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.

CHOSEN 280x420		99.85 3	99.87 1	99.80 95	99.99 45	99.97 8	99.97 199	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

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

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

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

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

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

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

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

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

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

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

PLC	98.56 2	99.70 37	99.74 13	99.58 128	100.00 1	98.79 162	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
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

DeepPCF-MVS	98.03 4	98.54 153	99.72 15	94.98 304	99.99 45	84.94 330	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

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.
API-MVS		99.72 29	99.70 17	99.79 99	99.97 76	99.37 126	99.96 202	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

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

TSAR-MVS + GP.		99.61 55	99.69 18	99.35 146	99.99 45	98.06 211	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

EPNet		99.62 53	99.69 18	99.42 139	99.99 45	98.37 180	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
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

#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

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

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

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

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

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

DeepC-MVS_fast	98.92 1	99.75 18	99.67 27	99.99 5	99.99 45	99.96 10	99.73 257	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
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

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

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

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

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

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

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

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

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

EI-MVSNet-UG-set		99.69 40	99.63 39	99.87 81	99.99 45	99.64 105	99.95 208	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

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

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

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

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

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

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
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

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

PS-MVSNAJ		99.64 50	99.57 51	99.85 85	99.78 122	99.81 78	99.95 208	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

ACMMP		99.65 48	99.57 51	99.89 75	99.99 45	99.66 103	99.75 252	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
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
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

1121		99.63 52	99.51 56	99.99 5	99.99 45	99.96 10	99.24 304	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

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
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
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

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

xiu_mvs_v2_base		99.51 63	99.41 61	99.82 89	99.70 131	99.73 88	99.92 216	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

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

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

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

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

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

OMC-MVS		99.27 91	99.38 66	98.96 171	99.95 82	97.06 252	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

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

MAR-MVS		99.49 66	99.36 68	99.89 75	99.97 76	99.66 103	99.74 253	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
HY-MVS	96.53 9	99.50 64	99.35 70	99.96 36	99.81 100	99.93 33	99.64 274	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

CSCG		99.28 90	99.35 70	99.05 164	99.99 45	97.15 248	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

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

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

AdaColmap		99.44 71	99.26 74	99.95 47	100.00 1	99.86 67	99.70 263	99.99 10	98.53 46	99.90 117	100.00 1	95.34 181	100.00 1	99.92 74	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

PVSNet	94.91 18	99.30 88	99.25 75	99.44 136	100.00 1	98.32 186	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

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	95.28 182	99.96 114	100.00 1	99.99 88	99.96 107

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

DWT-MVSNet_test		99.22 100	99.22 79	99.22 157	99.56 162	97.98 215	99.89 222	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

xiu_mvs_v1_base_debu		99.35 76	99.21 80	99.79 99	99.67 136	99.71 96	99.78 243	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	99.78 243	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	99.78 243	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

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

1314		99.38 74	99.19 84	99.96 36	98.88 231	99.89 49	99.24 304	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

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

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

lupinMVS		99.29 89	99.16 86	99.69 114	99.45 181	99.49 114	100.00 1	99.15 255	97.45 134	99.97 85	100.00 1	96.76 158	99.76 159	99.67 107	100.00 1	99.81 171

EPMVS		99.25 95	99.13 93	99.60 121	99.60 151	99.20 140	99.60 277	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

LS3D		99.31 87	99.13 93	99.87 81	99.99 45	99.71 96	99.55 281	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

PatchFormer-LS_test		99.14 106	99.12 95	99.19 158	99.54 163	97.86 225	99.66 272	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

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

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

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

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

EPP-MVSNet		99.10 109	99.00 101	99.40 141	99.51 174	98.68 167	99.92 216	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

mvs-test1		98.89 133	98.99 104	98.60 188	99.77 124	95.96 265	100.00 1	98.94 302	97.61 123	99.93 114	99.92 179	95.89 171	99.93 133	99.36 137	99.50 120	99.90 136

PMMVS		99.12 107	98.97 105	99.58 128	99.57 160	98.98 155	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		99.22 100	98.96 106	99.98 16	99.00 220	99.95 19	99.24 304	99.94 18	98.14 70	98.88 196	100.00 1	95.63 179	100.00 1	99.85 83	100.00 1	100.00 1

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

jason		99.11 108	98.96 106	99.59 124	99.17 202	99.31 129	100.00 1	99.13 264	97.38 138	99.83 125	100.00 1	95.54 180	99.72 164	99.57 118	99.97 98	99.74 186
jason: jason.
PatchmatchNet		99.03 115	98.96 106	99.26 154	99.49 179	98.33 183	99.38 294	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.
CDS-MVSNet		98.96 127	98.95 110	99.01 167	99.48 180	98.36 181	99.93 214	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
MDTV_nov1_ep13			98.94 111		99.53 166	98.36 181	99.39 293	99.46 95	96.54 189	99.99 76	99.63 229	98.92 96	99.86 143	98.30 188	98.71 133

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

tpmrst		98.98 125	98.93 112	99.14 161	99.61 149	97.74 228	99.52 284	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

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

CHOSEN 1792x2688		99.00 121	98.91 117	99.25 155	99.90 94	97.79 227	100.00 1	99.99 10	98.79 36	98.28 236	100.00 1	93.63 202	99.95 120	99.66 109	99.95 102	100.00 1

IS-MVSNet		99.08 110	98.91 117	99.59 124	99.65 140	99.38 124	99.78 243	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

CANet_DTU		99.02 119	98.90 120	99.41 140	99.88 97	98.71 165	100.00 1	99.29 211	98.84 30	100.00 1	100.00 1	94.02 198	100.00 1	98.08 200	99.96 100	99.52 201

Vis-MVSNet (Re-imp)		98.99 123	98.89 121	99.29 151	99.64 144	98.89 159	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

Effi-MVS+-dtu		98.51 157	98.86 122	97.47 252	99.77 124	94.21 299	100.00 1	98.94 302	97.61 123	99.91 116	98.75 292	95.89 171	99.51 198	99.36 137	99.48 121	98.68 208

UA-Net		99.06 112	98.83 123	99.74 110	99.52 171	99.40 123	99.08 325	99.45 97	97.64 121	99.83 125	100.00 1	95.80 173	99.94 131	98.35 185	99.80 114	99.88 153

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

MVSFormer		98.94 129	98.82 124	99.28 152	99.45 181	99.49 114	100.00 1	99.13 264	95.46 229	99.97 85	100.00 1	96.76 158	98.59 268	98.63 174	100.00 1	99.74 186

BH-w/o		98.82 137	98.81 126	98.88 176	99.62 147	96.71 259	100.00 1	99.28 219	97.09 157	98.81 202	100.00 1	94.91 190	99.96 114	99.54 122	100.00 1	99.96 107

DeepC-MVS	97.84 5	99.00 121	98.80 127	99.60 121	99.93 88	99.03 149	100.00 1	99.40 155	98.61 44	99.33 172	100.00 1	92.23 217	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
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	93.14 209	99.99 82	97.85 208	99.98 95	99.95 112

CostFormer		98.84 135	98.77 129	99.04 165	99.41 185	97.58 233	99.67 270	99.35 190	94.66 241	99.96 88	99.36 249	99.28 65	99.74 161	99.41 135	97.81 183	99.81 171

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	92.91 211	100.00 1	99.71 101	100.00 1	100.00 1

VNet		99.04 114	98.75 131	99.90 72	99.81 100	99.75 85	99.50 286	99.47 83	98.36 58	100.00 1	99.99 140	94.66 192	100.00 1	99.90 76	97.09 207	99.96 107

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	95.22 184	99.97 99	99.76 97	96.90 210	99.91 128

TAMVS		98.76 139	98.73 132	98.86 177	99.44 183	97.69 229	99.57 279	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

1112_ss		98.91 131	98.71 134	99.51 132	99.69 132	98.75 163	99.99 176	99.15 255	96.82 170	98.84 200	100.00 1	97.45 134	99.89 139	98.66 170	97.75 188	99.89 141

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	92.78 212	100.00 1	99.87 80	100.00 1	100.00 1

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	90.60 250	100.00 1	100.00 1	99.91 105	99.95 112

tpmp4_e23		98.71 142	98.66 136	98.84 178	99.60 151	96.98 254	99.83 231	99.35 190	94.29 251	99.90 117	99.50 243	99.17 75	99.73 162	98.22 190	98.13 164	99.81 171

QAPM		98.99 123	98.66 136	99.96 36	99.01 216	99.87 62	99.88 225	99.93 32	97.99 82	98.68 210	100.00 1	93.17 208	100.00 1	99.32 142	100.00 1	100.00 1

MVS_Test		98.93 130	98.65 139	99.77 109	99.62 147	99.50 111	99.99 176	99.19 246	95.52 224	99.96 88	99.86 186	96.54 164	99.98 95	98.65 172	98.48 139	99.82 169

BH-untuned		98.64 146	98.65 139	98.60 188	99.59 154	96.17 264	100.00 1	99.28 219	96.67 182	98.41 229	100.00 1	94.52 193	99.83 150	99.41 135	100.00 1	99.81 171

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

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	99.03 272	96.57 162	99.99 82	100.00 1	94.75 238	97.35 306

dp		98.72 141	98.61 143	99.03 166	99.53 166	97.39 237	99.45 288	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

mvs_anonymous		98.80 138	98.60 144	99.38 144	99.57 160	99.24 137	100.00 1	99.21 243	95.87 210	98.92 193	99.82 194	96.39 167	99.03 222	99.13 151	98.50 137	99.88 153

Test_1112_low_res		98.83 136	98.60 144	99.51 132	99.69 132	98.75 163	99.99 176	99.14 259	96.81 171	98.84 200	99.06 262	97.45 134	99.89 139	98.66 170	97.75 188	99.89 141

tpm2		98.64 146	98.58 146	98.81 181	99.42 184	97.12 249	99.69 267	99.37 176	93.63 272	99.94 109	99.67 218	98.96 91	99.47 202	98.62 176	97.95 171	99.83 166

Fast-Effi-MVS+-dtu		98.38 163	98.56 147	97.82 241	99.58 158	94.44 296	100.00 1	99.16 254	96.75 173	99.51 162	99.63 229	95.03 188	99.60 174	97.71 211	99.67 117	99.42 203

DP-MVS		98.86 134	98.54 148	99.81 92	99.97 76	99.45 120	99.52 284	99.40 155	94.35 250	98.36 230	100.00 1	96.13 169	99.97 99	99.12 152	100.00 1	100.00 1

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	97.73 255

ADS-MVSNet2		98.28 166	98.51 150	97.62 245	99.51 174	95.03 276	99.24 304	99.41 153	95.52 224	99.96 88	99.70 210	97.57 132	97.94 304	97.11 228	98.54 135	99.88 153

ADS-MVSNet		98.70 144	98.51 150	99.28 152	99.51 174	98.39 177	99.24 304	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

CVMVSNet		98.56 151	98.47 152	98.82 179	99.11 204	97.67 230	99.74 253	99.47 83	97.57 129	99.06 188	100.00 1	95.72 177	98.97 228	98.21 191	97.33 205	99.83 166

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	91.44 235	100.00 1	99.63 111	99.97 98	99.55 199

AllTest		98.55 152	98.40 154	98.99 168	99.93 88	97.35 240	100.00 1	99.40 155	97.08 159	99.09 184	99.98 141	93.37 204	99.95 120	96.94 231	99.84 111	99.68 193

tpmvs		98.59 148	98.38 155	99.23 156	99.69 132	97.90 220	99.31 299	99.47 83	94.52 245	99.68 153	99.28 254	97.64 130	99.89 139	97.71 211	98.17 163	99.89 141

PCF-MVS	98.23 3	98.69 145	98.37 156	99.62 117	99.78 122	99.02 150	99.23 310	99.06 293	96.43 194	98.08 242	100.00 1	94.72 191	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
XVG-OURS		98.30 164	98.36 157	98.13 222	99.58 158	95.91 268	100.00 1	99.36 182	98.69 38	99.23 176	100.00 1	91.20 239	99.92 136	99.34 139	97.82 182	98.56 212

XVG-OURS-SEG-HR		98.27 167	98.31 158	98.14 219	99.59 154	95.92 267	100.00 1	99.36 182	98.48 47	99.21 177	100.00 1	89.27 270	99.94 131	99.76 97	99.17 122	98.56 212

Vis-MVSNet		98.52 155	98.25 159	99.34 147	99.68 135	98.55 172	99.68 269	99.41 153	97.34 142	99.94 109	100.00 1	90.38 255	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
Effi-MVS+		98.58 149	98.24 160	99.61 118	99.60 151	99.26 133	97.85 341	99.10 272	96.22 204	99.97 85	99.89 182	93.75 200	99.77 158	99.43 129	98.34 152	99.81 171

RPSCF		97.37 189	98.24 160	94.76 306	99.80 114	84.57 331	99.99 176	99.05 295	94.95 236	99.82 134	100.00 1	94.03 197	100.00 1	98.15 193	98.38 150	99.70 191

EPNet_dtu		98.53 154	98.23 162	99.43 138	99.92 91	99.01 153	99.96 202	99.47 83	98.80 35	99.96 88	99.96 160	98.56 113	99.30 214	87.78 321	99.68 116	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
tpm		98.24 168	98.22 163	98.32 202	99.13 203	95.79 269	99.53 283	99.12 270	95.20 232	99.96 88	99.36 249	97.58 131	99.28 215	97.41 222	96.67 211	99.88 153

COLMAP_ROB	97.10 7	98.29 165	98.17 164	98.65 186	99.94 86	97.39 237	99.30 300	99.40 155	95.64 217	97.75 258	100.00 1	92.69 214	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
diffmvs		98.52 155	98.11 165	99.73 112	99.59 154	99.47 119	100.00 1	99.19 246	93.68 269	99.70 152	99.75 203	95.07 186	99.84 148	97.57 215	98.48 139	99.89 141

UGNet		98.41 161	98.11 165	99.31 150	99.54 163	98.55 172	99.18 313	100.00 1	98.64 43	99.79 137	99.04 267	87.61 285	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
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	88.99 273	99.82 152	98.83 164	100.00 1	99.77 179

cascas		98.43 159	98.07 168	99.50 134	99.65 140	99.02 150	100.00 1	99.22 239	94.21 254	99.72 144	99.98 141	92.03 220	99.93 133	99.68 105	98.12 165	99.54 200

PS-MVSNAJss		98.03 173	98.06 169	97.94 236	97.63 295	97.33 243	99.89 222	99.23 237	96.27 203	98.03 245	99.59 234	98.75 106	98.78 246	98.52 179	94.61 242	97.70 268

test0.0.03 1		98.12 171	98.03 170	98.39 195	99.11 204	98.07 210	100.00 1	99.93 32	96.70 178	96.91 279	99.95 172	99.31 55	98.19 286	91.93 295	98.44 142	98.91 206

Fast-Effi-MVS+		98.40 162	98.02 171	99.55 131	99.63 145	99.06 147	100.00 1	99.15 255	95.07 233	99.42 167	99.95 172	93.26 207	99.73 162	97.44 220	98.24 158	99.87 160

ab-mvs		98.42 160	98.02 171	99.61 118	99.71 130	99.00 154	99.10 323	99.64 72	96.70 178	99.04 189	99.81 197	90.64 249	99.98 95	99.64 110	97.93 172	99.84 163

EI-MVSNet		97.98 175	97.93 173	98.16 218	99.11 204	97.84 226	99.74 253	99.29 211	94.39 249	98.65 212	100.00 1	97.21 137	98.88 237	97.62 214	95.31 222	97.75 222

Patchmatch-test1		98.23 169	97.91 174	99.17 159	99.41 185	98.25 194	99.99 176	99.45 97	96.91 169	99.76 141	99.69 212	89.65 265	99.37 210	97.55 216	98.79 131	99.89 141

HQP-MVS		97.73 179	97.85 175	97.39 254	99.07 208	94.82 280	100.00 1	99.40 155	99.04 13	99.17 178	99.97 151	88.61 277	99.57 179	99.79 91	95.58 213	97.77 216

HQP_MVS		97.71 181	97.82 176	97.37 255	99.00 220	94.80 283	100.00 1	99.40 155	99.00 19	99.08 186	99.97 151	88.58 279	99.55 188	99.79 91	95.57 217	97.76 218

tpm cat1		98.05 172	97.76 177	98.92 174	99.50 177	97.10 251	99.77 247	99.30 207	90.20 307	99.72 144	98.71 294	97.71 128	99.86 143	96.75 241	98.20 161	99.81 171

TR-MVS		98.14 170	97.74 178	99.33 148	99.59 154	98.28 188	99.27 301	99.21 243	96.42 196	99.15 182	99.94 176	88.87 275	99.79 157	98.88 160	98.29 155	99.93 125

CLD-MVS		97.64 182	97.74 178	97.36 256	99.01 216	94.76 288	100.00 1	99.34 195	99.30 4	99.00 190	99.97 151	87.49 286	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
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	95.27 183	98.89 234	98.78 165	93.07 253	97.74 245

CR-MVSNet		98.02 174	97.71 181	98.93 172	99.31 196	98.86 160	99.13 321	99.00 300	96.53 190	99.96 88	98.98 278	96.94 155	98.10 295	91.18 298	98.40 145	99.84 163

FC-MVSNet-test		97.84 177	97.63 182	98.45 192	98.30 253	99.05 148	100.00 1	99.43 115	96.63 185	97.61 262	99.82 194	95.19 185	98.57 271	98.64 173	93.05 254	97.73 255

IterMVS-LS		97.56 185	97.44 183	97.92 239	99.38 193	97.90 220	99.89 222	99.10 272	94.41 248	98.32 233	99.54 240	97.21 137	98.11 292	97.50 219	91.62 267	97.75 222
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Patchmatch-test		97.83 178	97.42 184	99.06 162	99.08 207	97.66 231	98.66 334	99.21 243	93.65 271	98.25 239	99.58 235	99.47 40	99.57 179	90.25 309	98.59 134	99.95 112

ACMM	97.17 6	97.37 189	97.40 185	97.29 258	99.01 216	94.64 292	100.00 1	99.25 230	98.07 77	98.44 228	99.98 141	87.38 287	99.55 188	99.25 145	95.19 229	97.69 273
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
test_djsdf		97.55 186	97.38 186	98.07 226	97.50 302	97.99 214	100.00 1	99.13 264	95.46 229	98.47 227	99.85 188	92.01 222	98.59 268	98.63 174	95.36 220	97.62 291

TAPA-MVS	96.40 10	97.64 182	97.37 187	98.45 192	99.94 86	95.70 270	100.00 1	99.40 155	97.65 119	99.53 161	100.00 1	99.31 55	99.66 173	80.48 333	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
LPG-MVS_test		97.31 191	97.32 188	97.28 259	98.85 235	94.60 293	100.00 1	99.37 176	97.35 140	98.85 198	99.98 141	86.66 293	99.56 183	99.55 119	95.26 224	97.70 268

nrg030		97.64 182	97.27 189	98.75 183	98.34 249	99.53 110	100.00 1	99.22 239	96.21 205	98.27 237	99.95 172	94.40 194	98.98 227	99.23 146	89.78 292	97.75 222

GA-MVS		97.72 180	97.27 189	99.06 162	99.24 201	97.93 219	100.00 1	99.24 233	95.80 215	98.99 191	99.64 225	89.77 263	99.36 211	95.12 261	97.62 202	99.89 141

LCM-MVSNet-Re		96.52 228	97.21 191	94.44 307	99.27 199	85.80 329	99.85 229	96.61 347	95.98 208	92.75 310	98.48 302	93.97 199	97.55 309	99.58 117	98.43 143	99.98 91

OPM-MVS		97.21 194	97.18 192	97.32 257	98.08 273	94.66 290	100.00 1	99.28 219	98.65 42	98.92 193	99.98 141	86.03 299	99.56 183	98.28 189	95.41 219	97.72 260

ACMP	97.00 8	97.19 195	97.16 193	97.27 261	98.97 225	94.58 295	100.00 1	99.32 200	97.97 86	97.45 266	99.98 141	85.79 301	99.56 183	99.70 103	95.24 227	97.67 279
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
FMVSNet3		97.30 192	96.95 194	98.37 197	99.65 140	99.25 135	99.71 261	99.28 219	94.23 252	98.53 222	98.91 285	93.30 206	98.11 292	95.31 257	93.60 247	97.73 255

IB-MVS	96.24 12	97.54 187	96.95 194	99.33 148	99.67 136	98.10 208	100.00 1	99.47 83	97.42 137	99.26 175	99.69 212	98.83 101	99.89 139	99.43 129	78.77 332	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
anonymousdsp		97.16 197	96.88 196	98.00 232	97.08 313	98.06 211	99.81 238	99.15 255	94.58 243	97.84 254	99.62 231	90.49 252	98.60 266	97.98 203	95.32 221	97.33 308

testpf		97.02 206	96.87 197	97.44 253	99.50 177	95.18 274	95.70 346	99.33 197	91.35 299	98.00 249	99.22 256	96.29 168	98.49 277	94.42 270	98.07 168	98.67 209

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	98.90 286	94.93 189	98.89 234	97.54 218	87.61 310	97.75 222

pmmvs4		97.17 196	96.80 199	98.27 206	97.68 292	98.64 169	100.00 1	99.18 250	94.22 253	98.55 220	99.71 207	93.67 201	98.47 278	95.66 251	92.57 258	97.71 267

UniMVSNet_NR-MVSNet		97.16 197	96.80 199	98.22 213	98.38 248	98.41 175	100.00 1	99.45 97	96.14 206	97.76 255	99.64 225	95.05 187	98.50 275	97.98 203	86.84 313	97.75 222

jajsoiax		97.07 202	96.79 201	97.89 240	97.28 311	97.12 249	99.95 208	99.19 246	96.55 188	97.31 269	99.69 212	87.35 289	98.91 231	98.70 169	95.12 233	97.66 281

MIMVSNet		97.06 203	96.73 202	98.05 230	99.38 193	96.64 261	98.47 337	99.35 190	93.41 277	99.48 164	98.53 301	89.66 264	97.70 308	94.16 276	98.11 166	99.80 178

mvs_tets		97.00 207	96.69 203	97.94 236	97.41 310	97.27 244	99.60 277	99.18 250	96.51 192	97.35 268	99.69 212	86.53 295	98.91 231	98.84 162	95.09 234	97.65 285

WR-MVS		97.09 200	96.64 204	98.46 191	98.43 246	99.09 145	99.97 199	99.33 197	95.62 219	97.76 255	99.67 218	91.17 240	98.56 272	98.49 180	89.28 296	97.74 245

XXY-MVS		97.14 199	96.63 205	98.67 185	98.65 238	98.92 158	99.54 282	99.29 211	95.57 221	97.63 260	99.83 191	87.79 284	99.35 212	98.39 183	92.95 255	97.75 222

LFMVS		97.42 188	96.62 206	99.81 92	99.80 114	99.50 111	99.16 319	99.56 74	94.48 247	100.00 1	100.00 1	79.35 330	100.00 1	99.89 78	97.37 204	99.94 116

ACMH	96.25 11	96.77 211	96.62 206	97.21 262	98.96 226	94.43 297	99.64 274	99.33 197	97.43 136	96.55 286	99.97 151	83.52 312	99.54 191	99.07 154	95.13 232	97.66 281
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
EU-MVSNet		96.63 224	96.53 208	96.94 271	97.59 298	96.87 256	99.76 250	99.47 83	96.35 200	96.85 281	99.78 201	92.57 215	96.27 326	95.33 256	91.08 273	97.68 275

XVG-ACMP-BASELINE		96.60 226	96.52 209	96.84 282	98.41 247	93.29 307	99.99 176	99.32 200	97.76 105	98.51 225	99.29 253	81.95 318	99.54 191	98.40 182	95.03 235	97.68 275

DU-MVS		96.93 209	96.49 210	98.22 213	98.31 251	98.41 175	100.00 1	99.37 176	96.41 197	97.76 255	99.65 221	92.14 218	98.50 275	97.98 203	86.84 313	97.75 222

MVP-Stereo		96.51 229	96.48 211	96.60 290	95.65 323	94.25 298	98.84 332	98.16 324	95.85 214	95.23 296	99.04 267	92.54 216	99.13 218	92.98 288	99.98 95	96.43 318
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
IterMVS		96.76 215	96.46 212	97.63 243	99.41 185	96.89 255	99.99 176	99.13 264	94.74 240	97.59 263	99.66 220	89.63 267	98.28 285	95.71 249	92.31 260	97.72 260
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
VPA-MVSNet		97.03 205	96.43 213	98.82 179	98.64 239	99.32 128	99.38 294	99.47 83	96.73 176	98.91 195	98.94 283	87.00 291	99.40 208	99.23 146	89.59 293	97.76 218

Patchmtry		96.81 210	96.37 214	98.14 219	99.31 196	98.55 172	98.91 330	99.00 300	90.45 304	97.92 251	98.98 278	96.94 155	98.12 290	94.27 273	91.53 268	97.75 222

JIA-IIPM		97.09 200	96.34 215	99.36 145	98.88 231	98.59 170	99.81 238	99.43 115	84.81 332	99.96 88	90.34 344	98.55 114	99.52 196	97.00 230	98.28 157	99.98 91

ACMH+	96.20 13	96.49 231	96.33 216	97.00 268	99.06 212	93.80 302	99.81 238	99.31 205	97.32 143	95.89 293	99.97 151	82.62 316	99.54 191	98.34 186	94.63 241	97.65 285

WR-MVS_H		96.73 216	96.32 217	97.95 235	98.26 255	97.88 222	99.72 259	99.43 115	95.06 234	96.99 276	98.68 295	93.02 210	98.53 273	97.43 221	88.33 306	97.43 302

v1neww		96.77 211	96.27 218	98.26 208	98.16 263	98.23 195	100.00 1	99.09 275	93.94 259	98.73 207	99.05 264	91.65 225	98.82 242	95.75 247	90.04 283	97.74 245

v7new		96.77 211	96.27 218	98.26 208	98.16 263	98.23 195	100.00 1	99.09 275	93.94 259	98.73 207	99.05 264	91.65 225	98.82 242	95.75 247	90.04 283	97.74 245

v6		96.77 211	96.26 220	98.29 204	98.10 269	98.27 190	100.00 1	99.09 275	93.95 258	98.73 207	99.06 262	91.51 232	98.86 239	95.83 245	90.04 283	97.74 245

CP-MVSNet		96.73 216	96.25 221	98.18 216	98.21 258	98.67 168	99.77 247	99.32 200	95.06 234	97.20 273	99.65 221	90.10 257	98.19 286	98.06 202	88.90 300	97.66 281

v2v482		96.70 218	96.18 222	98.27 206	98.04 278	98.39 177	100.00 1	99.13 264	94.19 255	98.58 219	99.08 261	90.48 253	98.67 261	95.69 250	90.44 281	97.75 222

LF4IMVS		96.19 245	96.18 222	96.23 296	98.26 255	92.09 316	100.00 1	97.89 334	97.82 100	97.94 250	99.87 184	82.71 315	99.38 209	97.41 222	93.71 246	97.20 310

V42		96.65 222	96.16 224	98.11 225	98.17 262	98.23 195	99.99 176	99.09 275	93.97 256	98.74 206	99.05 264	91.09 245	98.82 242	95.46 255	89.90 290	97.27 309

divwei89l23v2f112		96.68 219	96.15 225	98.25 212	98.03 279	98.27 190	100.00 1	99.09 275	93.79 262	98.59 217	99.04 267	91.54 231	98.73 253	95.29 260	89.99 287	97.75 222

v7		96.64 223	96.14 226	98.13 222	98.18 260	97.97 216	99.99 176	99.09 275	93.62 273	98.76 204	99.30 252	91.13 242	98.70 258	94.37 271	90.80 276	97.74 245

v1141		96.66 220	96.12 227	98.26 208	98.05 276	98.28 188	100.00 1	99.09 275	93.71 263	98.59 217	99.04 267	91.57 229	98.73 253	95.05 262	90.00 286	97.75 222

v1		96.66 220	96.12 227	98.30 203	98.09 270	98.33 183	100.00 1	99.09 275	93.69 268	98.68 210	99.04 267	91.42 236	98.83 241	95.05 262	89.99 287	97.75 222

gg-mvs-nofinetune		96.95 208	96.10 229	99.50 134	99.41 185	99.36 127	99.07 327	99.52 76	83.69 335	99.96 88	83.60 352	100.00 1	99.20 216	99.68 105	99.99 88	99.96 107

LTVRE_ROB	95.29 16	96.32 240	96.10 229	96.99 269	98.55 242	93.88 301	99.45 288	99.28 219	94.50 246	96.46 287	99.52 241	84.86 304	99.48 201	97.26 225	95.03 235	97.59 295
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
X-MVStestdata		97.04 204	96.06 231	99.98 16	100.00 1	99.94 28	100.00 1	99.75 50	98.67 40	100.00 1	66.97 357	99.16 76	100.00 1	100.00 1	100.00 1	100.00 1

NR-MVSNet		96.63 224	96.04 232	98.38 196	98.31 251	98.98 155	99.22 312	99.35 190	95.87 210	94.43 302	99.65 221	92.73 213	98.40 281	96.78 239	88.05 307	97.75 222

TranMVSNet+NR-MVSNet		96.45 232	96.01 233	97.79 242	98.00 282	97.62 232	100.00 1	99.35 190	95.98 208	97.31 269	99.64 225	90.09 258	98.00 303	96.89 234	86.80 316	97.75 222

VDD-MVS		96.58 227	95.99 234	98.34 200	99.52 171	95.33 271	99.18 313	99.38 173	96.64 183	99.77 139	100.00 1	72.51 341	100.00 1	100.00 1	96.94 209	99.70 191

OurMVSNet-221017-0		96.14 251	95.98 235	96.62 289	97.49 304	93.44 305	99.92 216	98.16 324	95.86 212	97.65 259	99.95 172	85.71 302	98.78 246	94.93 265	94.18 245	97.64 288

v1144		96.51 229	95.97 236	98.13 222	97.98 283	98.04 213	99.99 176	99.08 283	93.51 276	98.62 215	98.98 278	90.98 248	98.62 263	93.79 281	90.79 277	97.74 245

testgi		96.18 246	95.93 237	96.93 272	98.98 224	94.20 300	100.00 1	99.07 285	97.16 151	96.06 290	99.86 186	84.08 311	97.79 306	90.38 306	97.80 184	98.81 207

ppachtmachnet_test		96.17 248	95.89 238	97.02 267	97.61 297	95.24 272	99.99 176	99.24 233	93.31 281	96.71 284	99.62 231	94.34 196	98.07 298	89.87 311	92.30 261	97.75 222

MS-PatchMatch		95.66 266	95.87 239	95.05 302	97.80 289	89.25 324	98.88 331	99.30 207	96.35 200	96.86 280	99.01 275	81.35 323	99.43 205	93.30 286	99.98 95	96.46 317

v148		96.29 241	95.84 240	97.63 243	97.74 290	96.53 262	100.00 1	99.07 285	93.52 275	98.01 248	99.42 248	91.22 238	98.60 266	96.37 243	87.22 312	97.75 222

v144192		96.40 235	95.81 241	98.17 217	97.89 287	98.11 207	99.99 176	99.06 293	93.39 278	98.75 205	99.09 260	90.43 254	98.66 262	93.10 287	90.55 280	97.75 222

GBi-Net		96.07 253	95.80 242	96.89 274	99.53 166	94.87 277	99.18 313	99.27 226	93.71 263	98.53 222	98.81 289	84.23 308	98.07 298	95.31 257	93.60 247	97.72 260

test1		96.07 253	95.80 242	96.89 274	99.53 166	94.87 277	99.18 313	99.27 226	93.71 263	98.53 222	98.81 289	84.23 308	98.07 298	95.31 257	93.60 247	97.72 260

PS-CasMVS		96.34 239	95.78 244	98.03 231	98.18 260	98.27 190	99.71 261	99.32 200	94.75 238	96.82 282	99.65 221	86.98 292	98.15 288	97.74 210	88.85 301	97.66 281

VPNet		96.41 233	95.76 245	98.33 201	98.61 240	98.30 187	99.48 287	99.45 97	96.98 162	98.87 197	99.88 183	81.57 320	98.93 229	99.22 148	87.82 309	97.76 218

PVSNet_0	93.57 19	96.41 233	95.74 246	98.41 194	99.84 98	95.22 273	100.00 1	100.00 1	98.08 76	97.55 264	99.78 201	84.40 306	100.00 1	100.00 1	81.99 324	100.00 1

v8		96.35 238	95.73 247	98.21 215	98.11 268	98.23 195	99.94 212	99.07 285	92.66 289	98.29 235	99.00 277	91.46 234	98.77 249	94.17 274	88.83 302	97.62 291

Baseline_NR-MVSNet		96.16 249	95.70 248	97.56 248	98.28 254	96.79 258	100.00 1	97.86 335	91.93 295	97.63 260	99.47 246	92.14 218	98.35 283	97.13 227	86.83 315	97.54 298

USDC		95.90 259	95.70 248	96.50 291	98.60 241	92.56 314	100.00 1	98.30 320	97.77 103	96.92 277	99.94 176	81.25 324	99.45 204	93.54 285	94.96 237	97.49 299

tfpnnormal		96.36 237	95.69 250	98.37 197	98.55 242	98.71 165	99.69 267	99.45 97	93.16 285	96.69 285	99.71 207	88.44 281	98.99 226	94.17 274	91.38 270	97.41 303

pmmvs5		95.94 258	95.61 251	96.95 270	97.42 308	94.66 290	100.00 1	98.08 328	93.60 274	97.05 275	99.43 247	87.02 290	98.46 279	95.76 246	92.12 262	97.72 260

FMVSNet2		96.22 244	95.60 252	98.06 229	99.53 166	98.33 183	99.45 288	99.27 226	93.71 263	98.03 245	98.84 288	84.23 308	98.10 295	93.97 279	93.40 250	97.73 255

VDDNet		96.39 236	95.55 253	98.90 175	99.27 199	97.45 234	99.15 320	99.92 36	91.28 300	99.98 81	100.00 1	73.55 339	100.00 1	99.85 83	96.98 208	99.24 205

v1921920		96.16 249	95.50 254	98.14 219	97.88 288	97.96 217	99.99 176	99.07 285	93.33 280	98.60 216	99.24 255	89.37 269	98.71 257	91.28 297	90.74 278	97.75 222

v10		96.14 251	95.50 254	98.07 226	98.19 259	97.96 217	99.83 231	99.07 285	92.10 293	98.07 244	98.94 283	91.07 246	98.61 264	92.41 294	89.82 291	97.63 289

v1192		96.18 246	95.49 256	98.26 208	98.01 280	98.15 205	99.99 176	99.08 283	93.36 279	98.54 221	98.97 281	89.47 268	98.89 234	91.15 299	90.82 275	97.75 222

SixPastTwentyTwo		95.71 265	95.49 256	96.38 293	97.42 308	93.01 308	99.84 230	98.23 321	94.75 238	95.98 291	99.97 151	85.35 303	98.43 280	94.71 266	93.17 252	97.69 273

PEN-MVS		96.01 256	95.48 258	97.58 247	97.74 290	97.26 245	99.90 219	99.29 211	94.55 244	96.79 283	99.55 238	87.38 287	97.84 305	96.92 233	87.24 311	97.65 285

FMVSNet5		95.32 271	95.43 259	94.99 303	99.39 192	92.99 310	99.25 303	99.24 233	90.45 304	97.44 267	98.45 303	95.78 174	94.39 335	87.02 322	91.88 265	97.59 295

v7n		96.06 255	95.42 260	97.99 234	97.58 299	97.35 240	99.86 228	99.11 271	92.81 288	97.91 252	99.49 244	90.99 247	98.92 230	92.51 291	88.49 305	97.70 268

V4		95.89 261	95.36 261	97.49 250	97.65 294	97.40 236	99.88 225	99.07 285	92.19 291	98.08 242	99.01 275	90.20 256	98.72 255	93.57 284	88.63 303	96.34 319

v52		95.88 263	95.35 262	97.48 251	97.66 293	97.38 239	99.88 225	99.07 285	92.19 291	98.09 241	99.02 274	90.06 259	98.72 255	93.58 283	88.61 304	96.34 319

LP		95.89 261	95.35 262	97.51 249	98.92 228	95.15 275	98.66 334	99.39 169	89.43 318	97.22 272	99.03 272	94.37 195	97.74 307	83.71 328	97.44 203	99.63 198

v1240		95.96 257	95.25 264	98.07 226	97.91 286	97.87 224	99.96 202	99.07 285	93.24 283	98.64 214	98.96 282	88.98 274	98.61 264	89.58 313	90.92 274	97.75 222

DSMNet-mixed		95.18 272	95.21 265	95.08 301	96.03 319	90.21 322	99.65 273	93.64 352	92.91 287	98.34 232	97.40 314	90.05 260	95.51 333	91.02 300	97.86 177	99.51 202

DI_MVS_plusplus_test		96.28 242	95.16 266	99.61 118	96.01 320	99.18 142	100.00 1	99.29 211	96.49 193	89.08 317	98.42 306	80.06 325	99.90 137	98.74 168	98.39 147	99.75 182

K. test v3		95.46 270	95.14 267	96.40 292	97.53 301	93.40 306	99.99 176	99.23 237	95.49 227	92.70 311	99.73 204	84.26 307	98.12 290	93.94 280	93.38 251	97.68 275

test_normal		96.24 243	95.12 268	99.60 121	96.00 321	99.16 143	100.00 1	99.29 211	96.43 194	88.96 320	98.40 307	80.06 325	99.90 137	98.53 178	98.39 147	99.75 182

TinyColmap		95.50 268	95.12 268	96.64 288	98.69 237	93.00 309	99.40 292	97.75 336	96.40 198	96.14 289	99.87 184	79.47 329	99.50 199	93.62 282	94.72 240	97.40 304

pm-mvs1		95.76 264	95.01 270	98.00 232	98.23 257	97.45 234	99.24 304	99.04 298	93.13 286	95.93 292	99.72 205	86.28 296	98.84 240	95.62 253	87.92 308	97.72 260

DTE-MVSNet		95.52 267	94.99 271	97.08 264	97.49 304	96.45 263	100.00 1	99.25 230	93.82 261	96.17 288	99.57 237	87.81 283	97.18 310	94.57 267	86.26 318	97.62 291

v748		95.47 269	94.95 272	97.04 265	97.46 307	94.76 288	99.93 214	99.10 272	91.95 294	97.11 274	99.18 257	89.94 262	98.68 259	94.01 278	85.88 319	97.67 279

PatchT		95.90 259	94.95 272	98.75 183	99.03 214	98.39 177	99.08 325	99.32 200	85.52 328	99.96 88	94.99 337	97.94 124	98.05 302	80.20 334	98.47 141	99.81 171

test2356		92.55 296	93.94 274	88.39 322	93.49 330	78.42 336	100.00 1	99.40 155	91.64 296	93.93 304	98.74 293	91.11 243	88.67 345	79.37 336	97.79 185	98.08 214

UnsupCasMVSNet_eth		94.25 277	93.89 275	95.34 300	97.63 295	92.13 315	99.73 257	99.36 182	94.88 237	92.78 308	98.63 298	82.72 314	96.53 316	94.57 267	84.73 321	97.36 305

RPMNet		95.10 273	93.82 276	98.93 172	99.31 196	98.86 160	99.13 321	99.38 173	79.82 340	99.96 88	95.13 335	95.69 178	98.10 295	77.54 340	98.40 145	99.84 163

TransMVSNet (Re)		94.78 274	93.72 277	97.93 238	98.34 249	97.88 222	99.23 310	97.98 332	91.60 297	94.55 300	99.71 207	87.89 282	98.36 282	89.30 318	84.92 320	97.56 297

test_0402		94.35 276	93.70 278	96.32 294	97.92 285	93.60 303	99.61 276	98.85 307	88.19 324	94.68 299	99.48 245	80.01 328	98.58 270	89.39 316	95.15 231	96.77 314

Patchmatch-RL test		93.49 283	93.63 279	93.05 315	91.78 332	83.41 332	98.21 339	96.95 343	91.58 298	91.05 313	97.64 313	99.40 48	95.83 330	94.11 277	81.95 325	99.91 128

FMVSNet1		94.45 275	93.63 279	96.89 274	98.87 233	94.87 277	99.18 313	99.27 226	90.95 303	97.31 269	98.81 289	72.89 340	98.07 298	92.61 289	92.81 256	97.72 260

new_pmnet		94.11 279	93.47 281	96.04 298	96.60 316	92.82 311	99.97 199	98.91 305	90.21 306	95.26 295	98.05 311	85.89 300	98.14 289	84.28 327	92.01 264	97.16 311

N_pmnet		91.88 301	93.37 282	87.40 324	97.24 312	66.33 349	99.90 219	91.05 354	89.77 313	95.65 294	98.58 300	90.05 260	98.11 292	85.39 325	92.72 257	97.75 222

Anonymous20231206		93.45 285	93.17 283	94.30 309	95.00 327	89.69 323	99.98 193	98.43 319	93.30 282	94.50 301	98.59 299	90.52 251	95.73 331	77.46 341	90.73 279	97.48 301

testus		91.61 304	92.92 284	87.70 323	93.91 329	74.98 340	100.00 1	98.19 323	92.59 290	93.90 305	98.68 295	81.43 321	90.77 343	79.82 335	97.71 194	97.34 307

pmmvs6		93.64 280	92.87 285	95.94 299	97.47 306	91.41 321	98.92 329	99.02 299	87.84 325	95.01 297	99.61 233	77.24 335	98.77 249	94.33 272	86.41 317	97.63 289

test20.03		93.11 292	92.85 286	93.88 314	95.19 326	91.83 317	100.00 1	98.87 306	93.68 269	92.76 309	98.88 287	89.20 271	92.71 340	77.88 339	89.19 297	97.09 312

MVS-HIRNet		94.12 278	92.73 287	98.29 204	99.33 195	95.95 266	99.38 294	99.19 246	74.54 342	98.26 238	86.34 348	86.07 297	99.06 221	91.60 296	99.87 110	99.85 162

EG-PatchMatch MVS		92.94 293	92.49 288	94.29 310	95.87 322	87.07 328	99.07 327	98.11 327	93.19 284	88.98 319	98.66 297	70.89 342	99.08 220	92.43 293	95.21 228	96.72 315

v18		93.55 281	92.42 289	96.91 273	98.12 266	98.26 193	99.83 231	98.74 309	89.99 309	88.94 321	95.64 324	92.02 221	96.54 313	90.27 308	78.26 333	95.94 327

v17		93.53 282	92.42 289	96.88 278	98.09 270	98.16 203	99.83 231	98.74 309	89.95 310	89.05 318	95.65 323	91.99 223	96.54 313	90.31 307	78.15 335	95.95 325

v16		93.48 284	92.34 291	96.89 274	98.13 265	98.19 201	99.82 236	98.74 309	89.94 311	88.90 322	95.62 325	91.65 225	96.54 313	90.03 310	78.22 334	95.95 325

v15		93.28 286	92.08 292	96.87 279	98.07 274	98.22 199	99.82 236	98.74 309	89.83 312	88.74 324	95.44 329	91.55 230	96.47 317	89.70 312	76.87 337	95.93 328

V14		93.24 287	92.04 293	96.87 279	98.07 274	98.20 200	99.80 241	98.74 309	89.76 314	88.64 325	95.53 326	91.47 233	96.47 317	89.49 314	76.84 338	95.92 329

CMPMVS	66.12 22	90.65 306	92.04 293	86.46 326	96.18 318	66.87 348	98.03 340	99.38 173	83.38 336	85.49 335	99.55 238	77.59 334	98.80 245	94.44 269	94.31 244	93.72 339
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
V9		93.20 288	91.99 295	96.85 281	98.05 276	98.16 203	99.77 247	98.73 315	89.67 315	88.64 325	95.44 329	91.34 237	96.47 317	89.46 315	76.79 339	95.92 329

v13		93.18 289	91.97 296	96.81 284	98.12 266	98.12 206	99.74 253	98.73 315	89.47 317	88.52 327	95.40 333	91.72 224	96.41 320	89.23 320	76.77 340	95.92 329

v12		93.18 289	91.97 296	96.80 285	98.09 270	98.10 208	99.76 250	98.73 315	89.61 316	88.45 328	95.41 332	91.63 228	96.39 322	89.32 317	76.76 341	95.91 332

v11		93.14 291	91.93 298	96.77 287	98.01 280	98.17 202	99.72 259	98.74 309	89.39 319	88.81 323	95.49 328	91.15 241	96.29 324	86.78 323	79.25 330	95.86 334

MIMVSNet1		91.96 298	91.20 299	94.23 311	94.94 328	91.69 319	99.34 297	99.22 239	88.23 322	94.18 303	98.45 303	75.52 338	93.41 339	79.37 336	91.49 269	97.60 294

OpenMVS_ROB	88.34 20	91.89 300	91.12 300	94.19 312	95.55 324	87.63 327	99.26 302	98.03 329	86.61 327	90.65 316	96.82 315	70.14 343	98.78 246	86.54 324	96.50 212	96.15 321

MDA-MVSNet_test_wron		92.61 295	91.09 301	97.19 263	96.71 315	97.26 245	100.00 1	99.14 259	88.61 321	67.90 348	98.32 310	89.03 272	96.57 312	90.47 305	89.59 293	97.74 245

YYNet1		92.44 297	90.92 302	97.03 266	96.20 317	97.06 252	99.99 176	99.14 259	88.21 323	67.93 347	98.43 305	88.63 276	96.28 325	90.64 301	89.08 299	97.74 245

pmmvs-eth3d		91.73 302	90.67 303	94.92 305	91.63 334	92.71 312	99.90 219	98.54 318	91.19 301	88.08 329	95.50 327	79.31 331	96.13 327	90.55 304	81.32 327	95.91 332

TDRefinement		91.93 299	90.48 304	96.27 295	81.60 347	92.65 313	99.10 323	97.61 339	93.96 257	93.77 306	99.85 188	80.03 327	99.53 195	97.82 209	70.59 344	96.63 316

Test4		92.63 294	90.45 305	99.17 159	92.81 331	99.02 150	99.98 193	99.13 264	96.60 186	82.04 340	96.27 319	51.35 349	98.75 252	97.55 216	98.36 151	99.75 182

MDA-MVSNet-bldmvs		91.65 303	89.94 306	96.79 286	96.72 314	96.70 260	99.42 291	98.94 302	88.89 320	66.97 350	98.37 308	81.43 321	95.91 329	89.24 319	89.46 295	97.75 222

new-patchmatchnet		90.30 308	89.46 307	92.84 316	90.77 335	88.55 326	99.83 231	98.80 308	90.07 308	87.86 330	95.00 336	78.77 332	94.30 336	84.86 326	79.15 331	95.68 336

pmmvs3		90.62 307	89.36 308	94.40 308	90.53 336	91.49 320	100.00 1	96.73 345	84.21 334	93.65 307	96.65 316	82.56 317	94.83 334	82.28 330	77.62 336	96.89 313

1111		88.62 310	89.13 309	87.08 325	87.71 339	77.22 337	99.96 202	97.71 337	85.51 329	83.47 338	96.26 320	95.76 175	90.96 341	66.63 347	89.17 298	93.07 340

test1235678		88.02 312	88.73 310	85.90 328	87.57 341	71.70 344	100.00 1	97.42 340	87.52 326	86.19 333	96.39 318	81.60 319	87.93 346	70.72 344	91.18 272	98.08 214

testing_2		90.79 305	88.26 311	98.35 199	89.11 338	98.56 171	99.70 263	99.14 259	93.70 267	73.80 343	94.06 339	55.19 346	98.76 251	97.17 226	92.50 259	97.74 245

UnsupCasMVSNet_bld		89.50 309	88.00 312	93.99 313	95.30 325	88.86 325	98.52 336	99.28 219	85.50 331	87.80 331	94.11 338	61.63 345	96.96 311	90.63 302	79.26 329	96.15 321

PM-MVS		88.39 311	87.41 313	91.31 317	91.73 333	82.02 334	99.79 242	96.62 346	91.06 302	90.71 315	95.73 322	48.60 351	95.96 328	90.56 303	81.91 326	95.97 324

test12356		86.30 313	87.15 314	83.77 332	84.24 344	72.00 342	99.94 212	96.80 344	84.63 333	85.16 336	96.51 317	77.02 336	86.31 349	70.06 345	89.93 289	93.00 341

.test1245		85.18 314	84.81 315	86.28 327	87.71 339	77.22 337	99.96 202	97.71 337	85.51 329	83.47 338	96.26 320	95.76 175	90.96 341	66.63 347	50.30 348	90.64 344

Gipuma		84.73 315	83.50 316	88.40 321	97.50 302	82.21 333	88.87 349	99.05 295	65.81 345	85.71 334	90.49 343	53.70 347	96.31 323	78.64 338	91.74 266	86.67 348
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
Anonymous20231211		84.35 316	82.41 317	90.15 318	89.14 337	78.88 335	98.71 333	98.22 322	70.20 344	86.88 332	95.44 329	47.11 353	95.72 332	81.14 331	74.88 342	95.84 335

testmvs		80.17 317	81.95 318	74.80 338	58.54 358	59.58 356	100.00 1	87.14 358	76.09 341	99.61 156	100.00 1	67.06 344	74.19 357	98.84 162	50.30 348	90.64 344

testmv		79.83 318	79.77 319	79.99 335	78.22 351	63.55 352	99.67 270	95.51 350	80.89 338	76.24 342	92.90 341	52.16 348	86.10 350	62.45 350	79.90 328	90.33 346

FPMVS		77.92 322	79.45 320	73.34 340	76.87 352	46.81 359	98.24 338	99.05 295	59.89 349	73.55 344	98.34 309	36.81 355	86.55 347	80.96 332	91.35 271	86.65 349

test123		79.44 319	79.23 321	80.05 334	80.03 349	71.72 343	100.00 1	77.93 361	62.52 346	94.81 298	99.69 212	78.21 333	74.53 356	92.57 290	27.33 356	93.90 337

PMMVS2		79.15 320	77.28 322	84.76 331	82.34 346	72.66 341	99.70 263	95.11 351	71.68 343	84.78 337	90.87 342	32.05 356	89.99 344	75.53 342	63.45 345	91.64 342

LCM-MVSNet		79.01 321	76.93 323	85.27 330	78.28 350	68.01 347	96.57 344	98.03 329	55.10 350	82.03 341	93.27 340	31.99 357	93.95 337	82.72 329	74.37 343	93.84 338

tmp_tt		75.80 323	74.26 324	80.43 333	52.91 360	53.67 358	87.42 351	97.98 332	61.80 347	67.04 349	100.00 1	76.43 337	96.40 321	96.47 242	28.26 355	91.23 343

no-one		74.65 324	71.03 325	85.51 329	80.99 348	75.42 339	99.70 263	97.15 341	81.02 337	66.48 351	80.55 355	29.10 358	93.65 338	73.74 343	30.53 354	87.47 347

E-PMN		70.72 325	70.06 326	72.69 342	83.92 345	65.48 351	99.95 208	92.72 353	49.88 353	72.30 345	86.26 349	47.17 352	77.43 354	53.83 354	44.49 350	75.17 356

EMVS		69.88 327	69.09 327	72.24 343	84.70 343	65.82 350	99.96 202	87.08 359	49.82 354	71.51 346	84.74 350	49.30 350	75.32 355	50.97 355	43.71 351	75.59 355

PNet_i23d		69.93 326	67.61 328	76.86 336	75.89 353	62.08 355	97.85 341	88.23 356	61.04 348	55.65 353	84.10 351	19.35 360	83.21 351	66.45 349	59.98 346	85.29 351

PMVS	60.66 23	65.98 330	65.05 329	68.75 344	55.06 359	38.40 360	88.19 350	96.98 342	48.30 355	44.82 356	88.52 346	12.22 363	86.49 348	67.58 346	83.79 323	81.35 353
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVE	68.59 21	67.22 328	64.68 330	74.84 337	74.67 355	62.32 354	95.84 345	90.87 355	50.98 352	58.72 352	81.05 353	12.20 364	78.95 353	61.06 352	56.75 347	83.24 352
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ANet_high		66.05 329	63.44 331	73.88 339	61.14 357	63.45 353	95.68 347	87.18 357	79.93 339	47.35 354	80.68 354	22.35 359	72.33 358	61.24 351	35.42 353	85.88 350

wuykxyi23d		62.75 331	59.23 332	73.34 340	61.53 356	59.39 357	93.28 348	86.17 360	53.70 351	46.89 355	77.89 356	12.35 361	79.96 352	60.86 353	40.35 352	80.68 354

pcd1.5k->3k		40.07 332	42.58 333	32.57 345	97.97 284	0.00 362	0.00 353	99.25 230	0.00 357	0.00 358	0.14 359	91.10 244	0.00 360	0.00 357	94.75 238	97.70 268

cdsmvs_eth3d_5k		24.41 334	32.55 334	0.00 347	0.00 361	0.00 362	0.00 353	99.39 169	0.00 357	0.00 358	100.00 1	93.55 203	0.00 360	0.00 357	0.00 358	0.00 358

wuyk23d		28.28 333	29.73 335	23.92 346	75.89 353	32.61 361	66.50 352	12.88 362	16.09 356	14.59 357	16.59 358	12.35 361	32.36 359	39.36 356	13.36 357	6.79 357

ab-mvs-re		8.33 335	11.11 336	0.00 347	0.00 361	0.00 362	0.00 353	0.00 363	0.00 357	0.00 358	100.00 1	0.00 365	0.00 360	0.00 357	0.00 358	0.00 358

pcd_1.5k_mvsjas		8.24 336	10.99 337	0.00 347	0.00 361	0.00 362	0.00 353	0.00 363	0.00 357	0.00 358	0.14 359	98.75 106	0.00 360	0.00 357	0.00 358	0.00 358

sosnet-low-res		0.01 337	0.02 338	0.00 347	0.00 361	0.00 362	0.00 353	0.00 363	0.00 357	0.00 358	0.14 359	0.00 365	0.00 360	0.00 357	0.00 358	0.00 358

sosnet		0.01 337	0.02 338	0.00 347	0.00 361	0.00 362	0.00 353	0.00 363	0.00 357	0.00 358	0.14 359	0.00 365	0.00 360	0.00 357	0.00 358	0.00 358

uncertanet		0.01 337	0.02 338	0.00 347	0.00 361	0.00 362	0.00 353	0.00 363	0.00 357	0.00 358	0.14 359	0.00 365	0.00 360	0.00 357	0.00 358	0.00 358

Regformer		0.01 337	0.02 338	0.00 347	0.00 361	0.00 362	0.00 353	0.00 363	0.00 357	0.00 358	0.14 359	0.00 365	0.00 360	0.00 357	0.00 358	0.00 358

uanet		0.01 337	0.02 338	0.00 347	0.00 361	0.00 362	0.00 353	0.00 363	0.00 357	0.00 358	0.14 359	0.00 365	0.00 360	0.00 357	0.00 358	0.00 358

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

test_part1								99.42 121				99.53 26			100.00 1	100.00 1

sam_mvs1												99.29 62				99.91 128

sam_mvs												99.33 51

semantic-postprocess				97.62 245	99.40 189	96.83 257		99.14 259	94.65 242	97.55 264	99.72 205	89.64 266	98.31 284	95.62 253	92.05 263	97.73 255

ambc				88.45 320	86.84 342	70.76 346	97.79 343	98.02 331		90.91 314	95.14 334	38.69 354	98.51 274	94.97 264	84.23 322	96.09 323

MTGPA								99.42 121

test_post1							99.32 298				88.24 347	99.33 51	99.59 176	98.31 187

test_post											89.05 345	99.49 37	99.59 176

patchmatchnet-post											97.79 312	99.41 47	99.54 191

GG-mvs-BLEND				99.59 124	99.54 163	99.49 114	99.17 318	99.52 76		99.96 88	99.68 217	100.00 1	99.33 213	99.71 101	99.99 88	99.96 107

MTMP								99.18 250

gm-plane-assit					99.52 171	97.26 245			95.86 212		100.00 1		99.43 205	98.76 167

test9_res														100.00 1	100.00 1	100.00 1

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_prior2														100.00 1	100.00 1	100.00 1

agg_prior					100.00 1	99.88 59		99.42 121		100.00 1			99.97 99

TestCases				98.99 168	99.93 88	97.35 240		99.40 155	97.08 159	99.09 184	99.98 141	93.37 204	99.95 120	96.94 231	99.84 111	99.68 193

test_prior4						99.93 33	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

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

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

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

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

testdata2													100.00 1	97.36 224

segment_acmp												99.55 24

testdata				99.66 116	99.99 45	98.97 157		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

testdata1							100.00 1		98.77 37

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

plane_prior7					99.00 220	94.78 287

plane_prior6					99.06 212	94.80 283						88.58 279

plane_prior5								99.40 155					99.55 188	99.79 91	95.57 217	97.76 218

plane_prior4											99.97 151

plane_prior3						94.79 286			99.03 16	99.08 186

plane_prior2							100.00 1		99.00 19

plane_prior1					99.02 215

plane_prior						94.80 283	100.00 1		99.03 16						95.58 213

n2								0.00 363

nn								0.00 363

door-mid								96.32 348

lessismore_v0				96.05 297	97.55 300	91.80 318		99.22 239		91.87 312	99.91 180	83.50 313	98.68 259	92.48 292	90.42 282	97.68 275

LGP-MVS_train				97.28 259	98.85 235	94.60 293		99.37 176	97.35 140	98.85 198	99.98 141	86.66 293	99.56 183	99.55 119	95.26 224	97.70 268

test11								99.42 121

door								96.13 349

HQP5-MVS						94.82 280

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

HQP3-MVS								99.40 155							95.58 213

HQP2-MVS												88.61 277

NP-MVS					99.07 208	94.81 282					99.97 151

MDTV_nov1_ep13_2view						99.24 137	99.56 280		96.31 202	99.96 88		98.86 100		98.92 158		99.89 141

ACMMP++_ref															94.58 243

ACMMP++															95.17 230

Test By Simon												99.10 79

ITE_SJBPF				96.84 282	98.96 226	93.49 304		98.12 326	98.12 74	98.35 231	99.97 151	84.45 305	99.56 183	95.63 252	95.25 226	97.49 299

DeepMVS_CX				89.98 319	98.90 229	71.46 345		99.18 250	97.61 123	96.92 277	99.83 191	86.07 297	99.83 150	96.02 244	97.65 201	98.65 210

High-resolution multi-view benchmark