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.

Anonymous202405211		97.87 178	97.53 184	98.90 176	99.81 100	96.70 262	99.35 300	99.46 95	92.98 290	98.83 203	99.99 140	90.63 253	100.00 1	99.70 103	97.03 209	100.00 1

SMA-MVS		99.71 32	99.62 44	99.98 16	99.99 45	99.95 19	100.00 1	99.42 122	97.61 123	100.00 1	100.00 1	99.55 24	100.00 1	100.00 1	100.00 1	100.00 1

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	99.83 126	99.96 161	97.01 143	100.00 1	99.54 123	97.77 187	99.97 97

test_part3							100.00 1		98.23 64		100.00 1		100.00 1	100.00 1

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	99.83 126	99.96 161	97.01 143	100.00 1	99.59 114	97.85 179	99.97 97

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	99.83 126	99.96 161	97.01 143	100.00 1	99.59 114	97.85 179	99.98 92

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	99.83 126	99.96 161	97.04 139	100.00 1	99.59 114	97.85 179	99.98 92

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	99.54 158	99.96 161	96.99 151	100.00 1	99.43 130	97.75 189	99.97 97

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	99.54 158	99.96 161	96.99 151	100.00 1	99.43 130	97.75 189	99.97 97

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	99.54 158	99.96 161	96.99 151	100.00 1	99.43 130	97.75 189	99.97 97

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	99.54 158	99.96 161	96.99 151	100.00 1	99.43 130	97.75 189	99.97 97

ESAPD		99.76 15	99.69 18	100.00 1	100.00 1	99.99 1	100.00 1	99.42 122	98.23 64	100.00 1	100.00 1	99.53 26	100.00 1	100.00 1	100.00 1	100.00 1

CANet_DTU		99.02 119	98.90 120	99.41 141	99.88 97	98.71 167	100.00 1	99.29 212	98.84 30	100.00 1	100.00 1	94.02 201	100.00 1	98.08 202	99.96 100	99.52 203

MVS_0304		98.98 125	98.66 137	99.94 59	99.95 82	99.86 67	100.00 1	99.29 212	98.38 55	99.81 137	100.00 1	90.60 254	100.00 1	100.00 1	99.91 105	99.95 113

MP-MVS-pluss		99.61 55	99.50 57	99.97 24	99.98 72	99.92 36	100.00 1	99.42 122	97.53 131	99.77 140	100.00 1	98.77 105	100.00 1	99.99 45	100.00 1	99.99 90
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
xiu_mvs_v1_base_debu		99.35 76	99.21 80	99.79 99	99.67 137	99.71 96	99.78 245	99.36 183	98.13 71	100.00 1	100.00 1	97.00 148	100.00 1	99.83 86	99.07 125	99.66 197

ACMMP_Plus		99.67 46	99.57 51	99.97 24	99.98 72	99.92 36	100.00 1	99.42 122	97.83 98	100.00 1	100.00 1	98.89 99	100.00 1	99.98 59	100.00 1	100.00 1

zzz-MVS		99.68 43	99.59 47	99.97 24	99.99 45	99.91 39	100.00 1	99.42 122	98.32 61	99.94 110	100.00 1	98.65 109	100.00 1	99.96 66	100.00 1	100.00 1

xiu_mvs_v2_base		99.51 63	99.41 61	99.82 89	99.70 132	99.73 88	99.92 218	99.40 156	98.15 69	100.00 1	100.00 1	98.50 115	100.00 1	99.85 83	99.13 123	99.74 188

xiu_mvs_v1_base		99.35 76	99.21 80	99.79 99	99.67 137	99.71 96	99.78 245	99.36 183	98.13 71	100.00 1	100.00 1	97.00 148	100.00 1	99.83 86	99.07 125	99.66 197

xiu_mvs_v1_base_debi		99.35 76	99.21 80	99.79 99	99.67 137	99.71 96	99.78 245	99.36 183	98.13 71	100.00 1	100.00 1	97.00 148	100.00 1	99.83 86	99.07 125	99.66 197

MTAPA		99.68 43	99.59 47	99.97 24	99.99 45	99.91 39	100.00 1	99.42 122	98.32 61	99.94 110	100.00 1	98.65 109	100.00 1	99.96 66	100.00 1	100.00 1

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

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

PS-MVSNAJ		99.64 50	99.57 51	99.85 85	99.78 123	99.81 78	99.95 210	99.42 122	98.38 55	100.00 1	100.00 1	98.75 106	100.00 1	99.88 79	99.99 88	99.74 188

#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

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 90

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

X-MVStestdata		97.04 206	96.06 235	99.98 16	100.00 1	99.94 28	100.00 1	99.75 50	98.67 40	100.00 1	66.97 361	99.16 76	100.00 1	100.00 1	100.00 1	100.00 1

旧先验2							100.00 1		98.11 75	100.00 1			100.00 1	99.67 108

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	97.91 209	100.00 1	100.00 1

无先验							100.00 1	99.80 43	97.98 84				100.00 1	99.33 141		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	99.50 128	100.00 1	100.00 1

testdata2													100.00 1	97.36 226

testdata				99.66 117	99.99 45	98.97 159		99.73 55	97.96 88	100.00 1	100.00 1	99.42 46	100.00 1	99.28 145	100.00 1	100.00 1

1314		99.38 74	99.19 84	99.96 36	98.88 233	99.89 49	99.24 308	99.93 32	98.88 27	98.79 205	100.00 1	97.02 142	100.00 1	100.00 1	100.00 1	100.00 1

1121		99.63 52	99.51 56	99.99 5	99.99 45	99.96 10	99.24 308	99.74 53	97.89 93	100.00 1	100.00 1	99.39 49	100.00 1	99.33 141	100.00 1	100.00 1

LFMVS		97.42 190	96.62 208	99.81 92	99.80 115	99.50 111	99.16 323	99.56 74	94.48 249	100.00 1	100.00 1	79.35 334	100.00 1	99.89 78	97.37 205	99.94 117

VDD-MVS		96.58 230	95.99 238	98.34 203	99.52 173	95.33 274	99.18 317	99.38 174	96.64 183	99.77 140	100.00 1	72.51 345	100.00 1	100.00 1	96.94 211	99.70 193

VDDNet		96.39 240	95.55 257	98.90 176	99.27 201	97.45 236	99.15 324	99.92 36	91.28 304	99.98 81	100.00 1	73.55 343	100.00 1	99.85 83	96.98 210	99.24 207

MVS		99.22 100	98.96 106	99.98 16	99.00 222	99.95 19	99.24 308	99.94 18	98.14 70	98.88 197	100.00 1	95.63 181	100.00 1	99.85 83	100.00 1	100.00 1

SD-MVS		99.81 9	99.75 12	99.99 5	99.99 45	99.96 10	100.00 1	99.42 122	99.01 18	100.00 1	100.00 1	99.33 51	100.00 1	100.00 1	100.00 1	100.00 1

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

VNet		99.04 114	98.75 131	99.90 72	99.81 100	99.75 85	99.50 289	99.47 83	98.36 58	100.00 1	99.99 140	94.66 195	100.00 1	99.90 76	97.09 208	99.96 108

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

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	99.83 126	99.96 161	97.01 143	100.00 1	99.54 123	97.77 187	99.97 97

MP-MVS		99.61 55	99.49 59	99.98 16	99.99 45	99.94 28	100.00 1	99.42 122	97.82 100	99.99 76	100.00 1	98.20 119	100.00 1	99.99 45	100.00 1	100.00 1
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
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	99.83 126	99.96 161	97.04 139	100.00 1	99.59 114	97.85 179	99.97 97

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	99.83 126	99.96 161	97.04 139	100.00 1	99.62 113	97.88 176	99.98 92

PGM-MVS		99.69 40	99.61 45	99.95 47	99.99 45	99.85 70	100.00 1	99.58 73	97.69 111	100.00 1	100.00 1	99.44 44	100.00 1	99.79 91	100.00 1	100.00 1

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

abl_6		99.53 61	99.40 62	99.92 68	100.00 1	99.76 83	100.00 1	99.42 122	97.21 149	100.00 1	100.00 1	98.12 121	100.00 1	99.82 90	100.00 1	100.00 1

mPP-MVS		99.69 40	99.60 46	99.97 24	100.00 1	99.91 39	100.00 1	99.42 122	97.91 92	100.00 1	100.00 1	99.04 83	100.00 1	100.00 1	100.00 1	100.00 1

EPNet		99.62 53	99.69 18	99.42 140	99.99 45	98.37 182	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	99.89 142
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 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 49	100.00 1	100.00 1	100.00 1	100.00 1

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

CP-MVS		99.67 46	99.58 49	99.95 47	100.00 1	99.84 71	100.00 1	99.42 122	97.77 103	100.00 1	100.00 1	99.07 80	100.00 1	100.00 1	100.00 1	100.00 1

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	99.73 144	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
CPTT-MVS		99.49 66	99.38 66	99.85 85	100.00 1	99.54 109	100.00 1	99.42 122	97.58 128	99.98 81	100.00 1	97.43 136	100.00 1	99.99 45	100.00 1	100.00 1

UGNet		98.41 162	98.11 166	99.31 151	99.54 164	98.55 174	99.18 317	100.00 1	98.64 43	99.79 138	99.04 270	87.61 289	100.00 1	99.30 144	99.89 107	99.40 206
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
sss		99.45 70	99.34 72	99.80 95	99.76 127	99.50 111	100.00 1	99.91 37	97.72 106	99.98 81	99.94 177	98.45 116	100.00 1	99.53 126	98.75 132	99.89 142

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

QAPM		98.99 123	98.66 137	99.96 36	99.01 218	99.87 62	99.88 227	99.93 32	97.99 82	98.68 212	100.00 1	93.17 211	100.00 1	99.32 143	100.00 1	100.00 1

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

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

RPSCF		97.37 191	98.24 161	94.76 310	99.80 115	84.57 335	99.99 176	99.05 298	94.95 237	99.82 135	100.00 1	94.03 200	100.00 1	98.15 195	98.38 150	99.70 193

CSCG		99.28 90	99.35 70	99.05 165	99.99 45	97.15 250	100.00 1	99.47 83	97.44 135	99.42 168	100.00 1	97.83 127	100.00 1	99.99 45	100.00 1	100.00 1

API-MVS		99.72 29	99.70 17	99.79 99	99.97 76	99.37 126	99.96 204	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

ACMMP		99.65 48	99.57 51	99.89 75	99.99 45	99.66 103	99.75 255	99.73 55	98.16 67	99.75 143	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
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	99.88 122	100.00 1	99.14 78	100.00 1	99.97 64	100.00 1	100.00 1

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

PVSNet	94.91 18	99.30 88	99.25 75	99.44 137	100.00 1	98.32 188	100.00 1	99.86 39	98.04 79	100.00 1	100.00 1	96.10 171	100.00 1	99.55 120	99.73 115	100.00 1

PVSNet_0	93.57 19	96.41 237	95.74 250	98.41 197	99.84 98	95.22 276	100.00 1	100.00 1	98.08 76	97.55 266	99.78 203	84.40 310	100.00 1	100.00 1	81.99 328	100.00 1

DeepPCF-MVS	98.03 4	98.54 154	99.72 15	94.98 308	99.99 45	84.94 334	100.00 1	99.42 122	99.98 1	100.00 1	100.00 1	98.11 122	100.00 1	100.00 1	100.00 1	100.00 1

DeepC-MVS_fast	98.92 1	99.75 18	99.67 27	99.99 5	99.99 45	99.96 10	99.73 260	99.52 76	99.06 10	100.00 1	100.00 1	98.80 104	100.00 1	99.95 71	100.00 1	100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MG-MVS		99.75 18	99.68 22	99.97 24	100.00 1	99.91 39	99.98 194	99.47 83	99.09 7	100.00 1	100.00 1	98.59 112	100.00 1	99.95 71	100.00 1	100.00 1

AdaColmap		99.44 71	99.26 74	99.95 47	100.00 1	99.86 67	99.70 266	99.99 10	98.53 46	99.90 118	100.00 1	95.34 183	100.00 1	99.92 74	100.00 1	100.00 1

PLC	98.56 2	99.70 37	99.74 13	99.58 129	100.00 1	98.79 164	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	99.94 117
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MAR-MVS		99.49 66	99.36 68	99.89 75	99.97 76	99.66 103	99.74 256	99.95 15	97.89 93	100.00 1	100.00 1	96.71 160	100.00 1	100.00 1	100.00 1	100.00 1
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
3Dnovator+	95.58 15	99.03 115	98.71 134	99.96 36	98.99 225	99.89 49	100.00 1	99.51 80	98.96 21	98.32 235	100.00 1	92.78 215	100.00 1	99.87 80	100.00 1	100.00 1

3Dnovator	95.63 14	99.06 112	98.76 130	99.96 36	98.86 236	99.90 45	99.98 194	99.93 32	98.95 24	98.49 228	100.00 1	92.91 214	100.00 1	99.71 101	100.00 1	100.00 1

OpenMVS	95.20 17	98.76 140	98.41 154	99.78 107	98.89 232	99.81 78	99.99 176	99.76 46	98.02 80	98.02 249	100.00 1	91.44 238	100.00 1	99.63 112	99.97 98	99.55 201

TSAR-MVS + MP.		99.82 7	99.77 8	99.99 5	100.00 1	99.96 10	100.00 1	99.43 116	99.05 12	100.00 1	100.00 1	99.45 43	99.99 83	100.00 1	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	99.44 107	98.43 49	100.00 1	100.00 1	99.23 69	99.99 83	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	99.44 107	98.42 51	100.00 1	100.00 1	99.22 70	99.99 83	99.99 45	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	99.44 107	99.06 10	100.00 1	100.00 1	99.56 23	99.99 83	100.00 1	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 48	99.55 55	99.97 24	99.99 45	99.91 39	100.00 1	99.48 82	97.54 130	100.00 1	100.00 1	98.97 89	99.99 83	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	99.42 122	98.02 80	100.00 1	100.00 1	99.32 54	99.99 83	100.00 1	100.00 1	100.00 1

TSAR-MVS + GP.		99.61 55	99.69 18	99.35 147	99.99 45	98.06 213	100.00 1	99.36 183	99.83 2	100.00 1	100.00 1	98.95 92	99.99 83	100.00 1	99.11 124	100.00 1

SteuartSystems-ACMMP		99.78 13	99.71 16	99.98 16	99.76 127	99.95 19	100.00 1	99.42 122	98.69 38	100.00 1	100.00 1	99.52 29	99.99 83	100.00 1	100.00 1	100.00 1
Skip Steuart: Steuart Systems R&D Blog.
PVSNet_BlendedMVS		98.71 143	98.62 143	98.98 171	99.98 72	99.60 107	100.00 1	100.00 1	97.23 146	100.00 1	99.03 275	96.57 162	99.99 83	100.00 1	94.75 240	97.35 310

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 83	100.00 1	99.88 108	99.90 137

HY-MVS	96.53 9	99.50 64	99.35 70	99.96 36	99.81 100	99.93 33	99.64 277	100.00 1	97.97 86	99.84 124	99.85 190	98.94 94	99.99 83	99.86 81	98.23 160	99.95 113

PatchMatch-RL		99.02 119	98.78 128	99.74 110	99.99 45	99.29 131	100.00 1	100.00 1	98.38 55	99.89 121	99.81 199	93.14 212	99.99 83	97.85 210	99.98 95	99.95 113

F-COLMAP		99.64 50	99.64 35	99.67 116	99.99 45	99.07 147	100.00 1	99.44 107	98.30 63	99.90 118	100.00 1	99.18 74	99.99 83	99.91 75	100.00 1	99.94 117

test_8					100.00 1	99.91 39	100.00 1	99.42 122	97.70 109	100.00 1	100.00 1	99.51 31	99.98 96

MVS_Test		98.93 131	98.65 140	99.77 109	99.62 148	99.50 111	99.99 176	99.19 248	95.52 225	99.96 88	99.86 188	96.54 164	99.98 96	98.65 174	98.48 139	99.82 171

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	99.84 124	100.00 1	98.94 94	99.98 96	99.86 81	98.21 161	99.94 117

ab-mvs		98.42 161	98.02 172	99.61 119	99.71 131	99.00 156	99.10 327	99.64 72	96.70 178	99.04 190	99.81 199	90.64 252	99.98 96	99.64 111	97.93 173	99.84 165

TEST9					100.00 1	99.95 19	100.00 1	99.42 122	97.65 119	100.00 1	100.00 1	99.53 26	99.97 100

train_agg		99.71 32	99.63 39	99.97 24	100.00 1	99.95 19	100.00 1	99.42 122	97.70 109	100.00 1	100.00 1	99.51 31	99.97 100	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	99.42 122	97.71 108	100.00 1	100.00 1	99.51 31	99.97 100	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	99.42 122	97.72 106	100.00 1	100.00 1	99.51 31	99.97 100	100.00 1	100.00 1	100.00 1

agg_prior					100.00 1	99.88 59		99.42 122		100.00 1			99.97 100

canonicalmvs		99.03 115	98.73 132	99.94 59	99.75 129	99.95 19	100.00 1	99.30 208	97.64 121	100.00 1	100.00 1	95.22 186	99.97 100	99.76 97	96.90 212	99.91 129

EI-MVSNet-UG-set		99.69 40	99.63 39	99.87 81	99.99 45	99.64 105	99.95 210	99.44 107	98.35 59	100.00 1	100.00 1	98.98 88	99.97 100	99.98 59	100.00 1	100.00 1

Regformer-3		99.73 26	99.65 31	99.96 36	100.00 1	99.89 49	100.00 1	99.44 107	98.40 52	100.00 1	100.00 1	99.03 86	99.97 100	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	99.44 107	98.40 52	100.00 1	100.00 1	99.03 86	99.97 100	99.99 45	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	99.97 100	100.00 1	100.00 1	100.00 1

test_prior				99.90 72	100.00 1	99.75 85		99.73 55					99.97 100			100.00 1

test12				99.95 47	99.99 45	99.89 49		99.42 122		100.00 1		99.24 68	99.97 100		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	99.42 122	97.53 131	100.00 1	100.00 1	99.27 66	99.97 100	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
DP-MVS		98.86 135	98.54 149	99.81 92	99.97 76	99.45 120	99.52 287	99.40 156	94.35 252	98.36 232	100.00 1	96.13 170	99.97 100	99.12 153	100.00 1	100.00 1

LS3D		99.31 87	99.13 93	99.87 81	99.99 45	99.71 96	99.55 284	99.46 95	97.32 143	99.82 135	100.00 1	96.85 157	99.97 100	99.14 151	100.00 1	99.92 128

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	99.78 139	100.00 1	95.28 184	99.96 115	100.00 1	99.99 88	99.96 108

HSP-MVS		99.81 9	99.77 8	99.94 59	100.00 1	99.86 67	100.00 1	99.42 122	98.87 29	100.00 1	100.00 1	99.65 18	99.96 115	100.00 1	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	99.98 194	99.44 107	98.35 59	99.99 76	100.00 1	99.04 83	99.96 115	99.98 59	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	99.42 122	97.09 157	100.00 1	100.00 1	98.95 92	99.96 115	99.98 59	100.00 1	100.00 1

HPM-MVS		99.59 59	99.50 57	99.89 75	100.00 1	99.70 100	100.00 1	99.42 122	97.46 133	100.00 1	100.00 1	98.60 111	99.96 115	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
BH-w/o		98.82 138	98.81 126	98.88 178	99.62 148	96.71 261	100.00 1	99.28 220	97.09 157	98.81 204	100.00 1	94.91 193	99.96 115	99.54 123	100.00 1	99.96 108

AllTest		98.55 153	98.40 155	98.99 169	99.93 88	97.35 242	100.00 1	99.40 156	97.08 159	99.09 185	99.98 142	93.37 207	99.95 121	96.94 233	99.84 111	99.68 195

TestCases				98.99 169	99.93 88	97.35 242		99.40 156	97.08 159	99.09 185	99.98 142	93.37 207	99.95 121	96.94 233	99.84 111	99.68 195

CHOSEN 1792x2688		99.00 121	98.91 117	99.25 156	99.90 94	97.79 229	100.00 1	99.99 10	98.79 36	98.28 238	100.00 1	93.63 205	99.95 121	99.66 110	99.95 102	100.00 1

114514_t		99.39 73	99.25 75	99.81 92	99.97 76	99.48 118	100.00 1	99.42 122	95.53 223	100.00 1	100.00 1	98.37 118	99.95 121	99.97 64	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	99.63 156	100.00 1	96.45 166	99.95 121	99.79 91	99.65 118	99.89 142

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	99.95 121	99.99 45	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	99.95 121	100.00 1	100.00 1	100.00 1

DeepC-MVS	97.84 5	99.00 121	98.80 127	99.60 122	99.93 88	99.03 151	100.00 1	99.40 156	98.61 44	99.33 173	100.00 1	92.23 220	99.95 121	99.74 99	99.96 100	99.83 168
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PCF-MVS	98.23 3	98.69 146	98.37 157	99.62 118	99.78 123	99.02 152	99.23 314	99.06 296	96.43 194	98.08 244	100.00 1	94.72 194	99.95 121	98.16 194	99.91 105	99.90 137
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MSDG		98.90 133	98.63 142	99.70 113	99.92 91	99.25 136	100.00 1	99.37 177	95.71 217	99.40 172	100.00 1	96.58 161	99.95 121	96.80 240	99.94 103	99.91 129

COLMAP_ROB	97.10 7	98.29 166	98.17 165	98.65 188	99.94 86	97.39 239	99.30 304	99.40 156	95.64 218	97.75 260	100.00 1	92.69 217	99.95 121	98.89 161	99.92 104	98.62 213
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
UA-Net		99.06 112	98.83 123	99.74 110	99.52 173	99.40 123	99.08 329	99.45 98	97.64 121	99.83 126	100.00 1	95.80 175	99.94 132	98.35 187	99.80 114	99.88 155

XVG-OURS-SEG-HR		98.27 168	98.31 159	98.14 222	99.59 155	95.92 270	100.00 1	99.36 183	98.48 47	99.21 178	100.00 1	89.27 274	99.94 132	99.76 97	99.17 122	98.56 214

mvs-test1		98.89 134	98.99 104	98.60 190	99.77 125	95.96 268	100.00 1	98.94 306	97.61 123	99.93 115	99.92 180	95.89 172	99.93 134	99.36 138	99.50 120	99.90 137

alignmvs		99.38 74	99.21 80	99.91 69	99.73 130	99.92 36	100.00 1	99.51 80	97.61 123	100.00 1	100.00 1	99.06 81	99.93 134	99.83 86	97.12 207	99.90 137

cascas		98.43 160	98.07 169	99.50 135	99.65 141	99.02 152	100.00 1	99.22 241	94.21 257	99.72 145	99.98 142	92.03 223	99.93 134	99.68 106	98.12 166	99.54 202

XVG-OURS		98.30 165	98.36 158	98.13 225	99.58 159	95.91 271	100.00 1	99.36 183	98.69 38	99.23 177	100.00 1	91.20 242	99.92 137	99.34 140	97.82 183	98.56 214

test_normal		96.24 247	95.12 272	99.60 122	96.00 325	99.16 144	100.00 1	99.29 212	96.43 194	88.96 324	98.40 311	80.06 329	99.90 138	98.53 180	98.39 147	99.75 184

DI_MVS_plusplus_test		96.28 246	95.16 270	99.61 119	96.01 324	99.18 143	100.00 1	99.29 212	96.49 193	89.08 321	98.42 310	80.06 329	99.90 138	98.74 170	98.39 147	99.75 184

tpmvs		98.59 149	98.38 156	99.23 157	99.69 133	97.90 222	99.31 303	99.47 83	94.52 247	99.68 154	99.28 256	97.64 130	99.89 140	97.71 213	98.17 164	99.89 142

Test_1112_low_res		98.83 137	98.60 145	99.51 133	99.69 133	98.75 165	99.99 176	99.14 262	96.81 171	98.84 201	99.06 264	97.45 134	99.89 140	98.66 172	97.75 189	99.89 142

1112_ss		98.91 132	98.71 134	99.51 133	99.69 133	98.75 165	99.99 176	99.15 258	96.82 170	98.84 201	100.00 1	97.45 134	99.89 140	98.66 172	97.75 189	99.89 142

IB-MVS	96.24 12	97.54 189	96.95 196	99.33 149	99.67 137	98.10 210	100.00 1	99.47 83	97.42 137	99.26 176	99.69 214	98.83 101	99.89 140	99.43 130	78.77 336	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
tpm cat1		98.05 173	97.76 178	98.92 175	99.50 179	97.10 253	99.77 249	99.30 208	90.20 311	99.72 145	98.71 297	97.71 128	99.86 144	96.75 244	98.20 162	99.81 173

tpmrst		98.98 125	98.93 112	99.14 162	99.61 150	97.74 230	99.52 287	99.36 183	96.05 208	99.98 81	99.64 227	99.04 83	99.86 144	98.94 159	98.19 163	99.82 171

MDTV_nov1_ep13			98.94 111		99.53 167	98.36 183	99.39 296	99.46 95	96.54 189	99.99 76	99.63 231	98.92 96	99.86 144	98.30 190	98.71 133

OMC-MVS		99.27 91	99.38 66	98.96 172	99.95 82	97.06 254	100.00 1	99.40 156	98.83 31	99.88 122	100.00 1	97.01 143	99.86 144	99.47 129	99.84 111	99.97 97

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	99.98 142	99.94 4	99.85 148	99.17 150	97.91 174	100.00 1

diffmvs		98.52 156	98.11 166	99.73 112	99.59 155	99.47 119	100.00 1	99.19 248	93.68 272	99.70 153	99.75 205	95.07 188	99.84 149	97.57 217	98.48 139	99.89 142

PatchFormer-LS_test		99.14 106	99.12 95	99.19 159	99.54 164	97.86 227	99.66 275	99.40 156	96.94 167	99.96 88	100.00 1	99.29 62	99.84 149	98.96 158	98.29 156	99.88 155

BH-untuned		98.64 147	98.65 140	98.60 190	99.59 155	96.17 267	100.00 1	99.28 220	96.67 182	98.41 231	100.00 1	94.52 196	99.83 151	99.41 136	100.00 1	99.81 173

DeepMVS_CX				89.98 323	98.90 231	71.46 349		99.18 252	97.61 123	96.92 279	99.83 193	86.07 301	99.83 151	96.02 247	97.65 202	98.65 212

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	99.98 142	99.94 4	99.82 153	98.87 163	97.87 177	100.00 1

DWT-MVSNet_test		99.22 100	99.22 79	99.22 158	99.56 163	97.98 217	99.89 224	99.39 170	97.20 150	99.96 88	100.00 1	99.52 29	99.82 153	99.11 154	98.34 153	99.87 162

dp		98.72 142	98.61 144	99.03 167	99.53 167	97.39 239	99.45 291	99.39 170	95.62 220	99.94 110	99.52 243	98.83 101	99.82 153	96.77 242	98.42 144	99.89 142

BH-RMVSNet		98.46 159	98.08 168	99.59 125	99.61 150	99.19 142	100.00 1	99.28 220	97.06 161	98.95 193	100.00 1	88.99 277	99.82 153	98.83 166	100.00 1	99.77 181

PMMVS		99.12 107	98.97 105	99.58 129	99.57 161	98.98 157	100.00 1	99.30 208	97.14 152	99.96 88	100.00 1	96.53 165	99.82 153	99.70 103	98.49 138	99.94 117

casdiffmvs		98.96 127	98.71 134	99.68 115	99.53 167	99.34 128	99.99 176	99.17 256	96.11 207	99.96 88	99.92 180	96.33 168	99.81 158	99.06 156	98.36 151	99.89 142

TR-MVS		98.14 171	97.74 179	99.33 149	99.59 155	98.28 190	99.27 305	99.21 245	96.42 196	99.15 183	99.94 177	88.87 279	99.79 159	98.88 162	98.29 156	99.93 126

Effi-MVS+		98.58 150	98.24 161	99.61 119	99.60 152	99.26 134	97.85 345	99.10 275	96.22 204	99.97 85	99.89 184	93.75 203	99.77 160	99.43 130	98.34 153	99.81 173

lupinMVS		99.29 89	99.16 86	99.69 114	99.45 183	99.49 114	100.00 1	99.15 258	97.45 134	99.97 85	100.00 1	96.76 158	99.76 161	99.67 108	100.00 1	99.81 173

EPP-MVSNet		99.10 109	99.00 101	99.40 142	99.51 176	98.68 169	99.92 218	99.43 116	95.47 229	99.65 155	100.00 1	99.51 31	99.76 161	99.53 126	98.00 170	99.75 184

CostFormer		98.84 136	98.77 129	99.04 166	99.41 187	97.58 235	99.67 273	99.35 191	94.66 243	99.96 88	99.36 251	99.28 65	99.74 163	99.41 136	97.81 184	99.81 173

Fast-Effi-MVS+		98.40 163	98.02 172	99.55 132	99.63 146	99.06 149	100.00 1	99.15 258	95.07 234	99.42 168	99.95 173	93.26 210	99.73 164	97.44 222	98.24 159	99.87 162

tpmp4_e23		98.71 143	98.66 137	98.84 180	99.60 152	96.98 256	99.83 233	99.35 191	94.29 253	99.90 118	99.50 245	99.17 75	99.73 164	98.22 192	98.13 165	99.81 173

jason		99.11 108	98.96 106	99.59 125	99.17 204	99.31 130	100.00 1	99.13 267	97.38 138	99.83 126	100.00 1	95.54 182	99.72 166	99.57 119	99.97 98	99.74 188
jason: jason.
EPMVS		99.25 95	99.13 93	99.60 122	99.60 152	99.20 141	99.60 280	100.00 1	96.93 168	99.92 116	99.36 251	99.05 82	99.71 167	98.77 168	98.94 129	99.90 137

conf0.01		99.32 80	99.16 86	99.80 95	99.79 117	99.73 88	100.00 1	99.71 63	97.66 112	99.71 147	100.00 1	99.78 6	99.70 168	98.15 195	97.67 196	99.97 97

conf0.002		99.32 80	99.16 86	99.80 95	99.79 117	99.73 88	100.00 1	99.71 63	97.66 112	99.71 147	100.00 1	99.78 6	99.70 168	98.15 195	97.67 196	99.97 97

thresconf0.02		99.32 80	99.16 86	99.79 99	99.79 117	99.73 88	100.00 1	99.71 63	97.66 112	99.71 147	100.00 1	99.78 6	99.70 168	98.15 195	97.67 196	99.94 117

tfpn_n400		99.32 80	99.16 86	99.79 99	99.79 117	99.73 88	100.00 1	99.71 63	97.66 112	99.71 147	100.00 1	99.78 6	99.70 168	98.15 195	97.67 196	99.94 117

tfpnconf		99.32 80	99.16 86	99.79 99	99.79 117	99.73 88	100.00 1	99.71 63	97.66 112	99.71 147	100.00 1	99.78 6	99.70 168	98.15 195	97.67 196	99.94 117

tfpnview11		99.32 80	99.16 86	99.79 99	99.79 117	99.73 88	100.00 1	99.71 63	97.66 112	99.71 147	100.00 1	99.78 6	99.70 168	98.15 195	97.67 196	99.94 117

Vis-MVSNet		98.52 156	98.25 160	99.34 148	99.68 136	98.55 174	99.68 272	99.41 154	97.34 142	99.94 110	100.00 1	90.38 259	99.70 168	99.03 157	98.84 130	99.76 183
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
TAPA-MVS	96.40 10	97.64 184	97.37 189	98.45 195	99.94 86	95.70 273	100.00 1	99.40 156	97.65 119	99.53 162	100.00 1	99.31 55	99.66 175	80.48 337	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
Fast-Effi-MVS+-dtu		98.38 164	98.56 148	97.82 244	99.58 159	94.44 300	100.00 1	99.16 257	96.75 173	99.51 163	99.63 231	95.03 190	99.60 176	97.71 213	99.67 117	99.42 205

PAPM		99.78 13	99.76 10	99.85 85	99.01 218	99.95 19	100.00 1	99.75 50	99.37 3	99.99 76	100.00 1	99.76 14	99.60 176	100.00 1	100.00 1	100.00 1

test_post1							99.32 302				88.24 351	99.33 51	99.59 178	98.31 189

test_post											89.05 349	99.49 37	99.59 178

ADS-MVSNet		98.70 145	98.51 151	99.28 153	99.51 176	98.39 179	99.24 308	99.44 107	95.52 225	99.96 88	99.70 212	97.57 132	99.58 180	97.11 230	98.54 135	99.88 155

Patchmatch-test		97.83 180	97.42 186	99.06 163	99.08 209	97.66 233	98.66 338	99.21 245	93.65 274	98.25 241	99.58 237	99.47 40	99.57 181	90.25 313	98.59 134	99.95 113

HQP4-MVS										99.17 179			99.57 181			97.77 218

HQP-MVS		97.73 181	97.85 176	97.39 257	99.07 210	94.82 284	100.00 1	99.40 156	99.04 13	99.17 179	99.97 152	88.61 281	99.57 181	99.79 91	95.58 215	97.77 218

CLD-MVS		97.64 184	97.74 179	97.36 259	99.01 218	94.76 292	100.00 1	99.34 196	99.30 4	99.00 191	99.97 152	87.49 290	99.57 181	99.96 66	95.58 215	97.75 224
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
OPM-MVS		97.21 196	97.18 194	97.32 260	98.08 275	94.66 294	100.00 1	99.28 220	98.65 42	98.92 194	99.98 142	86.03 303	99.56 185	98.28 191	95.41 221	97.72 263

LPG-MVS_test		97.31 193	97.32 190	97.28 262	98.85 237	94.60 297	100.00 1	99.37 177	97.35 140	98.85 199	99.98 142	86.66 297	99.56 185	99.55 120	95.26 226	97.70 271

LGP-MVS_train				97.28 262	98.85 237	94.60 297		99.37 177	97.35 140	98.85 199	99.98 142	86.66 297	99.56 185	99.55 120	95.26 226	97.70 271

ITE_SJBPF				96.84 286	98.96 228	93.49 308		98.12 330	98.12 74	98.35 233	99.97 152	84.45 309	99.56 185	95.63 255	95.25 228	97.49 303

ACMP	97.00 8	97.19 197	97.16 195	97.27 264	98.97 227	94.58 299	100.00 1	99.32 201	97.97 86	97.45 268	99.98 142	85.79 305	99.56 185	99.70 103	95.24 229	97.67 282
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
HQP_MVS		97.71 183	97.82 177	97.37 258	99.00 222	94.80 287	100.00 1	99.40 156	99.00 19	99.08 187	99.97 152	88.58 283	99.55 190	99.79 91	95.57 219	97.76 220

plane_prior5								99.40 156					99.55 190	99.79 91	95.57 219	97.76 220

ACMM	97.17 6	97.37 191	97.40 187	97.29 261	99.01 218	94.64 296	100.00 1	99.25 231	98.07 77	98.44 230	99.98 142	87.38 291	99.55 190	99.25 146	95.19 231	97.69 276
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
patchmatchnet-post											97.79 316	99.41 47	99.54 193

XVG-ACMP-BASELINE		96.60 229	96.52 211	96.84 286	98.41 249	93.29 311	99.99 176	99.32 201	97.76 105	98.51 227	99.29 255	81.95 322	99.54 193	98.40 184	95.03 237	97.68 278

ACMH+	96.20 13	96.49 235	96.33 220	97.00 271	99.06 214	93.80 306	99.81 240	99.31 206	97.32 143	95.89 297	99.97 152	82.62 320	99.54 193	98.34 188	94.63 243	97.65 289

ACMH	96.25 11	96.77 214	96.62 208	97.21 265	98.96 228	94.43 301	99.64 277	99.33 198	97.43 136	96.55 289	99.97 152	83.52 316	99.54 193	99.07 155	95.13 234	97.66 284
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TDRefinement		91.93 303	90.48 308	96.27 299	81.60 351	92.65 317	99.10 327	97.61 343	93.96 260	93.77 310	99.85 190	80.03 331	99.53 197	97.82 211	70.59 348	96.63 320

JIA-IIPM		97.09 202	96.34 219	99.36 146	98.88 233	98.59 172	99.81 240	99.43 116	84.81 336	99.96 88	90.34 348	98.55 114	99.52 198	97.00 232	98.28 158	99.98 92

IS-MVSNet		99.08 110	98.91 117	99.59 125	99.65 141	99.38 124	99.78 245	99.24 234	96.70 178	99.51 163	100.00 1	98.44 117	99.52 198	98.47 183	98.39 147	99.88 155

Effi-MVS+-dtu		98.51 158	98.86 122	97.47 255	99.77 125	94.21 303	100.00 1	98.94 306	97.61 123	99.91 117	98.75 295	95.89 172	99.51 200	99.36 138	99.48 121	98.68 210

PatchmatchNet		99.03 115	98.96 106	99.26 155	99.49 181	98.33 185	99.38 297	99.45 98	96.64 183	99.96 88	99.58 237	99.49 37	99.50 201	97.63 215	99.00 128	99.93 126
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
TinyColmap		95.50 272	95.12 272	96.64 292	98.69 239	93.00 313	99.40 295	97.75 340	96.40 198	96.14 293	99.87 186	79.47 333	99.50 201	93.62 285	94.72 242	97.40 308

LTVRE_ROB	95.29 16	96.32 244	96.10 233	96.99 272	98.55 244	93.88 305	99.45 291	99.28 220	94.50 248	96.46 290	99.52 243	84.86 308	99.48 203	97.26 227	95.03 237	97.59 299
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
tpm2		98.64 147	98.58 147	98.81 183	99.42 186	97.12 251	99.69 270	99.37 177	93.63 275	99.94 110	99.67 220	98.96 91	99.47 204	98.62 178	97.95 172	99.83 168

HyFIR lowres test		99.32 80	99.24 77	99.58 129	99.95 82	99.26 134	100.00 1	99.99 10	96.72 177	99.29 175	99.91 182	99.49 37	99.47 204	99.74 99	98.08 168	100.00 1

USDC		95.90 263	95.70 252	96.50 295	98.60 243	92.56 318	100.00 1	98.30 324	97.77 103	96.92 279	99.94 177	81.25 328	99.45 206	93.54 288	94.96 239	97.49 303

gm-plane-assit					99.52 173	97.26 247			95.86 213		100.00 1		99.43 207	98.76 169

MS-PatchMatch		95.66 270	95.87 243	95.05 306	97.80 292	89.25 328	98.88 335	99.30 208	96.35 200	96.86 282	99.01 278	81.35 327	99.43 207	93.30 289	99.98 95	96.46 321

CHOSEN 280x420		99.85 3	99.87 1	99.80 95	99.99 45	99.97 8	99.97 201	99.98 13	98.96 21	100.00 1	100.00 1	99.96 3	99.42 209	100.00 1	100.00 1	100.00 1

VPA-MVSNet		97.03 207	96.43 216	98.82 181	98.64 241	99.32 129	99.38 297	99.47 83	96.73 176	98.91 196	98.94 286	87.00 295	99.40 210	99.23 147	89.59 297	97.76 220

LF4IMVS		96.19 249	96.18 226	96.23 300	98.26 257	92.09 320	100.00 1	97.89 338	97.82 100	97.94 252	99.87 186	82.71 319	99.38 211	97.41 224	93.71 248	97.20 314

Patchmatch-test1		98.23 170	97.91 175	99.17 160	99.41 187	98.25 196	99.99 176	99.45 98	96.91 169	99.76 142	99.69 214	89.65 269	99.37 212	97.55 218	98.79 131	99.89 142

GA-MVS		97.72 182	97.27 191	99.06 163	99.24 203	97.93 221	100.00 1	99.24 234	95.80 216	98.99 192	99.64 227	89.77 267	99.36 213	95.12 264	97.62 203	99.89 142

XXY-MVS		97.14 201	96.63 207	98.67 187	98.65 240	98.92 160	99.54 285	99.29 212	95.57 222	97.63 262	99.83 193	87.79 288	99.35 214	98.39 185	92.95 257	97.75 224

GG-mvs-BLEND				99.59 125	99.54 164	99.49 114	99.17 322	99.52 76		99.96 88	99.68 219	100.00 1	99.33 215	99.71 101	99.99 88	99.96 108

EPNet_dtu		98.53 155	98.23 163	99.43 139	99.92 91	99.01 155	99.96 204	99.47 83	98.80 35	99.96 88	99.96 161	98.56 113	99.30 216	87.78 325	99.68 116	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
tpm		98.24 169	98.22 164	98.32 205	99.13 205	95.79 272	99.53 286	99.12 273	95.20 233	99.96 88	99.36 251	97.58 131	99.28 217	97.41 224	96.67 213	99.88 155

gg-mvs-nofinetune		96.95 211	96.10 233	99.50 135	99.41 187	99.36 127	99.07 331	99.52 76	83.69 339	99.96 88	83.60 356	100.00 1	99.20 218	99.68 106	99.99 88	99.96 108

TAMVS		98.76 140	98.73 132	98.86 179	99.44 185	97.69 231	99.57 282	99.34 196	96.57 187	99.12 184	99.81 199	98.83 101	99.16 219	97.97 208	97.91 174	99.73 192

MVP-Stereo		96.51 232	96.48 213	96.60 294	95.65 327	94.25 302	98.84 336	98.16 328	95.85 215	95.23 300	99.04 270	92.54 219	99.13 220	92.98 291	99.98 95	96.43 322
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
Vis-MVSNet (Re-imp)		98.99 123	98.89 121	99.29 152	99.64 145	98.89 161	99.98 194	99.31 206	96.74 174	99.48 165	100.00 1	98.11 122	99.10 221	98.39 185	98.34 153	99.89 142

EG-PatchMatch MVS		92.94 297	92.49 292	94.29 314	95.87 326	87.07 332	99.07 331	98.11 331	93.19 287	88.98 323	98.66 301	70.89 346	99.08 222	92.43 296	95.21 230	96.72 319

MVS-HIRNet		94.12 282	92.73 291	98.29 207	99.33 197	95.95 269	99.38 297	99.19 248	74.54 346	98.26 240	86.34 352	86.07 301	99.06 223	91.60 300	99.87 110	99.85 164

mvs_anonymous		98.80 139	98.60 145	99.38 145	99.57 161	99.24 138	100.00 1	99.21 245	95.87 211	98.92 194	99.82 196	96.39 167	99.03 224	99.13 152	98.50 137	99.88 155

TESTMET0.1,1		99.08 110	98.96 106	99.44 137	99.63 146	99.38 124	100.00 1	99.45 98	95.53 223	99.48 165	100.00 1	99.71 16	99.02 225	96.84 237	99.99 88	99.91 129

test-LLR		99.03 115	98.91 117	99.40 142	99.40 191	99.28 132	100.00 1	99.45 98	96.70 178	99.42 168	99.12 260	99.31 55	99.01 226	96.82 238	99.99 88	99.91 129

test-mter		98.96 127	98.82 124	99.40 142	99.40 191	99.28 132	100.00 1	99.45 98	95.44 232	99.42 168	99.12 260	99.70 17	99.01 226	96.82 238	99.99 88	99.91 129

tfpnnormal		96.36 241	95.69 254	98.37 200	98.55 244	98.71 167	99.69 270	99.45 98	93.16 288	96.69 288	99.71 209	88.44 285	98.99 228	94.17 277	91.38 273	97.41 307

nrg030		97.64 184	97.27 191	98.75 185	98.34 251	99.53 110	100.00 1	99.22 241	96.21 205	98.27 239	99.95 173	94.40 197	98.98 229	99.23 147	89.78 296	97.75 224

CVMVSNet		98.56 152	98.47 153	98.82 181	99.11 206	97.67 232	99.74 256	99.47 83	97.57 129	99.06 189	100.00 1	95.72 179	98.97 230	98.21 193	97.33 206	99.83 168

VPNet		96.41 237	95.76 249	98.33 204	98.61 242	98.30 189	99.48 290	99.45 98	96.98 162	98.87 198	99.88 185	81.57 324	98.93 231	99.22 149	87.82 313	97.76 220

v7n		96.06 259	95.42 264	97.99 237	97.58 303	97.35 242	99.86 230	99.11 274	92.81 292	97.91 254	99.49 246	90.99 250	98.92 232	92.51 294	88.49 309	97.70 271

jajsoiax		97.07 204	96.79 203	97.89 243	97.28 315	97.12 251	99.95 210	99.19 248	96.55 188	97.31 271	99.69 214	87.35 293	98.91 233	98.70 171	95.12 235	97.66 284

mvs_tets		97.00 209	96.69 205	97.94 239	97.41 314	97.27 246	99.60 280	99.18 252	96.51 192	97.35 270	99.69 214	86.53 299	98.91 233	98.84 164	95.09 236	97.65 289

CDS-MVSNet		98.96 127	98.95 110	99.01 168	99.48 182	98.36 183	99.93 216	99.37 177	96.79 172	99.31 174	99.83 193	99.77 13	98.91 233	98.07 203	97.98 171	99.77 181
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
FIs		97.95 177	97.73 181	98.62 189	98.53 246	99.24 138	100.00 1	99.43 116	96.74 174	97.87 255	99.82 196	95.27 185	98.89 236	98.78 167	93.07 255	97.74 248

v1192		96.18 250	95.49 260	98.26 211	98.01 283	98.15 207	99.99 176	99.08 286	93.36 282	98.54 223	98.97 284	89.47 272	98.89 236	91.15 303	90.82 278	97.75 224

UniMVSNet (Re)		97.29 195	96.85 200	98.59 192	98.49 247	99.13 145	100.00 1	99.42 122	96.52 191	98.24 242	98.90 289	94.93 192	98.89 236	97.54 220	87.61 314	97.75 224

EI-MVSNet		97.98 176	97.93 174	98.16 221	99.11 206	97.84 228	99.74 256	99.29 212	94.39 251	98.65 214	100.00 1	97.21 137	98.88 239	97.62 216	95.31 224	97.75 224

MVSTER		98.58 150	98.52 150	98.77 184	99.65 141	99.68 102	100.00 1	99.29 212	95.63 219	98.65 214	99.80 202	99.78 6	98.88 239	98.59 179	95.31 224	97.73 258

Anonymous20240521		96.99 210	96.48 213	98.53 193	98.07 276	99.07 147	99.76 252	99.23 238	94.26 254	96.16 292	98.68 298	94.96 191	98.87 241	96.76 243	90.41 286	97.66 284

v6		96.77 214	96.26 224	98.29 207	98.10 271	98.27 192	100.00 1	99.09 278	93.95 261	98.73 209	99.06 264	91.51 235	98.86 242	95.83 248	90.04 287	97.74 248

pm-mvs1		95.76 268	95.01 274	98.00 235	98.23 259	97.45 236	99.24 308	99.04 301	93.13 289	95.93 296	99.72 207	86.28 300	98.84 243	95.62 256	87.92 312	97.72 263

v1		96.66 223	96.12 231	98.30 206	98.09 272	98.33 185	100.00 1	99.09 278	93.69 271	98.68 212	99.04 270	91.42 239	98.83 244	95.05 265	89.99 291	97.75 224

v1neww		96.77 214	96.27 222	98.26 211	98.16 265	98.23 197	100.00 1	99.09 278	93.94 262	98.73 209	99.05 267	91.65 228	98.82 245	95.75 250	90.04 287	97.74 248

v7new		96.77 214	96.27 222	98.26 211	98.16 265	98.23 197	100.00 1	99.09 278	93.94 262	98.73 209	99.05 267	91.65 228	98.82 245	95.75 250	90.04 287	97.74 248

V42		96.65 225	96.16 228	98.11 228	98.17 264	98.23 197	99.99 176	99.09 278	93.97 259	98.74 208	99.05 267	91.09 248	98.82 245	95.46 258	89.90 294	97.27 313

CMPMVS	66.12 22	90.65 310	92.04 297	86.46 330	96.18 322	66.87 352	98.03 344	99.38 174	83.38 340	85.49 339	99.55 240	77.59 338	98.80 248	94.44 272	94.31 246	93.72 343
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PS-MVSNAJss		98.03 174	98.06 170	97.94 239	97.63 298	97.33 245	99.89 224	99.23 238	96.27 203	98.03 247	99.59 236	98.75 106	98.78 249	98.52 181	94.61 244	97.70 271

OurMVSNet-221017-0		96.14 255	95.98 239	96.62 293	97.49 308	93.44 309	99.92 218	98.16 328	95.86 213	97.65 261	99.95 173	85.71 306	98.78 249	94.93 268	94.18 247	97.64 292

OpenMVS_ROB	88.34 20	91.89 304	91.12 304	94.19 316	95.55 328	87.63 331	99.26 306	98.03 333	86.61 331	90.65 320	96.82 319	70.14 347	98.78 249	86.54 328	96.50 214	96.15 325

pmmvs6		93.64 284	92.87 289	95.94 303	97.47 310	91.41 325	98.92 333	99.02 302	87.84 329	95.01 301	99.61 235	77.24 339	98.77 252	94.33 275	86.41 321	97.63 293

v8		96.35 242	95.73 251	98.21 218	98.11 270	98.23 197	99.94 214	99.07 288	92.66 293	98.29 237	99.00 280	91.46 237	98.77 252	94.17 277	88.83 306	97.62 295

testing_2		90.79 309	88.26 315	98.35 202	89.11 342	98.56 173	99.70 266	99.14 262	93.70 270	73.80 347	94.06 343	55.19 350	98.76 254	97.17 228	92.50 261	97.74 248

Test4		92.63 298	90.45 309	99.17 160	92.81 335	99.02 152	99.98 194	99.13 267	96.60 186	82.04 344	96.27 323	51.35 353	98.75 255	97.55 218	98.36 151	99.75 184

v1141		96.66 223	96.12 231	98.26 211	98.05 279	98.28 190	100.00 1	99.09 278	93.71 266	98.59 219	99.04 270	91.57 232	98.73 256	95.05 265	90.00 290	97.75 224

divwei89l23v2f112		96.68 222	96.15 229	98.25 215	98.03 282	98.27 192	100.00 1	99.09 278	93.79 265	98.59 219	99.04 270	91.54 234	98.73 256	95.29 263	89.99 291	97.75 224

v52		95.88 267	95.35 266	97.48 254	97.66 296	97.38 241	99.88 227	99.07 288	92.19 295	98.09 243	99.02 277	90.06 263	98.72 258	93.58 286	88.61 308	96.34 323

V4		95.89 265	95.36 265	97.49 253	97.65 297	97.40 238	99.88 227	99.07 288	92.19 295	98.08 244	99.01 278	90.20 260	98.72 258	93.57 287	88.63 307	96.34 323

v1921920		96.16 253	95.50 258	98.14 222	97.88 291	97.96 219	99.99 176	99.07 288	93.33 283	98.60 218	99.24 257	89.37 273	98.71 260	91.28 301	90.74 281	97.75 224

v7		96.64 226	96.14 230	98.13 225	98.18 262	97.97 218	99.99 176	99.09 278	93.62 276	98.76 206	99.30 254	91.13 245	98.70 261	94.37 274	90.80 279	97.74 248

v748		95.47 273	94.95 276	97.04 268	97.46 311	94.76 292	99.93 216	99.10 275	91.95 298	97.11 276	99.18 259	89.94 266	98.68 262	94.01 281	85.88 323	97.67 282

lessismore_v0				96.05 301	97.55 304	91.80 322		99.22 241		91.87 316	99.91 182	83.50 317	98.68 262	92.48 295	90.42 285	97.68 278

v2v482		96.70 221	96.18 226	98.27 209	98.04 281	98.39 179	100.00 1	99.13 267	94.19 258	98.58 221	99.08 263	90.48 257	98.67 264	95.69 253	90.44 284	97.75 224

v144192		96.40 239	95.81 245	98.17 220	97.89 290	98.11 209	99.99 176	99.06 296	93.39 281	98.75 207	99.09 262	90.43 258	98.66 265	93.10 290	90.55 283	97.75 224

v1144		96.51 232	95.97 240	98.13 225	97.98 286	98.04 215	99.99 176	99.08 286	93.51 279	98.62 217	98.98 281	90.98 251	98.62 266	93.79 284	90.79 280	97.74 248

v1240		95.96 261	95.25 268	98.07 229	97.91 289	97.87 226	99.96 204	99.07 288	93.24 286	98.64 216	98.96 285	88.98 278	98.61 267	89.58 317	90.92 277	97.75 224

v10		96.14 255	95.50 258	98.07 229	98.19 261	97.96 219	99.83 233	99.07 288	92.10 297	98.07 246	98.94 286	91.07 249	98.61 267	92.41 297	89.82 295	97.63 293

anonymousdsp		97.16 199	96.88 198	98.00 235	97.08 317	98.06 213	99.81 240	99.15 258	94.58 245	97.84 256	99.62 233	90.49 256	98.60 269	97.98 205	95.32 223	97.33 312

v148		96.29 245	95.84 244	97.63 246	97.74 293	96.53 265	100.00 1	99.07 288	93.52 278	98.01 250	99.42 250	91.22 241	98.60 269	96.37 246	87.22 316	97.75 224

MVSFormer		98.94 130	98.82 124	99.28 153	99.45 183	99.49 114	100.00 1	99.13 267	95.46 230	99.97 85	100.00 1	96.76 158	98.59 271	98.63 176	100.00 1	99.74 188

test_djsdf		97.55 188	97.38 188	98.07 229	97.50 306	97.99 216	100.00 1	99.13 267	95.46 230	98.47 229	99.85 190	92.01 225	98.59 271	98.63 176	95.36 222	97.62 295

test_0402		94.35 280	93.70 282	96.32 298	97.92 288	93.60 307	99.61 279	98.85 311	88.19 328	94.68 303	99.48 247	80.01 332	98.58 273	89.39 320	95.15 233	96.77 318

FC-MVSNet-test		97.84 179	97.63 183	98.45 195	98.30 255	99.05 150	100.00 1	99.43 116	96.63 185	97.61 264	99.82 196	95.19 187	98.57 274	98.64 175	93.05 256	97.73 258

WR-MVS		97.09 202	96.64 206	98.46 194	98.43 248	99.09 146	99.97 201	99.33 198	95.62 220	97.76 257	99.67 220	91.17 243	98.56 275	98.49 182	89.28 300	97.74 248

WR-MVS_H		96.73 219	96.32 221	97.95 238	98.26 257	97.88 224	99.72 262	99.43 116	95.06 235	96.99 278	98.68 298	93.02 213	98.53 276	97.43 223	88.33 310	97.43 306

ambc				88.45 324	86.84 346	70.76 350	97.79 347	98.02 335		90.91 318	95.14 338	38.69 358	98.51 277	94.97 267	84.23 326	96.09 327

UniMVSNet_NR-MVSNet		97.16 199	96.80 201	98.22 216	98.38 250	98.41 177	100.00 1	99.45 98	96.14 206	97.76 257	99.64 227	95.05 189	98.50 278	97.98 205	86.84 317	97.75 224

DU-MVS		96.93 212	96.49 212	98.22 216	98.31 253	98.41 177	100.00 1	99.37 177	96.41 197	97.76 257	99.65 223	92.14 221	98.50 278	97.98 205	86.84 317	97.75 224

testpf		97.02 208	96.87 199	97.44 256	99.50 179	95.18 277	95.70 350	99.33 198	91.35 303	98.00 251	99.22 258	96.29 169	98.49 280	94.42 273	98.07 169	98.67 211

pmmvs4		97.17 198	96.80 201	98.27 209	97.68 295	98.64 171	100.00 1	99.18 252	94.22 256	98.55 222	99.71 209	93.67 204	98.47 281	95.66 254	92.57 260	97.71 270

pmmvs5		95.94 262	95.61 255	96.95 274	97.42 312	94.66 294	100.00 1	98.08 332	93.60 277	97.05 277	99.43 249	87.02 294	98.46 282	95.76 249	92.12 265	97.72 263

SixPastTwentyTwo		95.71 269	95.49 260	96.38 297	97.42 312	93.01 312	99.84 232	98.23 325	94.75 239	95.98 295	99.97 152	85.35 307	98.43 283	94.71 269	93.17 254	97.69 276

NR-MVSNet		96.63 227	96.04 236	98.38 199	98.31 253	98.98 157	99.22 316	99.35 191	95.87 211	94.43 306	99.65 223	92.73 216	98.40 284	96.78 241	88.05 311	97.75 224

TransMVSNet (Re)		94.78 278	93.72 281	97.93 241	98.34 251	97.88 224	99.23 314	97.98 336	91.60 301	94.55 304	99.71 209	87.89 286	98.36 285	89.30 322	84.92 324	97.56 301

Baseline_NR-MVSNet		96.16 253	95.70 252	97.56 251	98.28 256	96.79 260	100.00 1	97.86 339	91.93 299	97.63 262	99.47 248	92.14 221	98.35 286	97.13 229	86.83 319	97.54 302

semantic-postprocess				97.62 248	99.40 191	96.83 259		99.14 262	94.65 244	97.55 266	99.72 207	89.64 270	98.31 287	95.62 256	92.05 266	97.73 258

IterMVS		96.76 218	96.46 215	97.63 246	99.41 187	96.89 257	99.99 176	99.13 267	94.74 241	97.59 265	99.66 222	89.63 271	98.28 288	95.71 252	92.31 263	97.72 263
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test0.0.03 1		98.12 172	98.03 171	98.39 198	99.11 206	98.07 212	100.00 1	99.93 32	96.70 178	96.91 281	99.95 173	99.31 55	98.19 289	91.93 298	98.44 142	98.91 208

CP-MVSNet		96.73 219	96.25 225	98.18 219	98.21 260	98.67 170	99.77 249	99.32 201	95.06 235	97.20 275	99.65 223	90.10 261	98.19 289	98.06 204	88.90 304	97.66 284

PS-CasMVS		96.34 243	95.78 248	98.03 234	98.18 262	98.27 192	99.71 264	99.32 201	94.75 239	96.82 284	99.65 223	86.98 296	98.15 291	97.74 212	88.85 305	97.66 284

our_test_3		96.51 232	96.35 218	96.98 273	97.61 300	95.05 279	99.98 194	99.01 303	94.68 242	96.77 286	99.06 264	95.87 174	98.14 292	91.81 299	92.37 262	97.75 224

new_pmnet		94.11 283	93.47 285	96.04 302	96.60 320	92.82 315	99.97 201	98.91 309	90.21 310	95.26 299	98.05 315	85.89 304	98.14 292	84.28 331	92.01 267	97.16 315

K. test v3		95.46 274	95.14 271	96.40 296	97.53 305	93.40 310	99.99 176	99.23 238	95.49 228	92.70 315	99.73 206	84.26 311	98.12 294	93.94 283	93.38 253	97.68 278

Patchmtry		96.81 213	96.37 217	98.14 222	99.31 198	98.55 174	98.91 334	99.00 304	90.45 308	97.92 253	98.98 281	96.94 155	98.12 294	94.27 276	91.53 271	97.75 224

FMVSNet3		97.30 194	96.95 196	98.37 200	99.65 141	99.25 136	99.71 264	99.28 220	94.23 255	98.53 224	98.91 288	93.30 209	98.11 296	95.31 260	93.60 249	97.73 258

N_pmnet		91.88 305	93.37 286	87.40 328	97.24 316	66.33 353	99.90 221	91.05 358	89.77 317	95.65 298	98.58 304	90.05 264	98.11 296	85.39 329	92.72 259	97.75 224

IterMVS-LS		97.56 187	97.44 185	97.92 242	99.38 195	97.90 222	99.89 224	99.10 275	94.41 250	98.32 235	99.54 242	97.21 137	98.11 296	97.50 221	91.62 270	97.75 224
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CR-MVSNet		98.02 175	97.71 182	98.93 173	99.31 198	98.86 162	99.13 325	99.00 304	96.53 190	99.96 88	98.98 281	96.94 155	98.10 299	91.18 302	98.40 145	99.84 165

RPMNet		95.10 277	93.82 280	98.93 173	99.31 198	98.86 162	99.13 325	99.38 174	79.82 344	99.96 88	95.13 339	95.69 180	98.10 299	77.54 344	98.40 145	99.84 165

FMVSNet2		96.22 248	95.60 256	98.06 232	99.53 167	98.33 185	99.45 291	99.27 227	93.71 266	98.03 247	98.84 291	84.23 312	98.10 299	93.97 282	93.40 252	97.73 258

ppachtmachnet_test		96.17 252	95.89 242	97.02 270	97.61 300	95.24 275	99.99 176	99.24 234	93.31 284	96.71 287	99.62 233	94.34 199	98.07 302	89.87 315	92.30 264	97.75 224

GBi-Net		96.07 257	95.80 246	96.89 278	99.53 167	94.87 281	99.18 317	99.27 227	93.71 266	98.53 224	98.81 292	84.23 312	98.07 302	95.31 260	93.60 249	97.72 263

test1		96.07 257	95.80 246	96.89 278	99.53 167	94.87 281	99.18 317	99.27 227	93.71 266	98.53 224	98.81 292	84.23 312	98.07 302	95.31 260	93.60 249	97.72 263

FMVSNet1		94.45 279	93.63 283	96.89 278	98.87 235	94.87 281	99.18 317	99.27 227	90.95 307	97.31 271	98.81 292	72.89 344	98.07 302	92.61 292	92.81 258	97.72 263

PatchT		95.90 263	94.95 276	98.75 185	99.03 216	98.39 179	99.08 329	99.32 201	85.52 332	99.96 88	94.99 341	97.94 124	98.05 306	80.20 338	98.47 141	99.81 173

TranMVSNet+NR-MVSNet		96.45 236	96.01 237	97.79 245	98.00 285	97.62 234	100.00 1	99.35 191	95.98 209	97.31 271	99.64 227	90.09 262	98.00 307	96.89 236	86.80 320	97.75 224

ADS-MVSNet2		98.28 167	98.51 151	97.62 248	99.51 176	95.03 280	99.24 308	99.41 154	95.52 225	99.96 88	99.70 212	97.57 132	97.94 308	97.11 230	98.54 135	99.88 155

PEN-MVS		96.01 260	95.48 262	97.58 250	97.74 293	97.26 247	99.90 221	99.29 212	94.55 246	96.79 285	99.55 240	87.38 291	97.84 309	96.92 235	87.24 315	97.65 289

testgi		96.18 250	95.93 241	96.93 276	98.98 226	94.20 304	100.00 1	99.07 288	97.16 151	96.06 294	99.86 188	84.08 315	97.79 310	90.38 310	97.80 185	98.81 209

LP		95.89 265	95.35 266	97.51 252	98.92 230	95.15 278	98.66 338	99.39 170	89.43 322	97.22 274	99.03 275	94.37 198	97.74 311	83.71 332	97.44 204	99.63 200

MIMVSNet		97.06 205	96.73 204	98.05 233	99.38 195	96.64 264	98.47 341	99.35 191	93.41 280	99.48 165	98.53 305	89.66 268	97.70 312	94.16 279	98.11 167	99.80 180

LCM-MVSNet-Re		96.52 231	97.21 193	94.44 311	99.27 201	85.80 333	99.85 231	96.61 351	95.98 209	92.75 314	98.48 306	93.97 202	97.55 313	99.58 118	98.43 143	99.98 92

DTE-MVSNet		95.52 271	94.99 275	97.08 267	97.49 308	96.45 266	100.00 1	99.25 231	93.82 264	96.17 291	99.57 239	87.81 287	97.18 314	94.57 270	86.26 322	97.62 295

UnsupCasMVSNet_bld		89.50 313	88.00 316	93.99 317	95.30 329	88.86 329	98.52 340	99.28 220	85.50 335	87.80 335	94.11 342	61.63 349	96.96 315	90.63 306	79.26 333	96.15 325

MDA-MVSNet_test_wron		92.61 299	91.09 305	97.19 266	96.71 319	97.26 247	100.00 1	99.14 262	88.61 325	67.90 352	98.32 314	89.03 276	96.57 316	90.47 309	89.59 297	97.74 248

v18		93.55 285	92.42 293	96.91 277	98.12 268	98.26 195	99.83 233	98.74 313	89.99 313	88.94 325	95.64 328	92.02 224	96.54 317	90.27 312	78.26 337	95.94 331

v17		93.53 286	92.42 293	96.88 282	98.09 272	98.16 205	99.83 233	98.74 313	89.95 314	89.05 322	95.65 327	91.99 226	96.54 317	90.31 311	78.15 339	95.95 329

v16		93.48 288	92.34 295	96.89 278	98.13 267	98.19 203	99.82 238	98.74 313	89.94 315	88.90 326	95.62 329	91.65 228	96.54 317	90.03 314	78.22 338	95.95 329

UnsupCasMVSNet_eth		94.25 281	93.89 279	95.34 304	97.63 298	92.13 319	99.73 260	99.36 183	94.88 238	92.78 312	98.63 302	82.72 318	96.53 320	94.57 270	84.73 325	97.36 309

v15		93.28 290	92.08 296	96.87 283	98.07 276	98.22 201	99.82 238	98.74 313	89.83 316	88.74 328	95.44 333	91.55 233	96.47 321	89.70 316	76.87 341	95.93 332

V14		93.24 291	92.04 297	96.87 283	98.07 276	98.20 202	99.80 243	98.74 313	89.76 318	88.64 329	95.53 330	91.47 236	96.47 321	89.49 318	76.84 342	95.92 333

V9		93.20 292	91.99 299	96.85 285	98.05 279	98.16 205	99.77 249	98.73 319	89.67 319	88.64 329	95.44 333	91.34 240	96.47 321	89.46 319	76.79 343	95.92 333

v13		93.18 293	91.97 300	96.81 288	98.12 268	98.12 208	99.74 256	98.73 319	89.47 321	88.52 331	95.40 337	91.72 227	96.41 324	89.23 324	76.77 344	95.92 333

tmp_tt		75.80 327	74.26 328	80.43 337	52.91 364	53.67 362	87.42 355	97.98 336	61.80 351	67.04 353	100.00 1	76.43 341	96.40 325	96.47 245	28.26 359	91.23 347

v12		93.18 293	91.97 300	96.80 289	98.09 272	98.10 210	99.76 252	98.73 319	89.61 320	88.45 332	95.41 336	91.63 231	96.39 326	89.32 321	76.76 345	95.91 336

Gipuma		84.73 319	83.50 320	88.40 325	97.50 306	82.21 337	88.87 353	99.05 298	65.81 349	85.71 338	90.49 347	53.70 351	96.31 327	78.64 342	91.74 269	86.67 352
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
v11		93.14 295	91.93 302	96.77 291	98.01 283	98.17 204	99.72 262	98.74 313	89.39 323	88.81 327	95.49 332	91.15 244	96.29 328	86.78 327	79.25 334	95.86 338

YYNet1		92.44 301	90.92 306	97.03 269	96.20 321	97.06 254	99.99 176	99.14 262	88.21 327	67.93 351	98.43 309	88.63 280	96.28 329	90.64 305	89.08 303	97.74 248

EU-MVSNet		96.63 227	96.53 210	96.94 275	97.59 302	96.87 258	99.76 252	99.47 83	96.35 200	96.85 283	99.78 203	92.57 218	96.27 330	95.33 259	91.08 276	97.68 278

pmmvs-eth3d		91.73 306	90.67 307	94.92 309	91.63 338	92.71 316	99.90 221	98.54 322	91.19 305	88.08 333	95.50 331	79.31 335	96.13 331	90.55 308	81.32 331	95.91 336

PM-MVS		88.39 315	87.41 317	91.31 321	91.73 337	82.02 338	99.79 244	96.62 350	91.06 306	90.71 319	95.73 326	48.60 355	95.96 332	90.56 307	81.91 330	95.97 328

MDA-MVSNet-bldmvs		91.65 307	89.94 310	96.79 290	96.72 318	96.70 262	99.42 294	98.94 306	88.89 324	66.97 354	98.37 312	81.43 325	95.91 333	89.24 323	89.46 299	97.75 224

Patchmatch-RL test		93.49 287	93.63 283	93.05 319	91.78 336	83.41 336	98.21 343	96.95 347	91.58 302	91.05 317	97.64 317	99.40 48	95.83 334	94.11 280	81.95 329	99.91 129

Anonymous20231206		93.45 289	93.17 287	94.30 313	95.00 331	89.69 327	99.98 194	98.43 323	93.30 285	94.50 305	98.59 303	90.52 255	95.73 335	77.46 345	90.73 282	97.48 305

Anonymous20231211		84.35 320	82.41 321	90.15 322	89.14 341	78.88 339	98.71 337	98.22 326	70.20 348	86.88 336	95.44 333	47.11 357	95.72 336	81.14 335	74.88 346	95.84 339

DSMNet-mixed		95.18 276	95.21 269	95.08 305	96.03 323	90.21 326	99.65 276	93.64 356	92.91 291	98.34 234	97.40 318	90.05 264	95.51 337	91.02 304	97.86 178	99.51 204

pmmvs3		90.62 311	89.36 312	94.40 312	90.53 340	91.49 324	100.00 1	96.73 349	84.21 338	93.65 311	96.65 320	82.56 321	94.83 338	82.28 334	77.62 340	96.89 317

FMVSNet5		95.32 275	95.43 263	94.99 307	99.39 194	92.99 314	99.25 307	99.24 234	90.45 308	97.44 269	98.45 307	95.78 176	94.39 339	87.02 326	91.88 268	97.59 299

new-patchmatchnet		90.30 312	89.46 311	92.84 320	90.77 339	88.55 330	99.83 233	98.80 312	90.07 312	87.86 334	95.00 340	78.77 336	94.30 340	84.86 330	79.15 335	95.68 340

LCM-MVSNet		79.01 325	76.93 327	85.27 334	78.28 354	68.01 351	96.57 348	98.03 333	55.10 354	82.03 345	93.27 344	31.99 361	93.95 341	82.72 333	74.37 347	93.84 342

no-one		74.65 328	71.03 329	85.51 333	80.99 352	75.42 343	99.70 266	97.15 345	81.02 341	66.48 355	80.55 359	29.10 362	93.65 342	73.74 347	30.53 358	87.47 351

MIMVSNet1		91.96 302	91.20 303	94.23 315	94.94 332	91.69 323	99.34 301	99.22 241	88.23 326	94.18 307	98.45 307	75.52 342	93.41 343	79.37 340	91.49 272	97.60 298

test20.03		93.11 296	92.85 290	93.88 318	95.19 330	91.83 321	100.00 1	98.87 310	93.68 272	92.76 313	98.88 290	89.20 275	92.71 344	77.88 343	89.19 301	97.09 316

1111		88.62 314	89.13 313	87.08 329	87.71 343	77.22 341	99.96 204	97.71 341	85.51 333	83.47 342	96.26 324	95.76 177	90.96 345	66.63 351	89.17 302	93.07 344

.test1245		85.18 318	84.81 319	86.28 331	87.71 343	77.22 341	99.96 204	97.71 341	85.51 333	83.47 342	96.26 324	95.76 177	90.96 345	66.63 351	50.30 352	90.64 348

testus		91.61 308	92.92 288	87.70 327	93.91 333	74.98 344	100.00 1	98.19 327	92.59 294	93.90 309	98.68 298	81.43 325	90.77 347	79.82 339	97.71 195	97.34 311

PMMVS2		79.15 324	77.28 326	84.76 335	82.34 350	72.66 345	99.70 266	95.11 355	71.68 347	84.78 341	90.87 346	32.05 360	89.99 348	75.53 346	63.45 349	91.64 346

test2356		92.55 300	93.94 278	88.39 326	93.49 334	78.42 340	100.00 1	99.40 156	91.64 300	93.93 308	98.74 296	91.11 246	88.67 349	79.37 340	97.79 186	98.08 216

test1235678		88.02 316	88.73 314	85.90 332	87.57 345	71.70 348	100.00 1	97.42 344	87.52 330	86.19 337	96.39 322	81.60 323	87.93 350	70.72 348	91.18 275	98.08 216

FPMVS		77.92 326	79.45 324	73.34 344	76.87 356	46.81 363	98.24 342	99.05 298	59.89 353	73.55 348	98.34 313	36.81 359	86.55 351	80.96 336	91.35 274	86.65 353

PMVS	60.66 23	65.98 334	65.05 333	68.75 348	55.06 363	38.40 364	88.19 354	96.98 346	48.30 359	44.82 360	88.52 350	12.22 367	86.49 352	67.58 350	83.79 327	81.35 357
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
test12356		86.30 317	87.15 318	83.77 336	84.24 348	72.00 346	99.94 214	96.80 348	84.63 337	85.16 340	96.51 321	77.02 340	86.31 353	70.06 349	89.93 293	93.00 345

testmv		79.83 322	79.77 323	79.99 339	78.22 355	63.55 356	99.67 273	95.51 354	80.89 342	76.24 346	92.90 345	52.16 352	86.10 354	62.45 354	79.90 332	90.33 350

PNet_i23d		69.93 330	67.61 332	76.86 340	75.89 357	62.08 359	97.85 345	88.23 360	61.04 352	55.65 357	84.10 355	19.35 364	83.21 355	66.45 353	59.98 350	85.29 355

wuykxyi23d		62.75 335	59.23 336	73.34 344	61.53 360	59.39 361	93.28 352	86.17 364	53.70 355	46.89 359	77.89 360	12.35 365	79.96 356	60.86 357	40.35 356	80.68 358

MVE	68.59 21	67.22 332	64.68 334	74.84 341	74.67 359	62.32 358	95.84 349	90.87 359	50.98 356	58.72 356	81.05 357	12.20 368	78.95 357	61.06 356	56.75 351	83.24 356
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN		70.72 329	70.06 330	72.69 346	83.92 349	65.48 355	99.95 210	92.72 357	49.88 357	72.30 349	86.26 353	47.17 356	77.43 358	53.83 358	44.49 354	75.17 360

EMVS		69.88 331	69.09 331	72.24 347	84.70 347	65.82 354	99.96 204	87.08 363	49.82 358	71.51 350	84.74 354	49.30 354	75.32 359	50.97 359	43.71 355	75.59 359

test123		79.44 323	79.23 325	80.05 338	80.03 353	71.72 347	100.00 1	77.93 365	62.52 350	94.81 302	99.69 214	78.21 337	74.53 360	92.57 293	27.33 360	93.90 341

testmvs		80.17 321	81.95 322	74.80 342	58.54 362	59.58 360	100.00 1	87.14 362	76.09 345	99.61 157	100.00 1	67.06 348	74.19 361	98.84 164	50.30 352	90.64 348

ANet_high		66.05 333	63.44 335	73.88 343	61.14 361	63.45 357	95.68 351	87.18 361	79.93 343	47.35 358	80.68 358	22.35 363	72.33 362	61.24 355	35.42 357	85.88 354

wuyk23d		28.28 337	29.73 339	23.92 350	75.89 357	32.61 365	66.50 356	12.88 366	16.09 360	14.59 361	16.59 362	12.35 365	32.36 363	39.36 360	13.36 361	6.79 361

cdsmvs_eth3d_5k		24.41 338	32.55 338	0.00 351	0.00 365	0.00 366	0.00 357	99.39 170	0.00 361	0.00 362	100.00 1	93.55 206	0.00 364	0.00 361	0.00 362	0.00 362

pcd_1.5k_mvsjas		8.24 340	10.99 341	0.00 351	0.00 365	0.00 366	0.00 357	0.00 367	0.00 361	0.00 362	0.14 363	98.75 106	0.00 364	0.00 361	0.00 362	0.00 362

pcd1.5k->3k		40.07 336	42.58 337	32.57 349	97.97 287	0.00 366	0.00 357	99.25 231	0.00 361	0.00 362	0.14 363	91.10 247	0.00 364	0.00 361	94.75 240	97.70 271

sosnet-low-res		0.01 341	0.02 342	0.00 351	0.00 365	0.00 366	0.00 357	0.00 367	0.00 361	0.00 362	0.14 363	0.00 369	0.00 364	0.00 361	0.00 362	0.00 362

sosnet		0.01 341	0.02 342	0.00 351	0.00 365	0.00 366	0.00 357	0.00 367	0.00 361	0.00 362	0.14 363	0.00 369	0.00 364	0.00 361	0.00 362	0.00 362

uncertanet		0.01 341	0.02 342	0.00 351	0.00 365	0.00 366	0.00 357	0.00 367	0.00 361	0.00 362	0.14 363	0.00 369	0.00 364	0.00 361	0.00 362	0.00 362

Regformer		0.01 341	0.02 342	0.00 351	0.00 365	0.00 366	0.00 357	0.00 367	0.00 361	0.00 362	0.14 363	0.00 369	0.00 364	0.00 361	0.00 362	0.00 362

ab-mvs-re		8.33 339	11.11 340	0.00 351	0.00 365	0.00 366	0.00 357	0.00 367	0.00 361	0.00 362	100.00 1	0.00 369	0.00 364	0.00 361	0.00 362	0.00 362

uanet		0.01 341	0.02 342	0.00 351	0.00 365	0.00 366	0.00 357	0.00 367	0.00 361	0.00 362	0.14 363	0.00 369	0.00 364	0.00 361	0.00 362	0.00 362

GSMVS																99.91 129

test_part2					100.00 1	99.99 1				100.00 1

test_part1								99.42 122				99.53 26			100.00 1	100.00 1

sam_mvs1												99.29 62				99.91 129

sam_mvs												99.33 51

MTGPA								99.42 122

MTMP								99.18 252

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 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

新几何2							100.00 1

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

原ACMM2							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

segment_acmp												99.55 24

testdata1							100.00 1		98.77 37

plane_prior7					99.00 222	94.78 291

plane_prior6					99.06 214	94.80 287						88.58 283

plane_prior4											99.97 152

plane_prior3						94.79 290			99.03 16	99.08 187

plane_prior2							100.00 1		99.00 19

plane_prior1					99.02 217

plane_prior						94.80 287	100.00 1		99.03 16						95.58 215

n2								0.00 367

nn								0.00 367

door-mid								96.32 352

test11								99.42 122

door								96.13 353

HQP5-MVS						94.82 284

HQP-NCC					99.07 210		100.00 1		99.04 13	99.17 179

ACMP_Plane					99.07 210		100.00 1		99.04 13	99.17 179

BP-MVS														99.79 91

HQP3-MVS								99.40 156							95.58 215

HQP2-MVS												88.61 281

NP-MVS					99.07 210	94.81 286					99.97 152

MDTV_nov1_ep13_2view						99.24 138	99.56 283		96.31 202	99.96 88		98.86 100		98.92 160		99.89 142

ACMMP++_ref															94.58 245

ACMMP++															95.17 232

Test By Simon												99.10 79

High-resolution multi-view benchmark