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.

GG-mvs-BLEND				99.59 133	99.54 173	99.49 118	99.17 329	99.52 77		99.96 91	99.68 228	100.00 1	99.33 223	99.71 104	99.99 87	99.96 108

gg-mvs-nofinetune		96.95 218	96.10 241	99.50 143	99.41 198	99.36 133	99.07 340	99.52 77	83.69 348	99.96 91	83.60 364	100.00 1	99.20 226	99.68 109	99.99 87	99.96 108

CHOSEN 280x420		99.85 3	99.87 1	99.80 98	99.99 46	99.97 8	99.97 209	99.98 13	98.96 21	100.00 1	100.00 1	99.96 3	99.42 217	100.00 1	100.00 1	100.00 1

tfpn1000		99.47 72	99.34 75	99.87 84	99.89 98	99.80 83	100.00 1	99.72 62	97.83 98	99.96 91	99.98 149	99.94 4	99.82 159	98.87 170	97.87 182	100.00 1

tfpn_ndepth		99.52 63	99.39 65	99.89 78	99.90 96	99.83 75	100.00 1	99.72 62	97.95 89	99.96 91	99.98 149	99.94 4	99.85 151	99.17 154	97.91 179	100.00 1

0601test		99.51 64	99.37 69	99.95 47	99.82 101	99.90 45	100.00 1	99.47 84	97.48 134	100.00 1	100.00 1	99.80 6	100.00 1	99.98 58	97.75 194	99.94 117

Anonymous20240521		99.51 64	99.37 69	99.95 47	99.82 101	99.90 45	100.00 1	99.47 84	97.48 134	100.00 1	100.00 1	99.80 6	100.00 1	99.98 58	97.75 194	99.94 117

conf0.01		99.32 86	99.16 92	99.80 98	99.79 122	99.73 91	100.00 1	99.71 64	97.66 113	99.71 157	100.00 1	99.78 8	99.70 176	98.15 205	97.67 203	99.97 97

conf0.002		99.32 86	99.16 92	99.80 98	99.79 122	99.73 91	100.00 1	99.71 64	97.66 113	99.71 157	100.00 1	99.78 8	99.70 176	98.15 205	97.67 203	99.97 97

thresconf0.02		99.32 86	99.16 92	99.79 102	99.79 122	99.73 91	100.00 1	99.71 64	97.66 113	99.71 157	100.00 1	99.78 8	99.70 176	98.15 205	97.67 203	99.94 117

tfpn_n400		99.32 86	99.16 92	99.79 102	99.79 122	99.73 91	100.00 1	99.71 64	97.66 113	99.71 157	100.00 1	99.78 8	99.70 176	98.15 205	97.67 203	99.94 117

tfpnconf		99.32 86	99.16 92	99.79 102	99.79 122	99.73 91	100.00 1	99.71 64	97.66 113	99.71 157	100.00 1	99.78 8	99.70 176	98.15 205	97.67 203	99.94 117

tfpnview11		99.32 86	99.16 92	99.79 102	99.79 122	99.73 91	100.00 1	99.71 64	97.66 113	99.71 157	100.00 1	99.78 8	99.70 176	98.15 205	97.67 203	99.94 117

MVSTER		98.58 159	98.52 159	98.77 193	99.65 147	99.68 105	100.00 1	99.29 221	95.63 227	98.65 224	99.80 211	99.78 8	98.88 248	98.59 188	95.31 232	97.73 266

CDS-MVSNet		98.96 134	98.95 116	99.01 177	99.48 193	98.36 190	99.93 224	99.37 186	96.79 175	99.31 183	99.83 201	99.77 15	98.91 242	98.07 213	97.98 176	99.77 189
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PAPM		99.78 14	99.76 10	99.85 88	99.01 229	99.95 19	100.00 1	99.75 51	99.37 3	99.99 79	100.00 1	99.76 16	99.60 184	100.00 1	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 77	97.99 82	99.99 79	100.00 1	99.72 17	100.00 1	99.96 67	100.00 1	100.00 1

TESTMET0.1,1		99.08 116	98.96 112	99.44 145	99.63 152	99.38 129	100.00 1	99.45 105	95.53 231	99.48 174	100.00 1	99.71 18	99.02 233	96.84 246	99.99 87	99.91 132

test-mter		98.96 134	98.82 131	99.40 150	99.40 202	99.28 138	100.00 1	99.45 105	95.44 241	99.42 177	99.12 270	99.70 19	99.01 234	96.82 247	99.99 87	99.91 132

HSP-MVS		99.81 9	99.77 8	99.94 62	100.00 1	99.86 69	100.00 1	99.42 130	98.87 30	100.00 1	100.00 1	99.65 20	99.96 118	100.00 1	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 21	100.00 1	100.00 1	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 84	97.87 96	100.00 1	100.00 1	99.60 21	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 64	99.07 8	100.00 1	100.00 1	99.59 23	100.00 1	100.00 1	100.00 1	100.00 1

PLC	98.56 2	99.70 36	99.74 13	99.58 137	100.00 1	98.79 171	100.00 1	99.54 76	98.58 46	99.96 91	100.00 1	99.59 23	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
APDe-MVS		99.84 6	99.78 6	99.99 4	100.00 1	99.98 5	100.00 1	99.44 114	99.06 10	100.00 1	100.00 1	99.56 25	99.99 86	100.00 1	100.00 1	100.00 1

segment_acmp												99.55 26

TEST9					100.00 1	99.95 19	100.00 1	99.42 130	97.65 120	100.00 1	100.00 1	99.53 27	99.97 103

DWT-MVSNet_test		99.22 106	99.22 85	99.22 166	99.56 172	97.98 224	99.89 232	99.39 179	97.20 153	99.96 91	100.00 1	99.52 28	99.82 159	99.11 158	98.34 158	99.87 165

SteuartSystems-ACMMP		99.78 14	99.71 17	99.98 16	99.76 133	99.95 19	100.00 1	99.42 130	98.69 39	100.00 1	100.00 1	99.52 28	99.99 86	100.00 1	100.00 1	100.00 1
Skip Steuart: Steuart Systems R&D Blog.
train_agg		99.71 32	99.63 39	99.97 24	100.00 1	99.95 19	100.00 1	99.42 130	97.70 110	100.00 1	100.00 1	99.51 30	99.97 103	100.00 1	100.00 1	100.00 1

test_8					100.00 1	99.91 39	100.00 1	99.42 130	97.70 110	100.00 1	100.00 1	99.51 30	99.98 99

agg_prior3		99.71 32	99.63 39	99.97 24	100.00 1	99.95 19	100.00 1	99.42 130	97.71 109	100.00 1	100.00 1	99.51 30	99.97 103	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 61	100.00 1	99.42 130	97.72 106	100.00 1	100.00 1	99.51 30	99.97 103	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 84	98.16 67	100.00 1	100.00 1	99.51 30	100.00 1	100.00 1	100.00 1	100.00 1

EPP-MVSNet		99.10 115	99.00 107	99.40 150	99.51 187	98.68 176	99.92 226	99.43 123	95.47 238	99.65 164	100.00 1	99.51 30	99.76 169	99.53 129	98.00 175	99.75 192

test_post											89.05 357	99.49 36	99.59 186

HyFIR lowres test		99.32 86	99.24 82	99.58 137	99.95 84	99.26 141	100.00 1	99.99 10	96.72 180	99.29 184	99.91 190	99.49 36	99.47 212	99.74 102	98.08 173	100.00 1

PatchmatchNet		99.03 122	98.96 112	99.26 163	99.49 192	98.33 192	99.38 304	99.45 105	96.64 187	99.96 91	99.58 246	99.49 36	99.50 209	97.63 225	99.00 131	99.93 128
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Patchmatch-test		97.83 188	97.42 194	99.06 171	99.08 220	97.66 240	98.66 346	99.21 256	93.65 281	98.25 251	99.58 246	99.47 39	99.57 189	90.25 321	98.59 137	99.95 113

test_prior3		99.81 9	99.78 6	99.90 75	100.00 1	99.75 88	100.00 1	99.73 56	98.82 34	100.00 1	100.00 1	99.47 39	99.97 103	100.00 1	100.00 1	100.00 1

test_prior2							100.00 1		98.82 34	100.00 1	100.00 1	99.47 39		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	99.43 123	99.05 12	100.00 1	100.00 1	99.45 42	99.99 86	100.00 1	100.00 1	100.00 1

thisisatest0530		99.37 80	99.27 78	99.69 118	99.59 162	99.41 126	100.00 1	99.46 99	96.46 198	99.90 126	100.00 1	99.44 43	99.85 151	98.97 163	99.58 121	99.80 186

tttt0517		99.34 84	99.23 84	99.67 121	99.57 169	99.38 129	100.00 1	99.46 99	96.33 207	99.89 130	100.00 1	99.44 43	99.84 155	98.93 166	99.46 124	99.78 188

thisisatest0515		99.42 75	99.31 77	99.74 113	99.59 162	99.55 112	100.00 1	99.46 99	96.65 186	99.92 123	100.00 1	99.44 43	99.85 151	99.09 159	99.63 119	99.81 177

PGM-MVS		99.69 39	99.61 44	99.95 47	99.99 46	99.85 73	100.00 1	99.58 74	97.69 112	100.00 1	100.00 1	99.44 43	100.00 1	99.79 94	100.00 1	100.00 1

SMA-MVS		99.69 39	99.59 46	99.98 16	99.99 46	99.93 32	100.00 1	99.43 123	97.50 133	100.00 1	100.00 1	99.43 47	100.00 1	100.00 1	100.00 1	100.00 1

原ACMM1				99.93 65	100.00 1	99.80 83		99.66 72	98.18 66	100.00 1	100.00 1	99.43 47	100.00 1	99.50 131	100.00 1	100.00 1

testdata				99.66 123	99.99 46	98.97 166		99.73 56	97.96 88	100.00 1	100.00 1	99.42 49	100.00 1	99.28 148	100.00 1	100.00 1

patchmatchnet-post											97.79 325	99.41 50	99.54 201

Patchmatch-RL test		93.49 296	93.63 292	93.05 328	91.78 346	83.41 345	98.21 351	96.95 356	91.58 309	91.05 327	97.64 326	99.40 51	95.83 342	94.11 288	81.95 337	99.91 132

1121		99.63 53	99.51 57	99.99 4	99.99 46	99.96 10	99.24 315	99.74 54	97.89 93	100.00 1	100.00 1	99.39 52	100.00 1	99.33 144	100.00 1	100.00 1

CNVR-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 1	100.00 1	99.77 46	99.07 8	100.00 1	100.00 1	99.39 52	100.00 1	100.00 1	100.00 1	100.00 1

sam_mvs												99.33 54

test_post1							99.32 309				88.24 359	99.33 54	99.59 186	98.31 198

SD-MVS		99.81 9	99.75 12	99.99 4	99.99 46	99.96 10	100.00 1	99.42 130	99.01 18	100.00 1	100.00 1	99.33 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	99.42 130	98.02 80	100.00 1	100.00 1	99.32 57	99.99 86	100.00 1	100.00 1	100.00 1

HFP-MVS		99.74 23	99.67 27	99.96 36	100.00 1	99.89 51	100.00 1	99.76 47	97.95 89	100.00 1	100.00 1	99.31 58	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 51	100.00 1	99.76 47	98.07 77	100.00 1	100.00 1	99.31 58	100.00 1	99.99 44	100.00 1	100.00 1

test-LLR		99.03 122	98.91 123	99.40 150	99.40 202	99.28 138	100.00 1	99.45 105	96.70 181	99.42 177	99.12 270	99.31 58	99.01 234	96.82 247	99.99 87	99.91 132

test0.0.03 1		98.12 180	98.03 179	98.39 206	99.11 217	98.07 219	100.00 1	99.93 32	96.70 181	96.91 292	99.95 180	99.31 58	98.19 297	91.93 306	98.44 145	98.91 216

MCST-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 1	100.00 1	99.73 56	99.19 5	100.00 1	100.00 1	99.31 58	100.00 1	100.00 1	100.00 1	100.00 1

TAPA-MVS	96.40 10	97.64 192	97.37 197	98.45 203	99.94 88	95.70 282	100.00 1	99.40 164	97.65 120	99.53 171	100.00 1	99.31 58	99.66 183	80.48 344	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
test222					99.99 46	99.90 45	100.00 1	99.69 71	97.66 113	100.00 1	100.00 1	99.30 64			100.00 1	100.00 1

sam_mvs1												99.29 65				99.91 132

ACMMPR		99.74 23	99.67 27	99.96 36	100.00 1	99.89 51	100.00 1	99.76 47	97.95 89	100.00 1	100.00 1	99.29 65	100.00 1	99.99 44	100.00 1	100.00 1

PatchFormer-LS_test		99.14 112	99.12 101	99.19 167	99.54 173	97.86 234	99.66 282	99.40 164	96.94 170	99.96 91	100.00 1	99.29 65	99.84 155	98.96 164	98.29 161	99.88 158

CostFormer		98.84 144	98.77 136	99.04 175	99.41 198	97.58 242	99.67 280	99.35 200	94.66 252	99.96 91	99.36 261	99.28 68	99.74 171	99.41 139	97.81 189	99.81 177

旧先验1					99.99 46	99.88 61		99.82 41			100.00 1	99.27 69			100.00 1	100.00 1

APD-MVS		99.68 43	99.58 49	99.97 24	99.99 46	99.96 10	100.00 1	99.42 130	97.53 131	100.00 1	100.00 1	99.27 69	99.97 103	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
test12				99.95 47	99.99 46	99.89 51		99.42 130		100.00 1		99.24 71	99.97 103		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	99.44 114	98.43 50	100.00 1	100.00 1	99.23 72	99.99 86	99.99 44	100.00 1	100.00 1

ESAPD		99.79 12	99.73 14	99.99 4	99.99 46	99.98 5	100.00 1	99.42 130	98.91 26	100.00 1	100.00 1	99.22 73	100.00 1	100.00 1	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	99.44 114	98.42 52	100.00 1	100.00 1	99.22 73	99.99 86	99.99 44	100.00 1	100.00 1

HPM-MVS++		99.82 7	99.76 10	99.99 4	99.99 46	99.98 5	100.00 1	99.83 40	98.88 28	99.96 91	100.00 1	99.21 75	100.00 1	100.00 1	100.00 1	99.99 90

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 76	100.00 1	97.91 219	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 54	97.86 97	100.00 1	100.00 1	99.19 77	100.00 1	99.99 44	100.00 1	100.00 1

F-COLMAP		99.64 50	99.64 35	99.67 121	99.99 46	99.07 155	100.00 1	99.44 114	98.30 64	99.90 126	100.00 1	99.18 78	99.99 86	99.91 77	100.00 1	99.94 117

tpmp4_e23		98.71 152	98.66 144	98.84 189	99.60 158	96.98 265	99.83 241	99.35 200	94.29 262	99.90 126	99.50 254	99.17 79	99.73 172	98.22 202	98.13 170	99.81 177

XVS		99.79 12	99.73 14	99.98 16	100.00 1	99.94 27	100.00 1	99.75 51	98.67 41	100.00 1	100.00 1	99.16 80	100.00 1	100.00 1	100.00 1	100.00 1

X-MVStestdata		97.04 214	96.06 243	99.98 16	100.00 1	99.94 27	100.00 1	99.75 51	98.67 41	100.00 1	66.97 369	99.16 80	100.00 1	100.00 1	100.00 1	100.00 1

CNLPA		99.72 29	99.65 31	99.91 72	99.97 78	99.72 98	100.00 1	99.47 84	98.43 50	99.88 132	100.00 1	99.14 82	100.00 1	99.97 65	100.00 1	100.00 1

Test By Simon												99.10 83

CP-MVS		99.67 46	99.58 49	99.95 47	100.00 1	99.84 74	100.00 1	99.42 130	97.77 103	100.00 1	100.00 1	99.07 84	100.00 1	100.00 1	100.00 1	100.00 1

alignmvs		99.38 78	99.21 86	99.91 72	99.73 136	99.92 36	100.00 1	99.51 81	97.61 124	100.00 1	100.00 1	99.06 85	99.93 137	99.83 88	97.12 214	99.90 140

EPMVS		99.25 101	99.13 99	99.60 130	99.60 158	99.20 148	99.60 287	100.00 1	96.93 171	99.92 123	99.36 261	99.05 86	99.71 175	98.77 175	98.94 132	99.90 140

EI-MVSNet-Vis-set		99.70 36	99.64 35	99.87 84	100.00 1	99.64 108	99.98 202	99.44 114	98.35 60	99.99 79	100.00 1	99.04 87	99.96 118	99.98 58	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	99.42 130	97.91 92	100.00 1	100.00 1	99.04 87	100.00 1	100.00 1	100.00 1	100.00 1

tpmrst		98.98 132	98.93 118	99.14 170	99.61 156	97.74 237	99.52 294	99.36 192	96.05 215	99.98 84	99.64 236	99.04 87	99.86 147	98.94 165	98.19 168	99.82 175

Regformer-3		99.73 26	99.65 31	99.96 36	100.00 1	99.89 51	100.00 1	99.44 114	98.40 53	100.00 1	100.00 1	99.03 90	99.97 103	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 51	100.00 1	99.44 114	98.40 53	100.00 1	100.00 1	99.03 90	99.97 103	99.99 44	100.00 1	100.00 1

EI-MVSNet-UG-set		99.69 39	99.63 39	99.87 84	99.99 46	99.64 108	99.95 218	99.44 114	98.35 60	100.00 1	100.00 1	98.98 92	99.97 103	99.98 58	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 48	99.55 55	99.97 24	99.99 46	99.91 39	100.00 1	99.48 83	97.54 130	100.00 1	100.00 1	98.97 93	99.99 86	99.98 58	100.00 1	100.00 1

EPNet		99.62 54	99.69 19	99.42 148	99.99 46	98.37 189	100.00 1	99.89 38	98.83 32	100.00 1	100.00 1	98.97 93	100.00 1	99.90 78	99.61 120	99.89 145
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
tpm2		98.64 156	98.58 155	98.81 192	99.42 197	97.12 260	99.69 277	99.37 186	93.63 282	99.94 117	99.67 229	98.96 95	99.47 212	98.62 186	97.95 177	99.83 171

TSAR-MVS + GP.		99.61 56	99.69 19	99.35 155	99.99 46	98.06 220	100.00 1	99.36 192	99.83 2	100.00 1	100.00 1	98.95 96	99.99 86	100.00 1	99.11 127	100.00 1

HPM-MVS_fast		99.60 59	99.49 60	99.91 72	99.99 46	99.78 85	100.00 1	99.42 130	97.09 160	100.00 1	100.00 1	98.95 96	99.96 118	99.98 58	100.00 1	100.00 1

WTY-MVS		99.54 61	99.40 63	99.95 47	99.81 104	99.93 32	100.00 1	100.00 1	97.98 84	99.84 134	100.00 1	98.94 98	99.98 99	99.86 83	98.21 166	99.94 117

HY-MVS	96.53 9	99.50 67	99.35 73	99.96 36	99.81 104	99.93 32	99.64 284	100.00 1	97.97 86	99.84 134	99.85 198	98.94 98	99.99 86	99.86 83	98.23 165	99.95 113

MDTV_nov1_ep13			98.94 117		99.53 178	98.36 190	99.39 303	99.46 99	96.54 193	99.99 79	99.63 240	98.92 100	99.86 147	98.30 199	98.71 136

API-MVS		99.72 29	99.70 18	99.79 102	99.97 78	99.37 132	99.96 212	99.94 18	98.48 48	100.00 1	100.00 1	98.92 100	100.00 1	100.00 1	100.00 1	100.00 1

ACMMP		99.65 48	99.57 51	99.89 78	99.99 46	99.66 106	99.75 262	99.73 56	98.16 67	99.75 153	100.00 1	98.90 102	100.00 1	99.96 67	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
ACMMP_Plus		99.67 46	99.57 51	99.97 24	99.98 74	99.92 36	100.00 1	99.42 130	97.83 98	100.00 1	100.00 1	98.89 103	100.00 1	99.98 58	100.00 1	100.00 1

MDTV_nov1_ep13_2view						99.24 145	99.56 290		96.31 208	99.96 91		98.86 104		98.92 167		99.89 145

dp		98.72 151	98.61 152	99.03 176	99.53 178	97.39 247	99.45 298	99.39 179	95.62 228	99.94 117	99.52 252	98.83 105	99.82 159	96.77 251	98.42 147	99.89 145

TAMVS		98.76 149	98.73 139	98.86 188	99.44 196	97.69 238	99.57 289	99.34 205	96.57 191	99.12 193	99.81 207	98.83 105	99.16 227	97.97 218	97.91 179	99.73 200

IB-MVS	96.24 12	97.54 197	96.95 204	99.33 157	99.67 143	98.10 217	100.00 1	99.47 84	97.42 140	99.26 185	99.69 223	98.83 105	99.89 143	99.43 133	78.77 344	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
DeepC-MVS_fast	98.92 1	99.75 18	99.67 27	99.99 4	99.99 46	99.96 10	99.73 267	99.52 77	99.06 10	100.00 1	100.00 1	98.80 108	100.00 1	99.95 73	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
MP-MVS-pluss		99.61 56	99.50 58	99.97 24	99.98 74	99.92 36	100.00 1	99.42 130	97.53 131	99.77 150	100.00 1	98.77 109	100.00 1	99.99 44	100.00 1	99.99 90
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
pcd_1.5k_mvsjas		8.24 349	10.99 350	0.00 359	0.00 374	0.00 374	0.00 365	0.00 376	0.00 369	0.00 371	0.14 371	98.75 110	0.00 371	0.00 368	0.00 369	0.00 369

PS-MVSNAJss		98.03 182	98.06 178	97.94 248	97.63 308	97.33 253	99.89 232	99.23 247	96.27 210	98.03 257	99.59 245	98.75 110	98.78 257	98.52 190	94.61 252	97.70 280

PS-MVSNAJ		99.64 50	99.57 51	99.85 88	99.78 129	99.81 81	99.95 218	99.42 130	98.38 56	100.00 1	100.00 1	98.75 110	100.00 1	99.88 81	99.99 87	99.74 196

zzz-MVS		99.68 43	99.59 46	99.97 24	99.99 46	99.91 39	100.00 1	99.42 130	98.32 62	99.94 117	100.00 1	98.65 113	100.00 1	99.96 67	100.00 1	100.00 1

MTAPA		99.68 43	99.59 46	99.97 24	99.99 46	99.91 39	100.00 1	99.42 130	98.32 62	99.94 117	100.00 1	98.65 113	100.00 1	99.96 67	100.00 1	100.00 1

HPM-MVS		99.59 60	99.50 58	99.89 78	100.00 1	99.70 103	100.00 1	99.42 130	97.46 136	100.00 1	100.00 1	98.60 115	99.96 118	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
MG-MVS		99.75 18	99.68 22	99.97 24	100.00 1	99.91 39	99.98 202	99.47 84	99.09 7	100.00 1	100.00 1	98.59 116	100.00 1	99.95 73	100.00 1	100.00 1

EPNet_dtu		98.53 164	98.23 172	99.43 147	99.92 93	99.01 162	99.96 212	99.47 84	98.80 36	99.96 91	99.96 168	98.56 117	99.30 224	87.78 333	99.68 116	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
JIA-IIPM		97.09 210	96.34 226	99.36 154	98.88 244	98.59 179	99.81 248	99.43 123	84.81 345	99.96 91	90.34 356	98.55 118	99.52 206	97.00 241	98.28 163	99.98 92

xiu_mvs_v2_base		99.51 64	99.41 62	99.82 92	99.70 138	99.73 91	99.92 226	99.40 164	98.15 69	100.00 1	100.00 1	98.50 119	100.00 1	99.85 85	99.13 126	99.74 196

sss		99.45 73	99.34 75	99.80 98	99.76 133	99.50 115	100.00 1	99.91 37	97.72 106	99.98 84	99.94 184	98.45 120	100.00 1	99.53 129	98.75 135	99.89 145

IS-MVSNet		99.08 116	98.91 123	99.59 133	99.65 147	99.38 129	99.78 253	99.24 243	96.70 181	99.51 172	100.00 1	98.44 121	99.52 206	98.47 192	98.39 150	99.88 158

GST-MVS		99.64 50	99.53 56	99.95 47	100.00 1	99.86 69	100.00 1	99.79 44	97.72 106	99.95 115	100.00 1	98.39 122	100.00 1	99.96 67	99.99 87	100.00 1

114514_t		99.39 77	99.25 80	99.81 95	99.97 78	99.48 122	100.00 1	99.42 130	95.53 231	100.00 1	100.00 1	98.37 123	99.95 124	99.97 65	100.00 1	100.00 1

MP-MVS		99.61 56	99.49 60	99.98 16	99.99 46	99.94 27	100.00 1	99.42 130	97.82 100	99.99 79	100.00 1	98.20 124	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.
PHI-MVS		99.50 67	99.39 65	99.82 92	100.00 1	99.45 123	100.00 1	99.94 18	96.38 204	100.00 1	100.00 1	98.18 125	100.00 1	100.00 1	100.00 1	100.00 1

abl_6		99.53 62	99.40 63	99.92 71	100.00 1	99.76 86	100.00 1	99.42 130	97.21 152	100.00 1	100.00 1	98.12 126	100.00 1	99.82 93	100.00 1	100.00 1

Vis-MVSNet (Re-imp)		98.99 130	98.89 127	99.29 160	99.64 151	98.89 168	99.98 202	99.31 215	96.74 177	99.48 174	100.00 1	98.11 127	99.10 229	98.39 194	98.34 158	99.89 145

DeepPCF-MVS	98.03 4	98.54 163	99.72 16	94.98 317	99.99 46	84.94 343	100.00 1	99.42 130	99.98 1	100.00 1	100.00 1	98.11 127	100.00 1	100.00 1	100.00 1	100.00 1

PatchT		95.90 272	94.95 285	98.75 194	99.03 227	98.39 186	99.08 338	99.32 210	85.52 341	99.96 91	94.99 349	97.94 129	98.05 314	80.20 345	98.47 144	99.81 177

MVS_111021_LR		99.70 36	99.65 31	99.88 83	99.96 83	99.70 103	100.00 1	99.97 14	98.96 21	100.00 1	100.00 1	97.93 130	99.95 124	99.99 44	100.00 1	100.00 1

MVS_111021_HR		99.71 32	99.63 39	99.93 65	99.95 84	99.83 75	100.00 1	100.00 1	98.89 27	100.00 1	100.00 1	97.85 131	99.95 124	100.00 1	100.00 1	100.00 1

CSCG		99.28 96	99.35 73	99.05 173	99.99 46	97.15 259	100.00 1	99.47 84	97.44 138	99.42 177	100.00 1	97.83 132	100.00 1	99.99 44	100.00 1	100.00 1

tpm cat1		98.05 181	97.76 186	98.92 184	99.50 190	97.10 262	99.77 257	99.30 217	90.20 318	99.72 155	98.71 307	97.71 133	99.86 147	96.75 252	98.20 167	99.81 177

DELS-MVS		99.62 54	99.56 54	99.82 92	99.92 93	99.45 123	100.00 1	99.78 45	98.92 25	99.73 154	100.00 1	97.70 134	100.00 1	99.93 75	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
tpmvs		98.59 158	98.38 165	99.23 165	99.69 139	97.90 229	99.31 310	99.47 84	94.52 256	99.68 163	99.28 266	97.64 135	99.89 143	97.71 223	98.17 169	99.89 145

tpm		98.24 177	98.22 173	98.32 213	99.13 216	95.79 281	99.53 293	99.12 283	95.20 242	99.96 91	99.36 261	97.58 136	99.28 225	97.41 233	96.67 221	99.88 158

ADS-MVSNet2		98.28 175	98.51 160	97.62 257	99.51 187	95.03 289	99.24 315	99.41 162	95.52 233	99.96 91	99.70 221	97.57 137	97.94 316	97.11 239	98.54 138	99.88 158

ADS-MVSNet		98.70 154	98.51 160	99.28 161	99.51 187	98.39 186	99.24 315	99.44 114	95.52 233	99.96 91	99.70 221	97.57 137	99.58 188	97.11 239	98.54 138	99.88 158

Test_1112_low_res		98.83 145	98.60 153	99.51 141	99.69 139	98.75 172	99.99 184	99.14 272	96.81 174	98.84 210	99.06 274	97.45 139	99.89 143	98.66 179	97.75 194	99.89 145

1112_ss		98.91 139	98.71 141	99.51 141	99.69 139	98.75 172	99.99 184	99.15 268	96.82 173	98.84 210	100.00 1	97.45 139	99.89 143	98.66 179	97.75 194	99.89 145

CPTT-MVS		99.49 69	99.38 67	99.85 88	100.00 1	99.54 113	100.00 1	99.42 130	97.58 128	99.98 84	100.00 1	97.43 141	100.00 1	99.99 44	100.00 1	100.00 1

EI-MVSNet		97.98 184	97.93 182	98.16 229	99.11 217	97.84 235	99.74 263	99.29 221	94.39 260	98.65 224	100.00 1	97.21 142	98.88 248	97.62 226	95.31 232	97.75 232

IterMVS-LS		97.56 195	97.44 193	97.92 251	99.38 206	97.90 229	99.89 232	99.10 285	94.41 259	98.32 245	99.54 251	97.21 142	98.11 304	97.50 230	91.62 278	97.75 232
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
tfpn200view9		99.26 99	99.03 103	99.96 36	99.81 104	99.89 51	100.00 1	99.94 18	97.23 149	99.83 136	99.96 168	97.04 144	100.00 1	99.59 117	97.85 184	99.98 92

thres400		99.26 99	99.03 103	99.95 47	99.81 104	99.89 51	100.00 1	99.94 18	97.23 149	99.83 136	99.96 168	97.04 144	100.00 1	99.59 117	97.85 184	99.97 97

thres200		99.27 97	99.04 102	99.96 36	99.81 104	99.90 45	100.00 1	99.94 18	97.31 148	99.83 136	99.96 168	97.04 144	100.00 1	99.62 116	97.88 181	99.98 92

1314		99.38 78	99.19 90	99.96 36	98.88 244	99.89 51	99.24 315	99.93 32	98.88 28	98.79 214	100.00 1	97.02 147	100.00 1	100.00 1	100.00 1	100.00 1

tfpn111		99.24 104	99.00 107	99.95 47	99.81 104	99.87 64	100.00 1	99.94 18	97.13 156	99.83 136	99.96 168	97.01 148	100.00 1	99.54 126	97.77 192	99.97 97

conf200view11		99.25 101	99.01 105	99.95 47	99.81 104	99.87 64	100.00 1	99.94 18	97.13 156	99.83 136	99.96 168	97.01 148	100.00 1	99.59 117	97.85 184	99.97 97

thres100view900		99.25 101	99.01 105	99.95 47	99.81 104	99.87 64	100.00 1	99.94 18	97.13 156	99.83 136	99.96 168	97.01 148	100.00 1	99.59 117	97.85 184	99.98 92

thres600view7		99.24 104	99.00 107	99.95 47	99.81 104	99.87 64	100.00 1	99.94 18	97.13 156	99.83 136	99.96 168	97.01 148	100.00 1	99.54 126	97.77 192	99.97 97

OMC-MVS		99.27 97	99.38 67	98.96 181	99.95 84	97.06 263	100.00 1	99.40 164	98.83 32	99.88 132	100.00 1	97.01 148	99.86 147	99.47 132	99.84 111	99.97 97

xiu_mvs_v1_base_debu		99.35 81	99.21 86	99.79 102	99.67 143	99.71 99	99.78 253	99.36 192	98.13 71	100.00 1	100.00 1	97.00 153	100.00 1	99.83 88	99.07 128	99.66 205

xiu_mvs_v1_base		99.35 81	99.21 86	99.79 102	99.67 143	99.71 99	99.78 253	99.36 192	98.13 71	100.00 1	100.00 1	97.00 153	100.00 1	99.83 88	99.07 128	99.66 205

xiu_mvs_v1_base_debi		99.35 81	99.21 86	99.79 102	99.67 143	99.71 99	99.78 253	99.36 192	98.13 71	100.00 1	100.00 1	97.00 153	100.00 1	99.83 88	99.07 128	99.66 205

view600		99.18 108	98.93 118	99.93 65	99.81 104	99.83 75	100.00 1	99.94 18	96.96 166	99.54 167	99.96 168	96.99 156	100.00 1	99.43 133	97.75 194	99.97 97

view800		99.18 108	98.93 118	99.93 65	99.81 104	99.83 75	100.00 1	99.94 18	96.96 166	99.54 167	99.96 168	96.99 156	100.00 1	99.43 133	97.75 194	99.97 97

conf0.05thres1000		99.18 108	98.93 118	99.93 65	99.81 104	99.83 75	100.00 1	99.94 18	96.96 166	99.54 167	99.96 168	96.99 156	100.00 1	99.43 133	97.75 194	99.97 97

tfpn		99.18 108	98.93 118	99.93 65	99.81 104	99.83 75	100.00 1	99.94 18	96.96 166	99.54 167	99.96 168	96.99 156	100.00 1	99.43 133	97.75 194	99.97 97

CR-MVSNet		98.02 183	97.71 190	98.93 182	99.31 209	98.86 169	99.13 334	99.00 314	96.53 194	99.96 91	98.98 291	96.94 160	98.10 307	91.18 310	98.40 148	99.84 168

Patchmtry		96.81 221	96.37 224	98.14 230	99.31 209	98.55 181	98.91 343	99.00 314	90.45 315	97.92 263	98.98 291	96.94 160	98.12 302	94.27 284	91.53 279	97.75 232

casdiffmvs1		99.06 118	98.84 129	99.70 116	99.54 173	99.41 126	100.00 1	99.23 247	96.30 209	99.96 91	99.92 187	96.92 162	99.81 165	99.25 149	98.48 142	99.89 145

LS3D		99.31 93	99.13 99	99.87 84	99.99 46	99.71 99	99.55 291	99.46 99	97.32 146	99.82 145	100.00 1	96.85 163	99.97 103	99.14 155	100.00 1	99.92 131

MVSFormer		98.94 137	98.82 131	99.28 161	99.45 194	99.49 118	100.00 1	99.13 277	95.46 239	99.97 88	100.00 1	96.76 164	98.59 279	98.63 183	100.00 1	99.74 196

lupinMVS		99.29 95	99.16 92	99.69 118	99.45 194	99.49 118	100.00 1	99.15 268	97.45 137	99.97 88	100.00 1	96.76 164	99.76 169	99.67 111	100.00 1	99.81 177

MAR-MVS		99.49 69	99.36 71	99.89 78	99.97 78	99.66 106	99.74 263	99.95 15	97.89 93	100.00 1	100.00 1	96.71 166	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
diffmvs1		98.91 139	98.66 144	99.65 124	99.60 158	99.27 140	100.00 1	99.22 250	95.81 223	99.95 115	99.81 207	96.59 167	99.85 151	98.60 187	98.39 150	99.81 177

MSDG		98.90 141	98.63 150	99.70 116	99.92 93	99.25 143	100.00 1	99.37 186	95.71 225	99.40 181	100.00 1	96.58 168	99.95 124	96.80 249	99.94 103	99.91 132

PVSNet_BlendedMVS		98.71 152	98.62 151	98.98 180	99.98 74	99.60 110	100.00 1	100.00 1	97.23 149	100.00 1	99.03 285	96.57 169	99.99 86	100.00 1	94.75 248	97.35 318

PVSNet_Blended		99.48 71	99.36 71	99.83 91	99.98 74	99.60 110	100.00 1	100.00 1	97.79 102	100.00 1	100.00 1	96.57 169	99.99 86	100.00 1	99.88 108	99.90 140

MVS_Test		98.93 138	98.65 148	99.77 112	99.62 154	99.50 115	99.99 184	99.19 259	95.52 233	99.96 91	99.86 196	96.54 171	99.98 99	98.65 181	98.48 142	99.82 175

PMMVS		99.12 113	98.97 111	99.58 137	99.57 169	98.98 164	100.00 1	99.30 217	97.14 155	99.96 91	100.00 1	96.53 172	99.82 159	99.70 106	98.49 141	99.94 117

PVSNet_Blended_VisFu		99.33 85	99.18 91	99.78 110	99.82 101	99.49 118	100.00 1	99.95 15	97.36 142	99.63 165	100.00 1	96.45 173	99.95 124	99.79 94	99.65 118	99.89 145

mvs_anonymous		98.80 148	98.60 153	99.38 153	99.57 169	99.24 145	100.00 1	99.21 256	95.87 218	98.92 203	99.82 204	96.39 174	99.03 232	99.13 156	98.50 140	99.88 158

casdiffmvs		98.96 134	98.71 141	99.68 120	99.53 178	99.34 134	99.99 184	99.17 266	96.11 214	99.96 91	99.92 187	96.33 175	99.81 165	99.06 161	98.36 156	99.89 145

testpf		97.02 216	96.87 207	97.44 265	99.50 190	95.18 286	95.70 358	99.33 207	91.35 310	98.00 261	99.22 268	96.29 176	98.49 288	94.42 281	98.07 174	98.67 219

DP-MVS		98.86 143	98.54 158	99.81 95	99.97 78	99.45 123	99.52 294	99.40 164	94.35 261	98.36 242	100.00 1	96.13 177	99.97 103	99.12 157	100.00 1	100.00 1

PVSNet	94.91 18	99.30 94	99.25 80	99.44 145	100.00 1	98.32 195	100.00 1	99.86 39	98.04 79	100.00 1	100.00 1	96.10 178	100.00 1	99.55 123	99.73 115	100.00 1

diffmvs		98.82 146	98.55 157	99.61 126	99.54 173	99.08 154	100.00 1	99.22 250	95.48 237	99.96 91	99.77 214	96.00 179	99.82 159	98.63 183	98.37 155	99.93 128

Effi-MVS+-dtu		98.51 166	98.86 128	97.47 264	99.77 131	94.21 312	100.00 1	98.94 316	97.61 124	99.91 125	98.75 305	95.89 180	99.51 208	99.36 141	99.48 123	98.68 218

mvs-test1		98.89 142	98.99 110	98.60 199	99.77 131	95.96 277	100.00 1	98.94 316	97.61 124	99.93 122	99.92 187	95.89 180	99.93 137	99.36 141	99.50 122	99.90 140

our_test_3		96.51 240	96.35 225	96.98 282	97.61 310	95.05 288	99.98 202	99.01 313	94.68 251	96.77 297	99.06 274	95.87 182	98.14 300	91.81 307	92.37 270	97.75 232

UA-Net		99.06 118	98.83 130	99.74 113	99.52 184	99.40 128	99.08 338	99.45 105	97.64 122	99.83 136	100.00 1	95.80 183	99.94 135	98.35 196	99.80 114	99.88 158

FMVSNet5		95.32 284	95.43 272	94.99 316	99.39 205	92.99 323	99.25 314	99.24 243	90.45 315	97.44 280	98.45 316	95.78 184	94.39 346	87.02 334	91.88 276	97.59 307

1111		88.62 323	89.13 322	87.08 337	87.71 352	77.22 349	99.96 212	97.71 350	85.51 342	83.47 351	96.26 333	95.76 185	90.96 352	66.63 358	89.17 310	93.07 351

.test1245		85.18 327	84.81 328	86.28 339	87.71 352	77.22 349	99.96 212	97.71 350	85.51 342	83.47 351	96.26 333	95.76 185	90.96 352	66.63 358	50.30 359	90.64 355

CVMVSNet		98.56 161	98.47 162	98.82 190	99.11 217	97.67 239	99.74 263	99.47 84	97.57 129	99.06 198	100.00 1	95.72 187	98.97 239	98.21 203	97.33 213	99.83 171

RPMNet		95.10 286	93.82 289	98.93 182	99.31 209	98.86 169	99.13 334	99.38 183	79.82 353	99.96 91	95.13 347	95.69 188	98.10 307	77.54 351	98.40 148	99.84 168

MVS		99.22 106	98.96 112	99.98 16	99.00 233	99.95 19	99.24 315	99.94 18	98.14 70	98.88 206	100.00 1	95.63 189	100.00 1	99.85 85	100.00 1	100.00 1

jason		99.11 114	98.96 112	99.59 133	99.17 215	99.31 136	100.00 1	99.13 277	97.38 141	99.83 136	100.00 1	95.54 190	99.72 174	99.57 122	99.97 98	99.74 196
jason: jason.
AdaColmap		99.44 74	99.26 79	99.95 47	100.00 1	99.86 69	99.70 273	99.99 10	98.53 47	99.90 126	100.00 1	95.34 191	100.00 1	99.92 76	100.00 1	100.00 1

CANet		99.40 76	99.24 82	99.89 78	99.99 46	99.76 86	100.00 1	99.73 56	98.40 53	99.78 149	100.00 1	95.28 192	99.96 118	100.00 1	99.99 87	99.96 108

FIs		97.95 185	97.73 189	98.62 198	98.53 257	99.24 145	100.00 1	99.43 123	96.74 177	97.87 265	99.82 204	95.27 193	98.89 245	98.78 174	93.07 263	97.74 256

canonicalmvs		99.03 122	98.73 139	99.94 62	99.75 135	99.95 19	100.00 1	99.30 217	97.64 122	100.00 1	100.00 1	95.22 194	99.97 103	99.76 100	96.90 220	99.91 132

FC-MVSNet-test		97.84 187	97.63 191	98.45 203	98.30 266	99.05 157	100.00 1	99.43 123	96.63 189	97.61 275	99.82 204	95.19 195	98.57 282	98.64 182	93.05 264	97.73 266

UniMVSNet_NR-MVSNet		97.16 207	96.80 209	98.22 224	98.38 261	98.41 184	100.00 1	99.45 105	96.14 213	97.76 267	99.64 236	95.05 196	98.50 286	97.98 215	86.84 325	97.75 232

Fast-Effi-MVS+-dtu		98.38 172	98.56 156	97.82 253	99.58 167	94.44 309	100.00 1	99.16 267	96.75 176	99.51 172	99.63 240	95.03 197	99.60 184	97.71 223	99.67 117	99.42 213

UniMVSNet (Re)		97.29 203	96.85 208	98.59 201	98.49 258	99.13 152	100.00 1	99.42 130	96.52 195	98.24 252	98.90 299	94.93 198	98.89 245	97.54 229	87.61 322	97.75 232

BH-w/o		98.82 146	98.81 133	98.88 187	99.62 154	96.71 270	100.00 1	99.28 229	97.09 160	98.81 213	100.00 1	94.91 199	99.96 118	99.54 126	100.00 1	99.96 108

PCF-MVS	98.23 3	98.69 155	98.37 166	99.62 125	99.78 129	99.02 159	99.23 321	99.06 306	96.43 199	98.08 254	100.00 1	94.72 200	99.95 124	98.16 204	99.91 105	99.90 140
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
VNet		99.04 121	98.75 138	99.90 75	99.81 104	99.75 88	99.50 296	99.47 84	98.36 59	100.00 1	99.99 147	94.66 201	100.00 1	99.90 78	97.09 215	99.96 108

BH-untuned		98.64 156	98.65 148	98.60 199	99.59 162	96.17 276	100.00 1	99.28 229	96.67 185	98.41 241	100.00 1	94.52 202	99.83 157	99.41 139	100.00 1	99.81 177

nrg030		97.64 192	97.27 199	98.75 194	98.34 262	99.53 114	100.00 1	99.22 250	96.21 212	98.27 249	99.95 180	94.40 203	98.98 237	99.23 151	89.78 303	97.75 232

LP		95.89 274	95.35 275	97.51 261	98.92 241	95.15 287	98.66 346	99.39 179	89.43 329	97.22 285	99.03 285	94.37 204	97.74 319	83.71 340	97.44 211	99.63 208

ppachtmachnet_test		96.17 261	95.89 250	97.02 279	97.61 310	95.24 284	99.99 184	99.24 243	93.31 291	96.71 298	99.62 242	94.34 205	98.07 310	89.87 323	92.30 272	97.75 232

RPSCF		97.37 199	98.24 170	94.76 319	99.80 119	84.57 344	99.99 184	99.05 308	94.95 246	99.82 145	100.00 1	94.03 206	100.00 1	98.15 205	98.38 154	99.70 201

CANet_DTU		99.02 126	98.90 126	99.41 149	99.88 99	98.71 174	100.00 1	99.29 221	98.84 31	100.00 1	100.00 1	94.02 207	100.00 1	98.08 212	99.96 100	99.52 211

LCM-MVSNet-Re		96.52 239	97.21 201	94.44 320	99.27 212	85.80 342	99.85 239	96.61 360	95.98 216	92.75 324	98.48 315	93.97 208	97.55 321	99.58 121	98.43 146	99.98 92

Effi-MVS+		98.58 159	98.24 170	99.61 126	99.60 158	99.26 141	97.85 353	99.10 285	96.22 211	99.97 88	99.89 192	93.75 209	99.77 168	99.43 133	98.34 158	99.81 177

pmmvs4		97.17 206	96.80 209	98.27 217	97.68 305	98.64 178	100.00 1	99.18 262	94.22 264	98.55 232	99.71 218	93.67 210	98.47 289	95.66 262	92.57 268	97.71 279

CHOSEN 1792x2688		99.00 128	98.91 123	99.25 164	99.90 96	97.79 236	100.00 1	99.99 10	98.79 37	98.28 248	100.00 1	93.63 211	99.95 124	99.66 113	99.95 102	100.00 1

cdsmvs_eth3d_5k		24.41 347	32.55 347	0.00 359	0.00 374	0.00 374	0.00 365	99.39 179	0.00 369	0.00 371	100.00 1	93.55 212	0.00 371	0.00 368	0.00 369	0.00 369

AllTest		98.55 162	98.40 164	98.99 178	99.93 90	97.35 250	100.00 1	99.40 164	97.08 162	99.09 194	99.98 149	93.37 213	99.95 124	96.94 242	99.84 111	99.68 203

TestCases				98.99 178	99.93 90	97.35 250		99.40 164	97.08 162	99.09 194	99.98 149	93.37 213	99.95 124	96.94 242	99.84 111	99.68 203

FMVSNet3		97.30 202	96.95 204	98.37 208	99.65 147	99.25 143	99.71 271	99.28 229	94.23 263	98.53 234	98.91 298	93.30 215	98.11 304	95.31 268	93.60 257	97.73 266

Fast-Effi-MVS+		98.40 171	98.02 180	99.55 140	99.63 152	99.06 156	100.00 1	99.15 268	95.07 243	99.42 177	99.95 180	93.26 216	99.73 172	97.44 231	98.24 164	99.87 165

QAPM		98.99 130	98.66 144	99.96 36	99.01 229	99.87 64	99.88 235	99.93 32	97.99 82	98.68 222	100.00 1	93.17 217	100.00 1	99.32 146	100.00 1	100.00 1

PatchMatch-RL		99.02 126	98.78 135	99.74 113	99.99 46	99.29 137	100.00 1	100.00 1	98.38 56	99.89 130	99.81 207	93.14 218	99.99 86	97.85 220	99.98 95	99.95 113

WR-MVS_H		96.73 227	96.32 228	97.95 247	98.26 268	97.88 231	99.72 269	99.43 123	95.06 244	96.99 289	98.68 308	93.02 219	98.53 284	97.43 232	88.33 318	97.43 314

3Dnovator	95.63 14	99.06 118	98.76 137	99.96 36	98.86 247	99.90 45	99.98 202	99.93 32	98.95 24	98.49 238	100.00 1	92.91 220	100.00 1	99.71 104	100.00 1	100.00 1

3Dnovator+	95.58 15	99.03 122	98.71 141	99.96 36	98.99 236	99.89 51	100.00 1	99.51 81	98.96 21	98.32 245	100.00 1	92.78 221	100.00 1	99.87 82	100.00 1	100.00 1

NR-MVSNet		96.63 235	96.04 244	98.38 207	98.31 264	98.98 164	99.22 323	99.35 200	95.87 218	94.43 316	99.65 232	92.73 222	98.40 292	96.78 250	88.05 319	97.75 232

COLMAP_ROB	97.10 7	98.29 174	98.17 174	98.65 197	99.94 88	97.39 247	99.30 311	99.40 164	95.64 226	97.75 270	100.00 1	92.69 223	99.95 124	98.89 168	99.92 104	98.62 221
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
EU-MVSNet		96.63 235	96.53 218	96.94 284	97.59 312	96.87 267	99.76 260	99.47 84	96.35 205	96.85 294	99.78 212	92.57 224	96.27 338	95.33 267	91.08 284	97.68 287

MVP-Stereo		96.51 240	96.48 221	96.60 303	95.65 337	94.25 311	98.84 345	98.16 337	95.85 222	95.23 310	99.04 280	92.54 225	99.13 228	92.98 299	99.98 95	96.43 330
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
DeepC-MVS	97.84 5	99.00 128	98.80 134	99.60 130	99.93 90	99.03 158	100.00 1	99.40 164	98.61 45	99.33 182	100.00 1	92.23 226	99.95 124	99.74 102	99.96 100	99.83 171
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DU-MVS		96.93 219	96.49 220	98.22 224	98.31 264	98.41 184	100.00 1	99.37 186	96.41 202	97.76 267	99.65 232	92.14 227	98.50 286	97.98 215	86.84 325	97.75 232

Baseline_NR-MVSNet		96.16 262	95.70 260	97.56 260	98.28 267	96.79 269	100.00 1	97.86 348	91.93 306	97.63 273	99.47 257	92.14 227	98.35 294	97.13 238	86.83 327	97.54 310

cascas		98.43 168	98.07 177	99.50 143	99.65 147	99.02 159	100.00 1	99.22 250	94.21 265	99.72 155	99.98 149	92.03 229	99.93 137	99.68 109	98.12 171	99.54 210

v18		93.55 294	92.42 302	96.91 286	98.12 279	98.26 202	99.83 241	98.74 323	89.99 320	88.94 335	95.64 337	92.02 230	96.54 325	90.27 320	78.26 345	95.94 339

test_djsdf		97.55 196	97.38 196	98.07 237	97.50 316	97.99 223	100.00 1	99.13 277	95.46 239	98.47 239	99.85 198	92.01 231	98.59 279	98.63 183	95.36 230	97.62 303

v17		93.53 295	92.42 302	96.88 291	98.09 283	98.16 212	99.83 241	98.74 323	89.95 321	89.05 332	95.65 336	91.99 232	96.54 325	90.31 319	78.15 347	95.95 337

v13		93.18 302	91.97 309	96.81 297	98.12 279	98.12 215	99.74 263	98.73 329	89.47 328	88.52 341	95.40 345	91.72 233	96.41 332	89.23 332	76.77 352	95.92 341

v1neww		96.77 222	96.27 229	98.26 219	98.16 276	98.23 204	100.00 1	99.09 288	93.94 270	98.73 218	99.05 277	91.65 234	98.82 253	95.75 258	90.04 294	97.74 256

v7new		96.77 222	96.27 229	98.26 219	98.16 276	98.23 204	100.00 1	99.09 288	93.94 270	98.73 218	99.05 277	91.65 234	98.82 253	95.75 258	90.04 294	97.74 256

v16		93.48 297	92.34 304	96.89 287	98.13 278	98.19 210	99.82 246	98.74 323	89.94 322	88.90 336	95.62 338	91.65 234	96.54 325	90.03 322	78.22 346	95.95 337

v12		93.18 302	91.97 309	96.80 298	98.09 283	98.10 217	99.76 260	98.73 329	89.61 327	88.45 342	95.41 344	91.63 237	96.39 334	89.32 329	76.76 353	95.91 344

v1141		96.66 231	96.12 239	98.26 219	98.05 289	98.28 197	100.00 1	99.09 288	93.71 274	98.59 229	99.04 280	91.57 238	98.73 264	95.05 273	90.00 297	97.75 232

v15		93.28 299	92.08 305	96.87 292	98.07 287	98.22 208	99.82 246	98.74 323	89.83 323	88.74 338	95.44 342	91.55 239	96.47 329	89.70 324	76.87 349	95.93 340

divwei89l23v2f112		96.68 230	96.15 237	98.25 223	98.03 292	98.27 199	100.00 1	99.09 288	93.79 273	98.59 229	99.04 280	91.54 240	98.73 264	95.29 271	89.99 298	97.75 232

v6		96.77 222	96.26 231	98.29 215	98.10 282	98.27 199	100.00 1	99.09 288	93.95 269	98.73 218	99.06 274	91.51 241	98.86 250	95.83 256	90.04 294	97.74 256

V14		93.24 300	92.04 306	96.87 292	98.07 287	98.20 209	99.80 251	98.74 323	89.76 325	88.64 339	95.53 339	91.47 242	96.47 329	89.49 326	76.84 350	95.92 341

v8		96.35 250	95.73 259	98.21 226	98.11 281	98.23 204	99.94 222	99.07 298	92.66 300	98.29 247	99.00 290	91.46 243	98.77 260	94.17 285	88.83 314	97.62 303

OpenMVS	95.20 17	98.76 149	98.41 163	99.78 110	98.89 243	99.81 81	99.99 184	99.76 47	98.02 80	98.02 259	100.00 1	91.44 244	100.00 1	99.63 115	99.97 98	99.55 209

v1		96.66 231	96.12 239	98.30 214	98.09 283	98.33 192	100.00 1	99.09 288	93.69 279	98.68 222	99.04 280	91.42 245	98.83 252	95.05 273	89.99 298	97.75 232

V9		93.20 301	91.99 308	96.85 294	98.05 289	98.16 212	99.77 257	98.73 329	89.67 326	88.64 339	95.44 342	91.34 246	96.47 329	89.46 327	76.79 351	95.92 341

v148		96.29 253	95.84 252	97.63 255	97.74 303	96.53 274	100.00 1	99.07 298	93.52 285	98.01 260	99.42 260	91.22 247	98.60 277	96.37 254	87.22 324	97.75 232

XVG-OURS		98.30 173	98.36 167	98.13 233	99.58 167	95.91 280	100.00 1	99.36 192	98.69 39	99.23 186	100.00 1	91.20 248	99.92 140	99.34 143	97.82 188	98.56 222

WR-MVS		97.09 210	96.64 214	98.46 202	98.43 259	99.09 153	99.97 209	99.33 207	95.62 228	97.76 267	99.67 229	91.17 249	98.56 283	98.49 191	89.28 308	97.74 256

v11		93.14 304	91.93 311	96.77 300	98.01 293	98.17 211	99.72 269	98.74 323	89.39 330	88.81 337	95.49 341	91.15 250	96.29 336	86.78 335	79.25 342	95.86 346

v7		96.64 234	96.14 238	98.13 233	98.18 273	97.97 225	99.99 184	99.09 288	93.62 283	98.76 215	99.30 264	91.13 251	98.70 269	94.37 282	90.80 287	97.74 256

test2356		92.55 309	93.94 287	88.39 334	93.49 344	78.42 348	100.00 1	99.40 164	91.64 307	93.93 318	98.74 306	91.11 252	88.67 356	79.37 347	97.79 191	98.08 224

pcd1.5k->3k		40.07 345	42.58 346	32.57 357	97.97 297	0.00 374	0.00 365	99.25 240	0.00 369	0.00 371	0.14 371	91.10 253	0.00 371	0.00 368	94.75 248	97.70 280

V42		96.65 233	96.16 236	98.11 236	98.17 275	98.23 204	99.99 184	99.09 288	93.97 267	98.74 217	99.05 277	91.09 254	98.82 253	95.46 266	89.90 301	97.27 321

v10		96.14 264	95.50 267	98.07 237	98.19 272	97.96 226	99.83 241	99.07 298	92.10 304	98.07 256	98.94 296	91.07 255	98.61 275	92.41 305	89.82 302	97.63 301

v7n		96.06 268	95.42 273	97.99 246	97.58 313	97.35 250	99.86 238	99.11 284	92.81 299	97.91 264	99.49 255	90.99 256	98.92 241	92.51 302	88.49 317	97.70 280

v1144		96.51 240	95.97 248	98.13 233	97.98 296	98.04 222	99.99 184	99.08 296	93.51 286	98.62 227	98.98 291	90.98 257	98.62 274	93.79 292	90.79 288	97.74 256

ab-mvs		98.42 169	98.02 180	99.61 126	99.71 137	99.00 163	99.10 336	99.64 73	96.70 181	99.04 199	99.81 207	90.64 258	99.98 99	99.64 114	97.93 178	99.84 168

Anonymous202405211		97.87 186	97.53 192	98.90 185	99.81 104	96.70 271	99.35 307	99.46 99	92.98 297	98.83 212	99.99 147	90.63 259	100.00 1	99.70 106	97.03 216	100.00 1

MVS_0304		98.98 132	98.66 144	99.94 62	99.95 84	99.86 69	100.00 1	99.29 221	98.38 56	99.81 147	100.00 1	90.60 260	100.00 1	100.00 1	99.91 105	99.95 113

Anonymous20231206		93.45 298	93.17 296	94.30 322	95.00 341	89.69 336	99.98 202	98.43 333	93.30 292	94.50 315	98.59 312	90.52 261	95.73 343	77.46 352	90.73 290	97.48 313

anonymousdsp		97.16 207	96.88 206	98.00 244	97.08 327	98.06 220	99.81 248	99.15 268	94.58 254	97.84 266	99.62 242	90.49 262	98.60 277	97.98 215	95.32 231	97.33 320

v2v482		96.70 229	96.18 234	98.27 217	98.04 291	98.39 186	100.00 1	99.13 277	94.19 266	98.58 231	99.08 273	90.48 263	98.67 272	95.69 261	90.44 292	97.75 232

v144192		96.40 247	95.81 253	98.17 228	97.89 300	98.11 216	99.99 184	99.06 306	93.39 288	98.75 216	99.09 272	90.43 264	98.66 273	93.10 298	90.55 291	97.75 232

Vis-MVSNet		98.52 165	98.25 169	99.34 156	99.68 142	98.55 181	99.68 279	99.41 162	97.34 145	99.94 117	100.00 1	90.38 265	99.70 176	99.03 162	98.84 133	99.76 191
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
V4		95.89 274	95.36 274	97.49 262	97.65 307	97.40 246	99.88 235	99.07 298	92.19 302	98.08 254	99.01 288	90.20 266	98.72 266	93.57 295	88.63 315	96.34 331

CP-MVSNet		96.73 227	96.25 232	98.18 227	98.21 271	98.67 177	99.77 257	99.32 210	95.06 244	97.20 286	99.65 232	90.10 267	98.19 297	98.06 214	88.90 312	97.66 293

TranMVSNet+NR-MVSNet		96.45 244	96.01 245	97.79 254	98.00 295	97.62 241	100.00 1	99.35 200	95.98 216	97.31 282	99.64 236	90.09 268	98.00 315	96.89 245	86.80 328	97.75 232

v52		95.88 276	95.35 275	97.48 263	97.66 306	97.38 249	99.88 235	99.07 298	92.19 302	98.09 253	99.02 287	90.06 269	98.72 266	93.58 294	88.61 316	96.34 331

DSMNet-mixed		95.18 285	95.21 278	95.08 314	96.03 333	90.21 335	99.65 283	93.64 365	92.91 298	98.34 244	97.40 327	90.05 270	95.51 344	91.02 312	97.86 183	99.51 212

N_pmnet		91.88 314	93.37 295	87.40 336	97.24 326	66.33 361	99.90 229	91.05 367	89.77 324	95.65 308	98.58 313	90.05 270	98.11 304	85.39 337	92.72 267	97.75 232

v748		95.47 282	94.95 285	97.04 277	97.46 321	94.76 301	99.93 224	99.10 285	91.95 305	97.11 287	99.18 269	89.94 272	98.68 270	94.01 289	85.88 331	97.67 291

GA-MVS		97.72 190	97.27 199	99.06 171	99.24 214	97.93 228	100.00 1	99.24 243	95.80 224	98.99 201	99.64 236	89.77 273	99.36 221	95.12 272	97.62 210	99.89 145

MIMVSNet		97.06 213	96.73 212	98.05 242	99.38 206	96.64 273	98.47 349	99.35 200	93.41 287	99.48 174	98.53 314	89.66 274	97.70 320	94.16 287	98.11 172	99.80 186

Patchmatch-test1		98.23 178	97.91 183	99.17 168	99.41 198	98.25 203	99.99 184	99.45 105	96.91 172	99.76 152	99.69 223	89.65 275	99.37 220	97.55 227	98.79 134	99.89 145

semantic-postprocess				97.62 257	99.40 202	96.83 268		99.14 272	94.65 253	97.55 277	99.72 216	89.64 276	98.31 295	95.62 264	92.05 274	97.73 266

IterMVS		96.76 226	96.46 222	97.63 255	99.41 198	96.89 266	99.99 184	99.13 277	94.74 250	97.59 276	99.66 231	89.63 277	98.28 296	95.71 260	92.31 271	97.72 272
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v1192		96.18 259	95.49 269	98.26 219	98.01 293	98.15 214	99.99 184	99.08 296	93.36 289	98.54 233	98.97 294	89.47 278	98.89 245	91.15 311	90.82 286	97.75 232

v1921920		96.16 262	95.50 267	98.14 230	97.88 301	97.96 226	99.99 184	99.07 298	93.33 290	98.60 228	99.24 267	89.37 279	98.71 268	91.28 309	90.74 289	97.75 232

XVG-OURS-SEG-HR		98.27 176	98.31 168	98.14 230	99.59 162	95.92 279	100.00 1	99.36 192	98.48 48	99.21 187	100.00 1	89.27 280	99.94 135	99.76 100	99.17 125	98.56 222

test20.03		93.11 305	92.85 299	93.88 327	95.19 340	91.83 330	100.00 1	98.87 320	93.68 280	92.76 323	98.88 300	89.20 281	92.71 351	77.88 350	89.19 309	97.09 324

MDA-MVSNet_test_wron		92.61 308	91.09 314	97.19 275	96.71 329	97.26 256	100.00 1	99.14 272	88.61 333	67.90 361	98.32 323	89.03 282	96.57 324	90.47 317	89.59 304	97.74 256

BH-RMVSNet		98.46 167	98.08 176	99.59 133	99.61 156	99.19 149	100.00 1	99.28 229	97.06 164	98.95 202	100.00 1	88.99 283	99.82 159	98.83 173	100.00 1	99.77 189

v1240		95.96 270	95.25 277	98.07 237	97.91 299	97.87 233	99.96 212	99.07 298	93.24 293	98.64 226	98.96 295	88.98 284	98.61 275	89.58 325	90.92 285	97.75 232

Anonymous20231211		96.29 253	95.70 260	98.07 237	99.80 119	97.49 243	99.15 332	99.40 164	89.11 331	97.75 270	99.45 258	88.93 285	98.98 237	98.26 201	89.47 306	97.73 266

TR-MVS		98.14 179	97.74 187	99.33 157	99.59 162	98.28 197	99.27 312	99.21 256	96.42 201	99.15 192	99.94 184	88.87 286	99.79 167	98.88 169	98.29 161	99.93 128

YYNet1		92.44 310	90.92 315	97.03 278	96.20 331	97.06 263	99.99 184	99.14 272	88.21 336	67.93 360	98.43 318	88.63 287	96.28 337	90.64 313	89.08 311	97.74 256

HQP2-MVS												88.61 288

HQP-MVS		97.73 189	97.85 184	97.39 266	99.07 221	94.82 293	100.00 1	99.40 164	99.04 13	99.17 188	99.97 159	88.61 288	99.57 189	99.79 94	95.58 223	97.77 226

HQP_MVS		97.71 191	97.82 185	97.37 267	99.00 233	94.80 296	100.00 1	99.40 164	99.00 19	99.08 196	99.97 159	88.58 290	99.55 198	99.79 94	95.57 227	97.76 228

plane_prior6					99.06 225	94.80 296						88.58 290

tfpnnormal		96.36 249	95.69 263	98.37 208	98.55 255	98.71 174	99.69 277	99.45 105	93.16 295	96.69 299	99.71 218	88.44 292	98.99 236	94.17 285	91.38 281	97.41 315

TransMVSNet (Re)		94.78 287	93.72 290	97.93 250	98.34 262	97.88 231	99.23 321	97.98 345	91.60 308	94.55 314	99.71 218	87.89 293	98.36 293	89.30 330	84.92 332	97.56 309

DTE-MVSNet		95.52 280	94.99 284	97.08 276	97.49 318	96.45 275	100.00 1	99.25 240	93.82 272	96.17 302	99.57 248	87.81 294	97.18 322	94.57 278	86.26 330	97.62 303

XXY-MVS		97.14 209	96.63 215	98.67 196	98.65 251	98.92 167	99.54 292	99.29 221	95.57 230	97.63 273	99.83 201	87.79 295	99.35 222	98.39 194	92.95 265	97.75 232

UGNet		98.41 170	98.11 175	99.31 159	99.54 173	98.55 181	99.18 324	100.00 1	98.64 44	99.79 148	99.04 280	87.61 296	100.00 1	99.30 147	99.89 107	99.40 214
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
CLD-MVS		97.64 192	97.74 187	97.36 268	99.01 229	94.76 301	100.00 1	99.34 205	99.30 4	99.00 200	99.97 159	87.49 297	99.57 189	99.96 67	95.58 223	97.75 232
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
PEN-MVS		96.01 269	95.48 271	97.58 259	97.74 303	97.26 256	99.90 229	99.29 221	94.55 255	96.79 296	99.55 249	87.38 298	97.84 317	96.92 244	87.24 323	97.65 297

ACMM	97.17 6	97.37 199	97.40 195	97.29 270	99.01 229	94.64 305	100.00 1	99.25 240	98.07 77	98.44 240	99.98 149	87.38 298	99.55 198	99.25 149	95.19 239	97.69 285
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
jajsoiax		97.07 212	96.79 211	97.89 252	97.28 325	97.12 260	99.95 218	99.19 259	96.55 192	97.31 282	99.69 223	87.35 300	98.91 242	98.70 178	95.12 243	97.66 293

pmmvs5		95.94 271	95.61 264	96.95 283	97.42 322	94.66 303	100.00 1	98.08 341	93.60 284	97.05 288	99.43 259	87.02 301	98.46 290	95.76 257	92.12 273	97.72 272

VPA-MVSNet		97.03 215	96.43 223	98.82 190	98.64 252	99.32 135	99.38 304	99.47 84	96.73 179	98.91 205	98.94 296	87.00 302	99.40 218	99.23 151	89.59 304	97.76 228

PS-CasMVS		96.34 251	95.78 256	98.03 243	98.18 273	98.27 199	99.71 271	99.32 210	94.75 248	96.82 295	99.65 232	86.98 303	98.15 299	97.74 222	88.85 313	97.66 293

LPG-MVS_test		97.31 201	97.32 198	97.28 271	98.85 248	94.60 306	100.00 1	99.37 186	97.35 143	98.85 208	99.98 149	86.66 304	99.56 193	99.55 123	95.26 234	97.70 280

LGP-MVS_train				97.28 271	98.85 248	94.60 306		99.37 186	97.35 143	98.85 208	99.98 149	86.66 304	99.56 193	99.55 123	95.26 234	97.70 280

mvs_tets		97.00 217	96.69 213	97.94 248	97.41 324	97.27 255	99.60 287	99.18 262	96.51 196	97.35 281	99.69 223	86.53 306	98.91 242	98.84 171	95.09 244	97.65 297

pm-mvs1		95.76 277	95.01 283	98.00 244	98.23 270	97.45 244	99.24 315	99.04 311	93.13 296	95.93 306	99.72 216	86.28 307	98.84 251	95.62 264	87.92 320	97.72 272

MVS-HIRNet		94.12 291	92.73 300	98.29 215	99.33 208	95.95 278	99.38 304	99.19 259	74.54 355	98.26 250	86.34 360	86.07 308	99.06 231	91.60 308	99.87 110	99.85 167

DeepMVS_CX				89.98 331	98.90 242	71.46 357		99.18 262	97.61 124	96.92 290	99.83 201	86.07 308	99.83 157	96.02 255	97.65 209	98.65 220

OPM-MVS		97.21 204	97.18 202	97.32 269	98.08 286	94.66 303	100.00 1	99.28 229	98.65 43	98.92 203	99.98 149	86.03 310	99.56 193	98.28 200	95.41 229	97.72 272

new_pmnet		94.11 292	93.47 294	96.04 311	96.60 330	92.82 324	99.97 209	98.91 319	90.21 317	95.26 309	98.05 324	85.89 311	98.14 300	84.28 339	92.01 275	97.16 323

ACMP	97.00 8	97.19 205	97.16 203	97.27 273	98.97 238	94.58 308	100.00 1	99.32 210	97.97 86	97.45 279	99.98 149	85.79 312	99.56 193	99.70 106	95.24 237	97.67 291
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
OurMVSNet-221017-0		96.14 264	95.98 247	96.62 302	97.49 318	93.44 318	99.92 226	98.16 337	95.86 220	97.65 272	99.95 180	85.71 313	98.78 257	94.93 276	94.18 255	97.64 300

SixPastTwentyTwo		95.71 278	95.49 269	96.38 306	97.42 322	93.01 321	99.84 240	98.23 335	94.75 248	95.98 305	99.97 159	85.35 314	98.43 291	94.71 277	93.17 262	97.69 285

LTVRE_ROB	95.29 16	96.32 252	96.10 241	96.99 281	98.55 255	93.88 314	99.45 298	99.28 229	94.50 257	96.46 301	99.52 252	84.86 315	99.48 211	97.26 236	95.03 245	97.59 307
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
ITE_SJBPF				96.84 295	98.96 239	93.49 317		98.12 339	98.12 74	98.35 243	99.97 159	84.45 316	99.56 193	95.63 263	95.25 236	97.49 311

PVSNet_0	93.57 19	96.41 245	95.74 258	98.41 205	99.84 100	95.22 285	100.00 1	100.00 1	98.08 76	97.55 277	99.78 212	84.40 317	100.00 1	100.00 1	81.99 336	100.00 1

K. test v3		95.46 283	95.14 280	96.40 305	97.53 315	93.40 319	99.99 184	99.23 247	95.49 236	92.70 325	99.73 215	84.26 318	98.12 302	93.94 291	93.38 261	97.68 287

GBi-Net		96.07 266	95.80 254	96.89 287	99.53 178	94.87 290	99.18 324	99.27 236	93.71 274	98.53 234	98.81 302	84.23 319	98.07 310	95.31 268	93.60 257	97.72 272

test1		96.07 266	95.80 254	96.89 287	99.53 178	94.87 290	99.18 324	99.27 236	93.71 274	98.53 234	98.81 302	84.23 319	98.07 310	95.31 268	93.60 257	97.72 272

FMVSNet2		96.22 257	95.60 265	98.06 241	99.53 178	98.33 192	99.45 298	99.27 236	93.71 274	98.03 257	98.84 301	84.23 319	98.10 307	93.97 290	93.40 260	97.73 266

testgi		96.18 259	95.93 249	96.93 285	98.98 237	94.20 313	100.00 1	99.07 298	97.16 154	96.06 304	99.86 196	84.08 322	97.79 318	90.38 318	97.80 190	98.81 217

ACMH	96.25 11	96.77 222	96.62 216	97.21 274	98.96 239	94.43 310	99.64 284	99.33 207	97.43 139	96.55 300	99.97 159	83.52 323	99.54 201	99.07 160	95.13 242	97.66 293
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Anonymous20240529		96.93 219	96.22 233	99.05 173	99.79 122	97.30 254	99.16 330	99.47 84	88.51 334	98.69 221	100.00 1	83.50 324	100.00 1	99.83 88	97.02 217	99.83 171

lessismore_v0				96.05 310	97.55 314	91.80 331		99.22 250		91.87 326	99.91 190	83.50 324	98.68 270	92.48 303	90.42 293	97.68 287

UnsupCasMVSNet_eth		94.25 290	93.89 288	95.34 313	97.63 308	92.13 328	99.73 267	99.36 192	94.88 247	92.78 322	98.63 311	82.72 326	96.53 328	94.57 278	84.73 333	97.36 317

LF4IMVS		96.19 258	96.18 234	96.23 309	98.26 268	92.09 329	100.00 1	97.89 347	97.82 100	97.94 262	99.87 194	82.71 327	99.38 219	97.41 233	93.71 256	97.20 322

ACMH+	96.20 13	96.49 243	96.33 227	97.00 280	99.06 225	93.80 315	99.81 248	99.31 215	97.32 146	95.89 307	99.97 159	82.62 328	99.54 201	98.34 197	94.63 251	97.65 297

pmmvs3		90.62 320	89.36 321	94.40 321	90.53 350	91.49 333	100.00 1	96.73 358	84.21 347	93.65 321	96.65 329	82.56 329	94.83 345	82.28 342	77.62 348	96.89 325

XVG-ACMP-BASELINE		96.60 237	96.52 219	96.84 295	98.41 260	93.29 320	99.99 184	99.32 210	97.76 105	98.51 237	99.29 265	81.95 330	99.54 201	98.40 193	95.03 245	97.68 287

test1235678		88.02 325	88.73 323	85.90 340	87.57 354	71.70 356	100.00 1	97.42 353	87.52 339	86.19 346	96.39 331	81.60 331	87.93 357	70.72 355	91.18 283	98.08 224

VPNet		96.41 245	95.76 257	98.33 212	98.61 253	98.30 196	99.48 297	99.45 105	96.98 165	98.87 207	99.88 193	81.57 332	98.93 240	99.22 153	87.82 321	97.76 228

testus		91.61 317	92.92 297	87.70 335	93.91 343	74.98 352	100.00 1	98.19 336	92.59 301	93.90 319	98.68 308	81.43 333	90.77 354	79.82 346	97.71 202	97.34 319

MDA-MVSNet-bldmvs		91.65 316	89.94 319	96.79 299	96.72 328	96.70 271	99.42 301	98.94 316	88.89 332	66.97 363	98.37 321	81.43 333	95.91 341	89.24 331	89.46 307	97.75 232

MS-PatchMatch		95.66 279	95.87 251	95.05 315	97.80 302	89.25 337	98.88 344	99.30 217	96.35 205	96.86 293	99.01 288	81.35 335	99.43 215	93.30 297	99.98 95	96.46 329

USDC		95.90 272	95.70 260	96.50 304	98.60 254	92.56 327	100.00 1	98.30 334	97.77 103	96.92 290	99.94 184	81.25 336	99.45 214	93.54 296	94.96 247	97.49 311

test_normal		96.24 256	95.12 281	99.60 130	96.00 335	99.16 151	100.00 1	99.29 221	96.43 199	88.96 334	98.40 320	80.06 337	99.90 141	98.53 189	98.39 150	99.75 192

DI_MVS_plusplus_test		96.28 255	95.16 279	99.61 126	96.01 334	99.18 150	100.00 1	99.29 221	96.49 197	89.08 331	98.42 319	80.06 337	99.90 141	98.74 177	98.39 150	99.75 192

TDRefinement		91.93 312	90.48 317	96.27 308	81.60 360	92.65 326	99.10 336	97.61 352	93.96 268	93.77 320	99.85 198	80.03 339	99.53 205	97.82 221	70.59 355	96.63 328

test_0402		94.35 289	93.70 291	96.32 307	97.92 298	93.60 316	99.61 286	98.85 321	88.19 337	94.68 313	99.48 256	80.01 340	98.58 281	89.39 328	95.15 241	96.77 326

TinyColmap		95.50 281	95.12 281	96.64 301	98.69 250	93.00 322	99.40 302	97.75 349	96.40 203	96.14 303	99.87 194	79.47 341	99.50 209	93.62 293	94.72 250	97.40 316

LFMVS		97.42 198	96.62 216	99.81 95	99.80 119	99.50 115	99.16 330	99.56 75	94.48 258	100.00 1	100.00 1	79.35 342	100.00 1	99.89 80	97.37 212	99.94 117

pmmvs-eth3d		91.73 315	90.67 316	94.92 318	91.63 348	92.71 325	99.90 229	98.54 332	91.19 312	88.08 343	95.50 340	79.31 343	96.13 339	90.55 316	81.32 339	95.91 344

new-patchmatchnet		90.30 321	89.46 320	92.84 329	90.77 349	88.55 339	99.83 241	98.80 322	90.07 319	87.86 344	95.00 348	78.77 344	94.30 347	84.86 338	79.15 343	95.68 347

test123		79.44 331	79.23 333	80.05 346	80.03 362	71.72 355	100.00 1	77.93 374	62.52 358	94.81 312	99.69 223	78.21 345	74.53 367	92.57 301	27.33 367	93.90 348

CMPMVS	66.12 22	90.65 319	92.04 306	86.46 338	96.18 332	66.87 360	98.03 352	99.38 183	83.38 349	85.49 348	99.55 249	77.59 346	98.80 256	94.44 280	94.31 254	93.72 350
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs6		93.64 293	92.87 298	95.94 312	97.47 320	91.41 334	98.92 342	99.02 312	87.84 338	95.01 311	99.61 244	77.24 347	98.77 260	94.33 283	86.41 329	97.63 301

test12356		86.30 326	87.15 327	83.77 344	84.24 357	72.00 354	99.94 222	96.80 357	84.63 346	85.16 349	96.51 330	77.02 348	86.31 360	70.06 356	89.93 300	93.00 352

tmp_tt		75.80 335	74.26 336	80.43 345	52.91 373	53.67 370	87.42 363	97.98 345	61.80 359	67.04 362	100.00 1	76.43 349	96.40 333	96.47 253	28.26 366	91.23 354

MIMVSNet1		91.96 311	91.20 312	94.23 324	94.94 342	91.69 332	99.34 308	99.22 250	88.23 335	94.18 317	98.45 316	75.52 350	93.41 350	79.37 347	91.49 280	97.60 306

VDDNet		96.39 248	95.55 266	98.90 185	99.27 212	97.45 244	99.15 332	99.92 36	91.28 311	99.98 84	100.00 1	73.55 351	100.00 1	99.85 85	96.98 218	99.24 215

FMVSNet1		94.45 288	93.63 292	96.89 287	98.87 246	94.87 290	99.18 324	99.27 236	90.95 314	97.31 282	98.81 302	72.89 352	98.07 310	92.61 300	92.81 266	97.72 272

VDD-MVS		96.58 238	95.99 246	98.34 211	99.52 184	95.33 283	99.18 324	99.38 183	96.64 187	99.77 150	100.00 1	72.51 353	100.00 1	100.00 1	96.94 219	99.70 201

EG-PatchMatch MVS		92.94 306	92.49 301	94.29 323	95.87 336	87.07 341	99.07 340	98.11 340	93.19 294	88.98 333	98.66 310	70.89 354	99.08 230	92.43 304	95.21 238	96.72 327

OpenMVS_ROB	88.34 20	91.89 313	91.12 313	94.19 325	95.55 338	87.63 340	99.26 313	98.03 342	86.61 340	90.65 330	96.82 328	70.14 355	98.78 257	86.54 336	96.50 222	96.15 333

testmvs		80.17 329	81.95 330	74.80 350	58.54 371	59.58 368	100.00 1	87.14 371	76.09 354	99.61 166	100.00 1	67.06 356	74.19 368	98.84 171	50.30 359	90.64 355

UnsupCasMVSNet_bld		89.50 322	88.00 325	93.99 326	95.30 339	88.86 338	98.52 348	99.28 229	85.50 344	87.80 345	94.11 350	61.63 357	96.96 323	90.63 314	79.26 341	96.15 333

testing_2		90.79 318	88.26 324	98.35 210	89.11 351	98.56 180	99.70 273	99.14 272	93.70 278	73.80 356	94.06 351	55.19 358	98.76 262	97.17 237	92.50 269	97.74 256

Gipuma		84.73 328	83.50 329	88.40 333	97.50 316	82.21 346	88.87 361	99.05 308	65.81 357	85.71 347	90.49 355	53.70 359	96.31 335	78.64 349	91.74 277	86.67 359
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
testmv		79.83 330	79.77 331	79.99 347	78.22 364	63.55 364	99.67 280	95.51 363	80.89 351	76.24 355	92.90 353	52.16 360	86.10 361	62.45 361	79.90 340	90.33 357

Test4		92.63 307	90.45 318	99.17 168	92.81 345	99.02 159	99.98 202	99.13 277	96.60 190	82.04 353	96.27 332	51.35 361	98.75 263	97.55 227	98.36 156	99.75 192

EMVS		69.88 339	69.09 339	72.24 355	84.70 356	65.82 362	99.96 212	87.08 372	49.82 366	71.51 359	84.74 362	49.30 362	75.32 366	50.97 366	43.71 362	75.59 366

PM-MVS		88.39 324	87.41 326	91.31 330	91.73 347	82.02 347	99.79 252	96.62 359	91.06 313	90.71 329	95.73 335	48.60 363	95.96 340	90.56 315	81.91 338	95.97 336

E-PMN		70.72 337	70.06 338	72.69 354	83.92 358	65.48 363	99.95 218	92.72 366	49.88 365	72.30 358	86.26 361	47.17 364	77.43 365	53.83 365	44.49 361	75.17 367

ambc				88.45 332	86.84 355	70.76 358	97.79 355	98.02 344		90.91 328	95.14 346	38.69 365	98.51 285	94.97 275	84.23 334	96.09 335

FPMVS		77.92 334	79.45 332	73.34 352	76.87 365	46.81 371	98.24 350	99.05 308	59.89 361	73.55 357	98.34 322	36.81 366	86.55 358	80.96 343	91.35 282	86.65 360

PMMVS2		79.15 332	77.28 334	84.76 343	82.34 359	72.66 353	99.70 273	95.11 364	71.68 356	84.78 350	90.87 354	32.05 367	89.99 355	75.53 353	63.45 356	91.64 353

LCM-MVSNet		79.01 333	76.93 335	85.27 342	78.28 363	68.01 359	96.57 356	98.03 342	55.10 362	82.03 354	93.27 352	31.99 368	93.95 348	82.72 341	74.37 354	93.84 349

no-one		74.65 336	71.03 337	85.51 341	80.99 361	75.42 351	99.70 273	97.15 354	81.02 350	66.48 364	80.55 367	29.10 369	93.65 349	73.74 354	30.53 365	87.47 358

ANet_high		66.05 341	63.44 343	73.88 351	61.14 370	63.45 365	95.68 359	87.18 370	79.93 352	47.35 367	80.68 366	22.35 370	72.33 369	61.24 362	35.42 364	85.88 361

PNet_i23d		69.93 338	67.61 340	76.86 348	75.89 366	62.08 367	97.85 353	88.23 369	61.04 360	55.65 366	84.10 363	19.35 371	83.21 362	66.45 360	59.98 357	85.29 362

wuyk23d		28.28 346	29.73 348	23.92 358	75.89 366	32.61 373	66.50 364	12.88 375	16.09 368	14.59 370	16.59 370	12.35 372	32.36 370	39.36 367	13.36 368	6.79 368

wuykxyi23d		62.75 343	59.23 344	73.34 352	61.53 369	59.39 369	93.28 360	86.17 373	53.70 363	46.89 368	77.89 368	12.35 372	79.96 363	60.86 364	40.35 363	80.68 365

PMVS	60.66 23	65.98 342	65.05 341	68.75 356	55.06 372	38.40 372	88.19 362	96.98 355	48.30 367	44.82 369	88.52 358	12.22 374	86.49 359	67.58 357	83.79 335	81.35 364
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVE	68.59 21	67.22 340	64.68 342	74.84 349	74.67 368	62.32 366	95.84 357	90.87 368	50.98 364	58.72 365	81.05 365	12.20 375	78.95 364	61.06 363	56.75 358	83.24 363
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
test_part1				0.00 359		0.00 374	0.00 365	99.42 130				0.00 376	0.00 371	0.00 368	0.00 369	0.00 369

v1.0		41.47 344	55.29 345	0.00 359	100.00 1	0.00 374	0.00 365	99.42 130	98.23 65	100.00 1	100.00 1	0.00 376	0.00 371	0.00 368	0.00 369	0.00 369

sosnet-low-res		0.01 350	0.02 351	0.00 359	0.00 374	0.00 374	0.00 365	0.00 376	0.00 369	0.00 371	0.14 371	0.00 376	0.00 371	0.00 368	0.00 369	0.00 369

sosnet		0.01 350	0.02 351	0.00 359	0.00 374	0.00 374	0.00 365	0.00 376	0.00 369	0.00 371	0.14 371	0.00 376	0.00 371	0.00 368	0.00 369	0.00 369

uncertanet		0.01 350	0.02 351	0.00 359	0.00 374	0.00 374	0.00 365	0.00 376	0.00 369	0.00 371	0.14 371	0.00 376	0.00 371	0.00 368	0.00 369	0.00 369

Regformer		0.01 350	0.02 351	0.00 359	0.00 374	0.00 374	0.00 365	0.00 376	0.00 369	0.00 371	0.14 371	0.00 376	0.00 371	0.00 368	0.00 369	0.00 369

ab-mvs-re		8.33 348	11.11 349	0.00 359	0.00 374	0.00 374	0.00 365	0.00 376	0.00 369	0.00 371	100.00 1	0.00 376	0.00 371	0.00 368	0.00 369	0.00 369

uanet		0.01 350	0.02 351	0.00 359	0.00 374	0.00 374	0.00 365	0.00 376	0.00 369	0.00 371	0.14 371	0.00 376	0.00 371	0.00 368	0.00 369	0.00 369

GSMVS																99.91 132

test_part2					100.00 1	99.99 1				100.00 1

MTGPA								99.42 130

MTMP							100.00 1	99.18 262

gm-plane-assit					99.52 184	97.26 256			95.86 220		100.00 1		99.43 215	98.76 176

test9_res														100.00 1	100.00 1	100.00 1

agg_prior2														100.00 1	100.00 1	100.00 1

agg_prior					100.00 1	99.88 61		99.42 130		100.00 1			99.97 103

test_prior4						99.93 32	100.00 1

test_prior				99.90 75	100.00 1	99.75 88		99.73 56					99.97 103			100.00 1

旧先验2							100.00 1		98.11 75	100.00 1			100.00 1	99.67 111

新几何2							100.00 1

无先验							100.00 1	99.80 43	97.98 84				100.00 1	99.33 144		100.00 1

原ACMM2							100.00 1

testdata2													100.00 1	97.36 235

testdata1							100.00 1		98.77 38

plane_prior7					99.00 233	94.78 300

plane_prior5								99.40 164					99.55 198	99.79 94	95.57 227	97.76 228

plane_prior4											99.97 159

plane_prior3						94.79 299			99.03 16	99.08 196

plane_prior2							100.00 1		99.00 19

plane_prior1					99.02 228

plane_prior						94.80 296	100.00 1		99.03 16						95.58 223

n2								0.00 376

nn								0.00 376

door-mid								96.32 361

test11								99.42 130

door								96.13 362

HQP5-MVS						94.82 293

HQP-NCC					99.07 221		100.00 1		99.04 13	99.17 188

ACMP_Plane					99.07 221		100.00 1		99.04 13	99.17 188

BP-MVS														99.79 94

HQP4-MVS										99.17 188			99.57 189			97.77 226

HQP3-MVS								99.40 164							95.58 223

NP-MVS					99.07 221	94.81 295					99.97 159

ACMMP++_ref															94.58 253

ACMMP++															95.17 240

High-resolution multi-view benchmark