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.

9.14			99.57 53		99.99 48		100.00 1	99.42 123	97.54 127	100.00 1	100.00 1	99.15 79	99.99 85	100.00 1	100.00 1

testtj		99.70 36	99.61 44	99.99 7	100.00 1	99.98 9	100.00 1	99.53 66	97.71 110	100.00 1	100.00 1	99.23 69	100.00 1	100.00 1	100.00 1	100.00 1

save filter2										100.00 1	100.00 1	99.46 37	100.00 1	100.00 1	100.00 1	100.00 1

DVP-MVS		99.83 7	99.78 6	100.00 1	100.00 1	99.99 2	100.00 1	99.42 123	99.04 13	100.00 1	100.00 1	99.53 21	100.00 1	100.00 1	100.00 1	100.00 1

test_0728_THIRD									98.79 41	100.00 1	100.00 1	99.61 13	100.00 1	100.00 1	100.00 1	100.00 1

test_0728_SECOND				100.00 1	99.99 48	99.99 2	100.00 1	99.42 123					100.00 1	100.00 1	100.00 1	100.00 1

SR-MVS		99.68 44	99.58 50	99.98 20	100.00 1	99.95 24	100.00 1	99.64 61	97.59 123	100.00 1	100.00 1	98.99 90	99.99 85	100.00 1	100.00 1	100.00 1

DPM-MVS		99.63 55	99.51 60	100.00 1	99.90 100	100.00 1	100.00 1	99.43 115	99.00 21	100.00 1	100.00 1	99.58 18	100.00 1	97.64 222	100.00 1	100.00 1

SMA-MVS		99.69 40	99.59 47	99.98 20	99.99 48	99.93 37	100.00 1	99.43 115	97.50 132	100.00 1	100.00 1	99.43 43	100.00 1	100.00 1	100.00 1	100.00 1

DPE-MVS		99.79 13	99.73 15	99.99 7	99.99 48	99.98 9	100.00 1	99.42 123	98.91 30	100.00 1	100.00 1	99.22 71	100.00 1	100.00 1	100.00 1	100.00 1

CHOSEN 280x420		99.85 3	99.87 1	99.80 94	99.99 48	99.97 13	99.97 196	99.98 13	98.96 24	100.00 1	100.00 1	99.96 3	99.42 212	100.00 1	100.00 1	100.00 1

MP-MVS-pluss		99.61 59	99.50 62	99.97 29	99.98 79	99.92 42	100.00 1	99.42 123	97.53 129	99.77 150	100.00 1	98.77 108	100.00 1	99.99 49	100.00 1	99.99 94
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS		99.81 10	99.77 9	99.94 64	100.00 1	99.86 73	100.00 1	99.42 123	98.87 34	100.00 1	100.00 1	99.65 12	99.96 118	100.00 1	100.00 1	100.00 1

TSAR-MVS + MP.		99.82 8	99.77 9	99.99 7	100.00 1	99.96 15	100.00 1	99.43 115	99.05 12	100.00 1	100.00 1	99.45 38	99.99 85	100.00 1	100.00 1	100.00 1
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
ACMMP_NAP		99.67 48	99.57 53	99.97 29	99.98 79	99.92 42	100.00 1	99.42 123	97.83 100	100.00 1	100.00 1	98.89 102	100.00 1	99.98 63	100.00 1	100.00 1

zzz-MVS		99.68 44	99.59 47	99.97 29	99.99 48	99.91 45	100.00 1	99.42 123	98.32 66	99.94 121	100.00 1	98.65 112	100.00 1	99.96 72	100.00 1	100.00 1

MTAPA		99.68 44	99.59 47	99.97 29	99.99 48	99.91 45	100.00 1	99.42 123	98.32 66	99.94 121	100.00 1	98.65 112	100.00 1	99.96 72	100.00 1	100.00 1

test9_res														100.00 1	100.00 1	100.00 1

train_agg		99.71 33	99.63 40	99.97 29	100.00 1	99.95 24	100.00 1	99.42 123	97.70 111	100.00 1	100.00 1	99.51 26	99.97 104	100.00 1	100.00 1	100.00 1

agg_prior1		99.71 33	99.63 40	99.95 51	100.00 1	99.88 67	100.00 1	99.42 123	97.72 107	100.00 1	100.00 1	99.51 26	99.97 104	100.00 1	100.00 1	100.00 1

agg_prior2														100.00 1	100.00 1	100.00 1

HFP-MVS		99.74 24	99.67 28	99.96 40	100.00 1	99.89 57	100.00 1	99.76 43	97.95 92	100.00 1	100.00 1	99.31 55	100.00 1	99.99 49	100.00 1	100.00 1

region2R		99.72 30	99.64 36	99.97 29	100.00 1	99.90 51	100.00 1	99.74 50	97.86 99	100.00 1	100.00 1	99.19 75	100.00 1	99.99 49	100.00 1	100.00 1

#test#		99.75 19	99.68 23	99.96 40	100.00 1	99.89 57	100.00 1	99.76 43	98.07 80	100.00 1	100.00 1	99.31 55	100.00 1	99.99 49	100.00 1	100.00 1

EI-MVSNet-UG-set		99.69 40	99.63 40	99.87 80	99.99 48	99.64 101	99.95 203	99.44 105	98.35 64	100.00 1	100.00 1	98.98 91	99.97 104	99.98 63	100.00 1	100.00 1

EI-MVSNet-Vis-set		99.70 36	99.64 36	99.87 80	100.00 1	99.64 101	99.98 190	99.44 105	98.35 64	99.99 85	100.00 1	99.04 85	99.96 118	99.98 63	100.00 1	100.00 1

Regformer-3		99.73 27	99.65 32	99.96 40	100.00 1	99.89 57	100.00 1	99.44 105	98.40 58	100.00 1	100.00 1	99.03 88	99.97 104	99.99 49	100.00 1	100.00 1

Regformer-4		99.73 27	99.65 32	99.95 51	100.00 1	99.89 57	100.00 1	99.44 105	98.40 58	100.00 1	100.00 1	99.03 88	99.97 104	99.99 49	100.00 1	100.00 1

Regformer-1		99.75 19	99.68 23	99.98 20	100.00 1	99.94 32	100.00 1	99.44 105	98.43 55	100.00 1	100.00 1	99.23 69	99.99 85	99.99 49	100.00 1	100.00 1

Regformer-2		99.75 19	99.68 23	99.97 29	100.00 1	99.94 32	100.00 1	99.44 105	98.42 57	100.00 1	100.00 1	99.22 71	99.99 85	99.99 49	100.00 1	100.00 1

HPM-MVS++		99.82 8	99.76 11	99.99 7	99.99 48	99.98 9	100.00 1	99.83 35	98.88 32	99.96 97	100.00 1	99.21 73	100.00 1	100.00 1	100.00 1	99.99 94

XVS		99.79 13	99.73 15	99.98 20	100.00 1	99.94 32	100.00 1	99.75 47	98.67 46	100.00 1	100.00 1	99.16 77	100.00 1	100.00 1	100.00 1	100.00 1

test_prior3		99.81 10	99.78 6	99.90 72	100.00 1	99.75 86	100.00 1	99.73 52	98.82 38	100.00 1	100.00 1	99.47 34	99.97 104	100.00 1	100.00 1	100.00 1

test_prior2							100.00 1		98.82 38	100.00 1	100.00 1	99.47 34		100.00 1	100.00 1

X-MVStestdata		97.04 207	96.06 230	99.98 20	100.00 1	99.94 32	100.00 1	99.75 47	98.67 46	100.00 1	66.97 336	99.16 77	100.00 1	100.00 1	100.00 1	100.00 1

新几何1				99.99 7	100.00 1	99.96 15		99.81 38	97.89 95	100.00 1	100.00 1	99.20 74	100.00 1	97.91 215	100.00 1	100.00 1

旧先验1					99.99 48	99.88 67		99.82 36			100.00 1	99.27 66			100.00 1	100.00 1

原ACMM1				99.93 66	100.00 1	99.80 81		99.66 60	98.18 69	100.00 1	100.00 1	99.43 43	100.00 1	99.50 141	100.00 1	100.00 1

test222					99.99 48	99.90 51	100.00 1	99.69 59	97.66 114	100.00 1	100.00 1	99.30 61			100.00 1	100.00 1

testdata				99.66 111	99.99 48	98.97 157		99.73 52	97.96 91	100.00 1	100.00 1	99.42 45	100.00 1	99.28 154	100.00 1	100.00 1

1314		99.38 79	99.19 94	99.96 40	98.88 240	99.89 57	99.24 285	99.93 26	98.88 32	98.79 208	100.00 1	97.02 152	100.00 1	100.00 1	100.00 1	100.00 1

1121		99.63 55	99.51 60	99.99 7	99.99 48	99.96 15	99.24 285	99.74 50	97.89 95	100.00 1	100.00 1	99.39 49	100.00 1	99.33 150	100.00 1	100.00 1

MVS		99.22 102	98.96 109	99.98 20	99.00 229	99.95 24	99.24 285	99.94 18	98.14 73	98.88 199	100.00 1	95.63 181	100.00 1	99.85 90	100.00 1	100.00 1

SD-MVS		99.81 10	99.75 13	99.99 7	99.99 48	99.96 15	100.00 1	99.42 123	99.01 20	100.00 1	100.00 1	99.33 51	100.00 1	100.00 1	100.00 1	100.00 1
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
MSLP-MVS++		99.89 1	99.85 2	99.99 7	100.00 1	99.96 15	100.00 1	99.95 15	99.11 6	100.00 1	100.00 1	99.60 14	100.00 1	100.00 1	100.00 1	100.00 1

APDe-MVS		99.84 6	99.78 6	99.99 7	100.00 1	99.98 9	100.00 1	99.44 105	99.06 10	100.00 1	100.00 1	99.56 19	99.99 85	100.00 1	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 50	99.55 58	99.97 29	99.99 48	99.91 45	100.00 1	99.48 73	97.54 127	100.00 1	100.00 1	98.97 92	99.99 85	99.98 63	100.00 1	100.00 1

ACMMPR		99.74 24	99.67 28	99.96 40	100.00 1	99.89 57	100.00 1	99.76 43	97.95 92	100.00 1	100.00 1	99.29 62	100.00 1	99.99 49	100.00 1	100.00 1

MP-MVS		99.61 59	99.49 64	99.98 20	99.99 48	99.94 32	100.00 1	99.42 123	97.82 101	99.99 85	100.00 1	98.20 124	100.00 1	99.99 49	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 44	99.95 51	99.99 48	99.85 76	100.00 1	99.58 63	97.69 113	100.00 1	100.00 1	99.44 39	100.00 1	99.79 99	100.00 1	100.00 1

MCST-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 2	100.00 1	99.73 52	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 27	99.64 36	99.99 7	100.00 1	99.97 13	100.00 1	99.42 123	98.02 83	100.00 1	100.00 1	99.32 54	99.99 85	100.00 1	100.00 1	100.00 1

test12				99.95 51	99.99 48	99.89 57		99.42 123		100.00 1		99.24 68	99.97 104		100.00 1	100.00 1

abl_6		99.53 65	99.40 67	99.92 68	100.00 1	99.76 84	100.00 1	99.42 123	97.21 154	100.00 1	100.00 1	98.12 126	100.00 1	99.82 98	100.00 1	100.00 1

mPP-MVS		99.69 40	99.60 46	99.97 29	100.00 1	99.91 45	100.00 1	99.42 123	97.91 94	100.00 1	100.00 1	99.04 85	100.00 1	100.00 1	100.00 1	100.00 1

MVSFormer		98.94 128	98.82 124	99.28 152	99.45 189	99.49 111	100.00 1	99.13 269	95.46 234	99.97 94	100.00 1	96.76 162	98.59 265	98.63 186	100.00 1	99.74 188

lupinMVS		99.29 92	99.16 97	99.69 107	99.45 189	99.49 111	100.00 1	99.15 259	97.45 136	99.97 94	100.00 1	96.76 162	99.76 167	99.67 121	100.00 1	99.81 170

HPM-MVS_fast		99.60 62	99.49 64	99.91 69	99.99 48	99.78 82	100.00 1	99.42 123	97.09 160	100.00 1	100.00 1	98.95 95	99.96 118	99.98 63	100.00 1	100.00 1

HPM-MVS		99.59 63	99.50 62	99.89 75	100.00 1	99.70 96	100.00 1	99.42 123	97.46 135	100.00 1	100.00 1	98.60 114	99.96 118	99.99 49	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 44	99.58 50	99.97 29	99.99 48	99.96 15	100.00 1	99.42 123	97.53 129	100.00 1	100.00 1	99.27 66	99.97 104	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 2	100.00 1	99.77 42	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 2	100.00 1	99.71 58	99.07 8	100.00 1	100.00 1	99.59 16	100.00 1	100.00 1	100.00 1	100.00 1

114514_t		99.39 78	99.25 82	99.81 90	99.97 83	99.48 115	100.00 1	99.42 123	95.53 227	100.00 1	100.00 1	98.37 122	99.95 124	99.97 70	100.00 1	100.00 1

CP-MVS		99.67 48	99.58 50	99.95 51	100.00 1	99.84 77	100.00 1	99.42 123	97.77 104	100.00 1	100.00 1	99.07 82	100.00 1	100.00 1	100.00 1	100.00 1

SteuartSystems-ACMMP		99.78 15	99.71 18	99.98 20	99.76 125	99.95 24	100.00 1	99.42 123	98.69 44	100.00 1	100.00 1	99.52 24	99.99 85	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	98.88 179	99.62 149	96.71 246	100.00 1	99.28 220	97.09 160	98.81 206	100.00 1	94.91 191	99.96 118	99.54 137	100.00 1	99.96 104

DELS-MVS		99.62 57	99.56 57	99.82 87	99.92 97	99.45 116	100.00 1	99.78 41	98.92 29	99.73 154	100.00 1	97.70 135	100.00 1	99.93 80	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		98.64 147	98.65 138	98.60 190	99.59 156	96.17 252	100.00 1	99.28 220	96.67 186	98.41 228	100.00 1	94.52 195	99.83 156	99.41 145	100.00 1	99.81 170

CPTT-MVS		99.49 71	99.38 70	99.85 83	100.00 1	99.54 106	100.00 1	99.42 123	97.58 124	99.98 90	100.00 1	97.43 144	100.00 1	99.99 49	100.00 1	100.00 1

BH-RMVSNet		98.46 158	98.08 168	99.59 121	99.61 151	99.19 140	100.00 1	99.28 220	97.06 164	98.95 195	100.00 1	88.99 256	99.82 159	98.83 175	100.00 1	99.77 183

DP-MVS Recon		99.76 17	99.69 20	99.98 20	100.00 1	99.95 24	100.00 1	99.52 67	97.99 85	99.99 85	100.00 1	99.72 9	100.00 1	99.96 72	100.00 1	100.00 1

MVS_111021_LR		99.70 36	99.65 32	99.88 79	99.96 88	99.70 96	100.00 1	99.97 14	98.96 24	100.00 1	100.00 1	97.93 130	99.95 124	99.99 49	100.00 1	100.00 1

DP-MVS		98.86 134	98.54 148	99.81 90	99.97 83	99.45 116	99.52 264	99.40 160	94.35 257	98.36 229	100.00 1	96.13 172	99.97 104	99.12 161	100.00 1	100.00 1

QAPM		98.99 121	98.66 137	99.96 40	99.01 225	99.87 70	99.88 218	99.93 26	97.99 85	98.68 212	100.00 1	93.17 210	100.00 1	99.32 152	100.00 1	100.00 1

PAPM_NR		99.74 24	99.66 31	99.99 7	100.00 1	99.96 15	100.00 1	99.47 74	97.87 98	100.00 1	100.00 1	99.60 14	100.00 1	100.00 1	100.00 1	100.00 1

PAPR		99.76 17	99.68 23	99.99 7	100.00 1	99.96 15	100.00 1	99.47 74	98.16 70	100.00 1	100.00 1	99.51 26	100.00 1	100.00 1	100.00 1	100.00 1

MVS_111021_HR		99.71 33	99.63 40	99.93 66	99.95 89	99.83 78	100.00 1	100.00 1	98.89 31	100.00 1	100.00 1	97.85 131	99.95 124	100.00 1	100.00 1	100.00 1

CSCG		99.28 93	99.35 76	99.05 165	99.99 48	97.15 236	100.00 1	99.47 74	97.44 138	99.42 168	100.00 1	97.83 132	100.00 1	99.99 49	100.00 1	100.00 1

API-MVS		99.72 30	99.70 19	99.79 96	99.97 83	99.37 124	99.96 199	99.94 18	98.48 53	100.00 1	100.00 1	98.92 99	100.00 1	100.00 1	100.00 1	100.00 1

PAPM		99.78 15	99.76 11	99.85 83	99.01 225	99.95 24	100.00 1	99.75 47	99.37 3	99.99 85	100.00 1	99.76 8	99.60 177	100.00 1	100.00 1	100.00 1

CNLPA		99.72 30	99.65 32	99.91 69	99.97 83	99.72 91	100.00 1	99.47 74	98.43 55	99.88 135	100.00 1	99.14 80	100.00 1	99.97 70	100.00 1	100.00 1

PHI-MVS		99.50 69	99.39 69	99.82 87	100.00 1	99.45 116	100.00 1	99.94 18	96.38 203	100.00 1	100.00 1	98.18 125	100.00 1	100.00 1	100.00 1	100.00 1

F-COLMAP		99.64 52	99.64 36	99.67 109	99.99 48	99.07 147	100.00 1	99.44 105	98.30 68	99.90 130	100.00 1	99.18 76	99.99 85	99.91 82	100.00 1	99.94 112

DeepPCF-MVS	98.03 4	98.54 154	99.72 17	94.98 291	99.99 48	84.94 319	100.00 1	99.42 123	99.98 1	100.00 1	100.00 1	98.11 127	100.00 1	100.00 1	100.00 1	100.00 1

DeepC-MVS_fast	98.92 1	99.75 19	99.67 28	99.99 7	99.99 48	99.96 15	99.73 240	99.52 67	99.06 10	100.00 1	100.00 1	98.80 107	100.00 1	99.95 78	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 19	99.68 23	99.97 29	100.00 1	99.91 45	99.98 190	99.47 74	99.09 7	100.00 1	100.00 1	98.59 115	100.00 1	99.95 78	100.00 1	100.00 1

AdaColmap		99.44 75	99.26 81	99.95 51	100.00 1	99.86 73	99.70 245	99.99 10	98.53 52	99.90 130	100.00 1	95.34 183	100.00 1	99.92 81	100.00 1	100.00 1

PLC	98.56 2	99.70 36	99.74 14	99.58 125	100.00 1	98.79 162	100.00 1	99.54 65	98.58 51	99.96 97	100.00 1	99.59 16	100.00 1	100.00 1	100.00 1	99.94 112
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MAR-MVS		99.49 71	99.36 74	99.89 75	99.97 83	99.66 99	99.74 237	99.95 15	97.89 95	100.00 1	100.00 1	96.71 164	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	99.03 113	98.71 135	99.96 40	98.99 232	99.89 57	100.00 1	99.51 71	98.96 24	98.32 232	100.00 1	92.78 215	100.00 1	99.87 87	100.00 1	100.00 1

3Dnovator	95.63 14	99.06 110	98.76 130	99.96 40	98.86 243	99.90 51	99.98 190	99.93 26	98.95 27	98.49 225	100.00 1	92.91 214	100.00 1	99.71 110	100.00 1	100.00 1

TAPA-MVS	96.40 10	97.64 183	97.37 190	98.45 194	99.94 92	95.70 258	100.00 1	99.40 160	97.65 115	99.53 162	100.00 1	99.31 55	99.66 176	80.48 322	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
LS3D		99.31 90	99.13 98	99.87 80	99.99 48	99.71 92	99.55 261	99.46 89	97.32 147	99.82 146	100.00 1	96.85 161	99.97 104	99.14 159	100.00 1	99.92 121

GST-MVS		99.64 52	99.53 59	99.95 51	100.00 1	99.86 73	100.00 1	99.79 40	97.72 107	99.95 119	100.00 1	98.39 121	100.00 1	99.96 72	99.99 94	100.00 1

CANet		99.40 77	99.24 84	99.89 75	99.99 48	99.76 84	100.00 1	99.73 52	98.40 58	99.78 149	100.00 1	95.28 184	99.96 118	100.00 1	99.99 94	99.96 104

GG-mvs-BLEND				99.59 121	99.54 168	99.49 111	99.17 299	99.52 67		99.96 97	99.68 223	100.00 1	99.33 218	99.71 110	99.99 94	99.96 104

gg-mvs-nofinetune		96.95 210	96.10 228	99.50 131	99.41 193	99.36 125	99.07 311	99.52 67	83.69 319	99.96 97	83.60 332	100.00 1	99.20 222	99.68 119	99.99 94	99.96 104

PS-MVSNAJ		99.64 52	99.57 53	99.85 83	99.78 121	99.81 79	99.95 203	99.42 123	98.38 61	100.00 1	100.00 1	98.75 109	100.00 1	99.88 86	99.99 94	99.74 188

test-LLR		99.03 113	98.91 117	99.40 141	99.40 197	99.28 130	100.00 1	99.45 96	96.70 182	99.42 168	99.12 264	99.31 55	99.01 230	96.82 243	99.99 94	99.91 123

TESTMET0.1,1		99.08 108	98.96 109	99.44 135	99.63 145	99.38 121	100.00 1	99.45 96	95.53 227	99.48 165	100.00 1	99.71 10	99.02 229	96.84 242	99.99 94	99.91 123

test-mter		98.96 125	98.82 124	99.40 141	99.40 197	99.28 130	100.00 1	99.45 96	95.44 236	99.42 168	99.12 264	99.70 11	99.01 230	96.82 243	99.99 94	99.91 123

MVP-Stereo		96.51 226	96.48 214	96.60 276	95.65 313	94.25 286	98.84 316	98.16 311	95.85 219	95.23 296	99.04 271	92.54 220	99.13 224	92.98 286	99.98 102	96.43 313
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		95.66 262	95.87 238	95.05 289	97.80 282	89.25 313	98.88 315	99.30 210	96.35 204	96.86 278	99.01 275	81.35 306	99.43 210	93.30 284	99.98 102	96.46 312

PatchMatch-RL		99.02 117	98.78 128	99.74 103	99.99 48	99.29 129	100.00 1	100.00 1	98.38 61	99.89 133	99.81 205	93.14 212	99.99 85	97.85 217	99.98 102	99.95 109

jason		99.11 106	98.96 109	99.59 121	99.17 211	99.31 128	100.00 1	99.13 269	97.38 141	99.83 139	100.00 1	95.54 182	99.72 173	99.57 133	99.97 105	99.74 188
jason: jason.
OpenMVS	95.20 17	98.76 139	98.41 154	99.78 100	98.89 239	99.81 79	99.99 173	99.76 43	98.02 83	98.02 245	100.00 1	91.44 227	100.00 1	99.63 127	99.97 105	99.55 200

CANet_DTU		99.02 117	98.90 120	99.41 139	99.88 102	98.71 167	100.00 1	99.29 214	98.84 35	100.00 1	100.00 1	94.02 200	100.00 1	98.08 208	99.96 107	99.52 202

DeepC-MVS	97.84 5	99.00 119	98.80 127	99.60 119	99.93 94	99.03 150	100.00 1	99.40 160	98.61 50	99.33 173	100.00 1	92.23 221	99.95 124	99.74 107	99.96 107	99.83 162
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CHOSEN 1792x2688		99.00 119	98.91 117	99.25 155	99.90 100	97.79 214	100.00 1	99.99 10	98.79 41	98.28 235	100.00 1	93.63 204	99.95 124	99.66 124	99.95 109	100.00 1

baseline2		98.99 121	98.93 115	99.18 161	99.26 209	99.15 144	100.00 1	99.46 89	96.71 181	96.79 281	100.00 1	99.42 45	99.25 221	98.75 179	99.94 110	99.15 208

MSDG		98.90 132	98.63 140	99.70 106	99.92 97	99.25 134	100.00 1	99.37 180	95.71 221	99.40 172	100.00 1	96.58 165	99.95 124	96.80 245	99.94 110	99.91 123

COLMAP_ROB	97.10 7	98.29 166	98.17 166	98.65 188	99.94 92	97.39 225	99.30 281	99.40 160	95.64 222	97.75 256	100.00 1	92.69 218	99.95 124	98.89 171	99.92 112	98.62 213
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
PCF-MVS	98.23 3	98.69 144	98.37 158	99.62 115	99.78 121	99.02 151	99.23 291	99.06 289	96.43 199	98.08 241	100.00 1	94.72 192	99.95 124	98.16 206	99.91 113	99.90 132
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
UGNet		98.41 161	98.11 167	99.31 150	99.54 168	98.55 175	99.18 294	100.00 1	98.64 49	99.79 148	99.04 271	87.61 269	100.00 1	99.30 153	99.89 114	99.40 205
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 73	99.36 74	99.83 86	99.98 79	99.60 103	100.00 1	100.00 1	97.79 103	100.00 1	100.00 1	96.57 166	99.99 85	100.00 1	99.88 115	99.90 132

ACMMP		99.65 50	99.57 53	99.89 75	99.99 48	99.66 99	99.75 236	99.73 52	98.16 70	99.75 153	100.00 1	98.90 101	100.00 1	99.96 72	99.88 115	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		94.12 275	92.73 283	98.29 205	99.33 203	95.95 254	99.38 274	99.19 249	74.54 324	98.26 238	86.34 329	86.07 281	99.06 227	91.60 296	99.87 117	99.85 158

CS-MVS		99.33 87	99.23 87	99.65 112	99.63 145	99.18 141	100.00 1	99.27 227	97.45 136	99.96 97	100.00 1	97.22 146	99.87 147	99.67 121	99.86 118	99.90 132

AllTest		98.55 153	98.40 155	98.99 170	99.93 94	97.35 227	100.00 1	99.40 160	97.08 162	99.09 186	99.98 157	93.37 206	99.95 124	96.94 238	99.84 119	99.68 195

TestCases				98.99 170	99.93 94	97.35 227		99.40 160	97.08 162	99.09 186	99.98 157	93.37 206	99.95 124	96.94 238	99.84 119	99.68 195

OMC-MVS		99.27 94	99.38 70	98.96 173	99.95 89	97.06 240	100.00 1	99.40 160	98.83 36	99.88 135	100.00 1	97.01 153	99.86 148	99.47 142	99.84 119	99.97 101

UA-Net		99.06 110	98.83 123	99.74 103	99.52 177	99.40 120	99.08 309	99.45 96	97.64 117	99.83 139	100.00 1	95.80 177	99.94 135	98.35 198	99.80 122	99.88 149

PVSNet	94.91 18	99.30 91	99.25 82	99.44 135	100.00 1	98.32 188	100.00 1	99.86 34	98.04 82	100.00 1	100.00 1	96.10 173	100.00 1	99.55 134	99.73 123	100.00 1

ETV-MVS		99.26 96	99.19 94	99.45 134	99.63 145	98.75 163	100.00 1	99.27 227	96.93 168	99.95 119	100.00 1	97.47 140	99.79 163	99.74 107	99.72 124	99.82 166

EPNet_dtu		98.53 155	98.23 164	99.43 137	99.92 97	99.01 153	99.96 199	99.47 74	98.80 40	99.96 97	99.96 174	98.56 116	99.30 219	87.78 313	99.68 125	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	97.82 238	99.58 161	94.44 284	100.00 1	99.16 258	96.75 176	99.51 163	99.63 236	95.03 189	99.60 177	97.71 220	99.67 126	99.42 204

EIA-MVS		99.34 85	99.24 84	99.64 113	99.58 161	99.33 126	100.00 1	99.25 233	97.57 125	99.96 97	100.00 1	97.44 143	99.79 163	99.70 112	99.65 127	99.81 170

PVSNet_Blended_VisFu		99.33 87	99.18 96	99.78 100	99.82 104	99.49 111	100.00 1	99.95 15	97.36 142	99.63 159	100.00 1	96.45 170	99.95 124	99.79 99	99.65 127	99.89 138

thisisatest0515		99.42 76	99.31 79	99.74 103	99.59 156	99.55 105	100.00 1	99.46 89	96.65 187	99.92 127	100.00 1	99.44 39	99.85 152	99.09 163	99.63 129	99.81 170

EPNet		99.62 57	99.69 20	99.42 138	99.99 48	98.37 183	100.00 1	99.89 32	98.83 36	100.00 1	100.00 1	98.97 92	100.00 1	99.90 83	99.61 130	99.89 138
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
thisisatest0530		99.37 81	99.27 80	99.69 107	99.59 156	99.41 119	100.00 1	99.46 89	96.46 198	99.90 130	100.00 1	99.44 39	99.85 152	98.97 166	99.58 131	99.80 180

mvs-test1		98.89 133	98.99 107	98.60 190	99.77 123	95.96 253	100.00 1	98.94 300	97.61 119	99.93 126	99.92 187	95.89 174	99.93 137	99.36 147	99.50 132	99.90 132

Effi-MVS+-dtu		98.51 157	98.86 122	97.47 247	99.77 123	94.21 287	100.00 1	98.94 300	97.61 119	99.91 129	98.75 291	95.89 174	99.51 202	99.36 147	99.48 133	98.68 211

tttt0517		99.34 85	99.23 87	99.67 109	99.57 164	99.38 121	100.00 1	99.46 89	96.33 206	99.89 133	100.00 1	99.44 39	99.84 154	98.93 169	99.46 134	99.78 182

XVG-OURS-SEG-HR		98.27 168	98.31 160	98.14 215	99.59 156	95.92 255	100.00 1	99.36 186	98.48 53	99.21 178	100.00 1	89.27 253	99.94 135	99.76 105	99.17 135	98.56 214

xiu_mvs_v2_base		99.51 66	99.41 66	99.82 87	99.70 131	99.73 90	99.92 209	99.40 160	98.15 72	100.00 1	100.00 1	98.50 118	100.00 1	99.85 90	99.13 136	99.74 188

TSAR-MVS + GP.		99.61 59	99.69 20	99.35 146	99.99 48	98.06 199	100.00 1	99.36 186	99.83 2	100.00 1	100.00 1	98.95 95	99.99 85	100.00 1	99.11 137	100.00 1

xiu_mvs_v1_base_debu		99.35 82	99.21 90	99.79 96	99.67 136	99.71 92	99.78 228	99.36 186	98.13 74	100.00 1	100.00 1	97.00 156	100.00 1	99.83 93	99.07 138	99.66 197

xiu_mvs_v1_base		99.35 82	99.21 90	99.79 96	99.67 136	99.71 92	99.78 228	99.36 186	98.13 74	100.00 1	100.00 1	97.00 156	100.00 1	99.83 93	99.07 138	99.66 197

xiu_mvs_v1_base_debi		99.35 82	99.21 90	99.79 96	99.67 136	99.71 92	99.78 228	99.36 186	98.13 74	100.00 1	100.00 1	97.00 156	100.00 1	99.83 93	99.07 138	99.66 197

PatchmatchNet		99.03 113	98.96 109	99.26 154	99.49 186	98.33 186	99.38 274	99.45 96	96.64 188	99.96 97	99.58 243	99.49 31	99.50 203	97.63 223	99.00 141	99.93 119
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
EPMVS		99.25 99	99.13 98	99.60 119	99.60 153	99.20 139	99.60 257	100.00 1	96.93 168	99.92 127	99.36 258	99.05 84	99.71 174	98.77 177	98.94 142	99.90 132

Vis-MVSNet		98.52 156	98.25 161	99.34 147	99.68 135	98.55 175	99.68 250	99.41 158	97.34 145	99.94 121	100.00 1	90.38 241	99.70 175	99.03 165	98.84 143	99.76 185
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
SCA		98.30 164	97.98 174	99.23 156	99.41 193	98.25 192	99.99 173	99.45 96	96.91 170	99.76 152	99.58 243	89.65 248	99.54 194	98.31 200	98.79 144	99.91 123

sss		99.45 74	99.34 78	99.80 94	99.76 125	99.50 108	100.00 1	99.91 31	97.72 107	99.98 90	99.94 184	98.45 119	100.00 1	99.53 139	98.75 145	99.89 138

MDTV_nov1_ep13			98.94 114		99.53 172	98.36 184	99.39 273	99.46 89	96.54 193	99.99 85	99.63 236	98.92 99	99.86 148	98.30 202	98.71 146

MVS_0304		95.11 269	94.84 270	95.91 286	99.60 153	91.24 310	98.64 318	99.88 33	94.51 252	99.62 160	98.31 307	69.19 326	98.82 247	95.22 265	98.60 147	97.66 275

Patchmatch-test		97.83 179	97.42 187	99.06 163	99.08 216	97.66 218	98.66 317	99.21 246	93.65 272	98.25 239	99.58 243	99.47 34	99.57 182	90.25 307	98.59 148	99.95 109

ADS-MVSNet2		98.28 167	98.51 150	97.62 243	99.51 182	95.03 264	99.24 285	99.41 158	95.52 229	99.96 97	99.70 217	97.57 138	97.94 303	97.11 235	98.54 149	99.88 149

ADS-MVSNet		98.70 143	98.51 150	99.28 152	99.51 182	98.39 180	99.24 285	99.44 105	95.52 229	99.96 97	99.70 217	97.57 138	99.58 181	97.11 235	98.54 149	99.88 149

mvs_anonymous		98.80 138	98.60 144	99.38 144	99.57 164	99.24 136	100.00 1	99.21 246	95.87 215	98.92 196	99.82 202	96.39 171	99.03 228	99.13 160	98.50 151	99.88 149

PMMVS		99.12 105	98.97 108	99.58 125	99.57 164	98.98 155	100.00 1	99.30 210	97.14 157	99.96 97	100.00 1	96.53 169	99.82 159	99.70 112	98.49 152	99.94 112

MVS_Test		98.93 129	98.65 138	99.77 102	99.62 149	99.50 108	99.99 173	99.19 249	95.52 229	99.96 97	99.86 194	96.54 168	99.98 100	98.65 184	98.48 153	99.82 166

PatchT		95.90 258	94.95 269	98.75 185	99.03 223	98.39 180	99.08 309	99.32 203	85.52 315	99.96 97	94.99 319	97.94 129	98.05 299	80.20 323	98.47 154	99.81 170

test0.0.03 1		98.12 171	98.03 171	98.39 197	99.11 213	98.07 198	100.00 1	99.93 26	96.70 182	96.91 277	99.95 180	99.31 55	98.19 282	91.93 293	98.44 155	98.91 209

LCM-MVSNet-Re		96.52 225	97.21 195	94.44 294	99.27 207	85.80 318	99.85 220	96.61 329	95.98 213	92.75 308	98.48 299	93.97 201	97.55 308	99.58 132	98.43 156	99.98 96

dp		98.72 141	98.61 142	99.03 168	99.53 172	97.39 225	99.45 268	99.39 174	95.62 224	99.94 121	99.52 250	98.83 104	99.82 159	96.77 247	98.42 157	99.89 138

CR-MVSNet		98.02 174	97.71 183	98.93 174	99.31 204	98.86 160	99.13 304	99.00 298	96.53 194	99.96 97	98.98 277	96.94 159	98.10 292	91.18 298	98.40 158	99.84 159

RPMNet		95.10 270	93.82 273	98.93 174	99.31 204	98.86 160	99.13 304	99.38 177	79.82 322	99.96 97	95.13 317	95.69 180	98.10 292	77.54 327	98.40 158	99.84 159

DI_MVS_plusplus_test		96.28 242	95.16 264	99.61 116	96.01 311	99.18 141	100.00 1	99.29 214	96.49 197	89.08 315	98.42 303	80.06 308	99.90 142	98.74 180	98.39 160	99.75 186

IS-MVSNet		99.08 108	98.91 117	99.59 121	99.65 140	99.38 121	99.78 228	99.24 236	96.70 182	99.51 163	100.00 1	98.44 120	99.52 200	98.47 194	98.39 160	99.88 149

casdiffmvs		98.65 146	98.38 156	99.46 133	99.52 177	98.74 166	100.00 1	99.15 259	96.91 170	99.05 191	100.00 1	92.75 216	99.83 156	99.70 112	98.38 162	99.81 170

RPSCF		97.37 192	98.24 162	94.76 293	99.80 117	84.57 320	99.99 173	99.05 291	94.95 241	99.82 146	100.00 1	94.03 199	100.00 1	98.15 207	98.38 162	99.70 193

Effi-MVS+		98.58 150	98.24 162	99.61 116	99.60 153	99.26 132	97.85 324	99.10 276	96.22 209	99.97 94	99.89 190	93.75 202	99.77 166	99.43 143	98.34 164	99.81 170

DWT-MVSNet_test		99.22 102	99.22 89	99.22 158	99.56 167	97.98 203	99.89 215	99.39 174	97.20 155	99.96 97	100.00 1	99.52 24	99.82 159	99.11 162	98.34 164	99.87 156

baseline		98.69 144	98.45 153	99.41 139	99.52 177	98.67 170	100.00 1	99.17 257	97.03 165	99.13 184	100.00 1	93.17 210	99.74 170	99.70 112	98.34 164	99.81 170

Vis-MVSNet (Re-imp)		98.99 121	98.89 121	99.29 151	99.64 144	98.89 159	99.98 190	99.31 208	96.74 177	99.48 165	100.00 1	98.11 127	99.10 225	98.39 196	98.34 164	99.89 138

diffmvs		98.96 125	98.73 132	99.63 114	99.54 168	99.16 143	100.00 1	99.18 252	97.33 146	99.96 97	100.00 1	94.60 194	99.91 141	99.66 124	98.33 168	99.82 166

PatchFormer-LS_test		99.14 104	99.12 100	99.19 160	99.54 168	97.86 212	99.66 252	99.40 160	96.94 167	99.96 97	100.00 1	99.29 62	99.84 154	98.96 167	98.29 169	99.88 149

TR-MVS		98.14 170	97.74 180	99.33 148	99.59 156	98.28 190	99.27 282	99.21 246	96.42 200	99.15 183	99.94 184	88.87 259	99.79 163	98.88 172	98.29 169	99.93 119

JIA-IIPM		97.09 203	96.34 220	99.36 145	98.88 240	98.59 173	99.81 224	99.43 115	84.81 317	99.96 97	90.34 325	98.55 117	99.52 200	97.00 237	98.28 171	99.98 96

Fast-Effi-MVS+		98.40 162	98.02 172	99.55 128	99.63 145	99.06 148	100.00 1	99.15 259	95.07 238	99.42 168	99.95 180	93.26 209	99.73 172	97.44 227	98.24 172	99.87 156

HY-MVS	96.53 9	99.50 69	99.35 76	99.96 40	99.81 107	99.93 37	99.64 254	100.00 1	97.97 89	99.84 137	99.85 196	98.94 97	99.99 85	99.86 88	98.23 173	99.95 109

WTY-MVS		99.54 64	99.40 67	99.95 51	99.81 107	99.93 37	100.00 1	100.00 1	97.98 87	99.84 137	100.00 1	98.94 97	99.98 100	99.86 88	98.21 174	99.94 112

tpm cat1		98.05 172	97.76 179	98.92 176	99.50 185	97.10 239	99.77 233	99.30 210	90.20 303	99.72 155	98.71 292	97.71 134	99.86 148	96.75 248	98.20 175	99.81 170

tpmrst		98.98 124	98.93 115	99.14 162	99.61 151	97.74 215	99.52 264	99.36 186	96.05 212	99.98 90	99.64 232	99.04 85	99.86 148	98.94 168	98.19 176	99.82 166

tpmvs		98.59 149	98.38 156	99.23 156	99.69 132	97.90 207	99.31 280	99.47 74	94.52 251	99.68 157	99.28 262	97.64 136	99.89 143	97.71 220	98.17 177	99.89 138

cascas		98.43 159	98.07 169	99.50 131	99.65 140	99.02 151	100.00 1	99.22 242	94.21 260	99.72 155	99.98 157	92.03 224	99.93 137	99.68 119	98.12 178	99.54 201

MIMVSNet		97.06 206	96.73 205	98.05 226	99.38 201	96.64 249	98.47 320	99.35 194	93.41 277	99.48 165	98.53 298	89.66 247	97.70 307	94.16 277	98.11 179	99.80 180

HyFIR lowres test		99.32 89	99.24 84	99.58 125	99.95 89	99.26 132	100.00 1	99.99 10	96.72 180	99.29 175	99.91 188	99.49 31	99.47 206	99.74 107	98.08 180	100.00 1

EPP-MVSNet		99.10 107	99.00 105	99.40 141	99.51 182	98.68 169	99.92 209	99.43 115	95.47 233	99.65 158	100.00 1	99.51 26	99.76 167	99.53 139	98.00 181	99.75 186

CDS-MVSNet		98.96 125	98.95 113	99.01 169	99.48 187	98.36 184	99.93 208	99.37 180	96.79 175	99.31 174	99.83 199	99.77 7	98.91 238	98.07 209	97.98 182	99.77 183
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
tpm2		98.64 147	98.58 146	98.81 183	99.42 192	97.12 237	99.69 248	99.37 180	93.63 273	99.94 121	99.67 224	98.96 94	99.47 206	98.62 188	97.95 183	99.83 162

ab-mvs		98.42 160	98.02 172	99.61 116	99.71 129	99.00 154	99.10 307	99.64 61	96.70 182	99.04 192	99.81 205	90.64 235	99.98 100	99.64 126	97.93 184	99.84 159

TAMVS		98.76 139	98.73 132	98.86 180	99.44 191	97.69 216	99.57 259	99.34 199	96.57 191	99.12 185	99.81 205	98.83 104	99.16 223	97.97 214	97.91 185	99.73 192

thres200		99.27 94	99.04 101	99.96 40	99.81 107	99.90 51	100.00 1	99.94 18	97.31 149	99.83 139	99.96 174	97.04 149	100.00 1	99.62 128	97.88 186	99.98 96

DSMNet-mixed		95.18 268	95.21 263	95.08 288	96.03 310	90.21 311	99.65 253	93.64 333	92.91 288	98.34 231	97.40 311	90.05 244	95.51 322	91.02 300	97.86 187	99.51 203

thres100view900		99.25 99	99.01 104	99.95 51	99.81 107	99.87 70	100.00 1	99.94 18	97.13 158	99.83 139	99.96 174	97.01 153	100.00 1	99.59 129	97.85 188	99.98 96

tfpn200view9		99.26 96	99.03 102	99.96 40	99.81 107	99.89 57	100.00 1	99.94 18	97.23 151	99.83 139	99.96 174	97.04 149	100.00 1	99.59 129	97.85 188	99.98 96

thres400		99.26 96	99.03 102	99.95 51	99.81 107	99.89 57	100.00 1	99.94 18	97.23 151	99.83 139	99.96 174	97.04 149	100.00 1	99.59 129	97.85 188	99.97 101

XVG-OURS		98.30 164	98.36 159	98.13 218	99.58 161	95.91 256	100.00 1	99.36 186	98.69 44	99.23 177	100.00 1	91.20 229	99.92 140	99.34 149	97.82 191	98.56 214

CostFormer		98.84 135	98.77 129	99.04 167	99.41 193	97.58 220	99.67 251	99.35 194	94.66 247	99.96 97	99.36 258	99.28 65	99.74 170	99.41 145	97.81 192	99.81 170

testgi		96.18 245	95.93 236	96.93 267	98.98 233	94.20 288	100.00 1	99.07 281	97.16 156	96.06 290	99.86 194	84.08 295	97.79 306	90.38 306	97.80 193	98.81 210

thres600view7		99.24 101	99.00 105	99.95 51	99.81 107	99.87 70	100.00 1	99.94 18	97.13 158	99.83 139	99.96 174	97.01 153	100.00 1	99.54 137	97.77 194	99.97 101

test_yl		99.51 66	99.37 72	99.95 51	99.82 104	99.90 51	100.00 1	99.47 74	97.48 133	100.00 1	100.00 1	99.80 4	100.00 1	99.98 63	97.75 195	99.94 112

DCV-MVSNet		99.51 66	99.37 72	99.95 51	99.82 104	99.90 51	100.00 1	99.47 74	97.48 133	100.00 1	100.00 1	99.80 4	100.00 1	99.98 63	97.75 195	99.94 112

Test_1112_low_res		98.83 136	98.60 144	99.51 129	99.69 132	98.75 163	99.99 173	99.14 264	96.81 174	98.84 203	99.06 268	97.45 141	99.89 143	98.66 182	97.75 195	99.89 138

1112_ss		98.91 130	98.71 135	99.51 129	99.69 132	98.75 163	99.99 173	99.15 259	96.82 173	98.84 203	100.00 1	97.45 141	99.89 143	98.66 182	97.75 195	99.89 138

DeepMVS_CX				89.98 306	98.90 238	71.46 327		99.18 252	97.61 119	96.92 275	99.83 199	86.07 281	99.83 156	96.02 252	97.65 199	98.65 212

GA-MVS		97.72 181	97.27 193	99.06 163	99.24 210	97.93 206	100.00 1	99.24 236	95.80 220	98.99 194	99.64 232	89.77 246	99.36 215	95.12 266	97.62 200	99.89 138

LFMVS		97.42 190	96.62 209	99.81 90	99.80 117	99.50 108	99.16 300	99.56 64	94.48 254	100.00 1	100.00 1	79.35 312	100.00 1	99.89 85	97.37 201	99.94 112

CVMVSNet		98.56 152	98.47 152	98.82 181	99.11 213	97.67 217	99.74 237	99.47 74	97.57 125	99.06 190	100.00 1	95.72 179	98.97 235	98.21 205	97.33 202	99.83 162

alignmvs		99.38 79	99.21 90	99.91 69	99.73 128	99.92 42	100.00 1	99.51 71	97.61 119	100.00 1	100.00 1	99.06 83	99.93 137	99.83 93	97.12 203	99.90 132

VNet		99.04 112	98.75 131	99.90 72	99.81 107	99.75 86	99.50 266	99.47 74	98.36 63	100.00 1	99.99 154	94.66 193	100.00 1	99.90 83	97.09 204	99.96 104

Anonymous202405211		97.87 177	97.53 185	98.90 177	99.81 107	96.70 247	99.35 277	99.46 89	92.98 287	98.83 205	99.99 154	90.63 236	100.00 1	99.70 112	97.03 205	100.00 1

Anonymous20240529		96.93 211	96.22 224	99.05 165	99.79 120	97.30 231	99.16 300	99.47 74	88.51 309	98.69 211	100.00 1	83.50 297	100.00 1	99.83 93	97.02 206	99.83 162

VDDNet		96.39 235	95.55 253	98.90 177	99.27 207	97.45 223	99.15 302	99.92 30	91.28 296	99.98 90	100.00 1	73.55 320	100.00 1	99.85 90	96.98 207	99.24 206

VDD-MVS		96.58 224	95.99 233	98.34 202	99.52 177	95.33 259	99.18 294	99.38 177	96.64 188	99.77 150	100.00 1	72.51 322	100.00 1	100.00 1	96.94 208	99.70 193

canonicalmvs		99.03 113	98.73 132	99.94 64	99.75 127	99.95 24	100.00 1	99.30 210	97.64 117	100.00 1	100.00 1	95.22 186	99.97 104	99.76 105	96.90 209	99.91 123

tpm		98.24 169	98.22 165	98.32 204	99.13 212	95.79 257	99.53 263	99.12 274	95.20 237	99.96 97	99.36 258	97.58 137	99.28 220	97.41 229	96.67 210	99.88 149

OpenMVS_ROB	88.34 20	91.89 286	91.12 287	94.19 299	95.55 314	87.63 316	99.26 283	98.03 316	86.61 314	90.65 314	96.82 312	70.14 325	98.78 250	86.54 315	96.50 211	96.15 314

plane_prior						94.80 271	100.00 1		99.03 18						95.58 212

HQP3-MVS								99.40 160							95.58 212

HQP-MVS		97.73 180	97.85 176	97.39 248	99.07 217	94.82 268	100.00 1	99.40 160	99.04 13	99.17 179	99.97 165	88.61 261	99.57 182	99.79 99	95.58 212	97.77 216

CLD-MVS		97.64 183	97.74 180	97.36 250	99.01 225	94.76 276	100.00 1	99.34 199	99.30 4	99.00 193	99.97 165	87.49 270	99.57 182	99.96 72	95.58 212	97.75 223
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
HQP_MVS		97.71 182	97.82 178	97.37 249	99.00 229	94.80 271	100.00 1	99.40 160	99.00 21	99.08 188	99.97 165	88.58 263	99.55 191	99.79 99	95.57 216	97.76 218

plane_prior5								99.40 160					99.55 191	99.79 99	95.57 216	97.76 218

OPM-MVS		97.21 197	97.18 196	97.32 251	98.08 273	94.66 277	100.00 1	99.28 220	98.65 48	98.92 196	99.98 157	86.03 283	99.56 186	98.28 203	95.41 218	97.72 256

baseline1		98.91 130	98.61 142	99.81 90	99.71 129	99.77 83	99.78 228	99.44 105	97.51 131	98.81 206	99.99 154	98.25 123	99.76 167	98.60 189	95.41 218	99.89 138

test_djsdf		97.55 188	97.38 189	98.07 221	97.50 294	97.99 202	100.00 1	99.13 269	95.46 234	98.47 226	99.85 196	92.01 225	98.59 265	98.63 186	95.36 220	97.62 286

anonymousdsp		97.16 200	96.88 200	98.00 228	97.08 304	98.06 199	99.81 224	99.15 259	94.58 249	97.84 252	99.62 238	90.49 238	98.60 263	97.98 211	95.32 221	97.33 302

EI-MVSNet		97.98 175	97.93 175	98.16 214	99.11 213	97.84 213	99.74 237	99.29 214	94.39 256	98.65 213	100.00 1	97.21 147	98.88 244	97.62 224	95.31 222	97.75 223

MVSTER		98.58 150	98.52 149	98.77 184	99.65 140	99.68 98	100.00 1	99.29 214	95.63 223	98.65 213	99.80 208	99.78 6	98.88 244	98.59 190	95.31 222	97.73 250

LPG-MVS_test		97.31 194	97.32 191	97.28 253	98.85 244	94.60 280	100.00 1	99.37 180	97.35 143	98.85 201	99.98 157	86.66 277	99.56 186	99.55 134	95.26 224	97.70 264

LGP-MVS_train				97.28 253	98.85 244	94.60 280		99.37 180	97.35 143	98.85 201	99.98 157	86.66 277	99.56 186	99.55 134	95.26 224	97.70 264

ITE_SJBPF				96.84 271	98.96 235	93.49 292		98.12 313	98.12 77	98.35 230	99.97 165	84.45 289	99.56 186	95.63 257	95.25 226	97.49 294

ACMP	97.00 8	97.19 198	97.16 197	97.27 255	98.97 234	94.58 283	100.00 1	99.32 203	97.97 89	97.45 265	99.98 157	85.79 285	99.56 186	99.70 112	95.24 227	97.67 274
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
EG-PatchMatch MVS		92.94 281	92.49 284	94.29 297	95.87 312	87.07 317	99.07 311	98.11 314	93.19 284	88.98 316	98.66 294	70.89 323	99.08 226	92.43 291	95.21 228	96.72 310

ACMM	97.17 6	97.37 192	97.40 188	97.29 252	99.01 225	94.64 279	100.00 1	99.25 233	98.07 80	98.44 227	99.98 157	87.38 271	99.55 191	99.25 155	95.19 229	97.69 268
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
UniMVSNet_ETH3D		95.28 267	94.41 271	97.89 236	98.91 237	95.14 262	99.13 304	99.35 194	92.11 291	97.17 272	99.66 226	70.28 324	99.36 215	97.88 216	95.18 230	99.16 207

ACMMP++															95.17 231

test_0402		94.35 273	93.70 275	96.32 280	97.92 278	93.60 291	99.61 256	98.85 305	88.19 312	94.68 299	99.48 253	80.01 310	98.58 267	89.39 310	95.15 232	96.77 309

ACMH	96.25 11	96.77 214	96.62 209	97.21 256	98.96 235	94.43 285	99.64 254	99.33 201	97.43 139	96.55 286	99.97 165	83.52 296	99.54 194	99.07 164	95.13 233	97.66 275
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
jajsoiax		97.07 205	96.79 204	97.89 236	97.28 302	97.12 237	99.95 203	99.19 249	96.55 192	97.31 268	99.69 219	87.35 273	98.91 238	98.70 181	95.12 234	97.66 275

mvs_tets		97.00 209	96.69 206	97.94 232	97.41 301	97.27 232	99.60 257	99.18 252	96.51 196	97.35 267	99.69 219	86.53 279	98.91 238	98.84 173	95.09 235	97.65 280

XVG-ACMP-BASELINE		96.60 223	96.52 212	96.84 271	98.41 257	93.29 295	99.99 173	99.32 203	97.76 106	98.51 224	99.29 261	81.95 303	99.54 194	98.40 195	95.03 236	97.68 270

LTVRE_ROB	95.29 16	96.32 239	96.10 228	96.99 263	98.55 252	93.88 289	99.45 268	99.28 220	94.50 253	96.46 287	99.52 250	84.86 288	99.48 205	97.26 232	95.03 236	97.59 290
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
D2MVS		97.63 186	97.83 177	97.05 259	98.83 246	94.60 280	100.00 1	99.82 36	96.89 172	98.28 235	99.03 273	94.05 198	99.47 206	98.58 191	94.97 238	97.09 306

USDC		95.90 258	95.70 247	96.50 277	98.60 251	92.56 302	100.00 1	98.30 309	97.77 104	96.92 275	99.94 184	81.25 307	99.45 209	93.54 283	94.96 239	97.49 294

PVSNet_BlendedMVS		98.71 142	98.62 141	98.98 172	99.98 79	99.60 103	100.00 1	100.00 1	97.23 151	100.00 1	99.03 273	96.57 166	99.99 85	100.00 1	94.75 240	97.35 301

TinyColmap		95.50 264	95.12 266	96.64 274	98.69 247	93.00 297	99.40 272	97.75 323	96.40 202	96.14 289	99.87 192	79.47 311	99.50 203	93.62 282	94.72 241	97.40 299

ACMH+	96.20 13	96.49 229	96.33 221	97.00 262	99.06 221	93.80 290	99.81 224	99.31 208	97.32 147	95.89 293	99.97 165	82.62 301	99.54 194	98.34 199	94.63 242	97.65 280

PS-MVSNAJss		98.03 173	98.06 170	97.94 232	97.63 286	97.33 230	99.89 215	99.23 240	96.27 208	98.03 243	99.59 242	98.75 109	98.78 250	98.52 192	94.61 243	97.70 264

ACMMP++_ref															94.58 244

CMPMVS	66.12 22	90.65 291	92.04 285	86.46 310	96.18 309	66.87 330	98.03 323	99.38 177	83.38 320	85.49 321	99.55 247	77.59 316	98.80 249	94.44 272	94.31 245	93.72 323
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
OurMVSNet-221017-0		96.14 250	95.98 234	96.62 275	97.49 296	93.44 293	99.92 209	98.16 311	95.86 217	97.65 258	99.95 180	85.71 286	98.78 250	94.93 268	94.18 246	97.64 283

LF4IMVS		96.19 244	96.18 225	96.23 282	98.26 265	92.09 304	100.00 1	97.89 321	97.82 101	97.94 248	99.87 192	82.71 300	99.38 214	97.41 229	93.71 247	97.20 304

GBi-Net		96.07 252	95.80 241	96.89 268	99.53 172	94.87 265	99.18 294	99.27 227	93.71 267	98.53 221	98.81 288	84.23 292	98.07 295	95.31 262	93.60 248	97.72 256

test1		96.07 252	95.80 241	96.89 268	99.53 172	94.87 265	99.18 294	99.27 227	93.71 267	98.53 221	98.81 288	84.23 292	98.07 295	95.31 262	93.60 248	97.72 256

FMVSNet3		97.30 195	96.95 198	98.37 199	99.65 140	99.25 134	99.71 243	99.28 220	94.23 258	98.53 221	98.91 284	93.30 208	98.11 289	95.31 262	93.60 248	97.73 250

FMVSNet2		96.22 243	95.60 252	98.06 225	99.53 172	98.33 186	99.45 268	99.27 227	93.71 267	98.03 243	98.84 287	84.23 292	98.10 292	93.97 279	93.40 251	97.73 250

K. test v3		95.46 265	95.14 265	96.40 278	97.53 293	93.40 294	99.99 173	99.23 240	95.49 232	92.70 309	99.73 211	84.26 291	98.12 287	93.94 280	93.38 252	97.68 270

SixPastTwentyTwo		95.71 261	95.49 256	96.38 279	97.42 299	93.01 296	99.84 221	98.23 310	94.75 243	95.98 291	99.97 165	85.35 287	98.43 276	94.71 269	93.17 253	97.69 268

FIs		97.95 176	97.73 182	98.62 189	98.53 254	99.24 136	100.00 1	99.43 115	96.74 177	97.87 251	99.82 202	95.27 185	98.89 241	98.78 176	93.07 254	97.74 244

FC-MVSNet-test		97.84 178	97.63 184	98.45 194	98.30 263	99.05 149	100.00 1	99.43 115	96.63 190	97.61 261	99.82 202	95.19 187	98.57 268	98.64 185	93.05 255	97.73 250

XXY-MVS		97.14 202	96.63 208	98.67 187	98.65 248	98.92 158	99.54 262	99.29 214	95.57 226	97.63 259	99.83 199	87.79 268	99.35 217	98.39 196	92.95 256	97.75 223

FMVSNet1		94.45 272	93.63 276	96.89 268	98.87 242	94.87 265	99.18 294	99.27 227	90.95 299	97.31 268	98.81 288	72.89 321	98.07 295	92.61 287	92.81 257	97.72 256

N_pmnet		91.88 287	93.37 279	87.40 309	97.24 303	66.33 331	99.90 212	91.05 335	89.77 305	95.65 294	98.58 297	90.05 244	98.11 289	85.39 316	92.72 258	97.75 223

pmmvs4		97.17 199	96.80 202	98.27 206	97.68 285	98.64 172	100.00 1	99.18 252	94.22 259	98.55 219	99.71 214	93.67 203	98.47 274	95.66 256	92.57 259	97.71 263

testing_2		90.79 290	88.26 295	98.35 201	89.11 324	98.56 174	99.70 245	99.14 264	93.70 270	73.80 325	94.06 321	55.19 329	98.76 255	97.17 233	92.50 260	97.74 244

our_test_3		96.51 226	96.35 219	96.98 264	97.61 288	95.05 263	99.98 190	99.01 297	94.68 246	96.77 283	99.06 268	95.87 176	98.14 285	91.81 295	92.37 261	97.75 223

IterMVS		96.76 215	96.46 215	97.63 241	99.41 193	96.89 242	99.99 173	99.13 269	94.74 245	97.59 262	99.66 226	89.63 250	98.28 281	95.71 254	92.31 262	97.72 256
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ppachtmachnet_test		96.17 247	95.89 237	97.02 261	97.61 288	95.24 260	99.99 173	99.24 236	93.31 281	96.71 284	99.62 238	94.34 197	98.07 295	89.87 308	92.30 263	97.75 223

pmmvs5		95.94 257	95.61 251	96.95 265	97.42 299	94.66 277	100.00 1	98.08 315	93.60 274	97.05 273	99.43 256	87.02 274	98.46 275	95.76 253	92.12 264	97.72 256

IterMVS-SCA-FT		96.72 218	96.42 217	97.62 243	99.40 197	96.83 244	99.99 173	99.14 264	94.65 248	97.55 263	99.72 212	89.65 248	98.31 280	95.62 258	92.05 265	97.73 250

new_pmnet		94.11 276	93.47 278	96.04 284	96.60 307	92.82 299	99.97 196	98.91 303	90.21 302	95.26 295	98.05 308	85.89 284	98.14 285	84.28 318	92.01 266	97.16 305

FMVSNet5		95.32 266	95.43 260	94.99 290	99.39 200	92.99 298	99.25 284	99.24 236	90.45 300	97.44 266	98.45 300	95.78 178	94.39 324	87.02 314	91.88 267	97.59 290

Gipuma		84.73 296	83.50 298	88.40 308	97.50 294	82.21 322	88.87 329	99.05 291	65.81 326	85.71 320	90.49 324	53.70 330	96.31 314	78.64 325	91.74 268	86.67 327
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
IterMVS-LS		97.56 187	97.44 186	97.92 235	99.38 201	97.90 207	99.89 215	99.10 276	94.41 255	98.32 232	99.54 249	97.21 147	98.11 289	97.50 226	91.62 269	97.75 223
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Patchmtry		96.81 213	96.37 218	98.14 215	99.31 204	98.55 175	98.91 314	99.00 298	90.45 300	97.92 249	98.98 277	96.94 159	98.12 287	94.27 274	91.53 270	97.75 223

MIMVSNet1		91.96 284	91.20 286	94.23 298	94.94 318	91.69 307	99.34 278	99.22 242	88.23 310	94.18 303	98.45 300	75.52 319	93.41 327	79.37 324	91.49 271	97.60 289

miper_lstm_enhance		97.40 191	97.28 192	97.75 240	99.48 187	97.52 221	100.00 1	99.07 281	94.08 262	98.01 246	99.61 240	97.38 145	97.98 301	96.44 250	91.47 272	97.76 218

tfpnnormal		96.36 236	95.69 250	98.37 199	98.55 252	98.71 167	99.69 248	99.45 96	93.16 285	96.69 285	99.71 214	88.44 265	98.99 232	94.17 275	91.38 273	97.41 298

FPMVS		77.92 302	79.45 300	73.34 318	76.87 333	46.81 338	98.24 321	99.05 291	59.89 329	73.55 326	98.34 305	36.81 336	86.55 330	80.96 321	91.35 274	86.65 328

EU-MVSNet		96.63 221	96.53 211	96.94 266	97.59 290	96.87 243	99.76 235	99.47 74	96.35 204	96.85 279	99.78 209	92.57 219	96.27 316	95.33 261	91.08 275	97.68 270

v1240		95.96 256	95.25 262	98.07 221	97.91 279	97.87 211	99.96 199	99.07 281	93.24 283	98.64 215	98.96 281	88.98 257	98.61 261	89.58 309	90.92 276	97.75 223

v1192		96.18 245	95.49 256	98.26 208	98.01 275	98.15 195	99.99 173	99.08 279	93.36 279	98.54 220	98.97 280	89.47 251	98.89 241	91.15 299	90.82 277	97.75 223

v1144		96.51 226	95.97 235	98.13 218	97.98 277	98.04 201	99.99 173	99.08 279	93.51 276	98.62 216	98.98 277	90.98 234	98.62 260	93.79 281	90.79 278	97.74 244

v1921920		96.16 248	95.50 254	98.14 215	97.88 281	97.96 204	99.99 173	99.07 281	93.33 280	98.60 217	99.24 263	89.37 252	98.71 256	91.28 297	90.74 279	97.75 223

Anonymous20231206		93.45 279	93.17 280	94.30 296	95.00 317	89.69 312	99.98 190	98.43 308	93.30 282	94.50 301	98.59 296	90.52 237	95.73 321	77.46 328	90.73 280	97.48 296

v144192		96.40 234	95.81 240	98.17 213	97.89 280	98.11 196	99.99 173	99.06 289	93.39 278	98.75 209	99.09 266	90.43 240	98.66 259	93.10 285	90.55 281	97.75 223

v2v482		96.70 219	96.18 225	98.27 206	98.04 274	98.39 180	100.00 1	99.13 269	94.19 261	98.58 218	99.08 267	90.48 239	98.67 258	95.69 255	90.44 282	97.75 223

lessismore_v0				96.05 283	97.55 292	91.80 306		99.22 242		91.87 310	99.91 188	83.50 297	98.68 257	92.48 290	90.42 283	97.68 270

V42		96.65 220	96.16 227	98.11 220	98.17 271	98.23 193	99.99 173	99.09 278	93.97 263	98.74 210	99.05 270	91.09 231	98.82 247	95.46 260	89.90 284	97.27 303

v10		96.14 250	95.50 254	98.07 221	98.19 269	97.96 204	99.83 222	99.07 281	92.10 292	98.07 242	98.94 282	91.07 232	98.61 261	92.41 292	89.82 285	97.63 284

nrg030		97.64 183	97.27 193	98.75 185	98.34 259	99.53 107	100.00 1	99.22 242	96.21 210	98.27 237	99.95 180	94.40 196	98.98 233	99.23 156	89.78 286	97.75 223

VPA-MVSNet		97.03 208	96.43 216	98.82 181	98.64 249	99.32 127	99.38 274	99.47 74	96.73 179	98.91 198	98.94 282	87.00 275	99.40 213	99.23 156	89.59 287	97.76 218

MDA-MVSNet_test_wron		92.61 282	91.09 288	97.19 257	96.71 306	97.26 233	100.00 1	99.14 264	88.61 308	67.90 330	98.32 306	89.03 255	96.57 311	90.47 305	89.59 287	97.74 244

Anonymous20231211		96.29 240	95.70 247	98.07 221	99.80 117	97.49 222	99.15 302	99.40 160	89.11 306	97.75 256	99.45 255	88.93 258	98.98 233	98.26 204	89.47 289	97.73 250

MDA-MVSNet-bldmvs		91.65 289	89.94 292	96.79 273	96.72 305	96.70 247	99.42 271	98.94 300	88.89 307	66.97 332	98.37 304	81.43 305	95.91 319	89.24 312	89.46 290	97.75 223

WR-MVS		97.09 203	96.64 207	98.46 193	98.43 256	99.09 146	99.97 196	99.33 201	95.62 224	97.76 253	99.67 224	91.17 230	98.56 269	98.49 193	89.28 291	97.74 244

test20.03		93.11 280	92.85 282	93.88 301	95.19 316	91.83 305	100.00 1	98.87 304	93.68 271	92.76 307	98.88 286	89.20 254	92.71 328	77.88 326	89.19 292	97.09 306

YYNet1		92.44 283	90.92 289	97.03 260	96.20 308	97.06 240	99.99 173	99.14 264	88.21 311	67.93 329	98.43 302	88.63 260	96.28 315	90.64 301	89.08 293	97.74 244

CP-MVSNet		96.73 216	96.25 223	98.18 212	98.21 268	98.67 170	99.77 233	99.32 203	95.06 239	97.20 271	99.65 228	90.10 242	98.19 282	98.06 210	88.90 294	97.66 275

PS-CasMVS		96.34 238	95.78 243	98.03 227	98.18 270	98.27 191	99.71 243	99.32 203	94.75 243	96.82 280	99.65 228	86.98 276	98.15 284	97.74 219	88.85 295	97.66 275

v8		96.35 237	95.73 246	98.21 211	98.11 272	98.23 193	99.94 207	99.07 281	92.66 290	98.29 234	99.00 276	91.46 226	98.77 253	94.17 275	88.83 296	97.62 286

v7n		96.06 254	95.42 261	97.99 230	97.58 291	97.35 227	99.86 219	99.11 275	92.81 289	97.91 250	99.49 252	90.99 233	98.92 237	92.51 289	88.49 297	97.70 264

WR-MVS_H		96.73 216	96.32 222	97.95 231	98.26 265	97.88 209	99.72 242	99.43 115	95.06 239	96.99 274	98.68 293	93.02 213	98.53 270	97.43 228	88.33 298	97.43 297

NR-MVSNet		96.63 221	96.04 231	98.38 198	98.31 261	98.98 155	99.22 293	99.35 194	95.87 215	94.43 302	99.65 228	92.73 217	98.40 277	96.78 246	88.05 299	97.75 223

pm-mvs1		95.76 260	95.01 267	98.00 228	98.23 267	97.45 223	99.24 285	99.04 294	93.13 286	95.93 292	99.72 212	86.28 280	98.84 246	95.62 258	87.92 300	97.72 256

VPNet		96.41 231	95.76 244	98.33 203	98.61 250	98.30 189	99.48 267	99.45 96	96.98 166	98.87 200	99.88 191	81.57 304	98.93 236	99.22 158	87.82 301	97.76 218

UniMVSNet (Re)		97.29 196	96.85 201	98.59 192	98.49 255	99.13 145	100.00 1	99.42 123	96.52 195	98.24 240	98.90 285	94.93 190	98.89 241	97.54 225	87.61 302	97.75 223

ET-MVSNet_ETH3D		96.41 231	95.48 258	99.20 159	99.81 107	99.75 86	100.00 1	99.02 295	97.30 150	78.33 324	100.00 1	97.73 133	97.94 303	99.70 112	87.41 303	99.92 121

PEN-MVS		96.01 255	95.48 258	97.58 245	97.74 283	97.26 233	99.90 212	99.29 214	94.55 250	96.79 281	99.55 247	87.38 271	97.84 305	96.92 240	87.24 304	97.65 280

v148		96.29 240	95.84 239	97.63 241	97.74 283	96.53 250	100.00 1	99.07 281	93.52 275	98.01 246	99.42 257	91.22 228	98.60 263	96.37 251	87.22 305	97.75 223

UniMVSNet_NR-MVSNet		97.16 200	96.80 202	98.22 209	98.38 258	98.41 178	100.00 1	99.45 96	96.14 211	97.76 253	99.64 232	95.05 188	98.50 272	97.98 211	86.84 306	97.75 223

DU-MVS		96.93 211	96.49 213	98.22 209	98.31 261	98.41 178	100.00 1	99.37 180	96.41 201	97.76 253	99.65 228	92.14 222	98.50 272	97.98 211	86.84 306	97.75 223

Baseline_NR-MVSNet		96.16 248	95.70 247	97.56 246	98.28 264	96.79 245	100.00 1	97.86 322	91.93 293	97.63 259	99.47 254	92.14 222	98.35 279	97.13 234	86.83 308	97.54 293

TranMVSNet+NR-MVSNet		96.45 230	96.01 232	97.79 239	98.00 276	97.62 219	100.00 1	99.35 194	95.98 213	97.31 268	99.64 232	90.09 243	98.00 300	96.89 241	86.80 309	97.75 223

test_normal		81.70 297	78.65 302	90.84 305	87.31 325	78.56 324	73.97 332	99.07 281	93.91 265	56.04 334	78.33 335	40.91 334	97.97 302	91.83 294	86.53 310	96.00 317

pmmvs6		93.64 277	92.87 281	95.94 285	97.47 298	91.41 309	98.92 313	99.02 295	87.84 313	95.01 297	99.61 240	77.24 317	98.77 253	94.33 273	86.41 311	97.63 284

DTE-MVSNet		95.52 263	94.99 268	97.08 258	97.49 296	96.45 251	100.00 1	99.25 233	93.82 266	96.17 288	99.57 246	87.81 267	97.18 309	94.57 270	86.26 312	97.62 286

TransMVSNet (Re)		94.78 271	93.72 274	97.93 234	98.34 259	97.88 209	99.23 291	97.98 319	91.60 294	94.55 300	99.71 214	87.89 266	98.36 278	89.30 311	84.92 313	97.56 292

UnsupCasMVSNet_eth		94.25 274	93.89 272	95.34 287	97.63 286	92.13 303	99.73 240	99.36 186	94.88 242	92.78 306	98.63 295	82.72 299	96.53 312	94.57 270	84.73 314	97.36 300

ambc				88.45 307	86.84 326	70.76 328	97.79 325	98.02 318		90.91 312	95.14 316	38.69 335	98.51 271	94.97 267	84.23 315	96.09 316

PMVS	60.66 23	65.98 308	65.05 308	68.75 321	55.06 338	38.40 339	88.19 330	96.98 325	48.30 334	44.82 336	88.52 327	12.22 341	86.49 331	67.58 330	83.79 316	81.35 331
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PVSNet_0	93.57 19	96.41 231	95.74 245	98.41 196	99.84 103	95.22 261	100.00 1	100.00 1	98.08 79	97.55 263	99.78 209	84.40 290	100.00 1	100.00 1	81.99 317	100.00 1

Patchmatch-RL test		93.49 278	93.63 276	93.05 302	91.78 319	83.41 321	98.21 322	96.95 326	91.58 295	91.05 311	97.64 310	99.40 48	95.83 320	94.11 278	81.95 318	99.91 123

PM-MVS		88.39 295	87.41 297	91.31 304	91.73 320	82.02 323	99.79 227	96.62 328	91.06 298	90.71 313	95.73 314	48.60 332	95.96 318	90.56 303	81.91 319	95.97 318

pmmvs-eth3d		91.73 288	90.67 290	94.92 292	91.63 321	92.71 300	99.90 212	98.54 307	91.19 297	88.08 317	95.50 315	79.31 313	96.13 317	90.55 304	81.32 320	95.91 319

UnsupCasMVSNet_bld		89.50 294	88.00 296	93.99 300	95.30 315	88.86 314	98.52 319	99.28 220	85.50 316	87.80 319	94.11 320	61.63 328	96.96 310	90.63 302	79.26 321	96.15 314

new-patchmatchnet		90.30 293	89.46 293	92.84 303	90.77 322	88.55 315	99.83 222	98.80 306	90.07 304	87.86 318	95.00 318	78.77 314	94.30 325	84.86 317	79.15 322	95.68 320

IB-MVS	96.24 12	97.54 189	96.95 198	99.33 148	99.67 136	98.10 197	100.00 1	99.47 74	97.42 140	99.26 176	99.69 219	98.83 104	99.89 143	99.43 143	78.77 323	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
pmmvs3		90.62 292	89.36 294	94.40 295	90.53 323	91.49 308	100.00 1	96.73 327	84.21 318	93.65 305	96.65 313	82.56 302	94.83 323	82.28 320	77.62 324	96.89 308

LCM-MVSNet		79.01 301	76.93 304	85.27 311	78.28 332	68.01 329	96.57 326	98.03 316	55.10 330	82.03 323	93.27 322	31.99 338	93.95 326	82.72 319	74.37 325	93.84 322

TDRefinement		91.93 285	90.48 291	96.27 281	81.60 330	92.65 301	99.10 307	97.61 324	93.96 264	93.77 304	99.85 196	80.03 309	99.53 199	97.82 218	70.59 326	96.63 311

PMMVS2		79.15 300	77.28 303	84.76 312	82.34 329	72.66 325	99.70 245	95.11 332	71.68 325	84.78 322	90.87 323	32.05 337	89.99 329	75.53 329	63.45 327	91.64 324

MVE	68.59 21	67.22 306	64.68 309	74.84 315	74.67 335	62.32 335	95.84 327	90.87 336	50.98 331	58.72 333	81.05 333	12.20 342	78.95 332	61.06 332	56.75 328	83.24 330
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
testmvs		80.17 298	81.95 299	74.80 316	58.54 337	59.58 336	100.00 1	87.14 338	76.09 323	99.61 161	100.00 1	67.06 327	74.19 336	98.84 173	50.30 329	90.64 326

E-PMN		70.72 304	70.06 306	72.69 319	83.92 328	65.48 333	99.95 203	92.72 334	49.88 332	72.30 327	86.26 330	47.17 333	77.43 333	53.83 333	44.49 330	75.17 333

EMVS		69.88 305	69.09 307	72.24 320	84.70 327	65.82 332	99.96 199	87.08 339	49.82 333	71.51 328	84.74 331	49.30 331	75.32 334	50.97 334	43.71 331	75.59 332

ANet_high		66.05 307	63.44 310	73.88 317	61.14 336	63.45 334	95.68 328	87.18 337	79.93 321	47.35 335	80.68 334	22.35 339	72.33 337	61.24 331	35.42 332	85.88 329

tmp_tt		75.80 303	74.26 305	80.43 313	52.91 339	53.67 337	87.42 331	97.98 319	61.80 328	67.04 331	100.00 1	76.43 318	96.40 313	96.47 249	28.26 333	91.23 325

test123		79.44 299	79.23 301	80.05 314	80.03 331	71.72 326	100.00 1	77.93 340	62.52 327	94.81 298	99.69 219	78.21 315	74.53 335	92.57 288	27.33 334	93.90 321

wuyk23d		28.28 309	29.73 312	23.92 322	75.89 334	32.61 340	66.50 333	12.88 341	16.09 335	14.59 337	16.59 337	12.35 340	32.36 338	39.36 335	13.36 335	6.79 334

test_part1				0.00 323		0.00 341	0.00 334	99.42 123				0.00 343	0.00 339	0.00 336	0.00 336	0.00 335

cdsmvs_eth3d_5k		24.41 310	32.55 311	0.00 323	0.00 340	0.00 341	0.00 334	99.39 174	0.00 336	0.00 338	100.00 1	93.55 205	0.00 339	0.00 336	0.00 336	0.00 335

pcd_1.5k_mvsjas		8.24 312	10.99 314	0.00 323	0.00 340	0.00 341	0.00 334	0.00 342	0.00 336	0.00 338	0.14 338	98.75 109	0.00 339	0.00 336	0.00 336	0.00 335

sosnet-low-res		0.01 313	0.02 315	0.00 323	0.00 340	0.00 341	0.00 334	0.00 342	0.00 336	0.00 338	0.14 338	0.00 343	0.00 339	0.00 336	0.00 336	0.00 335

sosnet		0.01 313	0.02 315	0.00 323	0.00 340	0.00 341	0.00 334	0.00 342	0.00 336	0.00 338	0.14 338	0.00 343	0.00 339	0.00 336	0.00 336	0.00 335

uncertanet		0.01 313	0.02 315	0.00 323	0.00 340	0.00 341	0.00 334	0.00 342	0.00 336	0.00 338	0.14 338	0.00 343	0.00 339	0.00 336	0.00 336	0.00 335

Regformer		0.01 313	0.02 315	0.00 323	0.00 340	0.00 341	0.00 334	0.00 342	0.00 336	0.00 338	0.14 338	0.00 343	0.00 339	0.00 336	0.00 336	0.00 335

ab-mvs-re		8.33 311	11.11 313	0.00 323	0.00 340	0.00 341	0.00 334	0.00 342	0.00 336	0.00 338	100.00 1	0.00 343	0.00 339	0.00 336	0.00 336	0.00 335

uanet		0.01 313	0.02 315	0.00 323	0.00 340	0.00 341	0.00 334	0.00 342	0.00 336	0.00 338	0.14 338	0.00 343	0.00 339	0.00 336	0.00 336	0.00 335

save fliter					99.99 48	99.93 37	100.00 1	99.42 123	98.93 28

test0726					100.00 1	99.99 2	100.00 1	99.42 123	99.04 13	100.00 1	100.00 1	99.53 21

GSMVS																99.91 123

test_part2					100.00 1	99.99 2				100.00 1

sam_mvs1												99.29 62				99.91 123

sam_mvs												99.33 51

MTGPA								99.42 123

test_post1							99.32 279				88.24 328	99.33 51	99.59 179	98.31 200

test_post											89.05 326	99.49 31	99.59 179

patchmatchnet-post											97.79 309	99.41 47	99.54 194

MTMP							100.00 1	99.18 252

gm-plane-assit					99.52 177	97.26 233			95.86 217		100.00 1		99.43 210	98.76 178

TEST9					100.00 1	99.95 24	100.00 1	99.42 123	97.65 115	100.00 1	100.00 1	99.53 21	99.97 104

test_8					100.00 1	99.91 45	100.00 1	99.42 123	97.70 111	100.00 1	100.00 1	99.51 26	99.98 100

agg_prior					100.00 1	99.88 67		99.42 123		100.00 1			99.97 104

test_prior4						99.93 37	100.00 1

test_prior				99.90 72	100.00 1	99.75 86		99.73 52					99.97 104			100.00 1

旧先验2							100.00 1		98.11 78	100.00 1			100.00 1	99.67 121

新几何2							100.00 1

无先验							100.00 1	99.80 39	97.98 87				100.00 1	99.33 150		100.00 1

原ACMM2							100.00 1

testdata2													100.00 1	97.36 231

segment_acmp												99.55 20

testdata1							100.00 1		98.77 43

plane_prior7					99.00 229	94.78 275

plane_prior6					99.06 221	94.80 271						88.58 263

plane_prior4											99.97 165

plane_prior3						94.79 274			99.03 18	99.08 188

plane_prior2							100.00 1		99.00 21

plane_prior1					99.02 224

n2								0.00 342

nn								0.00 342

door-mid								96.32 330

test11								99.42 123

door								96.13 331

HQP5-MVS						94.82 268

HQP-NCC					99.07 217		100.00 1		99.04 13	99.17 179

ACMP_Plane					99.07 217		100.00 1		99.04 13	99.17 179

BP-MVS														99.79 99

HQP4-MVS										99.17 179			99.57 182			97.77 216

HQP2-MVS												88.61 261

NP-MVS					99.07 217	94.81 270					99.97 165

MDTV_nov1_ep13_2view						99.24 136	99.56 260		96.31 207	99.96 97		98.86 103		98.92 170		99.89 138

Test By Simon												99.10 81

High-resolution multi-view benchmark