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.

SMA-MVS		99.71 32	99.62 44	99.98 16	99.99 45	99.95 19	100.00 1	99.42 121	97.61 123	100.00 1	100.00 1	99.55 24	100.00 1	100.00 1	100.00 1	100.00 1

test_part1								99.42 121				99.53 26			100.00 1	100.00 1

ESAPD		99.76 15	99.69 18	100.00 1	100.00 1	99.99 1	100.00 1	99.42 121	98.23 64	100.00 1	100.00 1	99.53 26	100.00 1	100.00 1	100.00 1	100.00 1

CHOSEN 280x420		99.85 3	99.87 1	99.80 95	99.99 45	99.97 8	99.97 200	99.98 13	98.96 21	100.00 1	100.00 1	99.96 3	99.42 207	100.00 1	100.00 1	100.00 1

MP-MVS-pluss		99.61 55	99.50 57	99.97 24	99.98 72	99.92 36	100.00 1	99.42 121	97.53 131	99.77 139	100.00 1	98.77 105	100.00 1	99.99 45	100.00 1	99.99 89
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HSP-MVS		99.81 9	99.77 8	99.94 59	100.00 1	99.86 67	100.00 1	99.42 121	98.87 29	100.00 1	100.00 1	99.65 18	99.96 114	100.00 1	100.00 1	100.00 1

TSAR-MVS + MP.		99.82 7	99.77 8	99.99 5	100.00 1	99.96 10	100.00 1	99.43 115	99.05 12	100.00 1	100.00 1	99.45 43	99.99 82	100.00 1	100.00 1	100.00 1

ACMMP_Plus		99.67 46	99.57 51	99.97 24	99.98 72	99.92 36	100.00 1	99.42 121	97.83 98	100.00 1	100.00 1	98.89 99	100.00 1	99.98 59	100.00 1	100.00 1

zzz-MVS		99.68 43	99.59 47	99.97 24	99.99 45	99.91 39	100.00 1	99.42 121	98.32 61	99.94 109	100.00 1	98.65 109	100.00 1	99.96 66	100.00 1	100.00 1

MTAPA		99.68 43	99.59 47	99.97 24	99.99 45	99.91 39	100.00 1	99.42 121	98.32 61	99.94 109	100.00 1	98.65 109	100.00 1	99.96 66	100.00 1	100.00 1

test9_res														100.00 1	100.00 1	100.00 1

train_agg		99.71 32	99.63 39	99.97 24	100.00 1	99.95 19	100.00 1	99.42 121	97.70 109	100.00 1	100.00 1	99.51 31	99.97 99	100.00 1	100.00 1	100.00 1

agg_prior3		99.71 32	99.63 39	99.97 24	100.00 1	99.95 19	100.00 1	99.42 121	97.71 108	100.00 1	100.00 1	99.51 31	99.97 99	100.00 1	100.00 1	100.00 1

agg_prior1		99.71 32	99.63 39	99.95 47	100.00 1	99.88 59	100.00 1	99.42 121	97.72 106	100.00 1	100.00 1	99.51 31	99.97 99	100.00 1	100.00 1	100.00 1

agg_prior2														100.00 1	100.00 1	100.00 1

HFP-MVS		99.74 23	99.67 27	99.96 36	100.00 1	99.89 49	100.00 1	99.76 46	97.95 89	100.00 1	100.00 1	99.31 55	100.00 1	99.99 45	100.00 1	100.00 1

region2R		99.72 29	99.64 35	99.97 24	100.00 1	99.90 45	100.00 1	99.74 53	97.86 97	100.00 1	100.00 1	99.19 73	100.00 1	99.99 45	100.00 1	100.00 1

#test#		99.75 18	99.68 22	99.96 36	100.00 1	99.89 49	100.00 1	99.76 46	98.07 77	100.00 1	100.00 1	99.31 55	100.00 1	99.99 45	100.00 1	100.00 1

EI-MVSNet-UG-set		99.69 40	99.63 39	99.87 81	99.99 45	99.64 105	99.95 209	99.44 106	98.35 59	100.00 1	100.00 1	98.98 88	99.97 99	99.98 59	100.00 1	100.00 1

EI-MVSNet-Vis-set		99.70 37	99.64 35	99.87 81	100.00 1	99.64 105	99.98 193	99.44 106	98.35 59	99.99 76	100.00 1	99.04 83	99.96 114	99.98 59	100.00 1	100.00 1

Regformer-3		99.73 26	99.65 31	99.96 36	100.00 1	99.89 49	100.00 1	99.44 106	98.40 52	100.00 1	100.00 1	99.03 86	99.97 99	99.99 45	100.00 1	100.00 1

Regformer-4		99.73 26	99.65 31	99.95 47	100.00 1	99.89 49	100.00 1	99.44 106	98.40 52	100.00 1	100.00 1	99.03 86	99.97 99	99.99 45	100.00 1	100.00 1

Regformer-1		99.75 18	99.68 22	99.98 16	100.00 1	99.94 28	100.00 1	99.44 106	98.43 49	100.00 1	100.00 1	99.23 69	99.99 82	99.99 45	100.00 1	100.00 1

Regformer-2		99.75 18	99.68 22	99.97 24	100.00 1	99.94 28	100.00 1	99.44 106	98.42 51	100.00 1	100.00 1	99.22 70	99.99 82	99.99 45	100.00 1	100.00 1

HPM-MVS++		99.82 7	99.76 10	99.99 5	99.99 45	99.98 6	100.00 1	99.83 40	98.88 27	99.96 88	100.00 1	99.21 71	100.00 1	100.00 1	100.00 1	99.99 89

XVS		99.79 12	99.73 14	99.98 16	100.00 1	99.94 28	100.00 1	99.75 50	98.67 40	100.00 1	100.00 1	99.16 76	100.00 1	100.00 1	100.00 1	100.00 1

test_prior3		99.81 9	99.78 6	99.90 72	100.00 1	99.75 85	100.00 1	99.73 55	98.82 33	100.00 1	100.00 1	99.47 40	99.97 99	100.00 1	100.00 1	100.00 1

test_prior2							100.00 1		98.82 33	100.00 1	100.00 1	99.47 40		100.00 1	100.00 1

X-MVStestdata		97.04 204	96.06 233	99.98 16	100.00 1	99.94 28	100.00 1	99.75 50	98.67 40	100.00 1	66.97 359	99.16 76	100.00 1	100.00 1	100.00 1	100.00 1

新几何1				99.99 5	100.00 1	99.96 10		99.81 42	97.89 93	100.00 1	100.00 1	99.20 72	100.00 1	97.91 207	100.00 1	100.00 1

旧先验1					99.99 45	99.88 59		99.82 41			100.00 1	99.27 66			100.00 1	100.00 1

原ACMM1				99.93 62	100.00 1	99.80 80		99.66 71	98.18 66	100.00 1	100.00 1	99.43 45	100.00 1	99.50 127	100.00 1	100.00 1

test222					99.99 45	99.90 45	100.00 1	99.69 70	97.66 112	100.00 1	100.00 1	99.30 61			100.00 1	100.00 1

testdata				99.66 116	99.99 45	98.97 158		99.73 55	97.96 88	100.00 1	100.00 1	99.42 46	100.00 1	99.28 144	100.00 1	100.00 1

1314		99.38 74	99.19 84	99.96 36	98.88 231	99.89 49	99.24 306	99.93 32	98.88 27	98.79 203	100.00 1	97.02 142	100.00 1	100.00 1	100.00 1	100.00 1

1121		99.63 52	99.51 56	99.99 5	99.99 45	99.96 10	99.24 306	99.74 53	97.89 93	100.00 1	100.00 1	99.39 49	100.00 1	99.33 140	100.00 1	100.00 1

MVS		99.22 100	98.96 106	99.98 16	99.00 220	99.95 19	99.24 306	99.94 18	98.14 70	98.88 196	100.00 1	95.63 180	100.00 1	99.85 83	100.00 1	100.00 1

SD-MVS		99.81 9	99.75 12	99.99 5	99.99 45	99.96 10	100.00 1	99.42 121	99.01 18	100.00 1	100.00 1	99.33 51	100.00 1	100.00 1	100.00 1	100.00 1

MSLP-MVS++		99.89 1	99.85 2	99.99 5	100.00 1	99.96 10	100.00 1	99.95 15	99.11 6	100.00 1	100.00 1	99.60 19	100.00 1	100.00 1	100.00 1	100.00 1

APDe-MVS		99.84 6	99.78 6	99.99 5	100.00 1	99.98 6	100.00 1	99.44 106	99.06 10	100.00 1	100.00 1	99.56 23	99.99 82	100.00 1	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 48	99.55 55	99.97 24	99.99 45	99.91 39	100.00 1	99.48 82	97.54 130	100.00 1	100.00 1	98.97 89	99.99 82	99.98 59	100.00 1	100.00 1

ACMMPR		99.74 23	99.67 27	99.96 36	100.00 1	99.89 49	100.00 1	99.76 46	97.95 89	100.00 1	100.00 1	99.29 62	100.00 1	99.99 45	100.00 1	100.00 1

MP-MVS		99.61 55	99.49 59	99.98 16	99.99 45	99.94 28	100.00 1	99.42 121	97.82 100	99.99 76	100.00 1	98.20 119	100.00 1	99.99 45	100.00 1	100.00 1
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
PGM-MVS		99.69 40	99.61 45	99.95 47	99.99 45	99.85 70	100.00 1	99.58 73	97.69 111	100.00 1	100.00 1	99.44 44	100.00 1	99.79 91	100.00 1	100.00 1

MCST-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 1	100.00 1	99.73 55	99.19 5	100.00 1	100.00 1	99.31 55	100.00 1	100.00 1	100.00 1	100.00 1

CDPH-MVS		99.73 26	99.64 35	99.99 5	100.00 1	99.97 8	100.00 1	99.42 121	98.02 80	100.00 1	100.00 1	99.32 54	99.99 82	100.00 1	100.00 1	100.00 1

test12				99.95 47	99.99 45	99.89 49		99.42 121		100.00 1		99.24 68	99.97 99		100.00 1	100.00 1

abl_6		99.53 61	99.40 62	99.92 68	100.00 1	99.76 83	100.00 1	99.42 121	97.21 149	100.00 1	100.00 1	98.12 121	100.00 1	99.82 90	100.00 1	100.00 1

mPP-MVS		99.69 40	99.60 46	99.97 24	100.00 1	99.91 39	100.00 1	99.42 121	97.91 92	100.00 1	100.00 1	99.04 83	100.00 1	100.00 1	100.00 1	100.00 1

MVSFormer		98.94 129	98.82 124	99.28 152	99.45 181	99.49 114	100.00 1	99.13 265	95.46 229	99.97 85	100.00 1	96.76 158	98.59 269	98.63 174	100.00 1	99.74 186

lupinMVS		99.29 89	99.16 86	99.69 114	99.45 181	99.49 114	100.00 1	99.15 256	97.45 134	99.97 85	100.00 1	96.76 158	99.76 159	99.67 107	100.00 1	99.81 171

HPM-MVS_fast		99.60 58	99.49 59	99.91 69	99.99 45	99.78 82	100.00 1	99.42 121	97.09 157	100.00 1	100.00 1	98.95 92	99.96 114	99.98 59	100.00 1	100.00 1

HPM-MVS		99.59 59	99.50 57	99.89 75	100.00 1	99.70 100	100.00 1	99.42 121	97.46 133	100.00 1	100.00 1	98.60 111	99.96 114	99.99 45	100.00 1	100.00 1
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
APD-MVS		99.68 43	99.58 49	99.97 24	99.99 45	99.96 10	100.00 1	99.42 121	97.53 131	100.00 1	100.00 1	99.27 66	99.97 99	100.00 1	100.00 1	100.00 1
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
CNVR-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 1	100.00 1	99.77 45	99.07 8	100.00 1	100.00 1	99.39 49	100.00 1	100.00 1	100.00 1	100.00 1

NCCC		99.86 2	99.82 3	100.00 1	100.00 1	99.99 1	100.00 1	99.71 63	99.07 8	100.00 1	100.00 1	99.59 21	100.00 1	100.00 1	100.00 1	100.00 1

114514_t		99.39 73	99.25 75	99.81 92	99.97 76	99.48 118	100.00 1	99.42 121	95.53 222	100.00 1	100.00 1	98.37 118	99.95 120	99.97 64	100.00 1	100.00 1

CP-MVS		99.67 46	99.58 49	99.95 47	100.00 1	99.84 71	100.00 1	99.42 121	97.77 103	100.00 1	100.00 1	99.07 80	100.00 1	100.00 1	100.00 1	100.00 1

SteuartSystems-ACMMP		99.78 13	99.71 16	99.98 16	99.76 126	99.95 19	100.00 1	99.42 121	98.69 38	100.00 1	100.00 1	99.52 29	99.99 82	100.00 1	100.00 1	100.00 1
Skip Steuart: Steuart Systems R&D Blog.
BH-w/o		98.82 137	98.81 126	98.88 176	99.62 147	96.71 260	100.00 1	99.28 219	97.09 157	98.81 202	100.00 1	94.91 192	99.96 114	99.54 122	100.00 1	99.96 107

DELS-MVS		99.62 53	99.56 54	99.82 89	99.92 91	99.45 120	100.00 1	99.78 44	98.92 25	99.73 143	100.00 1	97.70 129	100.00 1	99.93 73	100.00 1	100.00 1
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
BH-untuned		98.64 146	98.65 139	98.60 188	99.59 154	96.17 265	100.00 1	99.28 219	96.67 182	98.41 229	100.00 1	94.52 195	99.83 150	99.41 135	100.00 1	99.81 171

CPTT-MVS		99.49 66	99.38 66	99.85 85	100.00 1	99.54 109	100.00 1	99.42 121	97.58 128	99.98 81	100.00 1	97.43 136	100.00 1	99.99 45	100.00 1	100.00 1

BH-RMVSNet		98.46 158	98.08 167	99.59 124	99.61 149	99.19 141	100.00 1	99.28 219	97.06 161	98.95 192	100.00 1	88.99 275	99.82 152	98.83 164	100.00 1	99.77 179

DP-MVS Recon		99.76 15	99.69 18	99.98 16	100.00 1	99.95 19	100.00 1	99.52 76	97.99 82	99.99 76	100.00 1	99.72 15	100.00 1	99.96 66	100.00 1	100.00 1

MVS_111021_LR		99.70 37	99.65 31	99.88 80	99.96 81	99.70 100	100.00 1	99.97 14	98.96 21	100.00 1	100.00 1	97.93 125	99.95 120	99.99 45	100.00 1	100.00 1

DP-MVS		98.86 134	98.54 148	99.81 92	99.97 76	99.45 120	99.52 286	99.40 155	94.35 251	98.36 230	100.00 1	96.13 169	99.97 99	99.12 152	100.00 1	100.00 1

QAPM		98.99 123	98.66 136	99.96 36	99.01 216	99.87 62	99.88 226	99.93 32	97.99 82	98.68 210	100.00 1	93.17 210	100.00 1	99.32 142	100.00 1	100.00 1

PAPM_NR		99.74 23	99.66 30	99.99 5	100.00 1	99.96 10	100.00 1	99.47 83	97.87 96	100.00 1	100.00 1	99.60 19	100.00 1	100.00 1	100.00 1	100.00 1

PAPR		99.76 15	99.68 22	99.99 5	100.00 1	99.96 10	100.00 1	99.47 83	98.16 67	100.00 1	100.00 1	99.51 31	100.00 1	100.00 1	100.00 1	100.00 1

MVS_111021_HR		99.71 32	99.63 39	99.93 62	99.95 82	99.83 72	100.00 1	100.00 1	98.89 26	100.00 1	100.00 1	97.85 126	99.95 120	100.00 1	100.00 1	100.00 1

CSCG		99.28 90	99.35 70	99.05 164	99.99 45	97.15 249	100.00 1	99.47 83	97.44 135	99.42 167	100.00 1	97.83 127	100.00 1	99.99 45	100.00 1	100.00 1

API-MVS		99.72 29	99.70 17	99.79 99	99.97 76	99.37 126	99.96 203	99.94 18	98.48 47	100.00 1	100.00 1	98.92 96	100.00 1	100.00 1	100.00 1	100.00 1

PAPM		99.78 13	99.76 10	99.85 85	99.01 216	99.95 19	100.00 1	99.75 50	99.37 3	99.99 76	100.00 1	99.76 14	99.60 174	100.00 1	100.00 1	100.00 1

CNLPA		99.72 29	99.65 31	99.91 69	99.97 76	99.72 95	100.00 1	99.47 83	98.43 49	99.88 121	100.00 1	99.14 78	100.00 1	99.97 64	100.00 1	100.00 1

PHI-MVS		99.50 64	99.39 64	99.82 89	100.00 1	99.45 120	100.00 1	99.94 18	96.38 199	100.00 1	100.00 1	98.18 120	100.00 1	100.00 1	100.00 1	100.00 1

F-COLMAP		99.64 50	99.64 35	99.67 115	99.99 45	99.07 146	100.00 1	99.44 106	98.30 63	99.90 117	100.00 1	99.18 74	99.99 82	99.91 75	100.00 1	99.94 116

DeepPCF-MVS	98.03 4	98.54 153	99.72 15	94.98 306	99.99 45	84.94 332	100.00 1	99.42 121	99.98 1	100.00 1	100.00 1	98.11 122	100.00 1	100.00 1	100.00 1	100.00 1

DeepC-MVS_fast	98.92 1	99.75 18	99.67 27	99.99 5	99.99 45	99.96 10	99.73 259	99.52 76	99.06 10	100.00 1	100.00 1	98.80 104	100.00 1	99.95 71	100.00 1	100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MG-MVS		99.75 18	99.68 22	99.97 24	100.00 1	99.91 39	99.98 193	99.47 83	99.09 7	100.00 1	100.00 1	98.59 112	100.00 1	99.95 71	100.00 1	100.00 1

AdaColmap		99.44 71	99.26 74	99.95 47	100.00 1	99.86 67	99.70 265	99.99 10	98.53 46	99.90 117	100.00 1	95.34 182	100.00 1	99.92 74	100.00 1	100.00 1

PLC	98.56 2	99.70 37	99.74 13	99.58 128	100.00 1	98.79 163	100.00 1	99.54 75	98.58 45	99.96 88	100.00 1	99.59 21	100.00 1	100.00 1	100.00 1	99.94 116
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MAR-MVS		99.49 66	99.36 68	99.89 75	99.97 76	99.66 103	99.74 255	99.95 15	97.89 93	100.00 1	100.00 1	96.71 160	100.00 1	100.00 1	100.00 1	100.00 1
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
3Dnovator+	95.58 15	99.03 115	98.71 134	99.96 36	98.99 223	99.89 49	100.00 1	99.51 80	98.96 21	98.32 233	100.00 1	92.78 214	100.00 1	99.87 80	100.00 1	100.00 1

3Dnovator	95.63 14	99.06 112	98.76 130	99.96 36	98.86 234	99.90 45	99.98 193	99.93 32	98.95 24	98.49 226	100.00 1	92.91 213	100.00 1	99.71 101	100.00 1	100.00 1

TAPA-MVS	96.40 10	97.64 182	97.37 187	98.45 193	99.94 86	95.70 271	100.00 1	99.40 155	97.65 119	99.53 161	100.00 1	99.31 55	99.66 173	80.48 335	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
LS3D		99.31 87	99.13 93	99.87 81	99.99 45	99.71 96	99.55 283	99.46 95	97.32 143	99.82 134	100.00 1	96.85 157	99.97 99	99.14 150	100.00 1	99.92 127

CANet		99.40 72	99.24 77	99.89 75	99.99 45	99.76 83	100.00 1	99.73 55	98.40 52	99.78 138	100.00 1	95.28 183	99.96 114	100.00 1	99.99 88	99.96 107

GG-mvs-BLEND				99.59 124	99.54 163	99.49 114	99.17 320	99.52 76		99.96 88	99.68 217	100.00 1	99.33 213	99.71 101	99.99 88	99.96 107

gg-mvs-nofinetune		96.95 209	96.10 231	99.50 134	99.41 185	99.36 127	99.07 329	99.52 76	83.69 337	99.96 88	83.60 354	100.00 1	99.20 216	99.68 105	99.99 88	99.96 107

PS-MVSNAJ		99.64 50	99.57 51	99.85 85	99.78 122	99.81 78	99.95 209	99.42 121	98.38 55	100.00 1	100.00 1	98.75 106	100.00 1	99.88 79	99.99 88	99.74 186

test-LLR		99.03 115	98.91 117	99.40 141	99.40 189	99.28 131	100.00 1	99.45 97	96.70 178	99.42 167	99.12 258	99.31 55	99.01 224	96.82 236	99.99 88	99.91 128

TESTMET0.1,1		99.08 110	98.96 106	99.44 136	99.63 145	99.38 124	100.00 1	99.45 97	95.53 222	99.48 164	100.00 1	99.71 16	99.02 223	96.84 235	99.99 88	99.91 128

test-mter		98.96 127	98.82 124	99.40 141	99.40 189	99.28 131	100.00 1	99.45 97	95.44 231	99.42 167	99.12 258	99.70 17	99.01 224	96.82 236	99.99 88	99.91 128

MVP-Stereo		96.51 230	96.48 211	96.60 292	95.65 325	94.25 300	98.84 334	98.16 326	95.85 214	95.23 298	99.04 268	92.54 218	99.13 218	92.98 289	99.98 95	96.43 320
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		95.66 268	95.87 241	95.05 304	97.80 290	89.25 326	98.88 333	99.30 207	96.35 200	96.86 280	99.01 276	81.35 325	99.43 205	93.30 287	99.98 95	96.46 319

PatchMatch-RL		99.02 119	98.78 128	99.74 110	99.99 45	99.29 130	100.00 1	100.00 1	98.38 55	99.89 120	99.81 197	93.14 211	99.99 82	97.85 208	99.98 95	99.95 112

jason		99.11 108	98.96 106	99.59 124	99.17 202	99.31 129	100.00 1	99.13 265	97.38 138	99.83 125	100.00 1	95.54 181	99.72 164	99.57 118	99.97 98	99.74 186
jason: jason.
OpenMVS	95.20 17	98.76 139	98.41 153	99.78 107	98.89 230	99.81 78	99.99 176	99.76 46	98.02 80	98.02 247	100.00 1	91.44 237	100.00 1	99.63 111	99.97 98	99.55 199

CANet_DTU		99.02 119	98.90 120	99.41 140	99.88 97	98.71 166	100.00 1	99.29 211	98.84 30	100.00 1	100.00 1	94.02 200	100.00 1	98.08 200	99.96 100	99.52 201

DeepC-MVS	97.84 5	99.00 121	98.80 127	99.60 121	99.93 88	99.03 150	100.00 1	99.40 155	98.61 44	99.33 172	100.00 1	92.23 219	99.95 120	99.74 99	99.96 100	99.83 166
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CHOSEN 1792x2688		99.00 121	98.91 117	99.25 155	99.90 94	97.79 228	100.00 1	99.99 10	98.79 36	98.28 236	100.00 1	93.63 204	99.95 120	99.66 109	99.95 102	100.00 1

MSDG		98.90 132	98.63 141	99.70 113	99.92 91	99.25 135	100.00 1	99.37 176	95.71 216	99.40 171	100.00 1	96.58 161	99.95 120	96.80 238	99.94 103	99.91 128

COLMAP_ROB	97.10 7	98.29 165	98.17 164	98.65 186	99.94 86	97.39 238	99.30 302	99.40 155	95.64 217	97.75 258	100.00 1	92.69 216	99.95 120	98.89 159	99.92 104	98.62 211
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
MVS_0304		98.98 125	98.66 136	99.94 59	99.95 82	99.86 67	100.00 1	99.29 211	98.38 55	99.81 136	100.00 1	90.60 252	100.00 1	100.00 1	99.91 105	99.95 112

PCF-MVS	98.23 3	98.69 145	98.37 156	99.62 117	99.78 122	99.02 151	99.23 312	99.06 294	96.43 194	98.08 242	100.00 1	94.72 193	99.95 120	98.16 192	99.91 105	99.90 136
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
UGNet		98.41 161	98.11 165	99.31 150	99.54 163	98.55 173	99.18 315	100.00 1	98.64 43	99.79 137	99.04 268	87.61 287	100.00 1	99.30 143	99.89 107	99.40 204
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
PVSNet_Blended		99.48 68	99.36 68	99.83 88	99.98 72	99.60 107	100.00 1	100.00 1	97.79 102	100.00 1	100.00 1	96.57 162	99.99 82	100.00 1	99.88 108	99.90 136

ACMMP		99.65 48	99.57 51	99.89 75	99.99 45	99.66 103	99.75 254	99.73 55	98.16 67	99.75 142	100.00 1	98.90 98	100.00 1	99.96 66	99.88 108	100.00 1
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
MVS-HIRNet		94.12 280	92.73 289	98.29 205	99.33 195	95.95 267	99.38 296	99.19 247	74.54 344	98.26 238	86.34 350	86.07 299	99.06 221	91.60 298	99.87 110	99.85 162

AllTest		98.55 152	98.40 154	98.99 168	99.93 88	97.35 241	100.00 1	99.40 155	97.08 159	99.09 184	99.98 141	93.37 206	99.95 120	96.94 231	99.84 111	99.68 193

TestCases				98.99 168	99.93 88	97.35 241		99.40 155	97.08 159	99.09 184	99.98 141	93.37 206	99.95 120	96.94 231	99.84 111	99.68 193

OMC-MVS		99.27 91	99.38 66	98.96 171	99.95 82	97.06 253	100.00 1	99.40 155	98.83 31	99.88 121	100.00 1	97.01 143	99.86 143	99.47 128	99.84 111	99.97 96

UA-Net		99.06 112	98.83 123	99.74 110	99.52 171	99.40 123	99.08 327	99.45 97	97.64 121	99.83 125	100.00 1	95.80 174	99.94 131	98.35 185	99.80 114	99.88 153

PVSNet	94.91 18	99.30 88	99.25 75	99.44 136	100.00 1	98.32 187	100.00 1	99.86 39	98.04 79	100.00 1	100.00 1	96.10 170	100.00 1	99.55 119	99.73 115	100.00 1

EPNet_dtu		98.53 154	98.23 162	99.43 138	99.92 91	99.01 154	99.96 203	99.47 83	98.80 35	99.96 88	99.96 160	98.56 113	99.30 214	87.78 323	99.68 116	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Fast-Effi-MVS+-dtu		98.38 163	98.56 147	97.82 242	99.58 158	94.44 298	100.00 1	99.16 255	96.75 173	99.51 162	99.63 229	95.03 189	99.60 174	97.71 211	99.67 117	99.42 203

PVSNet_Blended_VisFu		99.33 79	99.18 85	99.78 107	99.82 99	99.49 114	100.00 1	99.95 15	97.36 139	99.63 155	100.00 1	96.45 166	99.95 120	99.79 91	99.65 118	99.89 141

EPNet		99.62 53	99.69 18	99.42 139	99.99 45	98.37 181	100.00 1	99.89 38	98.83 31	100.00 1	100.00 1	98.97 89	100.00 1	99.90 76	99.61 119	99.89 141
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
mvs-test1		98.89 133	98.99 104	98.60 188	99.77 124	95.96 266	100.00 1	98.94 304	97.61 123	99.93 114	99.92 179	95.89 171	99.93 133	99.36 137	99.50 120	99.90 136

Effi-MVS+-dtu		98.51 157	98.86 122	97.47 253	99.77 124	94.21 301	100.00 1	98.94 304	97.61 123	99.91 116	98.75 293	95.89 171	99.51 198	99.36 137	99.48 121	98.68 208

XVG-OURS-SEG-HR		98.27 167	98.31 158	98.14 220	99.59 154	95.92 268	100.00 1	99.36 182	98.48 47	99.21 177	100.00 1	89.27 272	99.94 131	99.76 97	99.17 122	98.56 212

xiu_mvs_v2_base		99.51 63	99.41 61	99.82 89	99.70 131	99.73 88	99.92 217	99.40 155	98.15 69	100.00 1	100.00 1	98.50 115	100.00 1	99.85 83	99.13 123	99.74 186

TSAR-MVS + GP.		99.61 55	99.69 18	99.35 146	99.99 45	98.06 212	100.00 1	99.36 182	99.83 2	100.00 1	100.00 1	98.95 92	99.99 82	100.00 1	99.11 124	100.00 1

xiu_mvs_v1_base_debu		99.35 76	99.21 80	99.79 99	99.67 136	99.71 96	99.78 244	99.36 182	98.13 71	100.00 1	100.00 1	97.00 148	100.00 1	99.83 86	99.07 125	99.66 195

xiu_mvs_v1_base		99.35 76	99.21 80	99.79 99	99.67 136	99.71 96	99.78 244	99.36 182	98.13 71	100.00 1	100.00 1	97.00 148	100.00 1	99.83 86	99.07 125	99.66 195

xiu_mvs_v1_base_debi		99.35 76	99.21 80	99.79 99	99.67 136	99.71 96	99.78 244	99.36 182	98.13 71	100.00 1	100.00 1	97.00 148	100.00 1	99.83 86	99.07 125	99.66 195

PatchmatchNet		99.03 115	98.96 106	99.26 154	99.49 179	98.33 184	99.38 296	99.45 97	96.64 183	99.96 88	99.58 235	99.49 37	99.50 199	97.63 213	99.00 128	99.93 125
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
EPMVS		99.25 95	99.13 93	99.60 121	99.60 151	99.20 140	99.60 279	100.00 1	96.93 168	99.92 115	99.36 249	99.05 82	99.71 165	98.77 166	98.94 129	99.90 136

Vis-MVSNet		98.52 155	98.25 159	99.34 147	99.68 135	98.55 173	99.68 271	99.41 153	97.34 142	99.94 109	100.00 1	90.38 257	99.70 166	99.03 155	98.84 130	99.76 181
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Patchmatch-test1		98.23 169	97.91 174	99.17 159	99.41 185	98.25 195	99.99 176	99.45 97	96.91 169	99.76 141	99.69 212	89.65 267	99.37 210	97.55 216	98.79 131	99.89 141

sss		99.45 70	99.34 72	99.80 95	99.76 126	99.50 111	100.00 1	99.91 37	97.72 106	99.98 81	99.94 176	98.45 116	100.00 1	99.53 125	98.75 132	99.89 141

MDTV_nov1_ep13			98.94 111		99.53 166	98.36 182	99.39 295	99.46 95	96.54 189	99.99 76	99.63 229	98.92 96	99.86 143	98.30 188	98.71 133

Patchmatch-test		97.83 178	97.42 184	99.06 162	99.08 207	97.66 232	98.66 336	99.21 244	93.65 273	98.25 239	99.58 235	99.47 40	99.57 179	90.25 311	98.59 134	99.95 112

ADS-MVSNet2		98.28 166	98.51 150	97.62 246	99.51 174	95.03 278	99.24 306	99.41 153	95.52 224	99.96 88	99.70 210	97.57 132	97.94 306	97.11 228	98.54 135	99.88 153

ADS-MVSNet		98.70 144	98.51 150	99.28 152	99.51 174	98.39 178	99.24 306	99.44 106	95.52 224	99.96 88	99.70 210	97.57 132	99.58 178	97.11 228	98.54 135	99.88 153

mvs_anonymous		98.80 138	98.60 144	99.38 144	99.57 160	99.24 137	100.00 1	99.21 244	95.87 210	98.92 193	99.82 194	96.39 167	99.03 222	99.13 151	98.50 137	99.88 153

PMMVS		99.12 107	98.97 105	99.58 128	99.57 160	98.98 156	100.00 1	99.30 207	97.14 152	99.96 88	100.00 1	96.53 165	99.82 152	99.70 103	98.49 138	99.94 116

MVS_Test		98.93 130	98.65 139	99.77 109	99.62 147	99.50 111	99.99 176	99.19 247	95.52 224	99.96 88	99.86 186	96.54 164	99.98 95	98.65 172	98.48 139	99.82 169

diffmvs		98.52 155	98.11 165	99.73 112	99.59 154	99.47 119	100.00 1	99.19 247	93.68 271	99.70 152	99.75 203	95.07 187	99.84 148	97.57 215	98.48 139	99.89 141

PatchT		95.90 261	94.95 274	98.75 183	99.03 214	98.39 178	99.08 327	99.32 200	85.52 330	99.96 88	94.99 339	97.94 124	98.05 304	80.20 336	98.47 141	99.81 171

test0.0.03 1		98.12 171	98.03 170	98.39 196	99.11 204	98.07 211	100.00 1	99.93 32	96.70 178	96.91 279	99.95 172	99.31 55	98.19 287	91.93 296	98.44 142	98.91 206

LCM-MVSNet-Re		96.52 229	97.21 191	94.44 309	99.27 199	85.80 331	99.85 230	96.61 349	95.98 208	92.75 312	98.48 304	93.97 201	97.55 311	99.58 117	98.43 143	99.98 91

dp		98.72 141	98.61 143	99.03 166	99.53 166	97.39 238	99.45 290	99.39 169	95.62 219	99.94 109	99.52 241	98.83 101	99.82 152	96.77 240	98.42 144	99.89 141

CR-MVSNet		98.02 174	97.71 181	98.93 172	99.31 196	98.86 161	99.13 323	99.00 302	96.53 190	99.96 88	98.98 279	96.94 155	98.10 297	91.18 300	98.40 145	99.84 163

RPMNet		95.10 275	93.82 278	98.93 172	99.31 196	98.86 161	99.13 323	99.38 173	79.82 342	99.96 88	95.13 337	95.69 179	98.10 297	77.54 342	98.40 145	99.84 163

test_normal		96.24 245	95.12 270	99.60 121	96.00 323	99.16 143	100.00 1	99.29 211	96.43 194	88.96 322	98.40 309	80.06 327	99.90 137	98.53 178	98.39 147	99.75 182

DI_MVS_plusplus_test		96.28 244	95.16 268	99.61 118	96.01 322	99.18 142	100.00 1	99.29 211	96.49 193	89.08 319	98.42 308	80.06 327	99.90 137	98.74 168	98.39 147	99.75 182

IS-MVSNet		99.08 110	98.91 117	99.59 124	99.65 140	99.38 124	99.78 244	99.24 233	96.70 178	99.51 162	100.00 1	98.44 117	99.52 196	98.47 181	98.39 147	99.88 153

RPSCF		97.37 189	98.24 160	94.76 308	99.80 114	84.57 333	99.99 176	99.05 296	94.95 236	99.82 134	100.00 1	94.03 199	100.00 1	98.15 193	98.38 150	99.70 191

Test4		92.63 296	90.45 307	99.17 159	92.81 333	99.02 151	99.98 193	99.13 265	96.60 186	82.04 342	96.27 321	51.35 351	98.75 253	97.55 216	98.36 151	99.75 182

Effi-MVS+		98.58 149	98.24 160	99.61 118	99.60 151	99.26 133	97.85 343	99.10 273	96.22 204	99.97 85	99.89 182	93.75 202	99.77 158	99.43 129	98.34 152	99.81 171

DWT-MVSNet_test		99.22 100	99.22 79	99.22 157	99.56 162	97.98 216	99.89 223	99.39 169	97.20 150	99.96 88	100.00 1	99.52 29	99.82 152	99.11 153	98.34 152	99.87 160

Vis-MVSNet (Re-imp)		98.99 123	98.89 121	99.29 151	99.64 144	98.89 160	99.98 193	99.31 205	96.74 174	99.48 164	100.00 1	98.11 122	99.10 219	98.39 183	98.34 152	99.89 141

PatchFormer-LS_test		99.14 106	99.12 95	99.19 158	99.54 163	97.86 226	99.66 274	99.40 155	96.94 167	99.96 88	100.00 1	99.29 62	99.84 148	98.96 156	98.29 155	99.88 153

TR-MVS		98.14 170	97.74 178	99.33 148	99.59 154	98.28 189	99.27 303	99.21 244	96.42 196	99.15 182	99.94 176	88.87 277	99.79 157	98.88 160	98.29 155	99.93 125

JIA-IIPM		97.09 200	96.34 217	99.36 145	98.88 231	98.59 171	99.81 239	99.43 115	84.81 334	99.96 88	90.34 346	98.55 114	99.52 196	97.00 230	98.28 157	99.98 91

Fast-Effi-MVS+		98.40 162	98.02 171	99.55 131	99.63 145	99.06 148	100.00 1	99.15 256	95.07 233	99.42 167	99.95 172	93.26 209	99.73 162	97.44 220	98.24 158	99.87 160

HY-MVS	96.53 9	99.50 64	99.35 70	99.96 36	99.81 100	99.93 33	99.64 276	100.00 1	97.97 86	99.84 123	99.85 188	98.94 94	99.99 82	99.86 81	98.23 159	99.95 112

WTY-MVS		99.54 60	99.40 62	99.95 47	99.81 100	99.93 33	100.00 1	100.00 1	97.98 84	99.84 123	100.00 1	98.94 94	99.98 95	99.86 81	98.21 160	99.94 116

tpm cat1		98.05 172	97.76 177	98.92 174	99.50 177	97.10 252	99.77 248	99.30 207	90.20 309	99.72 144	98.71 295	97.71 128	99.86 143	96.75 242	98.20 161	99.81 171

tpmrst		98.98 125	98.93 112	99.14 161	99.61 149	97.74 229	99.52 286	99.36 182	96.05 207	99.98 81	99.64 225	99.04 83	99.86 143	98.94 157	98.19 162	99.82 169

tpmvs		98.59 148	98.38 155	99.23 156	99.69 132	97.90 221	99.31 301	99.47 83	94.52 246	99.68 153	99.28 254	97.64 130	99.89 139	97.71 211	98.17 163	99.89 141

tpmp4_e23		98.71 142	98.66 136	98.84 178	99.60 151	96.98 255	99.83 232	99.35 190	94.29 252	99.90 117	99.50 243	99.17 75	99.73 162	98.22 190	98.13 164	99.81 171

cascas		98.43 159	98.07 168	99.50 134	99.65 140	99.02 151	100.00 1	99.22 240	94.21 256	99.72 144	99.98 141	92.03 222	99.93 133	99.68 105	98.12 165	99.54 200

MIMVSNet		97.06 203	96.73 202	98.05 231	99.38 193	96.64 262	98.47 339	99.35 190	93.41 279	99.48 164	98.53 303	89.66 266	97.70 310	94.16 277	98.11 166	99.80 178

HyFIR lowres test		99.32 80	99.24 77	99.58 128	99.95 82	99.26 133	100.00 1	99.99 10	96.72 177	99.29 174	99.91 180	99.49 37	99.47 202	99.74 99	98.08 167	100.00 1

testpf		97.02 206	96.87 197	97.44 254	99.50 177	95.18 275	95.70 348	99.33 197	91.35 301	98.00 249	99.22 256	96.29 168	98.49 278	94.42 271	98.07 168	98.67 209

EPP-MVSNet		99.10 109	99.00 101	99.40 141	99.51 174	98.68 168	99.92 217	99.43 115	95.47 228	99.65 154	100.00 1	99.51 31	99.76 159	99.53 125	98.00 169	99.75 182

CDS-MVSNet		98.96 127	98.95 110	99.01 167	99.48 180	98.36 182	99.93 215	99.37 176	96.79 172	99.31 173	99.83 191	99.77 13	98.91 231	98.07 201	97.98 170	99.77 179
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
tpm2		98.64 146	98.58 146	98.81 181	99.42 184	97.12 250	99.69 269	99.37 176	93.63 274	99.94 109	99.67 218	98.96 91	99.47 202	98.62 176	97.95 171	99.83 166

ab-mvs		98.42 160	98.02 171	99.61 118	99.71 130	99.00 155	99.10 325	99.64 72	96.70 178	99.04 189	99.81 197	90.64 251	99.98 95	99.64 110	97.93 172	99.84 163

tfpn_ndepth		99.52 62	99.39 64	99.89 75	99.90 94	99.83 72	100.00 1	99.72 61	97.95 89	99.96 88	99.98 141	99.94 4	99.85 147	99.17 149	97.91 173	100.00 1

TAMVS		98.76 139	98.73 132	98.86 177	99.44 183	97.69 230	99.57 281	99.34 195	96.57 187	99.12 183	99.81 197	98.83 101	99.16 217	97.97 206	97.91 173	99.73 190

thres200		99.27 91	99.04 96	99.96 36	99.81 100	99.90 45	100.00 1	99.94 18	97.31 145	99.83 125	99.96 160	97.04 139	100.00 1	99.62 112	97.88 175	99.98 91

tfpn1000		99.47 69	99.34 72	99.87 81	99.89 96	99.80 80	100.00 1	99.72 61	97.83 98	99.96 88	99.98 141	99.94 4	99.82 152	98.87 161	97.87 176	100.00 1

DSMNet-mixed		95.18 274	95.21 267	95.08 303	96.03 321	90.21 324	99.65 275	93.64 354	92.91 289	98.34 232	97.40 316	90.05 262	95.51 335	91.02 302	97.86 177	99.51 202

conf200view11		99.25 95	99.01 99	99.95 47	99.81 100	99.87 62	100.00 1	99.94 18	97.13 153	99.83 125	99.96 160	97.01 143	100.00 1	99.59 113	97.85 178	99.97 96

thres100view900		99.25 95	99.01 99	99.95 47	99.81 100	99.87 62	100.00 1	99.94 18	97.13 153	99.83 125	99.96 160	97.01 143	100.00 1	99.59 113	97.85 178	99.98 91

tfpn200view9		99.26 93	99.03 97	99.96 36	99.81 100	99.89 49	100.00 1	99.94 18	97.23 146	99.83 125	99.96 160	97.04 139	100.00 1	99.59 113	97.85 178	99.98 91

thres400		99.26 93	99.03 97	99.95 47	99.81 100	99.89 49	100.00 1	99.94 18	97.23 146	99.83 125	99.96 160	97.04 139	100.00 1	99.59 113	97.85 178	99.97 96

XVG-OURS		98.30 164	98.36 157	98.13 223	99.58 158	95.91 269	100.00 1	99.36 182	98.69 38	99.23 176	100.00 1	91.20 241	99.92 136	99.34 139	97.82 182	98.56 212

CostFormer		98.84 135	98.77 129	99.04 165	99.41 185	97.58 234	99.67 272	99.35 190	94.66 242	99.96 88	99.36 249	99.28 65	99.74 161	99.41 135	97.81 183	99.81 171

testgi		96.18 248	95.93 239	96.93 274	98.98 224	94.20 302	100.00 1	99.07 286	97.16 151	96.06 292	99.86 186	84.08 313	97.79 308	90.38 308	97.80 184	98.81 207

test2356		92.55 298	93.94 276	88.39 324	93.49 332	78.42 338	100.00 1	99.40 155	91.64 298	93.93 306	98.74 294	91.11 245	88.67 347	79.37 338	97.79 185	98.08 214

tfpn111		99.24 98	99.00 101	99.95 47	99.81 100	99.87 62	100.00 1	99.94 18	97.13 153	99.83 125	99.96 160	97.01 143	100.00 1	99.54 122	97.77 186	99.97 96

thres600view7		99.24 98	99.00 101	99.95 47	99.81 100	99.87 62	100.00 1	99.94 18	97.13 153	99.83 125	99.96 160	97.01 143	100.00 1	99.54 122	97.77 186	99.97 96

view600		99.18 102	98.93 112	99.93 62	99.81 100	99.83 72	100.00 1	99.94 18	96.96 163	99.54 157	99.96 160	96.99 151	100.00 1	99.43 129	97.75 188	99.97 96

view800		99.18 102	98.93 112	99.93 62	99.81 100	99.83 72	100.00 1	99.94 18	96.96 163	99.54 157	99.96 160	96.99 151	100.00 1	99.43 129	97.75 188	99.97 96

conf0.05thres1000		99.18 102	98.93 112	99.93 62	99.81 100	99.83 72	100.00 1	99.94 18	96.96 163	99.54 157	99.96 160	96.99 151	100.00 1	99.43 129	97.75 188	99.97 96

tfpn		99.18 102	98.93 112	99.93 62	99.81 100	99.83 72	100.00 1	99.94 18	96.96 163	99.54 157	99.96 160	96.99 151	100.00 1	99.43 129	97.75 188	99.97 96

Test_1112_low_res		98.83 136	98.60 144	99.51 132	99.69 132	98.75 164	99.99 176	99.14 260	96.81 171	98.84 200	99.06 262	97.45 134	99.89 139	98.66 170	97.75 188	99.89 141

1112_ss		98.91 131	98.71 134	99.51 132	99.69 132	98.75 164	99.99 176	99.15 256	96.82 170	98.84 200	100.00 1	97.45 134	99.89 139	98.66 170	97.75 188	99.89 141

testus		91.61 306	92.92 286	87.70 325	93.91 331	74.98 342	100.00 1	98.19 325	92.59 292	93.90 307	98.68 296	81.43 323	90.77 345	79.82 337	97.71 194	97.34 309

conf0.01		99.32 80	99.16 86	99.80 95	99.79 116	99.73 88	100.00 1	99.71 63	97.66 112	99.71 146	100.00 1	99.78 6	99.70 166	98.15 193	97.67 195	99.97 96

conf0.002		99.32 80	99.16 86	99.80 95	99.79 116	99.73 88	100.00 1	99.71 63	97.66 112	99.71 146	100.00 1	99.78 6	99.70 166	98.15 193	97.67 195	99.97 96

thresconf0.02		99.32 80	99.16 86	99.79 99	99.79 116	99.73 88	100.00 1	99.71 63	97.66 112	99.71 146	100.00 1	99.78 6	99.70 166	98.15 193	97.67 195	99.94 116

tfpn_n400		99.32 80	99.16 86	99.79 99	99.79 116	99.73 88	100.00 1	99.71 63	97.66 112	99.71 146	100.00 1	99.78 6	99.70 166	98.15 193	97.67 195	99.94 116

tfpnconf		99.32 80	99.16 86	99.79 99	99.79 116	99.73 88	100.00 1	99.71 63	97.66 112	99.71 146	100.00 1	99.78 6	99.70 166	98.15 193	97.67 195	99.94 116

tfpnview11		99.32 80	99.16 86	99.79 99	99.79 116	99.73 88	100.00 1	99.71 63	97.66 112	99.71 146	100.00 1	99.78 6	99.70 166	98.15 193	97.67 195	99.94 116

DeepMVS_CX				89.98 321	98.90 229	71.46 347		99.18 251	97.61 123	96.92 277	99.83 191	86.07 299	99.83 150	96.02 245	97.65 201	98.65 210

GA-MVS		97.72 180	97.27 189	99.06 162	99.24 201	97.93 220	100.00 1	99.24 233	95.80 215	98.99 191	99.64 225	89.77 265	99.36 211	95.12 262	97.62 202	99.89 141

LP		95.89 263	95.35 264	97.51 250	98.92 228	95.15 276	98.66 336	99.39 169	89.43 320	97.22 272	99.03 273	94.37 197	97.74 309	83.71 330	97.44 203	99.63 198

LFMVS		97.42 188	96.62 206	99.81 92	99.80 114	99.50 111	99.16 321	99.56 74	94.48 248	100.00 1	100.00 1	79.35 332	100.00 1	99.89 78	97.37 204	99.94 116

CVMVSNet		98.56 151	98.47 152	98.82 179	99.11 204	97.67 231	99.74 255	99.47 83	97.57 129	99.06 188	100.00 1	95.72 178	98.97 228	98.21 191	97.33 205	99.83 166

alignmvs		99.38 74	99.21 80	99.91 69	99.73 129	99.92 36	100.00 1	99.51 80	97.61 123	100.00 1	100.00 1	99.06 81	99.93 133	99.83 86	97.12 206	99.90 136

VNet		99.04 114	98.75 131	99.90 72	99.81 100	99.75 85	99.50 288	99.47 83	98.36 58	100.00 1	99.99 140	94.66 194	100.00 1	99.90 76	97.09 207	99.96 107

VDDNet		96.39 238	95.55 255	98.90 175	99.27 199	97.45 235	99.15 322	99.92 36	91.28 302	99.98 81	100.00 1	73.55 341	100.00 1	99.85 83	96.98 208	99.24 205

VDD-MVS		96.58 228	95.99 236	98.34 201	99.52 171	95.33 272	99.18 315	99.38 173	96.64 183	99.77 139	100.00 1	72.51 343	100.00 1	100.00 1	96.94 209	99.70 191

canonicalmvs		99.03 115	98.73 132	99.94 59	99.75 128	99.95 19	100.00 1	99.30 207	97.64 121	100.00 1	100.00 1	95.22 185	99.97 99	99.76 97	96.90 210	99.91 128

tpm		98.24 168	98.22 163	98.32 203	99.13 203	95.79 270	99.53 285	99.12 271	95.20 232	99.96 88	99.36 249	97.58 131	99.28 215	97.41 222	96.67 211	99.88 153

OpenMVS_ROB	88.34 20	91.89 302	91.12 302	94.19 314	95.55 326	87.63 329	99.26 304	98.03 331	86.61 329	90.65 318	96.82 317	70.14 345	98.78 247	86.54 326	96.50 212	96.15 323

plane_prior						94.80 285	100.00 1		99.03 16						95.58 213

HQP3-MVS								99.40 155							95.58 213

HQP-MVS		97.73 179	97.85 175	97.39 255	99.07 208	94.82 282	100.00 1	99.40 155	99.04 13	99.17 178	99.97 151	88.61 279	99.57 179	99.79 91	95.58 213	97.77 216

CLD-MVS		97.64 182	97.74 178	97.36 257	99.01 216	94.76 290	100.00 1	99.34 195	99.30 4	99.00 190	99.97 151	87.49 288	99.57 179	99.96 66	95.58 213	97.75 222
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
HQP_MVS		97.71 181	97.82 176	97.37 256	99.00 220	94.80 285	100.00 1	99.40 155	99.00 19	99.08 186	99.97 151	88.58 281	99.55 188	99.79 91	95.57 217	97.76 218

plane_prior5								99.40 155					99.55 188	99.79 91	95.57 217	97.76 218

OPM-MVS		97.21 194	97.18 192	97.32 258	98.08 273	94.66 292	100.00 1	99.28 219	98.65 42	98.92 193	99.98 141	86.03 301	99.56 183	98.28 189	95.41 219	97.72 261

test_djsdf		97.55 186	97.38 186	98.07 227	97.50 304	97.99 215	100.00 1	99.13 265	95.46 229	98.47 227	99.85 188	92.01 224	98.59 269	98.63 174	95.36 220	97.62 293

anonymousdsp		97.16 197	96.88 196	98.00 233	97.08 315	98.06 212	99.81 239	99.15 256	94.58 244	97.84 254	99.62 231	90.49 254	98.60 267	97.98 203	95.32 221	97.33 310

EI-MVSNet		97.98 175	97.93 173	98.16 219	99.11 204	97.84 227	99.74 255	99.29 211	94.39 250	98.65 212	100.00 1	97.21 137	98.88 237	97.62 214	95.31 222	97.75 222

MVSTER		98.58 149	98.52 149	98.77 182	99.65 140	99.68 102	100.00 1	99.29 211	95.63 218	98.65 212	99.80 200	99.78 6	98.88 237	98.59 177	95.31 222	97.73 256

LPG-MVS_test		97.31 191	97.32 188	97.28 260	98.85 235	94.60 295	100.00 1	99.37 176	97.35 140	98.85 198	99.98 141	86.66 295	99.56 183	99.55 119	95.26 224	97.70 269

LGP-MVS_train				97.28 260	98.85 235	94.60 295		99.37 176	97.35 140	98.85 198	99.98 141	86.66 295	99.56 183	99.55 119	95.26 224	97.70 269

ITE_SJBPF				96.84 284	98.96 226	93.49 306		98.12 328	98.12 74	98.35 231	99.97 151	84.45 307	99.56 183	95.63 253	95.25 226	97.49 301

ACMP	97.00 8	97.19 195	97.16 193	97.27 262	98.97 225	94.58 297	100.00 1	99.32 200	97.97 86	97.45 266	99.98 141	85.79 303	99.56 183	99.70 103	95.24 227	97.67 280
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
EG-PatchMatch MVS		92.94 295	92.49 290	94.29 312	95.87 324	87.07 330	99.07 329	98.11 329	93.19 286	88.98 321	98.66 299	70.89 344	99.08 220	92.43 294	95.21 228	96.72 317

ACMM	97.17 6	97.37 189	97.40 185	97.29 259	99.01 216	94.64 294	100.00 1	99.25 230	98.07 77	98.44 228	99.98 141	87.38 289	99.55 188	99.25 145	95.19 229	97.69 274
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMMP++															95.17 230

test_0402		94.35 278	93.70 280	96.32 296	97.92 286	93.60 305	99.61 278	98.85 309	88.19 326	94.68 301	99.48 245	80.01 330	98.58 271	89.39 318	95.15 231	96.77 316

ACMH	96.25 11	96.77 212	96.62 206	97.21 263	98.96 226	94.43 299	99.64 276	99.33 197	97.43 136	96.55 287	99.97 151	83.52 314	99.54 191	99.07 154	95.13 232	97.66 282
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
jajsoiax		97.07 202	96.79 201	97.89 241	97.28 313	97.12 250	99.95 209	99.19 247	96.55 188	97.31 269	99.69 212	87.35 291	98.91 231	98.70 169	95.12 233	97.66 282

mvs_tets		97.00 207	96.69 203	97.94 237	97.41 312	97.27 245	99.60 279	99.18 251	96.51 192	97.35 268	99.69 212	86.53 297	98.91 231	98.84 162	95.09 234	97.65 287

XVG-ACMP-BASELINE		96.60 227	96.52 209	96.84 284	98.41 247	93.29 309	99.99 176	99.32 200	97.76 105	98.51 225	99.29 253	81.95 320	99.54 191	98.40 182	95.03 235	97.68 276

LTVRE_ROB	95.29 16	96.32 242	96.10 231	96.99 270	98.55 242	93.88 303	99.45 290	99.28 219	94.50 247	96.46 288	99.52 241	84.86 306	99.48 201	97.26 225	95.03 235	97.59 297
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
USDC		95.90 261	95.70 250	96.50 293	98.60 241	92.56 316	100.00 1	98.30 322	97.77 103	96.92 277	99.94 176	81.25 326	99.45 204	93.54 286	94.96 237	97.49 301

pcd1.5k->3k		40.07 334	42.58 335	32.57 347	97.97 285	0.00 364	0.00 355	99.25 230	0.00 359	0.00 360	0.14 361	91.10 246	0.00 362	0.00 359	94.75 238	97.70 269

PVSNet_BlendedMVS		98.71 142	98.62 142	98.98 170	99.98 72	99.60 107	100.00 1	100.00 1	97.23 146	100.00 1	99.03 273	96.57 162	99.99 82	100.00 1	94.75 238	97.35 308

TinyColmap		95.50 270	95.12 270	96.64 290	98.69 237	93.00 311	99.40 294	97.75 338	96.40 198	96.14 291	99.87 184	79.47 331	99.50 199	93.62 283	94.72 240	97.40 306

ACMH+	96.20 13	96.49 233	96.33 218	97.00 269	99.06 212	93.80 304	99.81 239	99.31 205	97.32 143	95.89 295	99.97 151	82.62 318	99.54 191	98.34 186	94.63 241	97.65 287

PS-MVSNAJss		98.03 173	98.06 169	97.94 237	97.63 296	97.33 244	99.89 223	99.23 237	96.27 203	98.03 245	99.59 234	98.75 106	98.78 247	98.52 179	94.61 242	97.70 269

ACMMP++_ref															94.58 243

CMPMVS	66.12 22	90.65 308	92.04 295	86.46 328	96.18 320	66.87 350	98.03 342	99.38 173	83.38 338	85.49 337	99.55 238	77.59 336	98.80 246	94.44 270	94.31 244	93.72 341
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
OurMVSNet-221017-0		96.14 253	95.98 237	96.62 291	97.49 306	93.44 307	99.92 217	98.16 326	95.86 212	97.65 259	99.95 172	85.71 304	98.78 247	94.93 266	94.18 245	97.64 290

LF4IMVS		96.19 247	96.18 224	96.23 298	98.26 255	92.09 318	100.00 1	97.89 336	97.82 100	97.94 250	99.87 184	82.71 317	99.38 209	97.41 222	93.71 246	97.20 312

GBi-Net		96.07 255	95.80 244	96.89 276	99.53 166	94.87 279	99.18 315	99.27 226	93.71 265	98.53 222	98.81 290	84.23 310	98.07 300	95.31 258	93.60 247	97.72 261

test1		96.07 255	95.80 244	96.89 276	99.53 166	94.87 279	99.18 315	99.27 226	93.71 265	98.53 222	98.81 290	84.23 310	98.07 300	95.31 258	93.60 247	97.72 261

FMVSNet3		97.30 192	96.95 194	98.37 198	99.65 140	99.25 135	99.71 263	99.28 219	94.23 254	98.53 222	98.91 286	93.30 208	98.11 294	95.31 258	93.60 247	97.73 256

FMVSNet2		96.22 246	95.60 254	98.06 230	99.53 166	98.33 184	99.45 290	99.27 226	93.71 265	98.03 245	98.84 289	84.23 310	98.10 297	93.97 280	93.40 250	97.73 256

K. test v3		95.46 272	95.14 269	96.40 294	97.53 303	93.40 308	99.99 176	99.23 237	95.49 227	92.70 313	99.73 204	84.26 309	98.12 292	93.94 281	93.38 251	97.68 276

SixPastTwentyTwo		95.71 267	95.49 258	96.38 295	97.42 310	93.01 310	99.84 231	98.23 323	94.75 238	95.98 293	99.97 151	85.35 305	98.43 281	94.71 267	93.17 252	97.69 274

FIs		97.95 176	97.73 180	98.62 187	98.53 244	99.24 137	100.00 1	99.43 115	96.74 174	97.87 253	99.82 194	95.27 184	98.89 234	98.78 165	93.07 253	97.74 246

FC-MVSNet-test		97.84 177	97.63 182	98.45 193	98.30 253	99.05 149	100.00 1	99.43 115	96.63 185	97.61 262	99.82 194	95.19 186	98.57 272	98.64 173	93.05 254	97.73 256

XXY-MVS		97.14 199	96.63 205	98.67 185	98.65 238	98.92 159	99.54 284	99.29 211	95.57 221	97.63 260	99.83 191	87.79 286	99.35 212	98.39 183	92.95 255	97.75 222

FMVSNet1		94.45 277	93.63 281	96.89 276	98.87 233	94.87 279	99.18 315	99.27 226	90.95 305	97.31 269	98.81 290	72.89 342	98.07 300	92.61 290	92.81 256	97.72 261

N_pmnet		91.88 303	93.37 284	87.40 326	97.24 314	66.33 351	99.90 220	91.05 356	89.77 315	95.65 296	98.58 302	90.05 262	98.11 294	85.39 327	92.72 257	97.75 222

pmmvs4		97.17 196	96.80 199	98.27 207	97.68 293	98.64 170	100.00 1	99.18 251	94.22 255	98.55 220	99.71 207	93.67 203	98.47 279	95.66 252	92.57 258	97.71 268

testing_2		90.79 307	88.26 313	98.35 200	89.11 340	98.56 172	99.70 265	99.14 260	93.70 269	73.80 345	94.06 341	55.19 348	98.76 252	97.17 226	92.50 259	97.74 246

our_test_3		96.51 230	96.35 216	96.98 271	97.61 298	95.05 277	99.98 193	99.01 301	94.68 241	96.77 284	99.06 262	95.87 173	98.14 290	91.81 297	92.37 260	97.75 222

IterMVS		96.76 216	96.46 213	97.63 244	99.41 185	96.89 256	99.99 176	99.13 265	94.74 240	97.59 263	99.66 220	89.63 269	98.28 286	95.71 250	92.31 261	97.72 261
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ppachtmachnet_test		96.17 250	95.89 240	97.02 268	97.61 298	95.24 273	99.99 176	99.24 233	93.31 283	96.71 285	99.62 231	94.34 198	98.07 300	89.87 313	92.30 262	97.75 222

pmmvs5		95.94 260	95.61 253	96.95 272	97.42 310	94.66 292	100.00 1	98.08 330	93.60 276	97.05 275	99.43 247	87.02 292	98.46 280	95.76 247	92.12 263	97.72 261

semantic-postprocess				97.62 246	99.40 189	96.83 258		99.14 260	94.65 243	97.55 264	99.72 205	89.64 268	98.31 285	95.62 254	92.05 264	97.73 256

new_pmnet		94.11 281	93.47 283	96.04 300	96.60 318	92.82 313	99.97 200	98.91 307	90.21 308	95.26 297	98.05 313	85.89 302	98.14 290	84.28 329	92.01 265	97.16 313

FMVSNet5		95.32 273	95.43 261	94.99 305	99.39 192	92.99 312	99.25 305	99.24 233	90.45 306	97.44 267	98.45 305	95.78 175	94.39 337	87.02 324	91.88 266	97.59 297

Gipuma		84.73 317	83.50 318	88.40 323	97.50 304	82.21 335	88.87 351	99.05 296	65.81 347	85.71 336	90.49 345	53.70 349	96.31 325	78.64 340	91.74 267	86.67 350
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
IterMVS-LS		97.56 185	97.44 183	97.92 240	99.38 193	97.90 221	99.89 223	99.10 273	94.41 249	98.32 233	99.54 240	97.21 137	98.11 294	97.50 219	91.62 268	97.75 222
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Patchmtry		96.81 211	96.37 215	98.14 220	99.31 196	98.55 173	98.91 332	99.00 302	90.45 306	97.92 251	98.98 279	96.94 155	98.12 292	94.27 274	91.53 269	97.75 222

MIMVSNet1		91.96 300	91.20 301	94.23 313	94.94 330	91.69 321	99.34 299	99.22 240	88.23 324	94.18 305	98.45 305	75.52 340	93.41 341	79.37 338	91.49 270	97.60 296

tfpnnormal		96.36 239	95.69 252	98.37 198	98.55 242	98.71 166	99.69 269	99.45 97	93.16 287	96.69 286	99.71 207	88.44 283	98.99 226	94.17 275	91.38 271	97.41 305

FPMVS		77.92 324	79.45 322	73.34 342	76.87 354	46.81 361	98.24 340	99.05 296	59.89 351	73.55 346	98.34 311	36.81 357	86.55 349	80.96 334	91.35 272	86.65 351

test1235678		88.02 314	88.73 312	85.90 330	87.57 343	71.70 346	100.00 1	97.42 342	87.52 328	86.19 335	96.39 320	81.60 321	87.93 348	70.72 346	91.18 273	98.08 214

EU-MVSNet		96.63 225	96.53 208	96.94 273	97.59 300	96.87 257	99.76 251	99.47 83	96.35 200	96.85 281	99.78 201	92.57 217	96.27 328	95.33 257	91.08 274	97.68 276

v1240		95.96 259	95.25 266	98.07 227	97.91 287	97.87 225	99.96 203	99.07 286	93.24 285	98.64 214	98.96 283	88.98 276	98.61 265	89.58 315	90.92 275	97.75 222

v1192		96.18 248	95.49 258	98.26 209	98.01 281	98.15 206	99.99 176	99.08 284	93.36 281	98.54 221	98.97 282	89.47 270	98.89 234	91.15 301	90.82 276	97.75 222

v7		96.64 224	96.14 228	98.13 223	98.18 260	97.97 217	99.99 176	99.09 276	93.62 275	98.76 204	99.30 252	91.13 244	98.70 259	94.37 272	90.80 277	97.74 246

v1144		96.51 230	95.97 238	98.13 223	97.98 284	98.04 214	99.99 176	99.08 284	93.51 278	98.62 215	98.98 279	90.98 250	98.62 264	93.79 282	90.79 278	97.74 246

v1921920		96.16 251	95.50 256	98.14 220	97.88 289	97.96 218	99.99 176	99.07 286	93.33 282	98.60 216	99.24 255	89.37 271	98.71 258	91.28 299	90.74 279	97.75 222

Anonymous20231206		93.45 287	93.17 285	94.30 311	95.00 329	89.69 325	99.98 193	98.43 321	93.30 284	94.50 303	98.59 301	90.52 253	95.73 333	77.46 343	90.73 280	97.48 303

v144192		96.40 237	95.81 243	98.17 218	97.89 288	98.11 208	99.99 176	99.06 294	93.39 280	98.75 205	99.09 260	90.43 256	98.66 263	93.10 288	90.55 281	97.75 222

v2v482		96.70 219	96.18 224	98.27 207	98.04 279	98.39 178	100.00 1	99.13 265	94.19 257	98.58 219	99.08 261	90.48 255	98.67 262	95.69 251	90.44 282	97.75 222

lessismore_v0				96.05 299	97.55 302	91.80 320		99.22 240		91.87 314	99.91 180	83.50 315	98.68 260	92.48 293	90.42 283	97.68 276

Anonymous20240521		96.99 208	96.48 211	98.53 191	98.07 274	99.07 146	99.76 251	99.23 237	94.26 253	96.16 290	98.68 296	94.96 190	98.87 239	96.76 241	90.41 284	97.66 282

v1neww		96.77 212	96.27 220	98.26 209	98.16 263	98.23 196	100.00 1	99.09 276	93.94 261	98.73 207	99.05 265	91.65 227	98.82 243	95.75 248	90.04 285	97.74 246

v7new		96.77 212	96.27 220	98.26 209	98.16 263	98.23 196	100.00 1	99.09 276	93.94 261	98.73 207	99.05 265	91.65 227	98.82 243	95.75 248	90.04 285	97.74 246

v6		96.77 212	96.26 222	98.29 205	98.10 269	98.27 191	100.00 1	99.09 276	93.95 260	98.73 207	99.06 262	91.51 234	98.86 240	95.83 246	90.04 285	97.74 246

v1141		96.66 221	96.12 229	98.26 209	98.05 277	98.28 189	100.00 1	99.09 276	93.71 265	98.59 217	99.04 268	91.57 231	98.73 254	95.05 263	90.00 288	97.75 222

divwei89l23v2f112		96.68 220	96.15 227	98.25 213	98.03 280	98.27 191	100.00 1	99.09 276	93.79 264	98.59 217	99.04 268	91.54 233	98.73 254	95.29 261	89.99 289	97.75 222

v1		96.66 221	96.12 229	98.30 204	98.09 270	98.33 184	100.00 1	99.09 276	93.69 270	98.68 210	99.04 268	91.42 238	98.83 242	95.05 263	89.99 289	97.75 222

test12356		86.30 315	87.15 316	83.77 334	84.24 346	72.00 344	99.94 213	96.80 346	84.63 335	85.16 338	96.51 319	77.02 338	86.31 351	70.06 347	89.93 291	93.00 343

V42		96.65 223	96.16 226	98.11 226	98.17 262	98.23 196	99.99 176	99.09 276	93.97 258	98.74 206	99.05 265	91.09 247	98.82 243	95.46 256	89.90 292	97.27 311

v10		96.14 253	95.50 256	98.07 227	98.19 259	97.96 218	99.83 232	99.07 286	92.10 295	98.07 244	98.94 284	91.07 248	98.61 265	92.41 295	89.82 293	97.63 291

nrg030		97.64 182	97.27 189	98.75 183	98.34 249	99.53 110	100.00 1	99.22 240	96.21 205	98.27 237	99.95 172	94.40 196	98.98 227	99.23 146	89.78 294	97.75 222

VPA-MVSNet		97.03 205	96.43 214	98.82 179	98.64 239	99.32 128	99.38 296	99.47 83	96.73 176	98.91 195	98.94 284	87.00 293	99.40 208	99.23 146	89.59 295	97.76 218

MDA-MVSNet_test_wron		92.61 297	91.09 303	97.19 264	96.71 317	97.26 246	100.00 1	99.14 260	88.61 323	67.90 350	98.32 312	89.03 274	96.57 314	90.47 307	89.59 295	97.74 246

MDA-MVSNet-bldmvs		91.65 305	89.94 308	96.79 288	96.72 316	96.70 261	99.42 293	98.94 304	88.89 322	66.97 352	98.37 310	81.43 323	95.91 331	89.24 321	89.46 297	97.75 222

WR-MVS		97.09 200	96.64 204	98.46 192	98.43 246	99.09 145	99.97 200	99.33 197	95.62 219	97.76 255	99.67 218	91.17 242	98.56 273	98.49 180	89.28 298	97.74 246

test20.03		93.11 294	92.85 288	93.88 316	95.19 328	91.83 319	100.00 1	98.87 308	93.68 271	92.76 311	98.88 288	89.20 273	92.71 342	77.88 341	89.19 299	97.09 314

1111		88.62 312	89.13 311	87.08 327	87.71 341	77.22 339	99.96 203	97.71 339	85.51 331	83.47 340	96.26 322	95.76 176	90.96 343	66.63 349	89.17 300	93.07 342

YYNet1		92.44 299	90.92 304	97.03 267	96.20 319	97.06 253	99.99 176	99.14 260	88.21 325	67.93 349	98.43 307	88.63 278	96.28 327	90.64 303	89.08 301	97.74 246

CP-MVSNet		96.73 217	96.25 223	98.18 217	98.21 258	98.67 169	99.77 248	99.32 200	95.06 234	97.20 273	99.65 221	90.10 259	98.19 287	98.06 202	88.90 302	97.66 282

PS-CasMVS		96.34 241	95.78 246	98.03 232	98.18 260	98.27 191	99.71 263	99.32 200	94.75 238	96.82 282	99.65 221	86.98 294	98.15 289	97.74 210	88.85 303	97.66 282

v8		96.35 240	95.73 249	98.21 216	98.11 268	98.23 196	99.94 213	99.07 286	92.66 291	98.29 235	99.00 278	91.46 236	98.77 250	94.17 275	88.83 304	97.62 293

V4		95.89 263	95.36 263	97.49 251	97.65 295	97.40 237	99.88 226	99.07 286	92.19 293	98.08 242	99.01 276	90.20 258	98.72 256	93.57 285	88.63 305	96.34 321

v52		95.88 265	95.35 264	97.48 252	97.66 294	97.38 240	99.88 226	99.07 286	92.19 293	98.09 241	99.02 275	90.06 261	98.72 256	93.58 284	88.61 306	96.34 321

v7n		96.06 257	95.42 262	97.99 235	97.58 301	97.35 241	99.86 229	99.11 272	92.81 290	97.91 252	99.49 244	90.99 249	98.92 230	92.51 292	88.49 307	97.70 269

WR-MVS_H		96.73 217	96.32 219	97.95 236	98.26 255	97.88 223	99.72 261	99.43 115	95.06 234	96.99 276	98.68 296	93.02 212	98.53 274	97.43 221	88.33 308	97.43 304

NR-MVSNet		96.63 225	96.04 234	98.38 197	98.31 251	98.98 156	99.22 314	99.35 190	95.87 210	94.43 304	99.65 221	92.73 215	98.40 282	96.78 239	88.05 309	97.75 222

pm-mvs1		95.76 266	95.01 272	98.00 233	98.23 257	97.45 235	99.24 306	99.04 299	93.13 288	95.93 294	99.72 205	86.28 298	98.84 241	95.62 254	87.92 310	97.72 261

VPNet		96.41 235	95.76 247	98.33 202	98.61 240	98.30 188	99.48 289	99.45 97	96.98 162	98.87 197	99.88 183	81.57 322	98.93 229	99.22 148	87.82 311	97.76 218

UniMVSNet (Re)		97.29 193	96.85 198	98.59 190	98.49 245	99.13 144	100.00 1	99.42 121	96.52 191	98.24 240	98.90 287	94.93 191	98.89 234	97.54 218	87.61 312	97.75 222

PEN-MVS		96.01 258	95.48 260	97.58 248	97.74 291	97.26 246	99.90 220	99.29 211	94.55 245	96.79 283	99.55 238	87.38 289	97.84 307	96.92 233	87.24 313	97.65 287

v148		96.29 243	95.84 242	97.63 244	97.74 291	96.53 263	100.00 1	99.07 286	93.52 277	98.01 248	99.42 248	91.22 240	98.60 267	96.37 244	87.22 314	97.75 222

UniMVSNet_NR-MVSNet		97.16 197	96.80 199	98.22 214	98.38 248	98.41 176	100.00 1	99.45 97	96.14 206	97.76 255	99.64 225	95.05 188	98.50 276	97.98 203	86.84 315	97.75 222

DU-MVS		96.93 210	96.49 210	98.22 214	98.31 251	98.41 176	100.00 1	99.37 176	96.41 197	97.76 255	99.65 221	92.14 220	98.50 276	97.98 203	86.84 315	97.75 222

Baseline_NR-MVSNet		96.16 251	95.70 250	97.56 249	98.28 254	96.79 259	100.00 1	97.86 337	91.93 297	97.63 260	99.47 246	92.14 220	98.35 284	97.13 227	86.83 317	97.54 300

TranMVSNet+NR-MVSNet		96.45 234	96.01 235	97.79 243	98.00 283	97.62 233	100.00 1	99.35 190	95.98 208	97.31 269	99.64 225	90.09 260	98.00 305	96.89 234	86.80 318	97.75 222

pmmvs6		93.64 282	92.87 287	95.94 301	97.47 308	91.41 323	98.92 331	99.02 300	87.84 327	95.01 299	99.61 233	77.24 337	98.77 250	94.33 273	86.41 319	97.63 291

DTE-MVSNet		95.52 269	94.99 273	97.08 265	97.49 306	96.45 264	100.00 1	99.25 230	93.82 263	96.17 289	99.57 237	87.81 285	97.18 312	94.57 268	86.26 320	97.62 293

v748		95.47 271	94.95 274	97.04 266	97.46 309	94.76 290	99.93 215	99.10 273	91.95 296	97.11 274	99.18 257	89.94 264	98.68 260	94.01 279	85.88 321	97.67 280

TransMVSNet (Re)		94.78 276	93.72 279	97.93 239	98.34 249	97.88 223	99.23 312	97.98 334	91.60 299	94.55 302	99.71 207	87.89 284	98.36 283	89.30 320	84.92 322	97.56 299

UnsupCasMVSNet_eth		94.25 279	93.89 277	95.34 302	97.63 296	92.13 317	99.73 259	99.36 182	94.88 237	92.78 310	98.63 300	82.72 316	96.53 318	94.57 268	84.73 323	97.36 307

ambc				88.45 322	86.84 344	70.76 348	97.79 345	98.02 333		90.91 316	95.14 336	38.69 356	98.51 275	94.97 265	84.23 324	96.09 325

PMVS	60.66 23	65.98 332	65.05 331	68.75 346	55.06 361	38.40 362	88.19 352	96.98 344	48.30 357	44.82 358	88.52 348	12.22 365	86.49 350	67.58 348	83.79 325	81.35 355
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PVSNet_0	93.57 19	96.41 235	95.74 248	98.41 195	99.84 98	95.22 274	100.00 1	100.00 1	98.08 76	97.55 264	99.78 201	84.40 308	100.00 1	100.00 1	81.99 326	100.00 1

Patchmatch-RL test		93.49 285	93.63 281	93.05 317	91.78 334	83.41 334	98.21 341	96.95 345	91.58 300	91.05 315	97.64 315	99.40 48	95.83 332	94.11 278	81.95 327	99.91 128

PM-MVS		88.39 313	87.41 315	91.31 319	91.73 335	82.02 336	99.79 243	96.62 348	91.06 304	90.71 317	95.73 324	48.60 353	95.96 330	90.56 305	81.91 328	95.97 326

pmmvs-eth3d		91.73 304	90.67 305	94.92 307	91.63 336	92.71 314	99.90 220	98.54 320	91.19 303	88.08 331	95.50 329	79.31 333	96.13 329	90.55 306	81.32 329	95.91 334

testmv		79.83 320	79.77 321	79.99 337	78.22 353	63.55 354	99.67 272	95.51 352	80.89 340	76.24 344	92.90 343	52.16 350	86.10 352	62.45 352	79.90 330	90.33 348

UnsupCasMVSNet_bld		89.50 311	88.00 314	93.99 315	95.30 327	88.86 327	98.52 338	99.28 219	85.50 333	87.80 333	94.11 340	61.63 347	96.96 313	90.63 304	79.26 331	96.15 323

v11		93.14 293	91.93 300	96.77 289	98.01 281	98.17 203	99.72 261	98.74 311	89.39 321	88.81 325	95.49 330	91.15 243	96.29 326	86.78 325	79.25 332	95.86 336

new-patchmatchnet		90.30 310	89.46 309	92.84 318	90.77 337	88.55 328	99.83 232	98.80 310	90.07 310	87.86 332	95.00 338	78.77 334	94.30 338	84.86 328	79.15 333	95.68 338

IB-MVS	96.24 12	97.54 187	96.95 194	99.33 148	99.67 136	98.10 209	100.00 1	99.47 83	97.42 137	99.26 175	99.69 212	98.83 101	99.89 139	99.43 129	78.77 334	100.00 1
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
v18		93.55 283	92.42 291	96.91 275	98.12 266	98.26 194	99.83 232	98.74 311	89.99 311	88.94 323	95.64 326	92.02 223	96.54 315	90.27 310	78.26 335	95.94 329

v16		93.48 286	92.34 293	96.89 276	98.13 265	98.19 202	99.82 237	98.74 311	89.94 313	88.90 324	95.62 327	91.65 227	96.54 315	90.03 312	78.22 336	95.95 327

v17		93.53 284	92.42 291	96.88 280	98.09 270	98.16 204	99.83 232	98.74 311	89.95 312	89.05 320	95.65 325	91.99 225	96.54 315	90.31 309	78.15 337	95.95 327

pmmvs3		90.62 309	89.36 310	94.40 310	90.53 338	91.49 322	100.00 1	96.73 347	84.21 336	93.65 309	96.65 318	82.56 319	94.83 336	82.28 332	77.62 338	96.89 315

v15		93.28 288	92.08 294	96.87 281	98.07 274	98.22 200	99.82 237	98.74 311	89.83 314	88.74 326	95.44 331	91.55 232	96.47 319	89.70 314	76.87 339	95.93 330

V14		93.24 289	92.04 295	96.87 281	98.07 274	98.20 201	99.80 242	98.74 311	89.76 316	88.64 327	95.53 328	91.47 235	96.47 319	89.49 316	76.84 340	95.92 331

V9		93.20 290	91.99 297	96.85 283	98.05 277	98.16 204	99.77 248	98.73 317	89.67 317	88.64 327	95.44 331	91.34 239	96.47 319	89.46 317	76.79 341	95.92 331

v13		93.18 291	91.97 298	96.81 286	98.12 266	98.12 207	99.74 255	98.73 317	89.47 319	88.52 329	95.40 335	91.72 226	96.41 322	89.23 322	76.77 342	95.92 331

v12		93.18 291	91.97 298	96.80 287	98.09 270	98.10 209	99.76 251	98.73 317	89.61 318	88.45 330	95.41 334	91.63 230	96.39 324	89.32 319	76.76 343	95.91 334

Anonymous20231211		84.35 318	82.41 319	90.15 320	89.14 339	78.88 337	98.71 335	98.22 324	70.20 346	86.88 334	95.44 331	47.11 355	95.72 334	81.14 333	74.88 344	95.84 337

LCM-MVSNet		79.01 323	76.93 325	85.27 332	78.28 352	68.01 349	96.57 346	98.03 331	55.10 352	82.03 343	93.27 342	31.99 359	93.95 339	82.72 331	74.37 345	93.84 340

TDRefinement		91.93 301	90.48 306	96.27 297	81.60 349	92.65 315	99.10 325	97.61 341	93.96 259	93.77 308	99.85 188	80.03 329	99.53 195	97.82 209	70.59 346	96.63 318

PMMVS2		79.15 322	77.28 324	84.76 333	82.34 348	72.66 343	99.70 265	95.11 353	71.68 345	84.78 339	90.87 344	32.05 358	89.99 346	75.53 344	63.45 347	91.64 344

PNet_i23d		69.93 328	67.61 330	76.86 338	75.89 355	62.08 357	97.85 343	88.23 358	61.04 350	55.65 355	84.10 353	19.35 362	83.21 353	66.45 351	59.98 348	85.29 353

MVE	68.59 21	67.22 330	64.68 332	74.84 339	74.67 357	62.32 356	95.84 347	90.87 357	50.98 354	58.72 354	81.05 355	12.20 366	78.95 355	61.06 354	56.75 349	83.24 354
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
.test1245		85.18 316	84.81 317	86.28 329	87.71 341	77.22 339	99.96 203	97.71 339	85.51 331	83.47 340	96.26 322	95.76 176	90.96 343	66.63 349	50.30 350	90.64 346

testmvs		80.17 319	81.95 320	74.80 340	58.54 360	59.58 358	100.00 1	87.14 360	76.09 343	99.61 156	100.00 1	67.06 346	74.19 359	98.84 162	50.30 350	90.64 346

E-PMN		70.72 327	70.06 328	72.69 344	83.92 347	65.48 353	99.95 209	92.72 355	49.88 355	72.30 347	86.26 351	47.17 354	77.43 356	53.83 356	44.49 352	75.17 358

EMVS		69.88 329	69.09 329	72.24 345	84.70 345	65.82 352	99.96 203	87.08 361	49.82 356	71.51 348	84.74 352	49.30 352	75.32 357	50.97 357	43.71 353	75.59 357

wuykxyi23d		62.75 333	59.23 334	73.34 342	61.53 358	59.39 359	93.28 350	86.17 362	53.70 353	46.89 357	77.89 358	12.35 363	79.96 354	60.86 355	40.35 354	80.68 356

ANet_high		66.05 331	63.44 333	73.88 341	61.14 359	63.45 355	95.68 349	87.18 359	79.93 341	47.35 356	80.68 356	22.35 361	72.33 360	61.24 353	35.42 355	85.88 352

no-one		74.65 326	71.03 327	85.51 331	80.99 350	75.42 341	99.70 265	97.15 343	81.02 339	66.48 353	80.55 357	29.10 360	93.65 340	73.74 345	30.53 356	87.47 349

tmp_tt		75.80 325	74.26 326	80.43 335	52.91 362	53.67 360	87.42 353	97.98 334	61.80 349	67.04 351	100.00 1	76.43 339	96.40 323	96.47 243	28.26 357	91.23 345

test123		79.44 321	79.23 323	80.05 336	80.03 351	71.72 345	100.00 1	77.93 363	62.52 348	94.81 300	99.69 212	78.21 335	74.53 358	92.57 291	27.33 358	93.90 339

wuyk23d		28.28 335	29.73 337	23.92 348	75.89 355	32.61 363	66.50 354	12.88 364	16.09 358	14.59 359	16.59 360	12.35 363	32.36 361	39.36 358	13.36 359	6.79 359

cdsmvs_eth3d_5k		24.41 336	32.55 336	0.00 349	0.00 363	0.00 364	0.00 355	99.39 169	0.00 359	0.00 360	100.00 1	93.55 205	0.00 362	0.00 359	0.00 360	0.00 360

pcd_1.5k_mvsjas		8.24 338	10.99 339	0.00 349	0.00 363	0.00 364	0.00 355	0.00 365	0.00 359	0.00 360	0.14 361	98.75 106	0.00 362	0.00 359	0.00 360	0.00 360

sosnet-low-res		0.01 339	0.02 340	0.00 349	0.00 363	0.00 364	0.00 355	0.00 365	0.00 359	0.00 360	0.14 361	0.00 367	0.00 362	0.00 359	0.00 360	0.00 360

sosnet		0.01 339	0.02 340	0.00 349	0.00 363	0.00 364	0.00 355	0.00 365	0.00 359	0.00 360	0.14 361	0.00 367	0.00 362	0.00 359	0.00 360	0.00 360

uncertanet		0.01 339	0.02 340	0.00 349	0.00 363	0.00 364	0.00 355	0.00 365	0.00 359	0.00 360	0.14 361	0.00 367	0.00 362	0.00 359	0.00 360	0.00 360

Regformer		0.01 339	0.02 340	0.00 349	0.00 363	0.00 364	0.00 355	0.00 365	0.00 359	0.00 360	0.14 361	0.00 367	0.00 362	0.00 359	0.00 360	0.00 360

ab-mvs-re		8.33 337	11.11 338	0.00 349	0.00 363	0.00 364	0.00 355	0.00 365	0.00 359	0.00 360	100.00 1	0.00 367	0.00 362	0.00 359	0.00 360	0.00 360

uanet		0.01 339	0.02 340	0.00 349	0.00 363	0.00 364	0.00 355	0.00 365	0.00 359	0.00 360	0.14 361	0.00 367	0.00 362	0.00 359	0.00 360	0.00 360

GSMVS																99.91 128

test_part3							100.00 1		98.23 64		100.00 1		100.00 1	100.00 1

test_part2					100.00 1	99.99 1				100.00 1

sam_mvs1												99.29 62				99.91 128

sam_mvs												99.33 51

MTGPA								99.42 121

test_post1							99.32 300				88.24 349	99.33 51	99.59 176	98.31 187

test_post											89.05 347	99.49 37	99.59 176

patchmatchnet-post											97.79 314	99.41 47	99.54 191

MTMP								99.18 251

gm-plane-assit					99.52 171	97.26 246			95.86 212		100.00 1		99.43 205	98.76 167

TEST9					100.00 1	99.95 19	100.00 1	99.42 121	97.65 119	100.00 1	100.00 1	99.53 26	99.97 99

test_8					100.00 1	99.91 39	100.00 1	99.42 121	97.70 109	100.00 1	100.00 1	99.51 31	99.98 95

agg_prior					100.00 1	99.88 59		99.42 121		100.00 1			99.97 99

test_prior4						99.93 33	100.00 1

test_prior				99.90 72	100.00 1	99.75 85		99.73 55					99.97 99			100.00 1

旧先验2							100.00 1		98.11 75	100.00 1			100.00 1	99.67 107

新几何2							100.00 1

无先验							100.00 1	99.80 43	97.98 84				100.00 1	99.33 140		100.00 1

原ACMM2							100.00 1

testdata2													100.00 1	97.36 224

segment_acmp												99.55 24

testdata1							100.00 1		98.77 37

plane_prior7					99.00 220	94.78 289

plane_prior6					99.06 212	94.80 285						88.58 281

plane_prior4											99.97 151

plane_prior3						94.79 288			99.03 16	99.08 186

plane_prior2							100.00 1		99.00 19

plane_prior1					99.02 215

n2								0.00 365

nn								0.00 365

door-mid								96.32 350

test11								99.42 121

door								96.13 351

HQP5-MVS						94.82 282

HQP-NCC					99.07 208		100.00 1		99.04 13	99.17 178

ACMP_Plane					99.07 208		100.00 1		99.04 13	99.17 178

BP-MVS														99.79 91

HQP4-MVS										99.17 178			99.57 179			97.77 216

HQP2-MVS												88.61 279

NP-MVS					99.07 208	94.81 284					99.97 151

MDTV_nov1_ep13_2view						99.24 137	99.56 282		96.31 202	99.96 88		98.86 100		98.92 158		99.89 141

Test By Simon												99.10 79

High-resolution multi-view benchmark