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.

test_part2					100.00 1	99.99 1				100.00 1

v1.0		41.47 339	55.29 340	0.00 354	100.00 1	0.00 369	0.00 360	99.42 125	98.23 65	100.00 1	100.00 1	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

HSP-MVS		99.81 9	99.77 8	99.94 60	100.00 1	99.86 68	100.00 1	99.42 125	98.87 30	100.00 1	100.00 1	99.65 19	99.96 116	100.00 1	100.00 1	100.00 1

TSAR-MVS + MP.		99.82 7	99.77 8	99.99 4	100.00 1	99.96 10	100.00 1	99.43 118	99.05 12	100.00 1	100.00 1	99.45 41	99.99 84	100.00 1	100.00 1	100.00 1

TEST9					100.00 1	99.95 19	100.00 1	99.42 125	97.65 119	100.00 1	100.00 1	99.53 26	99.97 101

train_agg		99.71 32	99.63 39	99.97 24	100.00 1	99.95 19	100.00 1	99.42 125	97.70 109	100.00 1	100.00 1	99.51 29	99.97 101	100.00 1	100.00 1	100.00 1

test_8					100.00 1	99.91 39	100.00 1	99.42 125	97.70 109	100.00 1	100.00 1	99.51 29	99.98 97

agg_prior3		99.71 32	99.63 39	99.97 24	100.00 1	99.95 19	100.00 1	99.42 125	97.71 108	100.00 1	100.00 1	99.51 29	99.97 101	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 60	100.00 1	99.42 125	97.72 106	100.00 1	100.00 1	99.51 29	99.97 101	100.00 1	100.00 1	100.00 1

agg_prior					100.00 1	99.88 60		99.42 125		100.00 1			99.97 101

HFP-MVS		99.74 23	99.67 27	99.96 36	100.00 1	99.89 50	100.00 1	99.76 46	97.95 89	100.00 1	100.00 1	99.31 54	100.00 1	99.99 44	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 44	100.00 1	100.00 1

#test#		99.75 18	99.68 22	99.96 36	100.00 1	99.89 50	100.00 1	99.76 46	98.07 77	100.00 1	100.00 1	99.31 54	100.00 1	99.99 44	100.00 1	100.00 1

EI-MVSNet-Vis-set		99.70 36	99.64 35	99.87 82	100.00 1	99.64 106	99.98 196	99.44 109	98.35 60	99.99 78	100.00 1	99.04 83	99.96 116	99.98 58	100.00 1	100.00 1

Regformer-3		99.73 26	99.65 31	99.96 36	100.00 1	99.89 50	100.00 1	99.44 109	98.40 53	100.00 1	100.00 1	99.03 86	99.97 101	99.99 44	100.00 1	100.00 1

Regformer-4		99.73 26	99.65 31	99.95 47	100.00 1	99.89 50	100.00 1	99.44 109	98.40 53	100.00 1	100.00 1	99.03 86	99.97 101	99.99 44	100.00 1	100.00 1

Regformer-1		99.75 18	99.68 22	99.98 16	100.00 1	99.94 27	100.00 1	99.44 109	98.43 50	100.00 1	100.00 1	99.23 68	99.99 84	99.99 44	100.00 1	100.00 1

Regformer-2		99.75 18	99.68 22	99.97 24	100.00 1	99.94 27	100.00 1	99.44 109	98.42 52	100.00 1	100.00 1	99.22 69	99.99 84	99.99 44	100.00 1	100.00 1

XVS		99.79 12	99.73 14	99.98 16	100.00 1	99.94 27	100.00 1	99.75 50	98.67 41	100.00 1	100.00 1	99.16 76	100.00 1	100.00 1	100.00 1	100.00 1

test_prior3		99.81 9	99.78 6	99.90 73	100.00 1	99.75 86	100.00 1	99.73 55	98.82 34	100.00 1	100.00 1	99.47 38	99.97 101	100.00 1	100.00 1	100.00 1

X-MVStestdata		97.04 208	96.06 238	99.98 16	100.00 1	99.94 27	100.00 1	99.75 50	98.67 41	100.00 1	66.97 364	99.16 76	100.00 1	100.00 1	100.00 1	100.00 1

test_prior				99.90 73	100.00 1	99.75 86		99.73 55					99.97 101			100.00 1

新几何1				99.99 4	100.00 1	99.96 10		99.81 42	97.89 93	100.00 1	100.00 1	99.20 72	100.00 1	97.91 213	100.00 1	100.00 1

原ACMM1				99.93 63	100.00 1	99.80 81		99.66 71	98.18 66	100.00 1	100.00 1	99.43 43	100.00 1	99.50 129	100.00 1	100.00 1

MSLP-MVS++		99.89 1	99.85 2	99.99 4	100.00 1	99.96 10	100.00 1	99.95 15	99.11 6	100.00 1	100.00 1	99.60 20	100.00 1	100.00 1	100.00 1	100.00 1

APDe-MVS		99.84 6	99.78 6	99.99 4	100.00 1	99.98 5	100.00 1	99.44 109	99.06 10	100.00 1	100.00 1	99.56 24	99.99 84	100.00 1	100.00 1	100.00 1

ACMMPR		99.74 23	99.67 27	99.96 36	100.00 1	99.89 50	100.00 1	99.76 46	97.95 89	100.00 1	100.00 1	99.29 61	100.00 1	99.99 44	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 54	100.00 1	100.00 1	100.00 1	100.00 1

CDPH-MVS		99.73 26	99.64 35	99.99 4	100.00 1	99.97 8	100.00 1	99.42 125	98.02 80	100.00 1	100.00 1	99.32 53	99.99 84	100.00 1	100.00 1	100.00 1

abl_6		99.53 61	99.40 62	99.92 69	100.00 1	99.76 84	100.00 1	99.42 125	97.21 150	100.00 1	100.00 1	98.12 121	100.00 1	99.82 91	100.00 1	100.00 1

mPP-MVS		99.69 39	99.60 45	99.97 24	100.00 1	99.91 39	100.00 1	99.42 125	97.91 92	100.00 1	100.00 1	99.04 83	100.00 1	100.00 1	100.00 1	100.00 1

HPM-MVS		99.59 59	99.50 57	99.89 76	100.00 1	99.70 101	100.00 1	99.42 125	97.46 134	100.00 1	100.00 1	98.60 111	99.96 116	99.99 44	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
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 48	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 22	100.00 1	100.00 1	100.00 1	100.00 1

CP-MVS		99.67 46	99.58 49	99.95 47	100.00 1	99.84 72	100.00 1	99.42 125	97.77 103	100.00 1	100.00 1	99.07 80	100.00 1	100.00 1	100.00 1	100.00 1

CPTT-MVS		99.49 67	99.38 66	99.85 86	100.00 1	99.54 110	100.00 1	99.42 125	97.58 127	99.98 83	100.00 1	97.43 136	100.00 1	99.99 44	100.00 1	100.00 1

DP-MVS Recon		99.76 16	99.69 19	99.98 16	100.00 1	99.95 19	100.00 1	99.52 76	97.99 82	99.99 78	100.00 1	99.72 16	100.00 1	99.96 66	100.00 1	100.00 1

PAPM_NR		99.74 23	99.66 30	99.99 4	100.00 1	99.96 10	100.00 1	99.47 83	97.87 96	100.00 1	100.00 1	99.60 20	100.00 1	100.00 1	100.00 1	100.00 1

PAPR		99.76 16	99.68 22	99.99 4	100.00 1	99.96 10	100.00 1	99.47 83	98.16 67	100.00 1	100.00 1	99.51 29	100.00 1	100.00 1	100.00 1	100.00 1

PHI-MVS		99.50 65	99.39 64	99.82 90	100.00 1	99.45 120	100.00 1	99.94 18	96.38 200	100.00 1	100.00 1	98.18 120	100.00 1	100.00 1	100.00 1	100.00 1

PVSNet	94.91 18	99.30 89	99.25 76	99.44 139	100.00 1	98.32 190	100.00 1	99.86 39	98.04 79	100.00 1	100.00 1	96.10 172	100.00 1	99.55 121	99.73 114	100.00 1

MG-MVS		99.75 18	99.68 22	99.97 24	100.00 1	99.91 39	99.98 196	99.47 83	99.09 7	100.00 1	100.00 1	98.59 112	100.00 1	99.95 71	100.00 1	100.00 1

AdaColmap		99.44 72	99.26 75	99.95 47	100.00 1	99.86 68	99.70 268	99.99 10	98.53 47	99.90 122	100.00 1	95.34 185	100.00 1	99.92 74	100.00 1	100.00 1

PLC	98.56 2	99.70 36	99.74 13	99.58 131	100.00 1	98.79 166	100.00 1	99.54 75	98.58 46	99.96 90	100.00 1	99.59 22	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
SMA-MVS		99.69 39	99.59 46	99.98 16	99.99 45	99.93 32	100.00 1	99.43 118	97.50 132	100.00 1	100.00 1	99.43 43	100.00 1	100.00 1	100.00 1	100.00 1

ESAPD		99.79 12	99.73 14	99.99 4	99.99 45	99.98 5	100.00 1	99.42 125	98.91 26	100.00 1	100.00 1	99.22 69	100.00 1	100.00 1	100.00 1	100.00 1

CHOSEN 280x420		99.85 3	99.87 1	99.80 96	99.99 45	99.97 8	99.97 203	99.98 13	98.96 21	100.00 1	100.00 1	99.96 3	99.42 211	100.00 1	100.00 1	100.00 1

CANet		99.40 73	99.24 78	99.89 76	99.99 45	99.76 84	100.00 1	99.73 55	98.40 53	99.78 143	100.00 1	95.28 186	99.96 116	100.00 1	99.99 87	99.96 107

zzz-MVS		99.68 43	99.59 46	99.97 24	99.99 45	99.91 39	100.00 1	99.42 125	98.32 62	99.94 114	100.00 1	98.65 109	100.00 1	99.96 66	100.00 1	100.00 1

MTAPA		99.68 43	99.59 46	99.97 24	99.99 45	99.91 39	100.00 1	99.42 125	98.32 62	99.94 114	100.00 1	98.65 109	100.00 1	99.96 66	100.00 1	100.00 1

EI-MVSNet-UG-set		99.69 39	99.63 39	99.87 82	99.99 45	99.64 106	99.95 212	99.44 109	98.35 60	100.00 1	100.00 1	98.98 88	99.97 101	99.98 58	100.00 1	100.00 1

HPM-MVS++		99.82 7	99.76 10	99.99 4	99.99 45	99.98 5	100.00 1	99.83 40	98.88 28	99.96 90	100.00 1	99.21 71	100.00 1	100.00 1	100.00 1	99.99 89

旧先验1					99.99 45	99.88 60		99.82 41			100.00 1	99.27 65			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 60			100.00 1	100.00 1

testdata				99.66 118	99.99 45	98.97 161		99.73 55	97.96 88	100.00 1	100.00 1	99.42 45	100.00 1	99.28 146	100.00 1	100.00 1

1121		99.63 52	99.51 56	99.99 4	99.99 45	99.96 10	99.24 310	99.74 53	97.89 93	100.00 1	100.00 1	99.39 48	100.00 1	99.33 142	100.00 1	100.00 1

SD-MVS		99.81 9	99.75 12	99.99 4	99.99 45	99.96 10	100.00 1	99.42 125	99.01 18	100.00 1	100.00 1	99.33 50	100.00 1	100.00 1	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 48	99.55 55	99.97 24	99.99 45	99.91 39	100.00 1	99.48 82	97.54 129	100.00 1	100.00 1	98.97 89	99.99 84	99.98 58	100.00 1	100.00 1

MP-MVS		99.61 55	99.49 59	99.98 16	99.99 45	99.94 27	100.00 1	99.42 125	97.82 100	99.99 78	100.00 1	98.20 119	100.00 1	99.99 44	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 39	99.61 44	99.95 47	99.99 45	99.85 71	100.00 1	99.58 73	97.69 111	100.00 1	100.00 1	99.44 42	100.00 1	99.79 92	100.00 1	100.00 1

test12				99.95 47	99.99 45	99.89 50		99.42 125		100.00 1		99.24 67	99.97 101		100.00 1	100.00 1

TSAR-MVS + GP.		99.61 55	99.69 19	99.35 149	99.99 45	98.06 215	100.00 1	99.36 187	99.83 2	100.00 1	100.00 1	98.95 92	99.99 84	100.00 1	99.11 123	100.00 1

HPM-MVS_fast		99.60 58	99.49 59	99.91 70	99.99 45	99.78 83	100.00 1	99.42 125	97.09 158	100.00 1	100.00 1	98.95 92	99.96 116	99.98 58	100.00 1	100.00 1

EPNet		99.62 53	99.69 19	99.42 142	99.99 45	98.37 184	100.00 1	99.89 38	98.83 32	100.00 1	100.00 1	98.97 89	100.00 1	99.90 76	99.61 118	99.89 143
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
APD-MVS		99.68 43	99.58 49	99.97 24	99.99 45	99.96 10	100.00 1	99.42 125	97.53 130	100.00 1	100.00 1	99.27 65	99.97 101	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
CSCG		99.28 91	99.35 71	99.05 167	99.99 45	97.15 254	100.00 1	99.47 83	97.44 136	99.42 171	100.00 1	97.83 127	100.00 1	99.99 44	100.00 1	100.00 1

PatchMatch-RL		99.02 121	98.78 130	99.74 111	99.99 45	99.29 132	100.00 1	100.00 1	98.38 56	99.89 125	99.81 202	93.14 213	99.99 84	97.85 214	99.98 94	99.95 112

ACMMP		99.65 48	99.57 51	99.89 76	99.99 45	99.66 104	99.75 257	99.73 55	98.16 67	99.75 147	100.00 1	98.90 98	100.00 1	99.96 66	99.88 107	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
F-COLMAP		99.64 50	99.64 35	99.67 117	99.99 45	99.07 149	100.00 1	99.44 109	98.30 64	99.90 122	100.00 1	99.18 74	99.99 84	99.91 75	100.00 1	99.94 116

DeepPCF-MVS	98.03 4	98.54 157	99.72 16	94.98 312	99.99 45	84.94 338	100.00 1	99.42 125	99.98 1	100.00 1	100.00 1	98.11 122	100.00 1	100.00 1	100.00 1	100.00 1

DeepC-MVS_fast	98.92 1	99.75 18	99.67 27	99.99 4	99.99 45	99.96 10	99.73 262	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
LS3D		99.31 88	99.13 94	99.87 82	99.99 45	99.71 97	99.55 286	99.46 97	97.32 144	99.82 139	100.00 1	96.85 158	99.97 101	99.14 153	100.00 1	99.92 129

MP-MVS-pluss		99.61 55	99.50 57	99.97 24	99.98 73	99.92 36	100.00 1	99.42 125	97.53 130	99.77 144	100.00 1	98.77 105	100.00 1	99.99 44	100.00 1	99.99 89
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_Plus		99.67 46	99.57 51	99.97 24	99.98 73	99.92 36	100.00 1	99.42 125	97.83 98	100.00 1	100.00 1	98.89 99	100.00 1	99.98 58	100.00 1	100.00 1

PVSNet_BlendedMVS		98.71 146	98.62 145	98.98 174	99.98 73	99.60 108	100.00 1	100.00 1	97.23 147	100.00 1	99.03 279	96.57 163	99.99 84	100.00 1	94.75 242	97.35 313

PVSNet_Blended		99.48 69	99.36 69	99.83 89	99.98 73	99.60 108	100.00 1	100.00 1	97.79 102	100.00 1	100.00 1	96.57 163	99.99 84	100.00 1	99.88 107	99.90 138

114514_t		99.39 74	99.25 76	99.81 93	99.97 77	99.48 119	100.00 1	99.42 125	95.53 225	100.00 1	100.00 1	98.37 118	99.95 122	99.97 64	100.00 1	100.00 1

DP-MVS		98.86 137	98.54 152	99.81 93	99.97 77	99.45 120	99.52 289	99.40 159	94.35 255	98.36 236	100.00 1	96.13 171	99.97 101	99.12 155	100.00 1	100.00 1

API-MVS		99.72 29	99.70 18	99.79 100	99.97 77	99.37 127	99.96 206	99.94 18	98.48 48	100.00 1	100.00 1	98.92 96	100.00 1	100.00 1	100.00 1	100.00 1

CNLPA		99.72 29	99.65 31	99.91 70	99.97 77	99.72 96	100.00 1	99.47 83	98.43 50	99.88 126	100.00 1	99.14 78	100.00 1	99.97 64	100.00 1	100.00 1

MAR-MVS		99.49 67	99.36 69	99.89 76	99.97 77	99.66 104	99.74 258	99.95 15	97.89 93	100.00 1	100.00 1	96.71 161	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
MVS_111021_LR		99.70 36	99.65 31	99.88 81	99.96 82	99.70 101	100.00 1	99.97 14	98.96 21	100.00 1	100.00 1	97.93 125	99.95 122	99.99 44	100.00 1	100.00 1

MVS_0304		98.98 127	98.66 139	99.94 60	99.95 83	99.86 68	100.00 1	99.29 216	98.38 56	99.81 141	100.00 1	90.60 255	100.00 1	100.00 1	99.91 104	99.95 112

HyFIR lowres test		99.32 81	99.24 78	99.58 131	99.95 83	99.26 135	100.00 1	99.99 10	96.72 178	99.29 178	99.91 185	99.49 35	99.47 206	99.74 100	98.08 168	100.00 1

MVS_111021_HR		99.71 32	99.63 39	99.93 63	99.95 83	99.83 73	100.00 1	100.00 1	98.89 27	100.00 1	100.00 1	97.85 126	99.95 122	100.00 1	100.00 1	100.00 1

OMC-MVS		99.27 92	99.38 66	98.96 175	99.95 83	97.06 258	100.00 1	99.40 159	98.83 32	99.88 126	100.00 1	97.01 143	99.86 145	99.47 130	99.84 110	99.97 96

TAPA-MVS	96.40 10	97.64 186	97.37 191	98.45 198	99.94 87	95.70 277	100.00 1	99.40 159	97.65 119	99.53 165	100.00 1	99.31 54	99.66 177	80.48 339	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
COLMAP_ROB	97.10 7	98.29 168	98.17 168	98.65 191	99.94 87	97.39 242	99.30 306	99.40 159	95.64 220	97.75 264	100.00 1	92.69 218	99.95 122	98.89 163	99.92 103	98.62 215
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
AllTest		98.55 156	98.40 158	98.99 172	99.93 89	97.35 245	100.00 1	99.40 159	97.08 160	99.09 188	99.98 144	93.37 208	99.95 122	96.94 236	99.84 110	99.68 197

TestCases				98.99 172	99.93 89	97.35 245		99.40 159	97.08 160	99.09 188	99.98 144	93.37 208	99.95 122	96.94 236	99.84 110	99.68 197

DeepC-MVS	97.84 5	99.00 123	98.80 129	99.60 124	99.93 89	99.03 153	100.00 1	99.40 159	98.61 45	99.33 176	100.00 1	92.23 221	99.95 122	99.74 100	99.96 99	99.83 169
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
EPNet_dtu		98.53 158	98.23 166	99.43 141	99.92 92	99.01 157	99.96 206	99.47 83	98.80 36	99.96 90	99.96 163	98.56 113	99.30 218	87.78 328	99.68 115	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DELS-MVS		99.62 53	99.56 54	99.82 90	99.92 92	99.45 120	100.00 1	99.78 44	98.92 25	99.73 148	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
MSDG		98.90 135	98.63 144	99.70 113	99.92 92	99.25 137	100.00 1	99.37 181	95.71 219	99.40 175	100.00 1	96.58 162	99.95 122	96.80 243	99.94 102	99.91 130

tfpn_ndepth		99.52 62	99.39 64	99.89 76	99.90 95	99.83 73	100.00 1	99.72 61	97.95 89	99.96 90	99.98 144	99.94 4	99.85 149	99.17 152	97.91 174	100.00 1

CHOSEN 1792x2688		99.00 123	98.91 118	99.25 158	99.90 95	97.79 231	100.00 1	99.99 10	98.79 37	98.28 242	100.00 1	93.63 206	99.95 122	99.66 111	99.95 101	100.00 1

tfpn1000		99.47 70	99.34 73	99.87 82	99.89 97	99.80 81	100.00 1	99.72 61	97.83 98	99.96 90	99.98 144	99.94 4	99.82 153	98.87 165	97.87 177	100.00 1

CANet_DTU		99.02 121	98.90 121	99.41 143	99.88 98	98.71 169	100.00 1	99.29 216	98.84 31	100.00 1	100.00 1	94.02 202	100.00 1	98.08 206	99.96 99	99.52 205

PVSNet_0	93.57 19	96.41 240	95.74 253	98.41 200	99.84 99	95.22 280	100.00 1	100.00 1	98.08 76	97.55 271	99.78 206	84.40 312	100.00 1	100.00 1	81.99 331	100.00 1

0601test		99.51 63	99.37 68	99.95 47	99.82 100	99.90 45	100.00 1	99.47 83	97.48 133	100.00 1	100.00 1	99.80 6	100.00 1	99.98 58	97.75 189	99.94 116

PVSNet_Blended_VisFu		99.33 80	99.18 86	99.78 108	99.82 100	99.49 115	100.00 1	99.95 15	97.36 140	99.63 159	100.00 1	96.45 167	99.95 122	99.79 92	99.65 117	99.89 143

Anonymous202405211		97.87 180	97.53 186	98.90 179	99.81 102	96.70 266	99.35 302	99.46 97	92.98 292	98.83 206	99.99 142	90.63 254	100.00 1	99.70 104	97.03 210	100.00 1

tfpn111		99.24 99	99.00 102	99.95 47	99.81 102	99.87 63	100.00 1	99.94 18	97.13 154	99.83 130	99.96 163	97.01 143	100.00 1	99.54 124	97.77 187	99.97 96

conf200view11		99.25 96	99.01 100	99.95 47	99.81 102	99.87 63	100.00 1	99.94 18	97.13 154	99.83 130	99.96 163	97.01 143	100.00 1	99.59 115	97.85 179	99.97 96

thres100view900		99.25 96	99.01 100	99.95 47	99.81 102	99.87 63	100.00 1	99.94 18	97.13 154	99.83 130	99.96 163	97.01 143	100.00 1	99.59 115	97.85 179	99.98 91

tfpn200view9		99.26 94	99.03 98	99.96 36	99.81 102	99.89 50	100.00 1	99.94 18	97.23 147	99.83 130	99.96 163	97.04 139	100.00 1	99.59 115	97.85 179	99.98 91

view600		99.18 103	98.93 113	99.93 63	99.81 102	99.83 73	100.00 1	99.94 18	96.96 164	99.54 161	99.96 163	96.99 151	100.00 1	99.43 131	97.75 189	99.97 96

view800		99.18 103	98.93 113	99.93 63	99.81 102	99.83 73	100.00 1	99.94 18	96.96 164	99.54 161	99.96 163	96.99 151	100.00 1	99.43 131	97.75 189	99.97 96

conf0.05thres1000		99.18 103	98.93 113	99.93 63	99.81 102	99.83 73	100.00 1	99.94 18	96.96 164	99.54 161	99.96 163	96.99 151	100.00 1	99.43 131	97.75 189	99.97 96

tfpn		99.18 103	98.93 113	99.93 63	99.81 102	99.83 73	100.00 1	99.94 18	96.96 164	99.54 161	99.96 163	96.99 151	100.00 1	99.43 131	97.75 189	99.97 96

VNet		99.04 116	98.75 133	99.90 73	99.81 102	99.75 86	99.50 291	99.47 83	98.36 59	100.00 1	99.99 142	94.66 196	100.00 1	99.90 76	97.09 209	99.96 107

thres600view7		99.24 99	99.00 102	99.95 47	99.81 102	99.87 63	100.00 1	99.94 18	97.13 154	99.83 130	99.96 163	97.01 143	100.00 1	99.54 124	97.77 187	99.97 96

thres400		99.26 94	99.03 98	99.95 47	99.81 102	99.89 50	100.00 1	99.94 18	97.23 147	99.83 130	99.96 163	97.04 139	100.00 1	99.59 115	97.85 179	99.97 96

thres200		99.27 92	99.04 97	99.96 36	99.81 102	99.90 45	100.00 1	99.94 18	97.31 146	99.83 130	99.96 163	97.04 139	100.00 1	99.62 114	97.88 176	99.98 91

WTY-MVS		99.54 60	99.40 62	99.95 47	99.81 102	99.93 32	100.00 1	100.00 1	97.98 84	99.84 128	100.00 1	98.94 94	99.98 97	99.86 81	98.21 161	99.94 116

HY-MVS	96.53 9	99.50 65	99.35 71	99.96 36	99.81 102	99.93 32	99.64 279	100.00 1	97.97 86	99.84 128	99.85 193	98.94 94	99.99 84	99.86 81	98.23 160	99.95 112

Anonymous20231211		96.29 248	95.70 255	98.07 232	99.80 117	97.49 238	99.15 327	99.40 159	89.11 326	97.75 264	99.45 252	88.93 280	98.98 231	98.26 195	89.47 301	97.73 260

LFMVS		97.42 192	96.62 210	99.81 93	99.80 117	99.50 112	99.16 325	99.56 74	94.48 252	100.00 1	100.00 1	79.35 337	100.00 1	99.89 78	97.37 206	99.94 116

RPSCF		97.37 193	98.24 164	94.76 314	99.80 117	84.57 339	99.99 178	99.05 303	94.95 240	99.82 139	100.00 1	94.03 201	100.00 1	98.15 199	98.38 149	99.70 195

Anonymous20240529		96.93 214	96.22 228	99.05 167	99.79 120	97.30 249	99.16 325	99.47 83	88.51 329	98.69 215	100.00 1	83.50 319	100.00 1	99.83 86	97.02 211	99.83 169

conf0.01		99.32 81	99.16 87	99.80 96	99.79 120	99.73 89	100.00 1	99.71 63	97.66 112	99.71 151	100.00 1	99.78 7	99.70 170	98.15 199	97.67 197	99.97 96

conf0.002		99.32 81	99.16 87	99.80 96	99.79 120	99.73 89	100.00 1	99.71 63	97.66 112	99.71 151	100.00 1	99.78 7	99.70 170	98.15 199	97.67 197	99.97 96

thresconf0.02		99.32 81	99.16 87	99.79 100	99.79 120	99.73 89	100.00 1	99.71 63	97.66 112	99.71 151	100.00 1	99.78 7	99.70 170	98.15 199	97.67 197	99.94 116

tfpn_n400		99.32 81	99.16 87	99.79 100	99.79 120	99.73 89	100.00 1	99.71 63	97.66 112	99.71 151	100.00 1	99.78 7	99.70 170	98.15 199	97.67 197	99.94 116

tfpnconf		99.32 81	99.16 87	99.79 100	99.79 120	99.73 89	100.00 1	99.71 63	97.66 112	99.71 151	100.00 1	99.78 7	99.70 170	98.15 199	97.67 197	99.94 116

tfpnview11		99.32 81	99.16 87	99.79 100	99.79 120	99.73 89	100.00 1	99.71 63	97.66 112	99.71 151	100.00 1	99.78 7	99.70 170	98.15 199	97.67 197	99.94 116

PS-MVSNAJ		99.64 50	99.57 51	99.85 86	99.78 127	99.81 79	99.95 212	99.42 125	98.38 56	100.00 1	100.00 1	98.75 106	100.00 1	99.88 79	99.99 87	99.74 190

PCF-MVS	98.23 3	98.69 149	98.37 160	99.62 119	99.78 127	99.02 154	99.23 316	99.06 301	96.43 195	98.08 248	100.00 1	94.72 195	99.95 122	98.16 198	99.91 104	99.90 138
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
Effi-MVS+-dtu		98.51 160	98.86 123	97.47 259	99.77 129	94.21 307	100.00 1	98.94 311	97.61 123	99.91 121	98.75 299	95.89 174	99.51 202	99.36 139	99.48 120	98.68 212

mvs-test1		98.89 136	98.99 105	98.60 193	99.77 129	95.96 272	100.00 1	98.94 311	97.61 123	99.93 119	99.92 182	95.89 174	99.93 135	99.36 139	99.50 119	99.90 138

SteuartSystems-ACMMP		99.78 14	99.71 17	99.98 16	99.76 131	99.95 19	100.00 1	99.42 125	98.69 39	100.00 1	100.00 1	99.52 27	99.99 84	100.00 1	100.00 1	100.00 1
Skip Steuart: Steuart Systems R&D Blog.
sss		99.45 71	99.34 73	99.80 96	99.76 131	99.50 112	100.00 1	99.91 37	97.72 106	99.98 83	99.94 179	98.45 116	100.00 1	99.53 127	98.75 131	99.89 143

canonicalmvs		99.03 117	98.73 134	99.94 60	99.75 133	99.95 19	100.00 1	99.30 212	97.64 121	100.00 1	100.00 1	95.22 188	99.97 101	99.76 98	96.90 214	99.91 130

alignmvs		99.38 75	99.21 81	99.91 70	99.73 134	99.92 36	100.00 1	99.51 80	97.61 123	100.00 1	100.00 1	99.06 81	99.93 135	99.83 86	97.12 208	99.90 138

ab-mvs		98.42 163	98.02 174	99.61 120	99.71 135	99.00 158	99.10 331	99.64 72	96.70 179	99.04 193	99.81 202	90.64 253	99.98 97	99.64 112	97.93 173	99.84 166

xiu_mvs_v2_base		99.51 63	99.41 61	99.82 90	99.70 136	99.73 89	99.92 220	99.40 159	98.15 69	100.00 1	100.00 1	98.50 115	100.00 1	99.85 83	99.13 122	99.74 190

tpmvs		98.59 152	98.38 159	99.23 159	99.69 137	97.90 224	99.31 305	99.47 83	94.52 250	99.68 157	99.28 260	97.64 130	99.89 141	97.71 217	98.17 164	99.89 143

Test_1112_low_res		98.83 139	98.60 147	99.51 135	99.69 137	98.75 167	99.99 178	99.14 267	96.81 172	98.84 204	99.06 268	97.45 134	99.89 141	98.66 174	97.75 189	99.89 143

1112_ss		98.91 134	98.71 136	99.51 135	99.69 137	98.75 167	99.99 178	99.15 263	96.82 171	98.84 204	100.00 1	97.45 134	99.89 141	98.66 174	97.75 189	99.89 143

Vis-MVSNet		98.52 159	98.25 163	99.34 150	99.68 140	98.55 176	99.68 274	99.41 157	97.34 143	99.94 114	100.00 1	90.38 260	99.70 170	99.03 159	98.84 129	99.76 185
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
xiu_mvs_v1_base_debu		99.35 77	99.21 81	99.79 100	99.67 141	99.71 97	99.78 247	99.36 187	98.13 71	100.00 1	100.00 1	97.00 148	100.00 1	99.83 86	99.07 124	99.66 199

xiu_mvs_v1_base		99.35 77	99.21 81	99.79 100	99.67 141	99.71 97	99.78 247	99.36 187	98.13 71	100.00 1	100.00 1	97.00 148	100.00 1	99.83 86	99.07 124	99.66 199

xiu_mvs_v1_base_debi		99.35 77	99.21 81	99.79 100	99.67 141	99.71 97	99.78 247	99.36 187	98.13 71	100.00 1	100.00 1	97.00 148	100.00 1	99.83 86	99.07 124	99.66 199

IB-MVS	96.24 12	97.54 191	96.95 198	99.33 151	99.67 141	98.10 212	100.00 1	99.47 83	97.42 138	99.26 179	99.69 217	98.83 101	99.89 141	99.43 131	78.77 339	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
MVSTER		98.58 153	98.52 153	98.77 187	99.65 145	99.68 103	100.00 1	99.29 216	95.63 221	98.65 218	99.80 205	99.78 7	98.88 242	98.59 182	95.31 226	97.73 260

FMVSNet3		97.30 196	96.95 198	98.37 203	99.65 145	99.25 137	99.71 266	99.28 224	94.23 258	98.53 228	98.91 292	93.30 210	98.11 299	95.31 263	93.60 251	97.73 260

cascas		98.43 162	98.07 171	99.50 137	99.65 145	99.02 154	100.00 1	99.22 246	94.21 260	99.72 149	99.98 144	92.03 224	99.93 135	99.68 107	98.12 166	99.54 204

IS-MVSNet		99.08 111	98.91 118	99.59 127	99.65 145	99.38 125	99.78 247	99.24 238	96.70 179	99.51 166	100.00 1	98.44 117	99.52 200	98.47 186	98.39 146	99.88 156

Vis-MVSNet (Re-imp)		98.99 125	98.89 122	99.29 154	99.64 149	98.89 163	99.98 196	99.31 210	96.74 175	99.48 168	100.00 1	98.11 122	99.10 223	98.39 188	98.34 153	99.89 143

Fast-Effi-MVS+		98.40 165	98.02 174	99.55 134	99.63 150	99.06 151	100.00 1	99.15 263	95.07 237	99.42 171	99.95 175	93.26 211	99.73 166	97.44 225	98.24 159	99.87 163

TESTMET0.1,1		99.08 111	98.96 107	99.44 139	99.63 150	99.38 125	100.00 1	99.45 100	95.53 225	99.48 168	100.00 1	99.71 17	99.02 227	96.84 240	99.99 87	99.91 130

MVS_Test		98.93 133	98.65 142	99.77 110	99.62 152	99.50 112	99.99 178	99.19 254	95.52 227	99.96 90	99.86 191	96.54 165	99.98 97	98.65 176	98.48 138	99.82 173

BH-w/o		98.82 140	98.81 128	98.88 181	99.62 152	96.71 265	100.00 1	99.28 224	97.09 158	98.81 207	100.00 1	94.91 194	99.96 116	99.54 124	100.00 1	99.96 107

tpmrst		98.98 127	98.93 113	99.14 164	99.61 154	97.74 232	99.52 289	99.36 187	96.05 210	99.98 83	99.64 230	99.04 83	99.86 145	98.94 161	98.19 163	99.82 173

BH-RMVSNet		98.46 161	98.08 170	99.59 127	99.61 154	99.19 143	100.00 1	99.28 224	97.06 162	98.95 196	100.00 1	88.99 278	99.82 153	98.83 168	100.00 1	99.77 183

Effi-MVS+		98.58 153	98.24 164	99.61 120	99.60 156	99.26 135	97.85 348	99.10 280	96.22 206	99.97 87	99.89 187	93.75 204	99.77 162	99.43 131	98.34 153	99.81 175

tpmp4_e23		98.71 146	98.66 139	98.84 183	99.60 156	96.98 260	99.83 235	99.35 195	94.29 256	99.90 122	99.50 248	99.17 75	99.73 166	98.22 196	98.13 165	99.81 175

EPMVS		99.25 96	99.13 94	99.60 124	99.60 156	99.20 142	99.60 282	100.00 1	96.93 169	99.92 120	99.36 255	99.05 82	99.71 169	98.77 170	98.94 128	99.90 138

XVG-OURS-SEG-HR		98.27 170	98.31 162	98.14 225	99.59 159	95.92 274	100.00 1	99.36 187	98.48 48	99.21 181	100.00 1	89.27 275	99.94 133	99.76 98	99.17 121	98.56 216

BH-untuned		98.64 150	98.65 142	98.60 193	99.59 159	96.17 271	100.00 1	99.28 224	96.67 183	98.41 235	100.00 1	94.52 197	99.83 151	99.41 137	100.00 1	99.81 175

TR-MVS		98.14 173	97.74 181	99.33 151	99.59 159	98.28 192	99.27 307	99.21 251	96.42 197	99.15 186	99.94 179	88.87 281	99.79 161	98.88 164	98.29 156	99.93 126

Fast-Effi-MVS+-dtu		98.38 166	98.56 150	97.82 248	99.58 162	94.44 304	100.00 1	99.16 262	96.75 174	99.51 166	99.63 234	95.03 191	99.60 178	97.71 217	99.67 116	99.42 207

XVG-OURS		98.30 167	98.36 161	98.13 228	99.58 162	95.91 275	100.00 1	99.36 187	98.69 39	99.23 180	100.00 1	91.20 243	99.92 138	99.34 141	97.82 183	98.56 216

mvs_anonymous		98.80 142	98.60 147	99.38 147	99.57 164	99.24 139	100.00 1	99.21 251	95.87 213	98.92 197	99.82 199	96.39 168	99.03 226	99.13 154	98.50 136	99.88 156

PMMVS		99.12 108	98.97 106	99.58 131	99.57 164	98.98 159	100.00 1	99.30 212	97.14 153	99.96 90	100.00 1	96.53 166	99.82 153	99.70 104	98.49 137	99.94 116

DWT-MVSNet_test		99.22 101	99.22 80	99.22 160	99.56 166	97.98 219	99.89 226	99.39 174	97.20 151	99.96 90	100.00 1	99.52 27	99.82 153	99.11 156	98.34 153	99.87 163

GG-mvs-BLEND				99.59 127	99.54 167	99.49 115	99.17 324	99.52 76		99.96 90	99.68 222	100.00 1	99.33 217	99.71 102	99.99 87	99.96 107

diffmvs		98.82 140	98.55 151	99.61 120	99.54 167	99.08 148	100.00 1	99.22 246	95.48 231	99.96 90	99.77 208	96.00 173	99.82 153	98.63 178	98.37 150	99.93 126

casdiffmvs1		99.06 113	98.84 124	99.70 113	99.54 167	99.41 123	100.00 1	99.23 242	96.30 204	99.96 90	99.92 182	96.92 157	99.81 159	99.25 147	98.48 138	99.89 143

PatchFormer-LS_test		99.14 107	99.12 96	99.19 161	99.54 167	97.86 229	99.66 277	99.40 159	96.94 168	99.96 90	100.00 1	99.29 61	99.84 150	98.96 160	98.29 156	99.88 156

UGNet		98.41 164	98.11 169	99.31 153	99.54 167	98.55 176	99.18 319	100.00 1	98.64 44	99.79 142	99.04 274	87.61 291	100.00 1	99.30 145	99.89 106	99.40 208
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
casdiffmvs		98.96 129	98.71 136	99.68 116	99.53 172	99.34 129	99.99 178	99.17 261	96.11 209	99.96 90	99.92 182	96.33 169	99.81 159	99.06 158	98.36 151	99.89 143

GBi-Net		96.07 261	95.80 249	96.89 282	99.53 172	94.87 285	99.18 319	99.27 231	93.71 269	98.53 228	98.81 296	84.23 314	98.07 305	95.31 263	93.60 251	97.72 266

test1		96.07 261	95.80 249	96.89 282	99.53 172	94.87 285	99.18 319	99.27 231	93.71 269	98.53 228	98.81 296	84.23 314	98.07 305	95.31 263	93.60 251	97.72 266

dp		98.72 145	98.61 146	99.03 170	99.53 172	97.39 242	99.45 293	99.39 174	95.62 222	99.94 114	99.52 246	98.83 101	99.82 153	96.77 245	98.42 143	99.89 143

FMVSNet2		96.22 252	95.60 260	98.06 236	99.53 172	98.33 187	99.45 293	99.27 231	93.71 269	98.03 251	98.84 295	84.23 314	98.10 302	93.97 285	93.40 254	97.73 260

MDTV_nov1_ep13			98.94 112		99.53 172	98.36 185	99.39 298	99.46 97	96.54 190	99.99 78	99.63 234	98.92 96	99.86 145	98.30 193	98.71 132

gm-plane-assit					99.52 178	97.26 251			95.86 215		100.00 1		99.43 209	98.76 171

UA-Net		99.06 113	98.83 125	99.74 111	99.52 178	99.40 124	99.08 333	99.45 100	97.64 121	99.83 130	100.00 1	95.80 177	99.94 133	98.35 190	99.80 113	99.88 156

VDD-MVS		96.58 233	95.99 241	98.34 206	99.52 178	95.33 278	99.18 319	99.38 178	96.64 184	99.77 144	100.00 1	72.51 348	100.00 1	100.00 1	96.94 213	99.70 195

ADS-MVSNet2		98.28 169	98.51 154	97.62 252	99.51 181	95.03 284	99.24 310	99.41 157	95.52 227	99.96 90	99.70 215	97.57 132	97.94 311	97.11 233	98.54 134	99.88 156

ADS-MVSNet		98.70 148	98.51 154	99.28 155	99.51 181	98.39 181	99.24 310	99.44 109	95.52 227	99.96 90	99.70 215	97.57 132	99.58 182	97.11 233	98.54 134	99.88 156

EPP-MVSNet		99.10 110	99.00 102	99.40 144	99.51 181	98.68 171	99.92 220	99.43 118	95.47 232	99.65 158	100.00 1	99.51 29	99.76 163	99.53 127	98.00 170	99.75 186

testpf		97.02 210	96.87 201	97.44 260	99.50 184	95.18 281	95.70 353	99.33 202	91.35 305	98.00 255	99.22 262	96.29 170	98.49 283	94.42 276	98.07 169	98.67 213

tpm cat1		98.05 175	97.76 180	98.92 178	99.50 184	97.10 257	99.77 251	99.30 212	90.20 313	99.72 149	98.71 301	97.71 128	99.86 145	96.75 247	98.20 162	99.81 175

PatchmatchNet		99.03 117	98.96 107	99.26 157	99.49 186	98.33 187	99.38 299	99.45 100	96.64 184	99.96 90	99.58 240	99.49 35	99.50 203	97.63 219	99.00 127	99.93 126
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
CDS-MVSNet		98.96 129	98.95 111	99.01 171	99.48 187	98.36 185	99.93 218	99.37 181	96.79 173	99.31 177	99.83 196	99.77 14	98.91 236	98.07 207	97.98 171	99.77 183
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MVSFormer		98.94 132	98.82 126	99.28 155	99.45 188	99.49 115	100.00 1	99.13 272	95.46 233	99.97 87	100.00 1	96.76 159	98.59 274	98.63 178	100.00 1	99.74 190

lupinMVS		99.29 90	99.16 87	99.69 115	99.45 188	99.49 115	100.00 1	99.15 263	97.45 135	99.97 87	100.00 1	96.76 159	99.76 163	99.67 109	100.00 1	99.81 175

TAMVS		98.76 143	98.73 134	98.86 182	99.44 190	97.69 233	99.57 284	99.34 200	96.57 188	99.12 187	99.81 202	98.83 101	99.16 221	97.97 212	97.91 174	99.73 194

tpm2		98.64 150	98.58 149	98.81 186	99.42 191	97.12 255	99.69 272	99.37 181	93.63 277	99.94 114	99.67 223	98.96 91	99.47 206	98.62 181	97.95 172	99.83 169

gg-mvs-nofinetune		96.95 213	96.10 236	99.50 137	99.41 192	99.36 128	99.07 335	99.52 76	83.69 343	99.96 90	83.60 359	100.00 1	99.20 220	99.68 107	99.99 87	99.96 107

Patchmatch-test1		98.23 172	97.91 177	99.17 162	99.41 192	98.25 198	99.99 178	99.45 100	96.91 170	99.76 146	99.69 217	89.65 270	99.37 214	97.55 221	98.79 130	99.89 143

CostFormer		98.84 138	98.77 131	99.04 169	99.41 192	97.58 237	99.67 275	99.35 195	94.66 246	99.96 90	99.36 255	99.28 64	99.74 165	99.41 137	97.81 184	99.81 175

IterMVS		96.76 221	96.46 217	97.63 250	99.41 192	96.89 261	99.99 178	99.13 272	94.74 244	97.59 270	99.66 225	89.63 272	98.28 291	95.71 255	92.31 265	97.72 266
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
semantic-postprocess				97.62 252	99.40 196	96.83 263		99.14 267	94.65 247	97.55 271	99.72 210	89.64 271	98.31 290	95.62 259	92.05 268	97.73 260

test-LLR		99.03 117	98.91 118	99.40 144	99.40 196	99.28 133	100.00 1	99.45 100	96.70 179	99.42 171	99.12 264	99.31 54	99.01 228	96.82 241	99.99 87	99.91 130

test-mter		98.96 129	98.82 126	99.40 144	99.40 196	99.28 133	100.00 1	99.45 100	95.44 235	99.42 171	99.12 264	99.70 18	99.01 228	96.82 241	99.99 87	99.91 130

FMVSNet5		95.32 279	95.43 267	94.99 311	99.39 199	92.99 318	99.25 309	99.24 238	90.45 310	97.44 274	98.45 311	95.78 178	94.39 341	87.02 329	91.88 270	97.59 302

MIMVSNet		97.06 207	96.73 206	98.05 237	99.38 200	96.64 268	98.47 344	99.35 195	93.41 282	99.48 168	98.53 309	89.66 269	97.70 315	94.16 282	98.11 167	99.80 182

IterMVS-LS		97.56 189	97.44 187	97.92 246	99.38 200	97.90 224	99.89 226	99.10 280	94.41 253	98.32 239	99.54 245	97.21 137	98.11 299	97.50 224	91.62 272	97.75 226
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MVS-HIRNet		94.12 286	92.73 295	98.29 210	99.33 202	95.95 273	99.38 299	99.19 254	74.54 350	98.26 244	86.34 355	86.07 303	99.06 225	91.60 303	99.87 109	99.85 165

CR-MVSNet		98.02 177	97.71 184	98.93 176	99.31 203	98.86 164	99.13 329	99.00 309	96.53 191	99.96 90	98.98 285	96.94 155	98.10 302	91.18 305	98.40 144	99.84 166

Patchmtry		96.81 216	96.37 219	98.14 225	99.31 203	98.55 176	98.91 338	99.00 309	90.45 310	97.92 257	98.98 285	96.94 155	98.12 297	94.27 279	91.53 273	97.75 226

RPMNet		95.10 281	93.82 284	98.93 176	99.31 203	98.86 164	99.13 329	99.38 178	79.82 348	99.96 90	95.13 342	95.69 182	98.10 302	77.54 346	98.40 144	99.84 166

VDDNet		96.39 243	95.55 261	98.90 179	99.27 206	97.45 239	99.15 327	99.92 36	91.28 306	99.98 83	100.00 1	73.55 346	100.00 1	99.85 83	96.98 212	99.24 209

LCM-MVSNet-Re		96.52 234	97.21 195	94.44 315	99.27 206	85.80 337	99.85 233	96.61 355	95.98 211	92.75 319	98.48 310	93.97 203	97.55 316	99.58 119	98.43 142	99.98 91

GA-MVS		97.72 184	97.27 193	99.06 165	99.24 208	97.93 223	100.00 1	99.24 238	95.80 218	98.99 195	99.64 230	89.77 268	99.36 215	95.12 267	97.62 204	99.89 143

jason		99.11 109	98.96 107	99.59 127	99.17 209	99.31 131	100.00 1	99.13 272	97.38 139	99.83 130	100.00 1	95.54 184	99.72 168	99.57 120	99.97 97	99.74 190
jason: jason.
tpm		98.24 171	98.22 167	98.32 208	99.13 210	95.79 276	99.53 288	99.12 278	95.20 236	99.96 90	99.36 255	97.58 131	99.28 219	97.41 227	96.67 215	99.88 156

EI-MVSNet		97.98 178	97.93 176	98.16 224	99.11 211	97.84 230	99.74 258	99.29 216	94.39 254	98.65 218	100.00 1	97.21 137	98.88 242	97.62 220	95.31 226	97.75 226

CVMVSNet		98.56 155	98.47 156	98.82 184	99.11 211	97.67 234	99.74 258	99.47 83	97.57 128	99.06 192	100.00 1	95.72 181	98.97 233	98.21 197	97.33 207	99.83 169

test0.0.03 1		98.12 174	98.03 173	98.39 201	99.11 211	98.07 214	100.00 1	99.93 32	96.70 179	96.91 286	99.95 175	99.31 54	98.19 292	91.93 301	98.44 141	98.91 210

Patchmatch-test		97.83 182	97.42 188	99.06 165	99.08 214	97.66 235	98.66 341	99.21 251	93.65 276	98.25 245	99.58 240	99.47 38	99.57 183	90.25 316	98.59 133	99.95 112

HQP-NCC					99.07 215		100.00 1		99.04 13	99.17 182

ACMP_Plane					99.07 215		100.00 1		99.04 13	99.17 182

NP-MVS					99.07 215	94.81 290					99.97 154

HQP-MVS		97.73 183	97.85 178	97.39 261	99.07 215	94.82 288	100.00 1	99.40 159	99.04 13	99.17 182	99.97 154	88.61 283	99.57 183	99.79 92	95.58 217	97.77 220

plane_prior6					99.06 219	94.80 291						88.58 285

ACMH+	96.20 13	96.49 238	96.33 222	97.00 275	99.06 219	93.80 310	99.81 242	99.31 210	97.32 144	95.89 302	99.97 154	82.62 323	99.54 195	98.34 191	94.63 245	97.65 292

PatchT		95.90 267	94.95 280	98.75 188	99.03 221	98.39 181	99.08 333	99.32 205	85.52 336	99.96 90	94.99 344	97.94 124	98.05 309	80.20 340	98.47 140	99.81 175

plane_prior1					99.02 222

QAPM		98.99 125	98.66 139	99.96 36	99.01 223	99.87 63	99.88 229	99.93 32	97.99 82	98.68 216	100.00 1	93.17 212	100.00 1	99.32 144	100.00 1	100.00 1

PAPM		99.78 14	99.76 10	99.85 86	99.01 223	99.95 19	100.00 1	99.75 50	99.37 3	99.99 78	100.00 1	99.76 15	99.60 178	100.00 1	100.00 1	100.00 1

ACMM	97.17 6	97.37 193	97.40 189	97.29 265	99.01 223	94.64 300	100.00 1	99.25 235	98.07 77	98.44 234	99.98 144	87.38 293	99.55 192	99.25 147	95.19 233	97.69 279
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CLD-MVS		97.64 186	97.74 181	97.36 263	99.01 223	94.76 296	100.00 1	99.34 200	99.30 4	99.00 194	99.97 154	87.49 292	99.57 183	99.96 66	95.58 217	97.75 226
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
MVS		99.22 101	98.96 107	99.98 16	99.00 227	99.95 19	99.24 310	99.94 18	98.14 70	98.88 200	100.00 1	95.63 183	100.00 1	99.85 83	100.00 1	100.00 1

HQP_MVS		97.71 185	97.82 179	97.37 262	99.00 227	94.80 291	100.00 1	99.40 159	99.00 19	99.08 190	99.97 154	88.58 285	99.55 192	99.79 92	95.57 221	97.76 222

plane_prior7					99.00 227	94.78 295

3Dnovator+	95.58 15	99.03 117	98.71 136	99.96 36	98.99 230	99.89 50	100.00 1	99.51 80	98.96 21	98.32 239	100.00 1	92.78 216	100.00 1	99.87 80	100.00 1	100.00 1

testgi		96.18 254	95.93 244	96.93 280	98.98 231	94.20 308	100.00 1	99.07 293	97.16 152	96.06 299	99.86 191	84.08 317	97.79 313	90.38 313	97.80 185	98.81 211

ACMP	97.00 8	97.19 199	97.16 197	97.27 268	98.97 232	94.58 303	100.00 1	99.32 205	97.97 86	97.45 273	99.98 144	85.79 307	99.56 187	99.70 104	95.24 231	97.67 285
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ITE_SJBPF				96.84 290	98.96 233	93.49 312		98.12 334	98.12 74	98.35 237	99.97 154	84.45 311	99.56 187	95.63 258	95.25 230	97.49 306

ACMH	96.25 11	96.77 217	96.62 210	97.21 269	98.96 233	94.43 305	99.64 279	99.33 202	97.43 137	96.55 294	99.97 154	83.52 318	99.54 195	99.07 157	95.13 236	97.66 287
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LP		95.89 269	95.35 270	97.51 256	98.92 235	95.15 282	98.66 341	99.39 174	89.43 324	97.22 279	99.03 279	94.37 199	97.74 314	83.71 335	97.44 205	99.63 202

DeepMVS_CX				89.98 326	98.90 236	71.46 352		99.18 257	97.61 123	96.92 284	99.83 196	86.07 303	99.83 151	96.02 250	97.65 203	98.65 214

OpenMVS	95.20 17	98.76 143	98.41 157	99.78 108	98.89 237	99.81 79	99.99 178	99.76 46	98.02 80	98.02 253	100.00 1	91.44 239	100.00 1	99.63 113	99.97 97	99.55 203

1314		99.38 75	99.19 85	99.96 36	98.88 238	99.89 50	99.24 310	99.93 32	98.88 28	98.79 208	100.00 1	97.02 142	100.00 1	100.00 1	100.00 1	100.00 1

JIA-IIPM		97.09 204	96.34 221	99.36 148	98.88 238	98.59 174	99.81 242	99.43 118	84.81 340	99.96 90	90.34 351	98.55 114	99.52 200	97.00 235	98.28 158	99.98 91

FMVSNet1		94.45 283	93.63 287	96.89 282	98.87 240	94.87 285	99.18 319	99.27 231	90.95 309	97.31 276	98.81 296	72.89 347	98.07 305	92.61 295	92.81 260	97.72 266

3Dnovator	95.63 14	99.06 113	98.76 132	99.96 36	98.86 241	99.90 45	99.98 196	99.93 32	98.95 24	98.49 232	100.00 1	92.91 215	100.00 1	99.71 102	100.00 1	100.00 1

LPG-MVS_test		97.31 195	97.32 192	97.28 266	98.85 242	94.60 301	100.00 1	99.37 181	97.35 141	98.85 202	99.98 144	86.66 299	99.56 187	99.55 121	95.26 228	97.70 274

LGP-MVS_train				97.28 266	98.85 242	94.60 301		99.37 181	97.35 141	98.85 202	99.98 144	86.66 299	99.56 187	99.55 121	95.26 228	97.70 274

TinyColmap		95.50 276	95.12 276	96.64 296	98.69 244	93.00 317	99.40 297	97.75 344	96.40 199	96.14 298	99.87 189	79.47 336	99.50 203	93.62 288	94.72 244	97.40 311

XXY-MVS		97.14 203	96.63 209	98.67 190	98.65 245	98.92 162	99.54 287	99.29 216	95.57 224	97.63 267	99.83 196	87.79 290	99.35 216	98.39 188	92.95 259	97.75 226

VPA-MVSNet		97.03 209	96.43 218	98.82 184	98.64 246	99.32 130	99.38 299	99.47 83	96.73 177	98.91 199	98.94 290	87.00 297	99.40 212	99.23 149	89.59 299	97.76 222

VPNet		96.41 240	95.76 252	98.33 207	98.61 247	98.30 191	99.48 292	99.45 100	96.98 163	98.87 201	99.88 188	81.57 327	98.93 234	99.22 151	87.82 316	97.76 222

USDC		95.90 267	95.70 255	96.50 299	98.60 248	92.56 322	100.00 1	98.30 329	97.77 103	96.92 284	99.94 179	81.25 331	99.45 208	93.54 291	94.96 241	97.49 306

tfpnnormal		96.36 244	95.69 258	98.37 203	98.55 249	98.71 169	99.69 272	99.45 100	93.16 290	96.69 293	99.71 212	88.44 287	98.99 230	94.17 280	91.38 275	97.41 310

LTVRE_ROB	95.29 16	96.32 247	96.10 236	96.99 276	98.55 249	93.88 309	99.45 293	99.28 224	94.50 251	96.46 295	99.52 246	84.86 310	99.48 205	97.26 230	95.03 239	97.59 302
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
FIs		97.95 179	97.73 183	98.62 192	98.53 251	99.24 139	100.00 1	99.43 118	96.74 175	97.87 259	99.82 199	95.27 187	98.89 239	98.78 169	93.07 257	97.74 250

UniMVSNet (Re)		97.29 197	96.85 202	98.59 195	98.49 252	99.13 146	100.00 1	99.42 125	96.52 192	98.24 246	98.90 293	94.93 193	98.89 239	97.54 223	87.61 317	97.75 226

WR-MVS		97.09 204	96.64 208	98.46 197	98.43 253	99.09 147	99.97 203	99.33 202	95.62 222	97.76 261	99.67 223	91.17 244	98.56 278	98.49 185	89.28 303	97.74 250

XVG-ACMP-BASELINE		96.60 232	96.52 213	96.84 290	98.41 254	93.29 315	99.99 178	99.32 205	97.76 105	98.51 231	99.29 259	81.95 325	99.54 195	98.40 187	95.03 239	97.68 281

UniMVSNet_NR-MVSNet		97.16 201	96.80 203	98.22 219	98.38 255	98.41 179	100.00 1	99.45 100	96.14 208	97.76 261	99.64 230	95.05 190	98.50 281	97.98 209	86.84 320	97.75 226

nrg030		97.64 186	97.27 193	98.75 188	98.34 256	99.53 111	100.00 1	99.22 246	96.21 207	98.27 243	99.95 175	94.40 198	98.98 231	99.23 149	89.78 298	97.75 226

TransMVSNet (Re)		94.78 282	93.72 285	97.93 245	98.34 256	97.88 226	99.23 316	97.98 340	91.60 303	94.55 309	99.71 212	87.89 288	98.36 288	89.30 325	84.92 327	97.56 304

DU-MVS		96.93 214	96.49 214	98.22 219	98.31 258	98.41 179	100.00 1	99.37 181	96.41 198	97.76 261	99.65 226	92.14 222	98.50 281	97.98 209	86.84 320	97.75 226

NR-MVSNet		96.63 230	96.04 239	98.38 202	98.31 258	98.98 159	99.22 318	99.35 195	95.87 213	94.43 311	99.65 226	92.73 217	98.40 287	96.78 244	88.05 314	97.75 226

FC-MVSNet-test		97.84 181	97.63 185	98.45 198	98.30 260	99.05 152	100.00 1	99.43 118	96.63 186	97.61 269	99.82 199	95.19 189	98.57 277	98.64 177	93.05 258	97.73 260

Baseline_NR-MVSNet		96.16 257	95.70 255	97.56 255	98.28 261	96.79 264	100.00 1	97.86 343	91.93 301	97.63 267	99.47 251	92.14 222	98.35 289	97.13 232	86.83 322	97.54 305

WR-MVS_H		96.73 222	96.32 223	97.95 242	98.26 262	97.88 226	99.72 264	99.43 118	95.06 238	96.99 283	98.68 302	93.02 214	98.53 279	97.43 226	88.33 313	97.43 309

LF4IMVS		96.19 253	96.18 229	96.23 304	98.26 262	92.09 324	100.00 1	97.89 342	97.82 100	97.94 256	99.87 189	82.71 322	99.38 213	97.41 227	93.71 250	97.20 317

pm-mvs1		95.76 272	95.01 278	98.00 239	98.23 264	97.45 239	99.24 310	99.04 306	93.13 291	95.93 301	99.72 210	86.28 302	98.84 246	95.62 259	87.92 315	97.72 266

CP-MVSNet		96.73 222	96.25 227	98.18 222	98.21 265	98.67 172	99.77 251	99.32 205	95.06 238	97.20 280	99.65 226	90.10 262	98.19 292	98.06 208	88.90 307	97.66 287

v10		96.14 259	95.50 262	98.07 232	98.19 266	97.96 221	99.83 235	99.07 293	92.10 299	98.07 250	98.94 290	91.07 250	98.61 270	92.41 300	89.82 297	97.63 296

v7		96.64 229	96.14 233	98.13 228	98.18 267	97.97 220	99.99 178	99.09 283	93.62 278	98.76 209	99.30 258	91.13 246	98.70 264	94.37 277	90.80 281	97.74 250

PS-CasMVS		96.34 246	95.78 251	98.03 238	98.18 267	98.27 194	99.71 266	99.32 205	94.75 242	96.82 289	99.65 226	86.98 298	98.15 294	97.74 216	88.85 308	97.66 287

V42		96.65 228	96.16 231	98.11 231	98.17 269	98.23 199	99.99 178	99.09 283	93.97 262	98.74 211	99.05 271	91.09 249	98.82 248	95.46 261	89.90 296	97.27 316

v1neww		96.77 217	96.27 224	98.26 214	98.16 270	98.23 199	100.00 1	99.09 283	93.94 265	98.73 212	99.05 271	91.65 229	98.82 248	95.75 253	90.04 289	97.74 250

v7new		96.77 217	96.27 224	98.26 214	98.16 270	98.23 199	100.00 1	99.09 283	93.94 265	98.73 212	99.05 271	91.65 229	98.82 248	95.75 253	90.04 289	97.74 250

v16		93.48 292	92.34 299	96.89 282	98.13 272	98.19 205	99.82 240	98.74 318	89.94 317	88.90 331	95.62 333	91.65 229	96.54 320	90.03 317	78.22 341	95.95 332

v18		93.55 289	92.42 297	96.91 281	98.12 273	98.26 197	99.83 235	98.74 318	89.99 315	88.94 330	95.64 332	92.02 225	96.54 320	90.27 315	78.26 340	95.94 334

v13		93.18 297	91.97 304	96.81 292	98.12 273	98.12 210	99.74 258	98.73 324	89.47 323	88.52 336	95.40 340	91.72 228	96.41 327	89.23 327	76.77 347	95.92 336

v8		96.35 245	95.73 254	98.21 221	98.11 275	98.23 199	99.94 216	99.07 293	92.66 295	98.29 241	99.00 284	91.46 238	98.77 255	94.17 280	88.83 309	97.62 298

v6		96.77 217	96.26 226	98.29 210	98.10 276	98.27 194	100.00 1	99.09 283	93.95 264	98.73 212	99.06 268	91.51 236	98.86 245	95.83 251	90.04 289	97.74 250

v17		93.53 290	92.42 297	96.88 286	98.09 277	98.16 207	99.83 235	98.74 318	89.95 316	89.05 327	95.65 331	91.99 227	96.54 320	90.31 314	78.15 342	95.95 332

v12		93.18 297	91.97 304	96.80 293	98.09 277	98.10 212	99.76 254	98.73 324	89.61 322	88.45 337	95.41 339	91.63 232	96.39 329	89.32 324	76.76 348	95.91 339

v1		96.66 226	96.12 234	98.30 209	98.09 277	98.33 187	100.00 1	99.09 283	93.69 274	98.68 216	99.04 274	91.42 240	98.83 247	95.05 268	89.99 293	97.75 226

OPM-MVS		97.21 198	97.18 196	97.32 264	98.08 280	94.66 298	100.00 1	99.28 224	98.65 43	98.92 197	99.98 144	86.03 305	99.56 187	98.28 194	95.41 223	97.72 266

Anonymous20240521		96.99 212	96.48 215	98.53 196	98.07 281	99.07 149	99.76 254	99.23 242	94.26 257	96.16 297	98.68 302	94.96 192	98.87 244	96.76 246	90.41 288	97.66 287

v15		93.28 294	92.08 300	96.87 287	98.07 281	98.22 203	99.82 240	98.74 318	89.83 318	88.74 333	95.44 337	91.55 234	96.47 324	89.70 319	76.87 344	95.93 335

V14		93.24 295	92.04 301	96.87 287	98.07 281	98.20 204	99.80 245	98.74 318	89.76 320	88.64 334	95.53 334	91.47 237	96.47 324	89.49 321	76.84 345	95.92 336

v1141		96.66 226	96.12 234	98.26 214	98.05 284	98.28 192	100.00 1	99.09 283	93.71 269	98.59 223	99.04 274	91.57 233	98.73 259	95.05 268	90.00 292	97.75 226

V9		93.20 296	91.99 303	96.85 289	98.05 284	98.16 207	99.77 251	98.73 324	89.67 321	88.64 334	95.44 337	91.34 241	96.47 324	89.46 322	76.79 346	95.92 336

v2v482		96.70 224	96.18 229	98.27 212	98.04 286	98.39 181	100.00 1	99.13 272	94.19 261	98.58 225	99.08 267	90.48 258	98.67 267	95.69 256	90.44 286	97.75 226

divwei89l23v2f112		96.68 225	96.15 232	98.25 218	98.03 287	98.27 194	100.00 1	99.09 283	93.79 268	98.59 223	99.04 274	91.54 235	98.73 259	95.29 266	89.99 293	97.75 226

v1192		96.18 254	95.49 264	98.26 214	98.01 288	98.15 209	99.99 178	99.08 291	93.36 284	98.54 227	98.97 288	89.47 273	98.89 239	91.15 306	90.82 280	97.75 226

v11		93.14 299	91.93 306	96.77 295	98.01 288	98.17 206	99.72 264	98.74 318	89.39 325	88.81 332	95.49 336	91.15 245	96.29 331	86.78 330	79.25 337	95.86 341

TranMVSNet+NR-MVSNet		96.45 239	96.01 240	97.79 249	98.00 290	97.62 236	100.00 1	99.35 195	95.98 211	97.31 276	99.64 230	90.09 263	98.00 310	96.89 239	86.80 323	97.75 226

v1144		96.51 235	95.97 243	98.13 228	97.98 291	98.04 217	99.99 178	99.08 291	93.51 281	98.62 221	98.98 285	90.98 252	98.62 269	93.79 287	90.79 282	97.74 250

pcd1.5k->3k		40.07 340	42.58 341	32.57 352	97.97 292	0.00 369	0.00 360	99.25 235	0.00 364	0.00 366	0.14 366	91.10 248	0.00 366	0.00 363	94.75 242	97.70 274

test_0402		94.35 284	93.70 286	96.32 302	97.92 293	93.60 311	99.61 281	98.85 316	88.19 332	94.68 308	99.48 250	80.01 335	98.58 276	89.39 323	95.15 235	96.77 321

v1240		95.96 265	95.25 272	98.07 232	97.91 294	97.87 228	99.96 206	99.07 293	93.24 288	98.64 220	98.96 289	88.98 279	98.61 270	89.58 320	90.92 279	97.75 226

v144192		96.40 242	95.81 248	98.17 223	97.89 295	98.11 211	99.99 178	99.06 301	93.39 283	98.75 210	99.09 266	90.43 259	98.66 268	93.10 293	90.55 285	97.75 226

v1921920		96.16 257	95.50 262	98.14 225	97.88 296	97.96 221	99.99 178	99.07 293	93.33 285	98.60 222	99.24 261	89.37 274	98.71 263	91.28 304	90.74 283	97.75 226

MS-PatchMatch		95.66 274	95.87 246	95.05 310	97.80 297	89.25 332	98.88 339	99.30 212	96.35 201	96.86 287	99.01 282	81.35 330	99.43 209	93.30 292	99.98 94	96.46 324

v148		96.29 248	95.84 247	97.63 250	97.74 298	96.53 269	100.00 1	99.07 293	93.52 280	98.01 254	99.42 254	91.22 242	98.60 272	96.37 249	87.22 319	97.75 226

PEN-MVS		96.01 264	95.48 266	97.58 254	97.74 298	97.26 251	99.90 223	99.29 216	94.55 249	96.79 290	99.55 243	87.38 293	97.84 312	96.92 238	87.24 318	97.65 292

pmmvs4		97.17 200	96.80 203	98.27 212	97.68 300	98.64 173	100.00 1	99.18 257	94.22 259	98.55 226	99.71 212	93.67 205	98.47 284	95.66 257	92.57 262	97.71 273

v52		95.88 271	95.35 270	97.48 258	97.66 301	97.38 244	99.88 229	99.07 293	92.19 297	98.09 247	99.02 281	90.06 264	98.72 261	93.58 289	88.61 311	96.34 326

V4		95.89 269	95.36 269	97.49 257	97.65 302	97.40 241	99.88 229	99.07 293	92.19 297	98.08 248	99.01 282	90.20 261	98.72 261	93.57 290	88.63 310	96.34 326

PS-MVSNAJss		98.03 176	98.06 172	97.94 243	97.63 303	97.33 248	99.89 226	99.23 242	96.27 205	98.03 251	99.59 239	98.75 106	98.78 252	98.52 184	94.61 246	97.70 274

UnsupCasMVSNet_eth		94.25 285	93.89 283	95.34 308	97.63 303	92.13 323	99.73 262	99.36 187	94.88 241	92.78 317	98.63 306	82.72 321	96.53 323	94.57 273	84.73 328	97.36 312

our_test_3		96.51 235	96.35 220	96.98 277	97.61 305	95.05 283	99.98 196	99.01 308	94.68 245	96.77 291	99.06 268	95.87 176	98.14 295	91.81 302	92.37 264	97.75 226

ppachtmachnet_test		96.17 256	95.89 245	97.02 274	97.61 305	95.24 279	99.99 178	99.24 238	93.31 286	96.71 292	99.62 236	94.34 200	98.07 305	89.87 318	92.30 266	97.75 226

EU-MVSNet		96.63 230	96.53 212	96.94 279	97.59 307	96.87 262	99.76 254	99.47 83	96.35 201	96.85 288	99.78 206	92.57 219	96.27 333	95.33 262	91.08 278	97.68 281

v7n		96.06 263	95.42 268	97.99 241	97.58 308	97.35 245	99.86 232	99.11 279	92.81 294	97.91 258	99.49 249	90.99 251	98.92 235	92.51 297	88.49 312	97.70 274

lessismore_v0				96.05 305	97.55 309	91.80 326		99.22 246		91.87 321	99.91 185	83.50 319	98.68 265	92.48 298	90.42 287	97.68 281

K. test v3		95.46 278	95.14 275	96.40 300	97.53 310	93.40 314	99.99 178	99.23 242	95.49 230	92.70 320	99.73 209	84.26 313	98.12 297	93.94 286	93.38 255	97.68 281

test_djsdf		97.55 190	97.38 190	98.07 232	97.50 311	97.99 218	100.00 1	99.13 272	95.46 233	98.47 233	99.85 193	92.01 226	98.59 274	98.63 178	95.36 224	97.62 298

Gipuma		84.73 323	83.50 324	88.40 328	97.50 311	82.21 341	88.87 356	99.05 303	65.81 352	85.71 342	90.49 350	53.70 354	96.31 330	78.64 344	91.74 271	86.67 354
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
DTE-MVSNet		95.52 275	94.99 279	97.08 271	97.49 313	96.45 270	100.00 1	99.25 235	93.82 267	96.17 296	99.57 242	87.81 289	97.18 317	94.57 273	86.26 325	97.62 298

OurMVSNet-221017-0		96.14 259	95.98 242	96.62 297	97.49 313	93.44 313	99.92 220	98.16 332	95.86 215	97.65 266	99.95 175	85.71 308	98.78 252	94.93 271	94.18 249	97.64 295

pmmvs6		93.64 288	92.87 293	95.94 307	97.47 315	91.41 329	98.92 337	99.02 307	87.84 333	95.01 306	99.61 238	77.24 342	98.77 255	94.33 278	86.41 324	97.63 296

v748		95.47 277	94.95 280	97.04 272	97.46 316	94.76 296	99.93 218	99.10 280	91.95 300	97.11 281	99.18 263	89.94 267	98.68 265	94.01 284	85.88 326	97.67 285

pmmvs5		95.94 266	95.61 259	96.95 278	97.42 317	94.66 298	100.00 1	98.08 336	93.60 279	97.05 282	99.43 253	87.02 296	98.46 285	95.76 252	92.12 267	97.72 266

SixPastTwentyTwo		95.71 273	95.49 264	96.38 301	97.42 317	93.01 316	99.84 234	98.23 330	94.75 242	95.98 300	99.97 154	85.35 309	98.43 286	94.71 272	93.17 256	97.69 279

mvs_tets		97.00 211	96.69 207	97.94 243	97.41 319	97.27 250	99.60 282	99.18 257	96.51 193	97.35 275	99.69 217	86.53 301	98.91 236	98.84 166	95.09 238	97.65 292

jajsoiax		97.07 206	96.79 205	97.89 247	97.28 320	97.12 255	99.95 212	99.19 254	96.55 189	97.31 276	99.69 217	87.35 295	98.91 236	98.70 173	95.12 237	97.66 287

N_pmnet		91.88 309	93.37 290	87.40 331	97.24 321	66.33 356	99.90 223	91.05 362	89.77 319	95.65 303	98.58 308	90.05 265	98.11 299	85.39 332	92.72 261	97.75 226

anonymousdsp		97.16 201	96.88 200	98.00 239	97.08 322	98.06 215	99.81 242	99.15 263	94.58 248	97.84 260	99.62 236	90.49 257	98.60 272	97.98 209	95.32 225	97.33 315

MDA-MVSNet-bldmvs		91.65 311	89.94 314	96.79 294	96.72 323	96.70 266	99.42 296	98.94 311	88.89 327	66.97 358	98.37 316	81.43 328	95.91 336	89.24 326	89.46 302	97.75 226

MDA-MVSNet_test_wron		92.61 303	91.09 309	97.19 270	96.71 324	97.26 251	100.00 1	99.14 267	88.61 328	67.90 356	98.32 318	89.03 277	96.57 319	90.47 312	89.59 299	97.74 250

new_pmnet		94.11 287	93.47 289	96.04 306	96.60 325	92.82 319	99.97 203	98.91 314	90.21 312	95.26 304	98.05 319	85.89 306	98.14 295	84.28 334	92.01 269	97.16 318

YYNet1		92.44 305	90.92 310	97.03 273	96.20 326	97.06 258	99.99 178	99.14 267	88.21 331	67.93 355	98.43 313	88.63 282	96.28 332	90.64 308	89.08 306	97.74 250

CMPMVS	66.12 22	90.65 314	92.04 301	86.46 333	96.18 327	66.87 355	98.03 347	99.38 178	83.38 344	85.49 343	99.55 243	77.59 341	98.80 251	94.44 275	94.31 248	93.72 345
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
DSMNet-mixed		95.18 280	95.21 273	95.08 309	96.03 328	90.21 330	99.65 278	93.64 360	92.91 293	98.34 238	97.40 322	90.05 265	95.51 339	91.02 307	97.86 178	99.51 206

DI_MVS_plusplus_test		96.28 250	95.16 274	99.61 120	96.01 329	99.18 144	100.00 1	99.29 216	96.49 194	89.08 326	98.42 314	80.06 332	99.90 139	98.74 172	98.39 146	99.75 186

test_normal		96.24 251	95.12 276	99.60 124	96.00 330	99.16 145	100.00 1	99.29 216	96.43 195	88.96 329	98.40 315	80.06 332	99.90 139	98.53 183	98.39 146	99.75 186

EG-PatchMatch MVS		92.94 301	92.49 296	94.29 318	95.87 331	87.07 336	99.07 335	98.11 335	93.19 289	88.98 328	98.66 305	70.89 349	99.08 224	92.43 299	95.21 232	96.72 322

MVP-Stereo		96.51 235	96.48 215	96.60 298	95.65 332	94.25 306	98.84 340	98.16 332	95.85 217	95.23 305	99.04 274	92.54 220	99.13 222	92.98 294	99.98 94	96.43 325
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
OpenMVS_ROB	88.34 20	91.89 308	91.12 308	94.19 320	95.55 333	87.63 335	99.26 308	98.03 337	86.61 335	90.65 325	96.82 323	70.14 350	98.78 252	86.54 331	96.50 216	96.15 328

UnsupCasMVSNet_bld		89.50 317	88.00 320	93.99 321	95.30 334	88.86 333	98.52 343	99.28 224	85.50 339	87.80 340	94.11 345	61.63 352	96.96 318	90.63 309	79.26 336	96.15 328

test20.03		93.11 300	92.85 294	93.88 322	95.19 335	91.83 325	100.00 1	98.87 315	93.68 275	92.76 318	98.88 294	89.20 276	92.71 346	77.88 345	89.19 304	97.09 319

Anonymous20231206		93.45 293	93.17 291	94.30 317	95.00 336	89.69 331	99.98 196	98.43 328	93.30 287	94.50 310	98.59 307	90.52 256	95.73 338	77.46 347	90.73 284	97.48 308

MIMVSNet1		91.96 306	91.20 307	94.23 319	94.94 337	91.69 327	99.34 303	99.22 246	88.23 330	94.18 312	98.45 311	75.52 345	93.41 345	79.37 342	91.49 274	97.60 301

testus		91.61 312	92.92 292	87.70 330	93.91 338	74.98 347	100.00 1	98.19 331	92.59 296	93.90 314	98.68 302	81.43 328	90.77 349	79.82 341	97.71 196	97.34 314

test2356		92.55 304	93.94 282	88.39 329	93.49 339	78.42 343	100.00 1	99.40 159	91.64 302	93.93 313	98.74 300	91.11 247	88.67 351	79.37 342	97.79 186	98.08 218

Test4		92.63 302	90.45 313	99.17 162	92.81 340	99.02 154	99.98 196	99.13 272	96.60 187	82.04 348	96.27 327	51.35 356	98.75 258	97.55 221	98.36 151	99.75 186

Patchmatch-RL test		93.49 291	93.63 287	93.05 323	91.78 341	83.41 340	98.21 346	96.95 351	91.58 304	91.05 322	97.64 321	99.40 47	95.83 337	94.11 283	81.95 332	99.91 130

PM-MVS		88.39 319	87.41 321	91.31 325	91.73 342	82.02 342	99.79 246	96.62 354	91.06 308	90.71 324	95.73 330	48.60 358	95.96 335	90.56 310	81.91 333	95.97 331

pmmvs-eth3d		91.73 310	90.67 311	94.92 313	91.63 343	92.71 320	99.90 223	98.54 327	91.19 307	88.08 338	95.50 335	79.31 338	96.13 334	90.55 311	81.32 334	95.91 339

new-patchmatchnet		90.30 316	89.46 315	92.84 324	90.77 344	88.55 334	99.83 235	98.80 317	90.07 314	87.86 339	95.00 343	78.77 339	94.30 342	84.86 333	79.15 338	95.68 342

pmmvs3		90.62 315	89.36 316	94.40 316	90.53 345	91.49 328	100.00 1	96.73 353	84.21 342	93.65 316	96.65 324	82.56 324	94.83 340	82.28 337	77.62 343	96.89 320

testing_2		90.79 313	88.26 319	98.35 205	89.11 346	98.56 175	99.70 268	99.14 267	93.70 273	73.80 351	94.06 346	55.19 353	98.76 257	97.17 231	92.50 263	97.74 250

1111		88.62 318	89.13 317	87.08 332	87.71 347	77.22 344	99.96 206	97.71 345	85.51 337	83.47 346	96.26 328	95.76 179	90.96 347	66.63 353	89.17 305	93.07 346

.test1245		85.18 322	84.81 323	86.28 334	87.71 347	77.22 344	99.96 206	97.71 345	85.51 337	83.47 346	96.26 328	95.76 179	90.96 347	66.63 353	50.30 354	90.64 350

test1235678		88.02 320	88.73 318	85.90 335	87.57 349	71.70 351	100.00 1	97.42 348	87.52 334	86.19 341	96.39 326	81.60 326	87.93 352	70.72 350	91.18 277	98.08 218

ambc				88.45 327	86.84 350	70.76 353	97.79 350	98.02 339		90.91 323	95.14 341	38.69 360	98.51 280	94.97 270	84.23 329	96.09 330

EMVS		69.88 334	69.09 334	72.24 350	84.70 351	65.82 357	99.96 206	87.08 367	49.82 361	71.51 354	84.74 357	49.30 357	75.32 361	50.97 361	43.71 357	75.59 361

test12356		86.30 321	87.15 322	83.77 339	84.24 352	72.00 349	99.94 216	96.80 352	84.63 341	85.16 344	96.51 325	77.02 343	86.31 355	70.06 351	89.93 295	93.00 347

E-PMN		70.72 332	70.06 333	72.69 349	83.92 353	65.48 358	99.95 212	92.72 361	49.88 360	72.30 353	86.26 356	47.17 359	77.43 360	53.83 360	44.49 356	75.17 362

PMMVS2		79.15 327	77.28 329	84.76 338	82.34 354	72.66 348	99.70 268	95.11 359	71.68 351	84.78 345	90.87 349	32.05 362	89.99 350	75.53 348	63.45 351	91.64 348

TDRefinement		91.93 307	90.48 312	96.27 303	81.60 355	92.65 321	99.10 331	97.61 347	93.96 263	93.77 315	99.85 193	80.03 334	99.53 199	97.82 215	70.59 350	96.63 323

no-one		74.65 331	71.03 332	85.51 336	80.99 356	75.42 346	99.70 268	97.15 349	81.02 345	66.48 359	80.55 362	29.10 364	93.65 344	73.74 349	30.53 360	87.47 353

test123		79.44 326	79.23 328	80.05 341	80.03 357	71.72 350	100.00 1	77.93 369	62.52 353	94.81 307	99.69 217	78.21 340	74.53 362	92.57 296	27.33 362	93.90 343

LCM-MVSNet		79.01 328	76.93 330	85.27 337	78.28 358	68.01 354	96.57 351	98.03 337	55.10 357	82.03 349	93.27 347	31.99 363	93.95 343	82.72 336	74.37 349	93.84 344

testmv		79.83 325	79.77 326	79.99 342	78.22 359	63.55 359	99.67 275	95.51 358	80.89 346	76.24 350	92.90 348	52.16 355	86.10 356	62.45 356	79.90 335	90.33 352

FPMVS		77.92 329	79.45 327	73.34 347	76.87 360	46.81 366	98.24 345	99.05 303	59.89 356	73.55 352	98.34 317	36.81 361	86.55 353	80.96 338	91.35 276	86.65 355

PNet_i23d		69.93 333	67.61 335	76.86 343	75.89 361	62.08 362	97.85 348	88.23 364	61.04 355	55.65 361	84.10 358	19.35 366	83.21 357	66.45 355	59.98 352	85.29 357

wuyk23d		28.28 341	29.73 343	23.92 353	75.89 361	32.61 368	66.50 359	12.88 370	16.09 363	14.59 365	16.59 365	12.35 367	32.36 365	39.36 362	13.36 363	6.79 363

MVE	68.59 21	67.22 335	64.68 337	74.84 344	74.67 363	62.32 361	95.84 352	90.87 363	50.98 359	58.72 360	81.05 360	12.20 370	78.95 359	61.06 358	56.75 353	83.24 358
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuykxyi23d		62.75 338	59.23 339	73.34 347	61.53 364	59.39 364	93.28 355	86.17 368	53.70 358	46.89 363	77.89 363	12.35 367	79.96 358	60.86 359	40.35 358	80.68 360

ANet_high		66.05 336	63.44 338	73.88 346	61.14 365	63.45 360	95.68 354	87.18 365	79.93 347	47.35 362	80.68 361	22.35 365	72.33 364	61.24 357	35.42 359	85.88 356

testmvs		80.17 324	81.95 325	74.80 345	58.54 366	59.58 363	100.00 1	87.14 366	76.09 349	99.61 160	100.00 1	67.06 351	74.19 363	98.84 166	50.30 354	90.64 350

PMVS	60.66 23	65.98 337	65.05 336	68.75 351	55.06 367	38.40 367	88.19 357	96.98 350	48.30 362	44.82 364	88.52 353	12.22 369	86.49 354	67.58 352	83.79 330	81.35 359
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tmp_tt		75.80 330	74.26 331	80.43 340	52.91 368	53.67 365	87.42 358	97.98 340	61.80 354	67.04 357	100.00 1	76.43 344	96.40 328	96.47 248	28.26 361	91.23 349

cdsmvs_eth3d_5k		24.41 342	32.55 342	0.00 354	0.00 369	0.00 369	0.00 360	99.39 174	0.00 364	0.00 366	100.00 1	93.55 207	0.00 366	0.00 363	0.00 364	0.00 364

pcd_1.5k_mvsjas		8.24 344	10.99 345	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.14 366	98.75 106	0.00 366	0.00 363	0.00 364	0.00 364

sosnet-low-res		0.01 345	0.02 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.14 366	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

sosnet		0.01 345	0.02 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.14 366	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

uncertanet		0.01 345	0.02 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.14 366	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

Regformer		0.01 345	0.02 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.14 366	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

ab-mvs-re		8.33 343	11.11 344	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	100.00 1	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

uanet		0.01 345	0.02 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.14 366	0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

GSMVS																99.91 130

test_part1				0.00 354		0.00 369	0.00 360	99.42 125				0.00 371	0.00 366	0.00 363	0.00 364	0.00 364

sam_mvs1												99.29 61				99.91 130

sam_mvs												99.33 50

MTGPA								99.42 125

test_post1							99.32 304				88.24 354	99.33 50	99.59 180	98.31 192

test_post											89.05 352	99.49 35	99.59 180

patchmatchnet-post											97.79 320	99.41 46	99.54 195

MTMP							100.00 1	99.18 257

test9_res														100.00 1	100.00 1	100.00 1

agg_prior2														100.00 1	100.00 1	100.00 1

test_prior4						99.93 32	100.00 1

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

旧先验2							100.00 1		98.11 75	100.00 1			100.00 1	99.67 109

新几何2							100.00 1

无先验							100.00 1	99.80 43	97.98 84				100.00 1	99.33 142		100.00 1

原ACMM2							100.00 1

testdata2													100.00 1	97.36 229

segment_acmp												99.55 25

testdata1							100.00 1		98.77 38

plane_prior5								99.40 159					99.55 192	99.79 92	95.57 221	97.76 222

plane_prior4											99.97 154

plane_prior3						94.79 294			99.03 16	99.08 190

plane_prior2							100.00 1		99.00 19

plane_prior						94.80 291	100.00 1		99.03 16						95.58 217

n2								0.00 371

nn								0.00 371

door-mid								96.32 356

test11								99.42 125

door								96.13 357

HQP5-MVS						94.82 288

BP-MVS														99.79 92

HQP4-MVS										99.17 182			99.57 183			97.77 220

HQP3-MVS								99.40 159							95.58 217

HQP2-MVS												88.61 283

MDTV_nov1_ep13_2view						99.24 139	99.56 285		96.31 203	99.96 90		98.86 100		98.92 162		99.89 143

ACMMP++_ref															94.58 247

ACMMP++															95.17 234

Test By Simon												99.10 79

High-resolution multi-view benchmark