	99.70 189	99.46 14	99.99 1	99.66 88

PLC	97.94 4	99.02 89	98.85 94	99.53 83	99.66 105	99.01 122	99.24 237	99.52 77	96.85 218	99.27 139	99.48 203	98.25 74	99.91 75	97.76 172	99.62 103	99.65 92
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
EPP-MVSNet		99.13 65	98.99 71	99.53 83	99.65 108	99.06 110	99.81 15	99.33 221	97.43 164	99.60 63	99.88 15	97.14 103	99.84 121	99.13 43	98.94 141	99.69 80

thres200		97.61 249	97.28 258	98.62 223	99.64 109	98.03 219	99.26 233	98.74 307	97.68 143	99.09 187	98.32 319	91.66 290	99.81 142	92.88 324	98.22 184	98.03 319

test12				99.75 40	99.64 109	99.61 45		99.29 235		99.21 162		98.38 67	99.89 96		99.74 81	99.74 60

ab-mvs		98.86 105	98.63 117	99.54 78	99.64 109	99.19 95	99.44 165	99.54 63	97.77 132	99.30 127	99.81 57	94.20 214	99.93 56	99.17 39	98.82 152	99.49 133

xiu_mvs_v1_base_debu		99.29 48	99.27 42	99.34 110	99.63 112	98.97 129	99.12 258	99.51 86	98.86 31	99.84 9	99.47 207	98.18 76	99.99 1	99.50 8	99.31 115	99.08 173

xiu_mvs_v1_base		99.29 48	99.27 42	99.34 110	99.63 112	98.97 129	99.12 258	99.51 86	98.86 31	99.84 9	99.47 207	98.18 76	99.99 1	99.50 8	99.31 115	99.08 173

xiu_mvs_v1_base_debi		99.29 48	99.27 42	99.34 110	99.63 112	98.97 129	99.12 258	99.51 86	98.86 31	99.84 9	99.47 207	98.18 76	99.99 1	99.50 8	99.31 115	99.08 173

DeepC-MVS_fast	98.69 1	99.49 13	99.39 15	99.77 37	99.63 112	99.59 49	99.36 201	99.46 142	99.07 9	99.79 19	99.82 47	98.85 31	99.92 65	98.68 91	99.87 39	99.82 31
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
UA-Net		99.42 31	99.29 38	99.80 31	99.62 116	99.55 54	99.50 138	99.70 15	98.79 40	99.77 25	99.96 1	97.45 94	99.96 19	98.92 59	99.90 24	99.89 2

CNVR-MVS		99.42 31	99.30 34	99.78 35	99.62 116	99.71 29	99.26 233	99.52 77	98.82 35	99.39 109	99.71 111	98.96 21	99.85 115	98.59 102	99.80 70	99.77 51

WTY-MVS		99.06 83	98.88 87	99.61 68	99.62 116	99.16 98	99.37 197	99.56 49	98.04 101	99.53 81	99.62 152	96.84 112	99.94 41	98.85 70	98.49 169	99.72 71

sss		99.17 61	99.05 61	99.53 83	99.62 116	98.97 129	99.36 201	99.62 31	97.83 125	99.67 45	99.65 136	97.37 98	99.95 34	99.19 36	99.19 122	99.68 84

NCCC		99.34 42	99.19 49	99.79 34	99.61 120	99.65 40	99.30 216	99.48 116	98.86 31	99.21 162	99.63 147	98.72 48	99.90 88	98.25 133	99.63 102	99.80 40

PCF-MVS	97.08 14	97.66 246	97.06 266	99.47 95	99.61 120	99.09 107	98.04 346	99.25 250	91.24 336	98.51 260	99.70 114	94.55 202	99.91 75	92.76 325	99.85 54	99.42 149
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MSLP-MVS++		99.46 21	99.47 8	99.44 102	99.60 122	99.16 98	99.41 181	99.71 13	98.98 19	99.45 95	99.78 82	99.19 4	99.54 214	99.28 28	99.84 59	99.63 102

DeepPCF-MVS	98.18 3	98.81 115	99.37 17	97.12 310	99.60 122	91.75 338	98.61 328	99.44 163	99.35 1	99.83 12	99.85 27	98.70 50	99.81 142	99.02 52	99.91 17	99.81 35

IterMVS-LS		98.46 135	98.42 132	98.58 226	99.59 124	98.00 220	99.37 197	99.43 171	96.94 212	99.07 189	99.59 161	97.87 83	99.03 294	98.32 131	95.62 272	98.71 222
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IterMVS		97.83 214	97.77 191	98.02 277	99.58 125	96.27 289	99.02 284	99.48 116	97.22 184	98.71 237	99.70 114	92.75 247	99.13 283	97.46 203	96.00 265	98.67 248
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CNLPA		99.14 64	98.99 71	99.59 70	99.58 125	99.41 74	99.16 251	99.44 163	98.45 60	99.19 168	99.49 197	98.08 79	99.89 96	97.73 176	99.75 79	99.48 135

Anonymous202405211		98.30 146	97.98 162	99.26 129	99.57 127	98.16 214	99.41 181	98.55 326	96.03 280	99.19 168	99.74 101	91.87 280	99.92 65	99.16 41	98.29 178	99.70 79

semantic-postprocess				98.06 274	99.57 127	96.36 286		99.49 106	97.18 186	98.71 237	99.72 109	92.70 253	99.14 280	97.44 205	95.86 268	98.67 248

PS-MVSNAJ		99.32 44	99.32 26	99.30 119	99.57 127	98.94 137	98.97 297	99.46 142	98.92 28	99.71 33	99.24 266	99.01 12	99.98 5	99.35 19	99.66 97	98.97 187

MG-MVS		99.13 65	99.02 69	99.45 99	99.57 127	98.63 184	99.07 269	99.34 213	98.99 18	99.61 60	99.82 47	97.98 82	99.87 105	97.00 228	99.80 70	99.85 9

PHI-MVS		99.30 46	99.17 51	99.70 51	99.56 131	99.52 61	99.58 102	99.80 8	97.12 192	99.62 58	99.73 105	98.58 57	99.90 88	98.61 99	99.91 17	99.68 84

AdaColmap		99.01 92	98.80 99	99.66 55	99.56 131	99.54 55	99.18 249	99.70 15	98.18 81	99.35 119	99.63 147	96.32 129	99.90 88	97.48 200	99.77 76	99.55 116

xiu_mvs_v2_base		99.26 53	99.25 46	99.29 122	99.53 133	98.91 142	99.02 284	99.45 154	98.80 39	99.71 33	99.26 263	98.94 25	99.98 5	99.34 23	99.23 119	98.98 186

casdiffmvs1		99.23 56	99.11 57	99.58 73	99.53 133	99.36 78	99.76 28	99.43 171	97.99 109	99.52 83	99.84 36	97.50 93	99.77 159	99.42 17	98.97 138	99.61 106

LFMVS		97.90 205	97.35 248	99.54 78	99.52 135	99.01 122	99.39 190	98.24 332	97.10 196	99.65 53	99.79 76	84.79 342	99.91 75	99.28 28	98.38 173	99.69 80

VNet		99.11 74	98.90 84	99.73 47	99.52 135	99.56 52	99.41 181	99.39 186	99.01 13	99.74 32	99.78 82	95.56 148	99.92 65	99.52 7	98.18 188	99.72 71

MVS_0304		99.06 83	98.86 92	99.66 55	99.51 137	99.36 78	99.22 242	99.51 86	98.95 24	99.58 67	99.65 136	93.74 233	99.98 5	99.66 1	99.95 6	99.64 98

Fast-Effi-MVS+		98.70 124	98.43 131	99.51 89	99.51 137	99.28 87	99.52 129	99.47 132	96.11 275	99.01 198	99.34 248	96.20 133	99.84 121	97.88 160	98.82 152	99.39 152

MVSFormer		99.17 61	99.12 55	99.29 122	99.51 137	98.94 137	99.88 1	99.46 142	97.55 152	99.80 17	99.65 136	97.39 95	99.28 258	99.03 50	99.85 54	99.65 92

lupinMVS		99.13 65	99.01 70	99.46 98	99.51 137	98.94 137	99.05 275	99.16 259	97.86 119	99.80 17	99.56 170	97.39 95	99.86 109	98.94 58	99.85 54	99.58 114

GBi-Net		97.68 242	97.48 225	98.29 254	99.51 137	97.26 246	99.43 170	99.48 116	96.49 239	99.07 189	99.32 254	90.26 302	98.98 300	97.10 222	96.65 250	98.62 273

test1		97.68 242	97.48 225	98.29 254	99.51 137	97.26 246	99.43 170	99.48 116	96.49 239	99.07 189	99.32 254	90.26 302	98.98 300	97.10 222	96.65 250	98.62 273

FMVSNet2		97.72 236	97.36 246	98.80 208	99.51 137	98.84 149	99.45 161	99.42 174	96.49 239	98.86 224	99.29 259	90.26 302	98.98 300	96.44 260	96.56 253	98.58 293

0601test		98.86 105	98.63 117	99.54 78	99.49 144	99.18 97	99.50 138	99.07 270	98.22 77	99.61 60	99.51 191	95.37 153	99.84 121	98.60 101	98.33 174	99.59 111

VDDNet		97.55 251	97.02 267	99.16 140	99.49 144	98.12 218	99.38 195	99.30 230	95.35 289	99.68 39	99.90 7	82.62 348	99.93 56	99.31 26	98.13 196	99.42 149

MVS_Test		99.10 77	98.97 74	99.48 92	99.49 144	99.14 102	99.67 59	99.34 213	97.31 175	99.58 67	99.76 91	97.65 90	99.82 138	98.87 65	99.07 131	99.46 142

BH-untuned		98.42 138	98.36 134	98.59 225	99.49 144	96.70 275	99.27 225	99.13 263	97.24 182	98.80 229	99.38 230	95.75 145	99.74 166	97.07 225	99.16 123	99.33 156

VDD-MVS		97.73 234	97.35 248	98.88 191	99.47 148	97.12 251	99.34 209	98.85 295	98.19 78	99.67 45	99.85 27	82.98 346	99.92 65	99.49 12	98.32 177	99.60 107

casdiffmvs		99.09 78	98.97 74	99.47 95	99.47 148	99.10 105	99.74 41	99.38 192	97.86 119	99.32 124	99.79 76	97.08 106	99.77 159	99.24 32	98.82 152	99.54 118

Effi-MVS+		98.81 115	98.59 126	99.48 92	99.46 150	99.12 104	98.08 345	99.50 101	97.50 157	99.38 111	99.41 221	96.37 128	99.81 142	99.11 45	98.54 166	99.51 129

jason		99.13 65	99.03 66	99.45 99	99.46 150	98.87 145	99.12 258	99.26 248	98.03 103	99.79 19	99.65 136	97.02 107	99.85 115	99.02 52	99.90 24	99.65 92
jason: jason.
TAMVS		99.12 70	99.08 59	99.24 133	99.46 150	98.55 191	99.51 133	99.46 142	98.09 91	99.45 95	99.82 47	98.34 70	99.51 215	98.70 87	98.93 142	99.67 87

ACMH+	97.24 10	97.92 203	97.78 187	98.32 251	99.46 150	96.68 277	99.56 115	99.54 63	98.41 64	97.79 296	99.87 20	90.18 306	99.66 196	98.05 151	97.18 245	98.62 273

diffmvs		98.99 94	98.87 88	99.35 109	99.45 154	98.74 173	99.62 85	99.45 154	97.43 164	99.13 175	99.72 109	97.23 101	99.87 105	98.86 68	98.90 146	99.45 145

MIMVSNet		97.73 234	97.45 230	98.57 227	99.45 154	97.50 242	99.02 284	98.98 279	96.11 275	99.41 104	99.14 273	90.28 301	98.74 313	95.74 272	98.93 142	99.47 139

alignmvs		98.81 115	98.56 128	99.58 73	99.43 156	99.42 73	99.51 133	98.96 282	98.61 51	99.35 119	98.92 292	94.78 187	99.77 159	99.35 19	98.11 204	99.54 118

canonicalmvs		99.02 89	98.86 92	99.51 89	99.42 157	99.32 82	99.80 19	99.48 116	98.63 49	99.31 126	98.81 301	97.09 104	99.75 165	99.27 30	97.90 210	99.47 139

HY-MVS	97.30 7	98.85 112	98.64 116	99.47 95	99.42 157	99.08 108	99.62 85	99.36 201	97.39 170	99.28 135	99.68 125	96.44 126	99.92 65	98.37 125	98.22 184	99.40 151

CDS-MVSNet		99.09 78	99.03 66	99.25 130	99.42 157	98.73 174	99.45 161	99.46 142	98.11 88	99.46 94	99.77 88	98.01 81	99.37 235	98.70 87	98.92 144	99.66 88
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
CANet		99.25 54	99.14 53	99.59 70	99.41 160	99.16 98	99.35 206	99.57 44	98.82 35	99.51 86	99.61 156	96.46 124	99.95 34	99.59 2	99.98 2	99.65 92

Fast-Effi-MVS+-dtu		98.77 121	98.83 98	98.60 224	99.41 160	96.99 263	99.52 129	99.49 106	98.11 88	99.24 152	99.34 248	96.96 110	99.79 149	97.95 156	99.45 106	99.02 182

BH-RMVSNet		98.41 139	98.08 152	99.40 106	99.41 160	98.83 152	99.30 216	98.77 303	97.70 141	98.94 211	99.65 136	92.91 245	99.74 166	96.52 258	99.55 104	99.64 98

ACMM	97.58 5	98.37 142	98.34 136	98.48 236	99.41 160	97.10 252	99.56 115	99.45 154	98.53 55	99.04 195	99.85 27	93.00 241	99.71 183	98.74 82	97.45 232	98.64 264
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH	97.28 8	98.10 171	97.99 161	98.44 243	99.41 160	96.96 267	99.60 93	99.56 49	98.09 91	98.15 280	99.91 5	90.87 298	99.70 189	98.88 61	97.45 232	98.67 248
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PAPR		98.63 131	98.34 136	99.51 89	99.40 165	99.03 119	98.80 315	99.36 201	96.33 254	99.00 205	99.12 277	98.46 61	99.84 121	95.23 284	99.37 114	99.66 88

API-MVS		99.04 86	99.03 66	99.06 150	99.40 165	99.31 85	99.55 121	99.56 49	98.54 54	99.33 123	99.39 229	98.76 42	99.78 157	96.98 230	99.78 74	98.07 315

FMVSNet3		98.03 184	97.76 194	98.84 203	99.39 167	98.98 126	99.40 188	99.38 192	96.67 228	99.07 189	99.28 260	92.93 242	98.98 300	97.10 222	96.65 250	98.56 295

GA-MVS		97.85 210	97.47 227	99.00 157	99.38 168	97.99 221	98.57 330	99.15 260	97.04 206	98.90 216	99.30 257	89.83 308	99.38 231	96.70 251	98.33 174	99.62 104

mvs_anonymous		99.03 88	98.99 71	99.16 140	99.38 168	98.52 197	99.51 133	99.38 192	97.79 130	99.38 111	99.81 57	97.30 99	99.45 219	99.35 19	98.99 136	99.51 129

ACMP	97.20 11	98.06 175	97.94 166	98.45 240	99.37 170	97.01 261	99.44 165	99.49 106	97.54 155	98.45 264	99.79 76	91.95 275	99.72 177	97.91 158	97.49 230	98.62 273
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
MAR-MVS		98.86 105	98.63 117	99.54 78	99.37 170	99.66 37	99.45 161	99.54 63	96.61 232	99.01 198	99.40 225	97.09 104	99.86 109	97.68 184	99.53 105	99.10 168
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
testgi		97.65 247	97.50 222	98.13 272	99.36 172	96.45 283	99.42 177	99.48 116	97.76 133	97.87 292	99.45 214	91.09 295	98.81 312	94.53 295	98.52 167	99.13 167

EI-MVSNet		98.67 127	98.67 112	98.68 219	99.35 173	97.97 222	99.50 138	99.38 192	96.93 213	99.20 165	99.83 40	97.87 83	99.36 239	98.38 124	97.56 222	98.71 222

CVMVSNet		98.57 132	98.67 112	98.30 253	99.35 173	95.59 298	99.50 138	99.55 56	98.60 52	99.39 109	99.83 40	94.48 205	99.45 219	98.75 81	98.56 165	99.85 9

BH-w/o		98.00 190	97.89 172	98.32 251	99.35 173	96.20 291	99.01 288	98.90 291	96.42 249	98.38 267	99.00 285	95.26 159	99.72 177	96.06 266	98.61 159	99.03 180

MVSTER		98.49 133	98.32 138	99.00 157	99.35 173	99.02 120	99.54 124	99.38 192	97.41 168	99.20 165	99.73 105	93.86 228	99.36 239	98.87 65	97.56 222	98.62 273

Effi-MVS+-dtu		98.78 119	98.89 86	98.47 238	99.33 177	96.91 269	99.57 108	99.30 230	98.47 58	99.41 104	98.99 286	96.78 114	99.74 166	98.73 84	99.38 110	98.74 218

CANet_DTU		98.97 97	98.87 88	99.25 130	99.33 177	98.42 207	99.08 268	99.30 230	99.16 5	99.43 99	99.75 96	95.27 157	99.97 11	98.56 108	99.95 6	99.36 153

mvs-test1		98.86 105	98.84 95	98.89 184	99.33 177	97.77 237	99.44 165	99.30 230	98.47 58	99.10 183	99.43 216	96.78 114	99.95 34	98.73 84	99.02 134	98.96 193

ADS-MVSNet2		98.02 186	98.07 154	97.87 287	99.33 177	95.19 310	99.23 238	99.08 267	96.24 263	99.10 183	99.67 130	94.11 219	98.93 309	96.81 245	99.05 132	99.48 135

ADS-MVSNet		98.20 160	98.08 152	98.56 229	99.33 177	96.48 282	99.23 238	99.15 260	96.24 263	99.10 183	99.67 130	94.11 219	99.71 183	96.81 245	99.05 132	99.48 135

LPG-MVS_test		98.22 155	98.13 147	98.49 234	99.33 177	97.05 258	99.58 102	99.55 56	97.46 159	99.24 152	99.83 40	92.58 262	99.72 177	98.09 143	97.51 225	98.68 237

LGP-MVS_train				98.49 234	99.33 177	97.05 258		99.55 56	97.46 159	99.24 152	99.83 40	92.58 262	99.72 177	98.09 143	97.51 225	98.68 237

FMVSNet1		96.84 276	96.36 277	98.29 254	99.32 184	97.26 246	99.43 170	99.48 116	95.11 291	98.55 259	99.32 254	83.95 345	98.98 300	95.81 271	96.26 260	98.62 273

PVSNet_0	94.43 19	96.09 297	95.47 299	97.94 282	99.31 185	94.34 322	97.81 347	99.70 15	97.12 192	97.46 298	98.75 305	89.71 309	99.79 149	97.69 182	81.69 350	99.68 84

Patchmatch-test1		98.16 164	98.14 146	98.22 266	99.30 186	95.55 299	99.07 269	98.97 280	97.57 150	99.43 99	99.60 159	92.72 250	99.60 208	97.38 208	99.20 121	99.50 132

LCM-MVSNet-Re		97.83 214	98.15 145	96.87 315	99.30 186	92.25 337	99.59 95	98.26 331	97.43 164	96.20 314	99.13 274	96.27 131	98.73 314	98.17 137	98.99 136	99.64 98

MVS-HIRNet		95.75 300	95.16 304	97.51 304	99.30 186	93.69 329	98.88 310	95.78 356	85.09 348	98.78 231	92.65 351	91.29 294	99.37 235	94.85 290	99.85 54	99.46 142

HQP_MVS		98.27 150	98.22 144	98.44 243	99.29 189	96.97 265	99.39 190	99.47 132	98.97 22	99.11 180	99.61 156	92.71 251	99.69 192	97.78 169	97.63 215	98.67 248

plane_prior7					99.29 189	97.03 260

ITE_SJBPF				98.08 273	99.29 189	96.37 285		98.92 286	98.34 67	98.83 226	99.75 96	91.09 295	99.62 206	95.82 270	97.40 236	98.25 312

DeepMVS_CX				93.34 327	99.29 189	82.27 352		99.22 253	85.15 347	96.33 313	99.05 282	90.97 297	99.73 173	93.57 314	97.77 213	98.01 320

CLD-MVS		98.16 164	98.10 149	98.33 250	99.29 189	96.82 272	98.75 320	99.44 163	97.83 125	99.13 175	99.55 173	92.92 243	99.67 194	98.32 131	97.69 214	98.48 299
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
plane_prior6					99.27 194	96.98 264						92.71 251

PMMVS		98.80 118	98.62 121	99.34 110	99.27 194	98.70 177	98.76 319	99.31 228	97.34 172	99.21 162	99.07 279	97.20 102	99.82 138	98.56 108	98.87 149	99.52 124

plane_prior1					99.26 196

XXY-MVS		98.38 141	98.09 151	99.24 133	99.26 196	99.32 82	99.56 115	99.55 56	97.45 162	98.71 237	99.83 40	93.23 237	99.63 205	98.88 61	96.32 259	98.76 213

tpmp4_e23		97.34 266	97.29 257	97.52 303	99.25 198	93.73 326	99.58 102	99.19 258	94.00 314	98.20 277	99.41 221	90.74 299	99.74 166	97.13 221	98.07 205	99.07 177

NP-MVS					99.23 199	96.92 268					99.40 225

LTVRE_ROB	97.16 12	98.02 186	97.90 168	98.40 246	99.23 199	96.80 273	99.70 45	99.60 35	97.12 192	98.18 279	99.70 114	91.73 286	99.72 177	98.39 122	97.45 232	98.68 237
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
UGNet		98.87 102	98.69 110	99.40 106	99.22 201	98.72 176	99.44 165	99.68 19	99.24 3	99.18 171	99.42 218	92.74 249	99.96 19	99.34 23	99.94 10	99.53 123
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
VPNet		97.84 212	97.44 236	99.01 155	99.21 202	98.94 137	99.48 152	99.57 44	98.38 65	99.28 135	99.73 105	88.89 316	99.39 230	99.19 36	93.27 317	98.71 222

IB-MVS	95.67 18	96.22 293	95.44 301	98.57 227	99.21 202	96.70 275	98.65 327	97.74 342	96.71 225	97.27 301	98.54 315	86.03 336	99.92 65	98.47 118	86.30 347	99.10 168
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
tfpnnormal		97.84 212	97.47 227	98.98 159	99.20 204	99.22 94	99.64 80	99.61 32	96.32 255	98.27 275	99.70 114	93.35 236	99.44 224	95.69 274	95.40 275	98.27 310

QAPM		98.67 127	98.30 140	99.80 31	99.20 204	99.67 35	99.77 25	99.72 11	94.74 296	98.73 235	99.90 7	95.78 144	99.98 5	96.96 232	99.88 35	99.76 54

HQP-NCC					99.19 206		98.98 294		98.24 73	98.66 246

ACMP_Plane					99.19 206		98.98 294		98.24 73	98.66 246

HQP-MVS		98.02 186	97.90 168	98.37 248	99.19 206	96.83 270	98.98 294	99.39 186	98.24 73	98.66 246	99.40 225	92.47 266	99.64 200	97.19 217	97.58 220	98.64 264

Patchmatch-test		97.93 200	97.65 209	98.77 212	99.18 209	97.07 256	99.03 281	99.14 262	96.16 270	98.74 234	99.57 168	94.56 201	99.72 177	93.36 317	99.11 126	99.52 124

FIs		98.78 119	98.63 117	99.23 135	99.18 209	99.54 55	99.83 12	99.59 38	98.28 71	98.79 230	99.81 57	96.75 117	99.37 235	99.08 47	96.38 257	98.78 208

CR-MVSNet		98.17 162	97.93 167	98.87 195	99.18 209	98.49 200	99.22 242	99.33 221	96.96 210	99.56 71	99.38 230	94.33 210	99.00 298	94.83 291	98.58 162	99.14 165

RPMNet		96.61 278	95.85 286	98.87 195	99.18 209	98.49 200	99.22 242	99.08 267	88.72 345	99.56 71	97.38 340	94.08 221	99.00 298	86.87 343	98.58 162	99.14 165

LS3D		99.27 51	99.12 55	99.74 45	99.18 209	99.75 24	99.56 115	99.57 44	98.45 60	99.49 90	99.85 27	97.77 87	99.94 41	98.33 129	99.84 59	99.52 124

tpm cat1		97.39 265	97.36 246	97.50 305	99.17 214	93.73 326	99.43 170	99.31 228	91.27 335	98.71 237	99.08 278	94.31 212	99.77 159	96.41 262	98.50 168	99.00 183

3Dnovator+	97.12 13	99.18 60	98.97 74	99.82 26	99.17 214	99.68 33	99.81 15	99.51 86	99.20 4	98.72 236	99.89 10	95.68 147	99.97 11	98.86 68	99.86 50	99.81 35

VPA-MVSNet		98.29 148	97.95 165	99.30 119	99.16 216	99.54 55	99.50 138	99.58 43	98.27 72	99.35 119	99.37 234	92.53 264	99.65 198	99.35 19	94.46 299	98.72 220

tpmrst		98.33 143	98.48 130	97.90 286	99.16 216	94.78 316	99.31 214	99.11 264	97.27 178	99.45 95	99.59 161	95.33 154	99.84 121	98.48 116	98.61 159	99.09 172

PatchmatchNet		98.31 145	98.36 134	98.19 269	99.16 216	95.32 306	99.27 225	98.92 286	97.37 171	99.37 113	99.58 164	94.90 179	99.70 189	97.43 206	99.21 120	99.54 118
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PatchFormer-LS_test		98.01 189	98.05 155	97.87 287	99.15 219	94.76 317	99.42 177	98.93 284	97.12 192	98.84 225	98.59 313	93.74 233	99.80 146	98.55 111	98.17 194	99.06 178

tpm2		97.44 263	97.34 251	97.74 297	99.15 219	94.36 321	99.45 161	98.94 283	93.45 324	98.90 216	99.44 215	91.35 293	99.59 210	97.31 211	98.07 205	99.29 158

CostFormer		97.72 236	97.73 198	97.71 298	99.15 219	94.02 324	99.54 124	99.02 276	94.67 297	99.04 195	99.35 245	92.35 272	99.77 159	98.50 115	97.94 209	99.34 155

TransMVSNet (Re)		97.15 271	96.58 274	98.86 199	99.12 222	98.85 148	99.49 147	98.91 289	95.48 288	97.16 304	99.80 68	93.38 235	99.11 286	94.16 310	91.73 327	98.62 273

3Dnovator	97.25 9	99.24 55	99.05 61	99.81 29	99.12 222	99.66 37	99.84 9	99.74 10	99.09 8	98.92 213	99.90 7	95.94 138	99.98 5	98.95 57	99.92 12	99.79 45

XVG-ACMP-BASELINE		97.83 214	97.71 200	98.20 268	99.11 224	96.33 287	99.41 181	99.52 77	98.06 99	99.05 194	99.50 194	89.64 310	99.73 173	97.73 176	97.38 238	98.53 296

FMVSNet5		96.43 282	96.19 279	97.15 308	99.11 224	95.89 295	99.32 211	99.52 77	94.47 306	98.34 271	99.07 279	87.54 331	97.07 340	92.61 326	95.72 270	98.47 300

MDTV_nov1_ep13			98.32 138		99.11 224	94.44 320	99.27 225	98.74 307	97.51 156	99.40 108	99.62 152	94.78 187	99.76 164	97.59 187	98.81 155

Patchmtry		97.75 231	97.40 242	98.81 206	99.10 227	98.87 145	99.11 264	99.33 221	94.83 294	98.81 227	99.38 230	94.33 210	99.02 295	96.10 265	95.57 273	98.53 296

dp		97.75 231	97.80 184	97.59 301	99.10 227	93.71 328	99.32 211	98.88 293	96.48 245	99.08 188	99.55 173	92.67 260	99.82 138	96.52 258	98.58 162	99.24 161

Baseline_NR-MVSNet		97.76 227	97.45 230	98.68 219	99.09 229	98.29 209	99.41 181	98.85 295	95.65 287	98.63 254	99.67 130	94.82 184	99.10 288	98.07 149	92.89 321	98.64 264

FC-MVSNet-test		98.75 122	98.62 121	99.15 142	99.08 230	99.45 70	99.86 8	99.60 35	98.23 76	98.70 243	99.82 47	96.80 113	99.22 273	99.07 48	96.38 257	98.79 207

USDC		97.34 266	97.20 262	97.75 296	99.07 231	95.20 309	98.51 333	99.04 274	97.99 109	98.31 272	99.86 23	89.02 314	99.55 213	95.67 276	97.36 239	98.49 298

TinyColmap		97.12 272	96.89 269	97.83 291	99.07 231	95.52 302	98.57 330	98.74 307	97.58 149	97.81 295	99.79 76	88.16 328	99.56 211	95.10 285	97.21 243	98.39 306

pm-mvs1		97.68 242	97.28 258	98.88 191	99.06 233	98.62 186	99.50 138	99.45 154	96.32 255	97.87 292	99.79 76	92.47 266	99.35 242	97.54 194	93.54 315	98.67 248

TR-MVS		97.76 227	97.41 241	98.82 205	99.06 233	97.87 227	98.87 311	98.56 325	96.63 231	98.68 245	99.22 268	92.49 265	99.65 198	95.40 281	97.79 212	98.95 200

PAPM		97.59 250	97.09 265	99.07 149	99.06 233	98.26 211	98.30 340	99.10 265	94.88 293	98.08 283	99.34 248	96.27 131	99.64 200	89.87 333	98.92 144	99.31 157

nrg030		98.64 130	98.42 132	99.28 124	99.05 236	99.69 32	99.81 15	99.46 142	98.04 101	99.01 198	99.82 47	96.69 119	99.38 231	99.34 23	94.59 298	98.78 208

tpmvs		97.98 191	98.02 157	97.84 290	99.04 237	94.73 318	99.31 214	99.20 255	96.10 279	98.76 233	99.42 218	94.94 174	99.81 142	96.97 231	98.45 170	98.97 187

OpenMVS	96.50 16	98.47 134	98.12 148	99.52 87	99.04 237	99.53 58	99.82 13	99.72 11	94.56 302	98.08 283	99.88 15	94.73 194	99.98 5	97.47 202	99.76 78	99.06 178

DWT-MVSNet_test		97.53 253	97.40 242	97.93 283	99.03 239	94.86 315	99.57 108	98.63 321	96.59 236	98.36 269	98.79 302	89.32 312	99.74 166	98.14 141	98.16 195	99.20 163

WR-MVS_H		98.13 166	97.87 179	98.90 181	99.02 240	98.84 149	99.70 45	99.59 38	97.27 178	98.40 266	99.19 270	95.53 149	99.23 270	98.34 128	93.78 313	98.61 282

tpm		97.67 245	97.55 215	98.03 275	99.02 240	95.01 313	99.43 170	98.54 327	96.44 247	99.12 178	99.34 248	91.83 281	99.60 208	97.75 174	96.46 255	99.48 135

UniMVSNet (Re)		98.29 148	98.00 159	99.13 146	99.00 242	99.36 78	99.49 147	99.51 86	97.95 112	98.97 208	99.13 274	96.30 130	99.38 231	98.36 127	93.34 316	98.66 259

v7		98.05 181	97.78 187	98.87 195	98.99 243	98.67 179	99.64 80	99.34 213	96.31 257	99.29 131	99.51 191	94.78 187	99.27 261	97.03 226	95.15 281	98.66 259

v10		97.85 210	97.52 218	98.86 199	98.99 243	98.67 179	99.75 36	99.41 176	95.70 286	98.98 207	99.41 221	94.75 193	99.23 270	96.01 268	94.63 297	98.67 248

PS-CasMVS		97.93 200	97.59 214	98.95 164	98.99 243	99.06 110	99.68 57	99.52 77	97.13 190	98.31 272	99.68 125	92.44 270	99.05 291	98.51 114	94.08 308	98.75 215

PatchT		97.03 275	96.44 276	98.79 209	98.99 243	98.34 208	99.16 251	99.07 270	92.13 330	99.52 83	97.31 342	94.54 203	98.98 300	88.54 336	98.73 158	99.03 180

Anonymous20240521		98.30 146	98.00 159	99.18 138	98.98 247	99.46 68	99.78 22	99.49 106	96.91 215	98.00 288	99.25 264	96.51 123	99.38 231	98.15 140	94.95 287	98.71 222

v13		96.24 290	95.58 295	98.25 261	98.98 247	98.83 152	99.75 36	99.29 235	94.35 309	93.89 334	97.60 335	95.17 164	98.11 326	94.27 307	86.86 345	97.81 327

V42		98.06 175	97.79 185	98.86 199	98.98 247	98.84 149	99.69 48	99.34 213	96.53 238	99.30 127	99.37 234	94.67 197	99.32 249	97.57 190	94.66 295	98.42 303

LF4IMVS		97.52 254	97.46 229	97.70 299	98.98 247	95.55 299	99.29 220	98.82 298	98.07 95	98.66 246	99.64 143	89.97 307	99.61 207	97.01 227	96.68 249	97.94 323

v1neww		98.12 168	97.84 180	98.93 168	98.97 251	98.81 161	99.66 68	99.35 205	96.49 239	99.29 131	99.37 234	95.02 169	99.32 249	97.73 176	94.73 290	98.67 248

v7new		98.12 168	97.84 180	98.93 168	98.97 251	98.81 161	99.66 68	99.35 205	96.49 239	99.29 131	99.37 234	95.02 169	99.32 249	97.73 176	94.73 290	98.67 248

CP-MVSNet		98.09 172	97.78 187	99.01 155	98.97 251	99.24 92	99.67 59	99.46 142	97.25 180	98.48 263	99.64 143	93.79 229	99.06 290	98.63 95	94.10 307	98.74 218

v16		96.39 285	95.76 291	98.26 257	98.96 254	98.81 161	99.76 28	99.28 242	94.57 300	94.10 326	97.70 328	95.04 168	98.16 320	94.70 293	87.77 338	97.80 329

v12		96.24 290	95.58 295	98.23 264	98.96 254	98.81 161	99.76 28	99.29 235	94.42 308	93.85 335	97.60 335	95.12 165	98.09 327	94.32 304	86.85 346	97.80 329

pcd1.5k->3k		40.85 338	43.49 340	32.93 351	98.95 256	0.00 369	0.00 360	99.53 73	0.00 364	0.00 366	0.27 366	95.32 155	0.00 366	0.00 363	97.30 240	98.80 206

v18		96.42 283	95.80 290	98.26 257	98.95 256	98.82 159	99.76 28	99.28 242	94.58 299	94.12 325	97.70 328	95.22 162	98.16 320	94.83 291	87.80 337	97.79 334

v8		97.95 199	97.63 211	98.93 168	98.95 256	98.81 161	99.80 19	99.41 176	96.03 280	99.10 183	99.42 218	94.92 177	99.30 255	96.94 234	94.08 308	98.66 259

v17		96.42 283	95.81 288	98.25 261	98.94 259	98.80 166	99.76 28	99.28 242	94.57 300	94.18 324	97.71 327	95.23 161	98.16 320	94.86 289	87.73 339	97.80 329

v15		96.28 287	95.62 293	98.25 261	98.94 259	98.83 152	99.76 28	99.29 235	94.52 304	94.02 329	97.61 334	95.02 169	98.13 324	94.53 295	86.92 342	97.80 329

v6		98.12 168	97.84 180	98.94 165	98.94 259	98.83 152	99.66 68	99.34 213	96.49 239	99.30 127	99.37 234	94.95 173	99.34 245	97.77 171	94.74 289	98.67 248

V14		96.26 288	95.60 294	98.26 257	98.94 259	98.83 152	99.76 28	99.29 235	94.49 305	93.96 331	97.66 331	94.99 172	98.13 324	94.41 298	86.90 343	97.80 329

V9		96.25 289	95.58 295	98.26 257	98.94 259	98.83 152	99.75 36	99.29 235	94.45 307	93.96 331	97.62 333	94.94 174	98.14 323	94.40 299	86.87 344	97.81 327

v11		96.23 292	95.57 298	98.21 267	98.93 264	98.83 152	99.72 42	99.29 235	94.29 310	94.05 328	97.64 332	94.88 181	98.04 328	92.89 323	88.43 335	97.77 335

TESTMET0.1,1		97.55 251	97.27 260	98.40 246	98.93 264	96.53 280	98.67 324	97.61 350	96.96 210	98.64 253	99.28 260	88.63 322	99.45 219	97.30 212	99.38 110	99.21 162

v1		98.05 181	97.76 194	98.93 168	98.92 266	98.80 166	99.57 108	99.35 205	96.39 253	99.28 135	99.36 241	94.86 182	99.32 249	97.38 208	94.72 292	98.68 237

UniMVSNet_NR-MVSNet		98.22 155	97.97 163	98.96 162	98.92 266	98.98 126	99.48 152	99.53 73	97.76 133	98.71 237	99.46 211	96.43 127	99.22 273	98.57 105	92.87 322	98.69 232

v1141		98.05 181	97.76 194	98.91 177	98.91 268	98.78 170	99.57 108	99.35 205	96.41 251	99.23 157	99.36 241	94.93 176	99.27 261	97.38 208	94.72 292	98.68 237

divwei89l23v2f112		98.06 175	97.78 187	98.91 177	98.90 269	98.77 171	99.57 108	99.35 205	96.45 246	99.24 152	99.37 234	94.92 177	99.27 261	97.50 198	94.71 294	98.68 237

v2v482		98.06 175	97.77 191	98.92 173	98.90 269	98.82 159	99.57 108	99.36 201	96.65 229	99.19 168	99.35 245	94.20 214	99.25 267	97.72 180	94.97 285	98.69 232

LP		97.04 274	96.80 270	97.77 295	98.90 269	95.23 308	98.97 297	99.06 272	94.02 313	98.09 282	99.41 221	93.88 226	98.82 311	90.46 331	98.42 172	99.26 160

1314		98.68 126	98.54 129	99.11 147	98.89 272	98.65 182	99.27 225	99.49 106	96.89 216	97.99 289	99.56 170	97.72 89	99.83 129	97.74 175	99.27 118	98.84 203

OPM-MVS		98.19 161	98.10 149	98.45 240	98.88 273	97.07 256	99.28 222	99.38 192	98.57 53	99.22 159	99.81 57	92.12 274	99.66 196	98.08 147	97.54 224	98.61 282

v1192		97.81 218	97.44 236	98.91 177	98.88 273	98.68 178	99.51 133	99.34 213	96.18 268	99.20 165	99.34 248	94.03 222	99.36 239	95.32 283	95.18 279	98.69 232

EPMVS		97.82 217	97.65 209	98.35 249	98.88 273	95.98 293	99.49 147	94.71 359	97.57 150	99.26 143	99.48 203	92.46 269	99.71 183	97.87 161	99.08 130	99.35 154

v1144		97.98 191	97.69 201	98.85 202	98.87 276	98.66 181	99.54 124	99.35 205	96.27 260	99.23 157	99.35 245	94.67 197	99.23 270	96.73 249	95.16 280	98.68 237

DU-MVS		98.08 174	97.79 185	98.96 162	98.87 276	98.98 126	99.41 181	99.45 154	97.87 118	98.71 237	99.50 194	94.82 184	99.22 273	98.57 105	92.87 322	98.68 237

NR-MVSNet		97.97 194	97.61 212	99.02 154	98.87 276	99.26 90	99.47 157	99.42 174	97.63 146	97.08 305	99.50 194	95.07 167	99.13 283	97.86 162	93.59 314	98.68 237

WR-MVS		98.06 175	97.73 198	99.06 150	98.86 279	99.25 91	99.19 248	99.35 205	97.30 176	98.66 246	99.43 216	93.94 224	99.21 277	98.58 103	94.28 303	98.71 222

v1240		97.69 240	97.32 254	98.79 209	98.85 280	98.43 205	99.48 152	99.36 201	96.11 275	99.27 139	99.36 241	93.76 231	99.24 269	94.46 297	95.23 278	98.70 227

test_0402		96.64 277	96.24 278	97.85 289	98.85 280	96.43 284	99.44 165	99.26 248	93.52 321	96.98 308	99.52 188	88.52 323	99.20 278	92.58 327	97.50 227	97.93 324

v144192		97.92 203	97.60 213	98.87 195	98.83 282	98.65 182	99.55 121	99.34 213	96.20 266	99.32 124	99.40 225	94.36 209	99.26 266	96.37 263	95.03 284	98.70 227

v1921920		97.80 221	97.45 230	98.84 203	98.80 283	98.53 193	99.52 129	99.34 213	96.15 272	99.24 152	99.47 207	93.98 223	99.29 257	95.40 281	95.13 282	98.69 232

v52		97.79 223	97.50 222	98.66 222	98.80 283	98.62 186	99.87 4	99.44 163	95.87 283	99.01 198	99.46 211	94.44 208	99.33 246	96.65 256	93.96 311	98.05 316

gg-mvs-nofinetune		96.17 295	95.32 302	98.73 215	98.79 285	98.14 216	99.38 195	94.09 360	91.07 338	98.07 286	91.04 355	89.62 311	99.35 242	96.75 248	99.09 129	98.68 237

V4		97.80 221	97.51 220	98.67 221	98.79 285	98.63 184	99.87 4	99.44 163	95.87 283	99.01 198	99.46 211	94.52 204	99.33 246	96.64 257	93.97 310	98.05 316

test-LLR		98.06 175	97.90 168	98.55 231	98.79 285	97.10 252	98.67 324	97.75 340	97.34 172	98.61 257	98.85 297	94.45 206	99.45 219	97.25 213	99.38 110	99.10 168

test-mter		97.49 260	97.13 264	98.55 231	98.79 285	97.10 252	98.67 324	97.75 340	96.65 229	98.61 257	98.85 297	88.23 327	99.45 219	97.25 213	99.38 110	99.10 168

PS-MVSNAJss		98.92 100	98.92 81	98.90 181	98.78 289	98.53 193	99.78 22	99.54 63	98.07 95	99.00 205	99.76 91	99.01 12	99.37 235	99.13 43	97.23 242	98.81 205

MVS		97.28 268	96.55 275	99.48 92	98.78 289	98.95 134	99.27 225	99.39 186	83.53 349	98.08 283	99.54 176	96.97 109	99.87 105	94.23 308	99.16 123	99.63 102

TranMVSNet+NR-MVSNet		97.93 200	97.66 204	98.76 214	98.78 289	98.62 186	99.65 78	99.49 106	97.76 133	98.49 262	99.60 159	94.23 213	98.97 307	98.00 152	92.90 320	98.70 227

PEN-MVS		97.76 227	97.44 236	98.72 216	98.77 292	98.54 192	99.78 22	99.51 86	97.06 205	98.29 274	99.64 143	92.63 261	98.89 310	98.09 143	93.16 318	98.72 220

v7n		97.87 208	97.52 218	98.92 173	98.76 293	98.58 190	99.84 9	99.46 142	96.20 266	98.91 214	99.70 114	94.89 180	99.44 224	96.03 267	93.89 312	98.75 215

v148		97.79 223	97.55 215	98.50 233	98.74 294	97.72 240	99.54 124	99.33 221	96.26 261	98.90 216	99.51 191	94.68 196	99.14 280	97.83 164	93.15 319	98.63 271

JIA-IIPM		97.50 258	97.02 267	98.93 168	98.73 295	97.80 236	99.30 216	98.97 280	91.73 334	98.91 214	94.86 349	95.10 166	99.71 183	97.58 188	97.98 208	99.28 159

Gipuma		90.99 322	90.15 323	93.51 326	98.73 295	90.12 341	93.98 356	99.45 154	79.32 351	92.28 340	94.91 348	69.61 352	97.98 331	87.42 339	95.67 271	92.45 352
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
EU-MVSNet		97.98 191	98.03 156	97.81 293	98.72 297	96.65 278	99.66 68	99.66 25	98.09 91	98.35 270	99.82 47	95.25 160	98.01 330	97.41 207	95.30 277	98.78 208

K. test v3		97.10 273	96.79 271	98.01 278	98.72 297	96.33 287	99.87 4	97.05 354	97.59 147	96.16 315	99.80 68	88.71 318	99.04 292	96.69 252	96.55 254	98.65 262

OurMVSNet-221017-0		97.88 206	97.77 191	98.19 269	98.71 299	96.53 280	99.88 1	99.00 277	97.79 130	98.78 231	99.94 3	91.68 287	99.35 242	97.21 215	96.99 248	98.69 232

test_djsdf		98.67 127	98.57 127	98.98 159	98.70 300	98.91 142	99.88 1	99.46 142	97.55 152	99.22 159	99.88 15	95.73 146	99.28 258	99.03 50	97.62 217	98.75 215

pmmvs6		96.53 280	96.09 281	97.82 292	98.69 301	95.47 303	99.37 197	99.47 132	93.46 323	97.41 299	99.78 82	87.06 334	99.33 246	96.92 236	92.70 324	98.65 262

v748		97.52 254	97.23 261	98.41 245	98.69 301	97.23 249	99.87 4	99.45 154	95.72 285	98.51 260	99.53 183	94.13 218	99.30 255	96.78 247	92.39 326	98.70 227

lessismore_v0				97.79 294	98.69 301	95.44 305		94.75 358		95.71 319	99.87 20	88.69 319	99.32 249	95.89 269	94.93 288	98.62 273

mvs_tets		98.40 140	98.23 143	98.91 177	98.67 304	98.51 199	99.66 68	99.53 73	98.19 78	98.65 252	99.81 57	92.75 247	99.44 224	99.31 26	97.48 231	98.77 211

SixPastTwentyTwo		97.50 258	97.33 253	98.03 275	98.65 305	96.23 290	99.77 25	98.68 319	97.14 189	97.90 291	99.93 4	90.45 300	99.18 279	97.00 228	96.43 256	98.67 248

UnsupCasMVSNet_eth		96.44 281	96.12 280	97.40 307	98.65 305	95.65 296	99.36 201	99.51 86	97.13 190	96.04 318	98.99 286	88.40 325	98.17 319	96.71 250	90.27 330	98.40 305

DTE-MVSNet		97.51 257	97.19 263	98.46 239	98.63 307	98.13 217	99.84 9	99.48 116	96.68 227	97.97 290	99.67 130	92.92 243	98.56 316	96.88 244	92.60 325	98.70 227

our_test_3		97.65 247	97.68 202	97.55 302	98.62 308	94.97 314	98.84 313	99.30 230	96.83 220	98.19 278	99.34 248	97.01 108	99.02 295	95.00 288	96.01 264	98.64 264

ppachtmachnet_test		97.49 260	97.45 230	97.61 300	98.62 308	95.24 307	98.80 315	99.46 142	96.11 275	98.22 276	99.62 152	96.45 125	98.97 307	93.77 312	95.97 266	98.61 282

pmmvs4		98.13 166	97.90 168	98.81 206	98.61 310	98.87 145	98.99 290	99.21 254	96.44 247	99.06 193	99.58 164	95.90 140	99.11 286	97.18 219	96.11 262	98.46 302

jajsoiax		98.43 137	98.28 141	98.88 191	98.60 311	98.43 205	99.82 13	99.53 73	98.19 78	98.63 254	99.80 68	93.22 239	99.44 224	99.22 34	97.50 227	98.77 211

cascas		97.69 240	97.43 239	98.48 236	98.60 311	97.30 243	98.18 344	99.39 186	92.96 326	98.41 265	98.78 304	93.77 230	99.27 261	98.16 138	98.61 159	98.86 202

pmmvs5		97.52 254	97.30 256	98.16 271	98.57 313	96.73 274	99.27 225	98.90 291	96.14 273	98.37 268	99.53 183	91.54 292	99.14 280	97.51 197	95.87 267	98.63 271

GG-mvs-BLEND				98.45 240	98.55 314	98.16 214	99.43 170	93.68 361		97.23 302	98.46 316	89.30 313	99.22 273	95.43 280	98.22 184	97.98 321

gm-plane-assit					98.54 315	92.96 333			94.65 298		99.15 272		99.64 200	97.56 192

anonymousdsp		98.44 136	98.28 141	98.94 165	98.50 316	98.96 133	99.77 25	99.50 101	97.07 203	98.87 219	99.77 88	94.76 192	99.28 258	98.66 92	97.60 218	98.57 294

N_pmnet		94.95 309	95.83 287	92.31 332	98.47 317	79.33 355	99.12 258	92.81 365	93.87 316	97.68 297	99.13 274	93.87 227	99.01 297	91.38 329	96.19 261	98.59 290

MS-PatchMatch		97.24 270	97.32 254	96.99 311	98.45 318	93.51 331	98.82 314	99.32 227	97.41 168	98.13 281	99.30 257	88.99 315	99.56 211	95.68 275	99.80 70	97.90 326

test0.0.03 1		97.71 239	97.42 240	98.56 229	98.41 319	97.82 231	98.78 317	98.63 321	97.34 172	98.05 287	98.98 289	94.45 206	98.98 300	95.04 287	97.15 246	98.89 201

testpf		95.66 301	96.02 284	94.58 325	98.35 320	92.32 336	97.25 352	97.91 339	92.83 327	97.03 307	98.99 286	88.69 319	98.61 315	95.72 273	97.40 236	92.80 350

EPNet_dtu		98.03 184	97.96 164	98.23 264	98.27 321	95.54 301	99.23 238	98.75 304	99.02 10	97.82 294	99.71 111	96.11 134	99.48 216	93.04 322	99.65 99	99.69 80
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MDA-MVSNet-bldmvs		94.96 308	93.98 313	97.92 284	98.24 322	97.27 245	99.15 254	99.33 221	93.80 317	80.09 355	99.03 284	88.31 326	97.86 334	93.49 316	94.36 302	98.62 273

MDA-MVSNet_test_wron		95.45 303	94.60 308	98.01 278	98.16 323	97.21 250	99.11 264	99.24 251	93.49 322	80.73 354	98.98 289	93.02 240	98.18 318	94.22 309	94.45 300	98.64 264

new_pmnet		96.38 286	96.03 282	97.41 306	98.13 324	95.16 312	99.05 275	99.20 255	93.94 315	97.39 300	98.79 302	91.61 291	99.04 292	90.43 332	95.77 269	98.05 316

YYNet1		95.36 305	94.51 310	97.92 284	97.89 325	97.10 252	99.10 266	99.23 252	93.26 325	80.77 353	99.04 283	92.81 246	98.02 329	94.30 305	94.18 306	98.64 264

DSMNet-mixed		97.25 269	97.35 248	96.95 313	97.84 326	93.61 330	99.57 108	96.63 355	96.13 274	98.87 219	98.61 312	94.59 200	97.70 337	95.08 286	98.86 150	99.55 116

EG-PatchMatch MVS		95.97 298	95.69 292	96.81 316	97.78 327	92.79 334	99.16 251	98.93 284	96.16 270	94.08 327	99.22 268	82.72 347	99.47 217	95.67 276	97.50 227	98.17 313

DI_MVS_plusplus_test		97.45 262	96.79 271	99.44 102	97.76 328	99.04 112	99.21 245	98.61 323	97.74 136	94.01 330	98.83 299	87.38 333	99.83 129	98.63 95	98.90 146	99.44 146

test_normal		97.44 263	96.77 273	99.44 102	97.75 329	99.00 124	99.10 266	98.64 320	97.71 139	93.93 333	98.82 300	87.39 332	99.83 129	98.61 99	98.97 138	99.49 133

MVP-Stereo		97.81 218	97.75 197	97.99 280	97.53 330	96.60 279	98.96 299	98.85 295	97.22 184	97.23 302	99.36 241	95.28 156	99.46 218	95.51 278	99.78 74	97.92 325
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
test20.03		96.12 296	95.96 285	96.63 318	97.44 331	95.45 304	99.51 133	99.38 192	96.55 237	96.16 315	99.25 264	93.76 231	96.17 345	87.35 341	94.22 305	98.27 310

UnsupCasMVSNet_bld		93.53 317	92.51 319	96.58 320	97.38 332	93.82 325	98.24 341	99.48 116	91.10 337	93.10 338	96.66 344	74.89 350	98.37 317	94.03 311	87.71 340	97.56 339

MIMVSNet1		95.51 302	95.04 305	96.92 314	97.38 332	95.60 297	99.52 129	99.50 101	93.65 319	96.97 309	99.17 271	85.28 340	96.56 344	88.36 337	95.55 274	98.60 289

OpenMVS_ROB	92.34 20	94.38 313	93.70 314	96.41 321	97.38 332	93.17 332	99.06 273	98.75 304	86.58 346	94.84 323	98.26 321	81.53 349	99.32 249	89.01 335	97.87 211	96.76 341

Anonymous20231206		96.22 293	96.03 282	96.79 317	97.31 335	94.14 323	99.63 82	99.08 267	96.17 269	97.04 306	99.06 281	93.94 224	97.76 336	86.96 342	95.06 283	98.47 300

CMPMVS	69.68 23	94.13 314	94.90 306	91.84 333	97.24 336	80.01 354	98.52 332	99.48 116	89.01 343	91.99 341	99.67 130	85.67 338	99.13 283	95.44 279	97.03 247	96.39 343
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
EPNet		98.86 105	98.71 108	99.30 119	97.20 337	98.18 213	99.62 85	98.91 289	99.28 2	98.63 254	99.81 57	95.96 135	99.99 1	99.24 32	99.72 85	99.73 65
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
testus		94.61 310	95.30 303	92.54 331	96.44 338	84.18 347	98.36 336	99.03 275	94.18 311	96.49 311	98.57 314	88.74 317	95.09 349	87.41 340	98.45 170	98.36 309

Test4		95.05 307	93.67 315	99.22 136	96.07 339	98.94 137	99.20 247	99.27 247	97.71 139	89.96 347	97.59 337	66.18 354	99.25 267	98.06 150	98.96 140	99.47 139

Patchmatch-RL test		95.84 299	95.81 288	95.95 322	95.61 340	90.57 340	98.24 341	98.39 328	95.10 292	95.20 320	98.67 307	94.78 187	97.77 335	96.28 264	90.02 331	99.51 129

PM-MVS		92.96 318	92.23 320	95.14 324	95.61 340	89.98 342	99.37 197	98.21 333	94.80 295	95.04 322	97.69 330	65.06 355	97.90 333	94.30 305	89.98 332	97.54 340

pmmvs-eth3d		95.34 306	94.73 307	97.15 308	95.53 342	95.94 294	99.35 206	99.10 265	95.13 290	93.55 336	97.54 338	88.15 329	97.91 332	94.58 294	89.69 333	97.61 337

test2356		94.07 316	94.46 311	92.89 329	95.18 343	86.13 345	97.60 350	99.06 272	93.61 320	96.15 317	98.28 320	85.60 339	93.95 351	86.68 344	98.00 207	98.59 290

new-patchmatchnet		94.48 311	94.08 312	95.67 323	95.08 344	92.41 335	99.18 249	99.28 242	94.55 303	93.49 337	97.37 341	87.86 330	97.01 341	91.57 328	88.36 336	97.61 337

pmmvs3		94.09 315	93.25 317	96.60 319	94.76 345	94.49 319	98.92 306	98.18 335	89.66 340	96.48 312	98.06 322	86.28 335	97.33 339	89.68 334	87.20 341	97.97 322

testing_2		94.44 312	92.93 318	98.98 159	94.16 346	99.00 124	99.42 177	99.28 242	96.60 234	84.86 349	96.84 343	70.91 351	99.27 261	98.23 134	96.08 263	98.68 237

1111		92.30 320	92.21 321	92.55 330	93.30 347	86.27 343	99.15 254	98.74 307	91.94 331	90.85 344	97.82 325	84.18 343	95.21 347	79.65 350	94.27 304	96.19 344

.test1245		83.42 327	86.17 325	75.15 349	93.30 347	86.27 343	99.15 254	98.74 307	91.94 331	90.85 344	97.82 325	84.18 343	95.21 347	79.65 350	39.90 360	43.98 361

test1235678		92.91 319	93.30 316	91.71 335	93.14 349	83.01 349	98.75 320	98.58 324	92.80 328	92.45 339	97.91 324	88.51 324	93.54 352	82.26 348	95.35 276	98.59 290

ambc				93.06 328	92.68 350	82.36 351	98.47 334	98.73 316		95.09 321	97.41 339	55.55 358	99.10 288	96.42 261	91.32 328	97.71 336

test12356		91.74 321	92.19 322	90.37 338	91.22 351	82.41 350	98.61 328	98.28 330	90.66 339	91.82 342	97.92 323	84.90 341	92.61 353	81.64 349	94.66 295	96.09 345

EMVS		80.02 331	79.22 332	82.43 347	91.19 352	76.40 358	97.55 351	92.49 367	66.36 359	83.01 352	91.27 353	64.63 356	85.79 361	65.82 359	60.65 355	85.08 358

E-PMN		80.61 330	79.88 331	82.81 345	90.75 353	76.38 359	97.69 348	95.76 357	66.44 358	83.52 350	92.25 352	62.54 357	87.16 360	68.53 358	61.40 354	84.89 359

PMMVS2		86.87 324	85.37 327	91.35 337	90.21 354	83.80 348	98.89 309	97.45 352	83.13 350	91.67 343	95.03 347	48.49 360	94.70 350	85.86 345	77.62 351	95.54 346

TDRefinement		95.42 304	94.57 309	97.97 281	89.83 355	96.11 292	99.48 152	98.75 304	96.74 223	96.68 310	99.88 15	88.65 321	99.71 183	98.37 125	82.74 349	98.09 314

no-one		83.04 328	80.12 330	91.79 334	89.44 356	85.65 346	99.32 211	98.32 329	89.06 342	79.79 357	89.16 357	44.86 362	96.67 343	84.33 347	46.78 358	93.05 349

LCM-MVSNet		86.80 325	85.22 328	91.53 336	87.81 357	80.96 353	98.23 343	98.99 278	71.05 354	90.13 346	96.51 345	48.45 361	96.88 342	90.51 330	85.30 348	96.76 341

testmv		87.91 323	87.80 324	88.24 339	87.68 358	77.50 357	99.07 269	97.66 349	89.27 341	86.47 348	96.22 346	68.35 353	92.49 355	76.63 354	88.82 334	94.72 348

FPMVS		84.93 326	85.65 326	82.75 346	86.77 359	63.39 364	98.35 338	98.92 286	74.11 353	83.39 351	98.98 289	50.85 359	92.40 356	84.54 346	94.97 285	92.46 351

PNet_i23d		79.43 332	77.68 333	84.67 342	86.18 360	71.69 362	96.50 354	93.68 361	75.17 352	71.33 358	91.18 354	32.18 365	90.62 357	78.57 353	74.34 352	91.71 354

wuyk23d		40.18 339	41.29 342	36.84 350	86.18 360	49.12 366	79.73 359	22.81 369	27.64 361	25.46 365	28.45 365	21.98 367	48.89 363	55.80 360	23.56 363	12.51 363

MVE	76.82 21	76.91 334	74.31 336	84.70 341	85.38 362	76.05 360	96.88 353	93.17 363	67.39 357	71.28 359	89.01 358	21.66 370	87.69 359	71.74 357	72.29 353	90.35 355
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuykxyi23d		74.42 336	71.19 337	84.14 344	76.16 363	74.29 361	96.00 355	92.57 366	69.57 355	63.84 361	87.49 359	21.98 367	88.86 358	75.56 356	57.50 356	89.26 357

ANet_high		77.30 333	74.86 335	84.62 343	75.88 364	77.61 356	97.63 349	93.15 364	88.81 344	64.27 360	89.29 356	36.51 363	83.93 362	75.89 355	52.31 357	92.33 353

PMVS	70.75 22	75.98 335	74.97 334	79.01 348	70.98 365	55.18 365	93.37 357	98.21 333	65.08 360	61.78 362	93.83 350	21.74 369	92.53 354	78.59 352	91.12 329	89.34 356
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tmp_tt		82.80 329	81.52 329	86.66 340	66.61 366	68.44 363	92.79 358	97.92 337	68.96 356	80.04 356	99.85 27	85.77 337	96.15 346	97.86 162	43.89 359	95.39 347

test123		39.01 341	42.50 341	28.53 352	39.17 367	20.91 367	98.75 320	19.17 370	19.83 363	38.57 363	66.67 361	33.16 364	15.42 364	37.50 362	29.66 362	49.26 360

testmvs		39.17 340	43.78 339	25.37 353	36.04 368	16.84 368	98.36 336	26.56 368	20.06 362	38.51 364	67.32 360	29.64 366	15.30 365	37.59 361	39.90 360	43.98 361

cdsmvs_eth3d_5k		24.64 342	32.85 343	0.00 354	0.00 369	0.00 369	0.00 360	99.51 86	0.00 364	0.00 366	99.56 170	96.58 121	0.00 366	0.00 363	0.00 364	0.00 364

pcd_1.5k_mvsjas		8.27 344	11.03 345	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.27 366	99.01 12	0.00 366	0.00 363	0.00 364	0.00 364

sosnet-low-res		0.02 345	0.03 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.27 366	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

sosnet		0.02 345	0.03 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.27 366	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

uncertanet		0.02 345	0.03 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.27 366	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

Regformer		0.02 345	0.03 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.27 366	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

ab-mvs-re		8.30 343	11.06 344	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	99.58 164	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

uanet		0.02 345	0.03 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.27 366	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

GSMVS																99.52 124

test_part1				0.00 354		0.00 369	0.00 360	99.48 116				0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

sam_mvs1												94.86 182				99.52 124

sam_mvs												94.72 195

MTGPA								99.47 132

test_post1							99.23 238				65.14 363	94.18 217	99.71 183	97.58 188

test_post											65.99 362	94.65 199	99.73 173

patchmatchnet-post											98.70 306	94.79 186	99.74 166

MTMP							99.54 124	98.88 293

test9_res														97.49 199	99.72 85	99.75 55

agg_prior2														97.21 215	99.73 84	99.75 55

test_prior4						99.56 52	98.99 290

test_prior2							98.96 299		98.34 67	99.01 198	99.52 188	98.68 51		97.96 154	99.74 81

旧先验2							98.96 299		96.70 226	99.47 92			99.94 41	98.19 135

新几何2							99.01 288

无先验							98.99 290	99.51 86	96.89 216				99.93 56	97.53 195		99.72 71

原ACMM2							98.95 303

testdata2													99.95 34	96.67 253

segment_acmp												98.96 21

testdata1							98.85 312		98.32 70

plane_prior5								99.47 132					99.69 192	97.78 169	97.63 215	98.67 248

plane_prior4											99.61 156

plane_prior3						97.00 262			98.69 47	99.11 180

plane_prior2							99.39 190		98.97 22

plane_prior						96.97 265	99.21 245		98.45 60						97.60 218

n2								0.00 371

nn								0.00 371

door-mid								98.05 336

test11								99.35 205

door								97.92 337

HQP5-MVS						96.83 270

BP-MVS														97.19 217

HQP4-MVS										98.66 246			99.64 200			98.64 264

HQP3-MVS								99.39 186							97.58 220

HQP2-MVS												92.47 266

MDTV_nov1_ep13_2view						95.18 311	99.35 206		96.84 219	99.58 67		95.19 163		97.82 165		99.46 142

ACMMP++_ref															97.19 244

ACMMP++															97.43 235

Test By Simon												98.75 45

High-resolution multi-view benchmark