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.

APDe-MVS		99.02 1	98.84 1	99.55 3	99.57 26	98.96 5	99.39 5	98.93 36	97.38 18	99.41 4	99.54 1	96.66 6	99.84 45	98.86 2	99.85 2	99.87 1

SteuartSystems-ACMMP		98.90 3	98.75 2	99.36 14	99.22 75	98.43 19	99.10 54	98.87 51	97.38 18	99.35 7	99.40 8	97.78 1	99.87 37	97.77 41	99.85 2	99.78 8
Skip Steuart: Steuart Systems R&D Blog.
SD-MVS		98.64 11	98.68 3	98.53 76	99.33 46	98.36 24	98.90 79	98.85 55	97.28 22	99.72 1	99.39 9	96.63 8	97.60 308	98.17 23	99.85 2	99.64 55

ESAPD		98.92 2	98.67 4	99.65 1	99.58 25	99.20 1	98.42 180	98.91 42	97.58 7	99.54 3	99.46 6	97.10 2	99.94 3	97.64 48	99.84 7	99.83 2

TSAR-MVS + MP.		98.78 4	98.62 5	99.24 27	99.69 17	98.28 30	99.14 46	98.66 111	96.84 44	99.56 2	99.31 23	96.34 12	99.70 95	98.32 20	99.73 36	99.73 29

MSLP-MVS++		98.56 23	98.57 6	98.55 73	99.26 67	96.80 86	98.71 132	99.05 23	97.28 22	98.84 31	99.28 28	96.47 11	99.40 139	98.52 14	99.70 39	99.47 79

CNVR-MVS		98.78 4	98.56 7	99.45 10	99.32 49	98.87 8	98.47 173	98.81 64	97.72 4	98.76 37	99.16 45	97.05 3	99.78 78	98.06 26	99.66 44	99.69 37

Regformer-4		98.64 11	98.53 8	98.99 49	99.43 39	97.37 66	98.40 182	98.79 73	97.46 13	99.09 17	99.31 23	95.86 33	99.80 61	98.64 4	99.76 25	99.79 5

HSP-MVS		98.70 6	98.52 9	99.24 27	99.75 3	98.23 31	99.26 19	98.58 124	97.52 8	99.41 4	98.78 90	96.00 25	99.79 73	97.79 40	99.59 54	99.69 37

Regformer-2		98.69 8	98.52 9	99.19 30	99.35 41	98.01 44	98.37 184	98.81 64	97.48 12	99.21 13	99.21 35	96.13 18	99.80 61	98.40 18	99.73 36	99.75 22

Regformer-1		98.66 9	98.51 11	99.12 42	99.35 41	97.81 53	98.37 184	98.76 79	97.49 11	99.20 14	99.21 35	96.08 21	99.79 73	98.42 16	99.73 36	99.75 22

Regformer-3		98.59 17	98.50 12	98.86 59	99.43 39	97.05 77	98.40 182	98.68 101	97.43 14	99.06 18	99.31 23	95.80 34	99.77 83	98.62 6	99.76 25	99.78 8

XVS		98.70 6	98.49 13	99.34 15	99.70 15	98.35 25	99.29 15	98.88 48	97.40 15	98.46 49	99.20 38	95.90 31	99.89 28	97.85 36	99.74 34	99.78 8

DeepPCF-MVS	96.37 2	97.93 50	98.48 14	96.30 242	99.00 92	89.54 306	97.43 273	98.87 51	98.16 2	99.26 10	99.38 13	96.12 19	99.64 105	98.30 21	99.77 19	99.72 32

HFP-MVS		98.63 13	98.40 15	99.32 18	99.72 11	98.29 28	99.23 24	98.96 31	96.10 67	98.94 25	99.17 42	96.06 22	99.92 14	97.62 49	99.78 16	99.75 22

EI-MVSNet-Vis-set		98.47 30	98.39 16	98.69 64	99.46 36	96.49 102	98.30 195	98.69 98	97.21 29	98.84 31	99.36 18	95.41 41	99.78 78	98.62 6	99.65 45	99.80 4

region2R		98.61 14	98.38 17	99.29 20	99.74 7	98.16 37	99.23 24	98.93 36	96.15 62	98.94 25	99.17 42	95.91 30	99.94 3	97.55 54	99.79 12	99.78 8

MCST-MVS		98.65 10	98.37 18	99.48 7	99.60 24	98.87 8	98.41 181	98.68 101	97.04 39	98.52 48	98.80 88	96.78 5	99.83 46	97.93 30	99.61 50	99.74 27

ACMMPR		98.59 17	98.36 19	99.29 20	99.74 7	98.15 38	99.23 24	98.95 33	96.10 67	98.93 29	99.19 41	95.70 35	99.94 3	97.62 49	99.79 12	99.78 8

CP-MVS		98.57 22	98.36 19	99.19 30	99.66 19	97.86 49	99.34 11	98.87 51	95.96 70	98.60 45	99.13 47	96.05 24	99.94 3	97.77 41	99.86 1	99.77 15

NCCC		98.61 14	98.35 21	99.38 12	99.28 64	98.61 13	98.45 174	98.76 79	97.82 3	98.45 53	98.93 77	96.65 7	99.83 46	97.38 61	99.41 78	99.71 34

EI-MVSNet-UG-set		98.41 32	98.34 22	98.61 69	99.45 37	96.32 110	98.28 197	98.68 101	97.17 32	98.74 38	99.37 14	95.25 47	99.79 73	98.57 8	99.54 66	99.73 29

MVS_111021_HR		98.47 30	98.34 22	98.88 58	99.22 75	97.32 67	97.91 237	99.58 3	97.20 30	98.33 58	99.00 66	95.99 26	99.64 105	98.05 28	99.76 25	99.69 37

DeepC-MVS_fast	96.70 1	98.55 24	98.34 22	99.18 34	99.25 68	98.04 42	98.50 170	98.78 75	97.72 4	98.92 30	99.28 28	95.27 46	99.82 52	97.55 54	99.77 19	99.69 37
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
APD-MVS_3200maxsize		98.53 27	98.33 25	99.15 39	99.50 31	97.92 48	99.15 45	98.81 64	96.24 60	99.20 14	99.37 14	95.30 45	99.80 61	97.73 43	99.67 41	99.72 32

ACMMP_Plus		98.61 14	98.30 26	99.55 3	99.62 23	98.95 6	98.82 101	98.81 64	95.80 74	99.16 16	99.47 5	95.37 42	99.92 14	97.89 34	99.75 31	99.79 5

MTAPA		98.58 19	98.29 27	99.46 8	99.76 1	98.64 11	98.90 79	98.74 83	97.27 26	98.02 69	99.39 9	94.81 56	99.96 1	97.91 31	99.79 12	99.77 15

#test#		98.54 26	98.27 28	99.32 18	99.72 11	98.29 28	98.98 71	98.96 31	95.65 80	98.94 25	99.17 42	96.06 22	99.92 14	97.21 64	99.78 16	99.75 22

mPP-MVS		98.51 28	98.26 29	99.25 26	99.75 3	98.04 42	99.28 17	98.81 64	96.24 60	98.35 57	99.23 32	95.46 40	99.94 3	97.42 59	99.81 9	99.77 15

SMA-MVS		98.58 19	98.25 30	99.56 2	99.51 29	99.04 4	98.95 74	98.80 71	93.67 179	99.37 6	99.52 3	96.52 10	99.89 28	98.06 26	99.81 9	99.76 21

zzz-MVS		98.55 24	98.25 30	99.46 8	99.76 1	98.64 11	98.55 162	98.74 83	97.27 26	98.02 69	99.39 9	94.81 56	99.96 1	97.91 31	99.79 12	99.77 15

HPM-MVS++		98.58 19	98.25 30	99.55 3	99.50 31	99.08 3	98.72 131	98.66 111	97.51 9	98.15 60	98.83 85	95.70 35	99.92 14	97.53 56	99.67 41	99.66 50

TSAR-MVS + GP.		98.38 34	98.24 33	98.81 60	99.22 75	97.25 72	98.11 218	98.29 175	97.19 31	98.99 24	99.02 61	96.22 13	99.67 101	98.52 14	98.56 112	99.51 71

PGM-MVS		98.49 29	98.23 34	99.27 25	99.72 11	98.08 41	98.99 68	99.49 5	95.43 89	99.03 19	99.32 22	95.56 37	99.94 3	96.80 84	99.77 19	99.78 8

MVS_111021_LR		98.34 38	98.23 34	98.67 66	99.27 65	96.90 83	97.95 232	99.58 3	97.14 34	98.44 54	99.01 65	95.03 53	99.62 110	97.91 31	99.75 31	99.50 73

DELS-MVS		98.40 33	98.20 36	98.99 49	99.00 92	97.66 55	97.75 254	98.89 45	97.71 6	98.33 58	98.97 68	94.97 54	99.88 36	98.42 16	99.76 25	99.42 88
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
HPM-MVS_fast		98.38 34	98.13 37	99.12 42	99.75 3	97.86 49	99.44 4	98.82 61	94.46 142	98.94 25	99.20 38	95.16 50	99.74 89	97.58 51	99.85 2	99.77 15

HPM-MVS		98.36 36	98.10 38	99.13 40	99.74 7	97.82 52	99.53 1	98.80 71	94.63 135	98.61 44	98.97 68	95.13 51	99.77 83	97.65 47	99.83 8	99.79 5
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
PHI-MVS		98.34 38	98.06 39	99.18 34	99.15 82	98.12 40	99.04 63	99.09 19	93.32 197	98.83 33	99.10 51	96.54 9	99.83 46	97.70 45	99.76 25	99.59 63

abl_6		98.30 42	98.03 40	99.13 40	99.56 27	97.76 54	99.13 50	98.82 61	96.14 63	99.26 10	99.37 14	93.33 78	99.93 10	96.96 71	99.67 41	99.69 37

MP-MVS		98.33 40	98.01 41	99.28 22	99.75 3	98.18 36	99.22 30	98.79 73	96.13 64	97.92 79	99.23 32	94.54 61	99.94 3	96.74 86	99.78 16	99.73 29
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
APD-MVS		98.35 37	98.00 42	99.42 11	99.51 29	98.72 10	98.80 110	98.82 61	94.52 138	99.23 12	99.25 31	95.54 39	99.80 61	96.52 94	99.77 19	99.74 27
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ACMMP		98.23 43	97.95 43	99.09 44	99.74 7	97.62 58	99.03 64	99.41 6	95.98 69	97.60 99	99.36 18	94.45 66	99.93 10	97.14 65	98.85 99	99.70 36
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
MP-MVS-pluss		98.31 41	97.92 44	99.49 6	99.72 11	98.88 7	98.43 178	98.78 75	94.10 149	97.69 91	99.42 7	95.25 47	99.92 14	98.09 25	99.80 11	99.67 48
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
test_prior3		98.22 44	97.90 45	99.19 30	99.31 51	98.22 33	97.80 250	98.84 56	96.12 65	97.89 81	98.69 97	95.96 27	99.70 95	96.89 75	99.60 51	99.65 52

PS-MVSNAJ		97.73 57	97.77 46	97.62 140	98.68 129	95.58 149	97.34 282	98.51 136	97.29 21	98.66 41	97.88 172	94.51 62	99.90 26	97.87 35	99.17 88	97.39 205

CANet		98.05 45	97.76 47	98.90 57	98.73 122	97.27 69	98.35 186	98.78 75	97.37 20	97.72 89	98.96 73	91.53 116	99.92 14	98.79 3	99.65 45	99.51 71

CSCG		97.85 54	97.74 48	98.20 97	99.67 18	95.16 166	99.22 30	99.32 7	93.04 205	97.02 118	98.92 79	95.36 43	99.91 23	97.43 58	99.64 47	99.52 68

xiu_mvs_v2_base		97.66 63	97.70 49	97.56 148	98.61 135	95.46 155	97.44 271	98.46 146	97.15 33	98.65 42	98.15 149	94.33 68	99.80 61	97.84 38	98.66 108	97.41 203

UA-Net		97.96 47	97.62 50	98.98 51	98.86 114	97.47 63	98.89 83	99.08 20	96.67 50	98.72 39	99.54 1	93.15 81	99.81 54	94.87 144	98.83 100	99.65 52

MG-MVS		97.81 55	97.60 51	98.44 83	99.12 84	95.97 122	97.75 254	98.78 75	96.89 43	98.46 49	99.22 34	93.90 75	99.68 100	94.81 148	99.52 68	99.67 48

DeepC-MVS	95.98 3	97.88 51	97.58 52	98.77 61	99.25 68	96.93 81	98.83 99	98.75 82	96.96 42	96.89 126	99.50 4	90.46 131	99.87 37	97.84 38	99.76 25	99.52 68
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
xiu_mvs_v1_base_debu		97.60 64	97.56 53	97.72 128	98.35 144	95.98 118	97.86 245	98.51 136	97.13 35	99.01 21	98.40 124	91.56 112	99.80 61	98.53 10	98.68 104	97.37 207

xiu_mvs_v1_base		97.60 64	97.56 53	97.72 128	98.35 144	95.98 118	97.86 245	98.51 136	97.13 35	99.01 21	98.40 124	91.56 112	99.80 61	98.53 10	98.68 104	97.37 207

xiu_mvs_v1_base_debi		97.60 64	97.56 53	97.72 128	98.35 144	95.98 118	97.86 245	98.51 136	97.13 35	99.01 21	98.40 124	91.56 112	99.80 61	98.53 10	98.68 104	97.37 207

train_agg		97.97 46	97.52 56	99.33 17	99.31 51	98.50 15	97.92 234	98.73 88	92.98 208	97.74 87	98.68 99	96.20 14	99.80 61	96.59 90	99.57 57	99.68 43

agg_prior1		97.95 48	97.51 57	99.28 22	99.30 56	98.38 20	97.81 249	98.72 90	93.16 202	97.57 101	98.66 102	96.14 17	99.81 54	96.63 89	99.56 63	99.66 50

CDPH-MVS		97.94 49	97.49 58	99.28 22	99.47 35	98.44 17	97.91 237	98.67 108	92.57 223	98.77 36	98.85 83	95.93 29	99.72 90	95.56 127	99.69 40	99.68 43

casdiffmvs1		97.72 58	97.49 58	98.41 87	98.52 141	96.71 91	99.14 46	98.32 168	95.15 111	98.46 49	98.31 137	93.10 82	99.21 161	98.14 24	98.27 126	99.31 95

MVSFormer		97.57 67	97.49 58	97.84 118	98.07 167	95.76 144	99.47 2	98.40 157	94.98 119	98.79 34	98.83 85	92.34 90	98.41 263	96.91 73	99.59 54	99.34 91

PVSNet_Blended_VisFu		97.70 60	97.46 61	98.44 83	99.27 65	95.91 138	98.63 148	99.16 17	94.48 141	97.67 92	98.88 81	92.80 85	99.91 23	97.11 66	99.12 89	99.50 73

DP-MVS Recon		97.86 53	97.46 61	99.06 47	99.53 28	98.35 25	98.33 188	98.89 45	92.62 220	98.05 65	98.94 76	95.34 44	99.65 103	96.04 108	99.42 77	99.19 111

agg_prior3		97.87 52	97.42 63	99.23 29	99.29 59	98.23 31	97.92 234	98.72 90	92.38 236	97.59 100	98.64 104	96.09 20	99.79 73	96.59 90	99.57 57	99.68 43

VNet		97.79 56	97.40 64	98.96 53	98.88 112	97.55 60	98.63 148	98.93 36	96.74 47	99.02 20	98.84 84	90.33 134	99.83 46	98.53 10	96.66 164	99.50 73

OMC-MVS		97.55 69	97.34 65	98.20 97	99.33 46	95.92 136	98.28 197	98.59 119	95.52 85	97.97 75	99.10 51	93.28 80	99.49 131	95.09 142	98.88 96	99.19 111

CPTT-MVS		97.72 58	97.32 66	98.92 55	99.64 20	97.10 76	99.12 52	98.81 64	92.34 237	98.09 63	99.08 57	93.01 83	99.92 14	96.06 107	99.77 19	99.75 22

EPP-MVSNet		97.46 70	97.28 67	97.99 111	98.64 132	95.38 157	99.33 13	98.31 169	93.61 182	97.19 108	99.07 58	94.05 72	99.23 153	96.89 75	98.43 119	99.37 90

MVS_0304		97.70 60	97.25 68	99.07 45	98.90 103	97.83 51	98.20 203	98.74 83	97.51 9	98.03 68	99.06 59	86.12 232	99.93 10	99.02 1	99.64 47	99.44 86

API-MVS		97.41 78	97.25 68	97.91 114	98.70 126	96.80 86	98.82 101	98.69 98	94.53 137	98.11 62	98.28 139	94.50 65	99.57 119	94.12 167	99.49 69	97.37 207

canonicalmvs		97.67 62	97.23 70	98.98 51	98.70 126	98.38 20	99.34 11	98.39 159	96.76 46	97.67 92	97.40 209	92.26 94	99.49 131	98.28 22	96.28 186	99.08 129

lupinMVS		97.44 74	97.22 71	98.12 104	98.07 167	95.76 144	97.68 259	97.76 237	94.50 139	98.79 34	98.61 106	92.34 90	99.30 145	97.58 51	99.59 54	99.31 95

CHOSEN 280x420		97.18 90	97.18 72	97.20 167	98.81 118	93.27 256	95.78 332	99.15 18	95.25 105	96.79 133	98.11 152	92.29 93	99.07 179	98.56 9	99.85 2	99.25 105

casdiffmvs		97.42 76	97.12 73	98.31 92	98.35 144	96.55 100	99.05 60	98.20 188	94.97 121	97.55 103	98.11 152	92.33 92	99.18 164	97.70 45	97.85 141	99.18 115

PVSNet_Blended		97.38 80	97.12 73	98.14 101	99.25 68	95.35 160	97.28 286	99.26 8	93.13 203	97.94 77	98.21 146	92.74 86	99.81 54	96.88 78	99.40 80	99.27 103

Vis-MVSNet		97.42 76	97.11 75	98.34 90	98.66 130	96.23 113	99.22 30	99.00 26	96.63 52	98.04 67	99.21 35	88.05 194	99.35 144	96.01 110	99.21 86	99.45 85
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PAPM_NR		97.46 70	97.11 75	98.50 78	99.50 31	96.41 106	98.63 148	98.60 118	95.18 108	97.06 115	98.06 156	94.26 70	99.57 119	93.80 174	98.87 98	99.52 68

jason		97.32 84	97.08 77	98.06 109	97.45 206	95.59 148	97.87 244	97.91 232	94.79 127	98.55 47	98.83 85	91.12 120	99.23 153	97.58 51	99.60 51	99.34 91
jason: jason.
alignmvs		97.56 68	97.07 78	99.01 48	98.66 130	98.37 23	98.83 99	98.06 224	96.74 47	98.00 74	97.65 192	90.80 127	99.48 135	98.37 19	96.56 168	99.19 111

diffmvs1		97.35 83	97.07 78	98.20 97	98.25 152	96.13 116	98.61 151	98.34 165	95.47 86	97.66 95	98.01 160	92.54 88	99.30 145	96.44 97	98.29 125	99.17 117

CNLPA		97.45 73	97.03 80	98.73 62	99.05 86	97.44 65	98.07 222	98.53 132	95.32 102	96.80 132	98.53 113	93.32 79	99.72 90	94.31 162	99.31 84	99.02 133

MVS_Test		97.28 85	97.00 81	98.13 103	98.33 149	95.97 122	98.74 126	98.07 222	94.27 145	98.44 54	98.07 155	92.48 89	99.26 150	96.43 98	98.19 129	99.16 118

sss		97.39 79	96.98 82	98.61 69	98.60 136	96.61 95	98.22 201	98.93 36	93.97 157	98.01 72	98.48 118	91.98 104	99.85 42	96.45 96	98.15 130	99.39 89

3Dnovator	94.51 5	97.46 70	96.93 83	99.07 45	97.78 184	97.64 56	99.35 10	99.06 21	97.02 40	93.75 239	99.16 45	89.25 147	99.92 14	97.22 63	99.75 31	99.64 55

WTY-MVS		97.37 81	96.92 84	98.72 63	98.86 114	96.89 85	98.31 193	98.71 95	95.26 104	97.67 92	98.56 112	92.21 97	99.78 78	95.89 113	96.85 160	99.48 78

IS-MVSNet		97.22 87	96.88 85	98.25 95	98.85 116	96.36 108	99.19 36	97.97 229	95.39 91	97.23 107	98.99 67	91.11 121	98.93 197	94.60 153	98.59 110	99.47 79

EPNet		97.28 85	96.87 86	98.51 77	94.98 325	96.14 115	98.90 79	97.02 294	98.28 1	95.99 172	99.11 49	91.36 117	99.89 28	96.98 68	99.19 87	99.50 73
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		97.12 93	96.80 87	98.08 107	99.30 56	94.56 220	98.05 223	99.71 1	93.57 183	97.09 111	98.91 80	88.17 188	99.89 28	96.87 81	99.56 63	99.81 3

F-COLMAP		97.09 95	96.80 87	97.97 112	99.45 37	94.95 179	98.55 162	98.62 117	93.02 206	96.17 167	98.58 111	94.01 73	99.81 54	93.95 170	98.90 95	99.14 121

TAMVS		97.02 97	96.79 89	97.70 133	98.06 169	95.31 162	98.52 165	98.31 169	93.95 158	97.05 116	98.61 106	93.49 77	98.52 239	95.33 134	97.81 142	99.29 101

0601test		97.22 87	96.78 90	98.54 75	98.73 122	96.60 96	98.45 174	98.31 169	94.70 128	98.02 69	98.42 123	90.80 127	99.70 95	96.81 83	96.79 162	99.34 91

PLC	95.07 4	97.20 89	96.78 90	98.44 83	99.29 59	96.31 112	98.14 213	98.76 79	92.41 234	96.39 163	98.31 137	94.92 55	99.78 78	94.06 168	98.77 103	99.23 107
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
3Dnovator+	94.38 6	97.43 75	96.78 90	99.38 12	97.83 182	98.52 14	99.37 7	98.71 95	97.09 38	92.99 260	99.13 47	89.36 144	99.89 28	96.97 69	99.57 57	99.71 34

1121		97.37 81	96.77 93	99.16 37	99.34 43	97.99 47	98.19 207	98.68 101	90.14 288	98.01 72	98.97 68	94.80 58	99.87 37	93.36 183	99.46 74	99.61 58

diffmvs		97.03 96	96.75 94	97.88 116	98.14 164	95.25 164	98.54 164	98.13 204	95.17 109	97.03 117	97.94 166	91.83 107	99.30 145	96.01 110	97.94 136	99.11 124

AdaColmap		97.15 92	96.70 95	98.48 80	99.16 80	96.69 92	98.01 227	98.89 45	94.44 143	96.83 128	98.68 99	90.69 129	99.76 85	94.36 159	99.29 85	98.98 137

Effi-MVS+		97.12 93	96.69 96	98.39 88	98.19 158	96.72 90	97.37 278	98.43 154	93.71 172	97.65 96	98.02 158	92.20 98	99.25 151	96.87 81	97.79 143	99.19 111

CDS-MVSNet		96.99 98	96.69 96	97.90 115	98.05 170	95.98 118	98.20 203	98.33 167	93.67 179	96.95 119	98.49 117	93.54 76	98.42 256	95.24 140	97.74 146	99.31 95
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
mvs-test1		96.60 110	96.68 98	96.37 236	97.89 179	91.81 275	98.56 160	98.10 217	96.57 53	96.52 148	97.94 166	90.81 125	99.45 137	95.72 120	98.01 133	97.86 191

LS3D		97.16 91	96.66 99	98.68 65	98.53 140	97.19 74	98.93 77	98.90 43	92.83 217	95.99 172	99.37 14	92.12 100	99.87 37	93.67 177	99.57 57	98.97 138

PVSNet_BlendedMVS		96.73 107	96.60 100	97.12 173	99.25 68	95.35 160	98.26 199	99.26 8	94.28 144	97.94 77	97.46 204	92.74 86	99.81 54	96.88 78	93.32 240	96.20 301

Effi-MVS+-dtu		96.29 122	96.56 101	95.51 267	97.89 179	90.22 299	98.80 110	98.10 217	96.57 53	96.45 162	96.66 278	90.81 125	98.91 199	95.72 120	97.99 134	97.40 204

CANet_DTU		96.96 99	96.55 102	98.21 96	98.17 162	96.07 117	97.98 230	98.21 185	97.24 28	97.13 110	98.93 77	86.88 221	99.91 23	95.00 143	99.37 82	98.66 157

Vis-MVSNet (Re-imp)		96.87 103	96.55 102	97.83 119	98.73 122	95.46 155	99.20 34	98.30 173	94.96 122	96.60 141	98.87 82	90.05 137	98.59 227	93.67 177	98.60 109	99.46 83

mvs_anonymous		96.70 108	96.53 104	97.18 169	98.19 158	93.78 243	98.31 193	98.19 190	94.01 153	94.47 196	98.27 142	92.08 102	98.46 248	97.39 60	97.91 137	99.31 95

HyFIR lowres test		96.90 102	96.49 105	98.14 101	99.33 46	95.56 151	97.38 276	99.65 2	92.34 237	97.61 98	98.20 147	89.29 146	99.10 176	96.97 69	97.60 150	99.77 15

XVG-OURS		96.55 114	96.41 106	96.99 180	98.75 121	93.76 244	97.50 270	98.52 134	95.67 78	96.83 128	99.30 27	88.95 158	99.53 128	95.88 114	96.26 187	97.69 198

MAR-MVS		96.91 101	96.40 107	98.45 82	98.69 128	96.90 83	98.66 146	98.68 101	92.40 235	97.07 114	97.96 164	91.54 115	99.75 87	93.68 176	98.92 94	98.69 153
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
XVG-OURS-SEG-HR		96.51 115	96.34 108	97.02 179	98.77 120	93.76 244	97.79 252	98.50 141	95.45 88	96.94 121	99.09 55	87.87 200	99.55 127	96.76 85	95.83 204	97.74 194

PMMVS		96.60 110	96.33 109	97.41 159	97.90 178	93.93 239	97.35 281	98.41 155	92.84 216	97.76 85	97.45 206	91.10 122	99.20 162	96.26 102	97.91 137	99.11 124

UGNet		96.78 106	96.30 110	98.19 100	98.24 153	95.89 140	98.88 86	98.93 36	97.39 17	96.81 131	97.84 176	82.60 292	99.90 26	96.53 93	99.49 69	98.79 148
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
114514_t		96.93 100	96.27 111	98.92 55	99.50 31	97.63 57	98.85 95	98.90 43	84.80 336	97.77 84	99.11 49	92.84 84	99.66 102	94.85 145	99.77 19	99.47 79

PS-MVSNAJss		96.43 117	96.26 112	96.92 188	95.84 305	95.08 171	99.16 44	98.50 141	95.87 72	93.84 237	98.34 134	94.51 62	98.61 224	96.88 78	93.45 237	97.06 217

PAPR		96.84 104	96.24 113	98.65 67	98.72 125	96.92 82	97.36 280	98.57 125	93.33 196	96.67 135	97.57 199	94.30 69	99.56 121	91.05 246	98.59 110	99.47 79

HY-MVS	93.96 8	96.82 105	96.23 114	98.57 71	98.46 142	97.00 78	98.14 213	98.21 185	93.95 158	96.72 134	97.99 163	91.58 111	99.76 85	94.51 157	96.54 169	98.95 142

PVSNet	91.96 18	96.35 120	96.15 115	96.96 183	99.17 79	92.05 272	96.08 324	98.68 101	93.69 175	97.75 86	97.80 182	88.86 161	99.69 99	94.26 164	99.01 91	99.15 119

FIs		96.51 115	96.12 116	97.67 136	97.13 227	97.54 61	99.36 8	99.22 14	95.89 71	94.03 230	98.35 130	91.98 104	98.44 253	96.40 99	92.76 247	97.01 220

FC-MVSNet-test		96.42 118	96.05 117	97.53 149	96.95 234	97.27 69	99.36 8	99.23 12	95.83 73	93.93 232	98.37 128	92.00 103	98.32 272	96.02 109	92.72 248	97.00 221

CVMVSNet		95.43 166	96.04 118	93.57 315	97.93 176	83.62 338	98.12 216	98.59 119	95.68 77	96.56 142	99.02 61	87.51 210	97.51 311	93.56 180	97.44 152	99.60 61

PatchMatch-RL		96.59 112	96.03 119	98.27 93	99.31 51	96.51 101	97.91 237	99.06 21	93.72 171	96.92 124	98.06 156	88.50 183	99.65 103	91.77 231	99.00 92	98.66 157

1112_ss		96.63 109	96.00 120	98.50 78	98.56 137	96.37 107	98.18 211	98.10 217	92.92 211	94.84 185	98.43 121	92.14 99	99.58 118	94.35 160	96.51 170	99.56 67

DP-MVS		96.59 112	95.93 121	98.57 71	99.34 43	96.19 114	98.70 135	98.39 159	89.45 306	94.52 194	99.35 20	91.85 106	99.85 42	92.89 202	98.88 96	99.68 43

HQP_MVS		96.14 127	95.90 122	96.85 189	97.42 207	94.60 218	98.80 110	98.56 126	97.28 22	95.34 176	98.28 139	87.09 216	99.03 185	96.07 105	94.27 214	96.92 226

Fast-Effi-MVS+-dtu		95.87 135	95.85 123	95.91 255	97.74 186	91.74 279	98.69 137	98.15 201	95.56 83	94.92 183	97.68 191	88.98 156	98.79 214	93.19 188	97.78 144	97.20 215

EI-MVSNet		95.96 131	95.83 124	96.36 237	97.93 176	93.70 249	98.12 216	98.27 176	93.70 174	95.07 180	99.02 61	92.23 96	98.54 232	94.68 149	93.46 235	96.84 241

1314		96.25 126	95.73 125	97.79 122	97.13 227	95.55 153	98.19 207	98.59 119	93.47 186	92.03 284	97.82 180	91.33 118	99.49 131	94.62 152	98.44 117	98.32 178

nrg030		96.28 124	95.72 126	97.96 113	96.90 239	98.15 38	99.39 5	98.31 169	95.47 86	94.42 205	98.35 130	92.09 101	98.69 217	97.50 57	89.05 285	97.04 219

BH-untuned		95.95 132	95.72 126	96.65 206	98.55 139	92.26 269	98.23 200	97.79 236	93.73 170	94.62 191	98.01 160	88.97 157	99.00 188	93.04 193	98.51 113	98.68 154

MVSTER		96.06 129	95.72 126	97.08 177	98.23 154	95.93 129	98.73 129	98.27 176	94.86 126	95.07 180	98.09 154	88.21 187	98.54 232	96.59 90	93.46 235	96.79 245

ab-mvs		96.42 118	95.71 129	98.55 73	98.63 133	96.75 89	97.88 243	98.74 83	93.84 163	96.54 146	98.18 148	85.34 253	99.75 87	95.93 112	96.35 178	99.15 119

Fast-Effi-MVS+		96.28 124	95.70 130	98.03 110	98.29 151	95.97 122	98.58 155	98.25 181	91.74 252	95.29 179	97.23 222	91.03 124	99.15 166	92.90 200	97.96 135	98.97 138

test_djsdf		96.00 130	95.69 131	96.93 186	95.72 309	95.49 154	99.47 2	98.40 157	94.98 119	94.58 192	97.86 173	89.16 150	98.41 263	96.91 73	94.12 222	96.88 236

tpmrst		95.63 147	95.69 131	95.44 273	97.54 198	88.54 322	96.97 296	97.56 246	93.50 185	97.52 104	96.93 262	89.49 141	99.16 165	95.25 139	96.42 173	98.64 159

Test_1112_low_res		96.34 121	95.66 133	98.36 89	98.56 137	95.94 126	97.71 256	98.07 222	92.10 243	94.79 189	97.29 218	91.75 108	99.56 121	94.17 165	96.50 171	99.58 65

PatchmatchNet		95.71 143	95.52 134	96.29 243	97.58 195	90.72 292	96.84 309	97.52 252	94.06 151	97.08 112	96.96 255	89.24 148	98.90 202	92.03 222	98.37 120	99.26 104
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tttt0517		96.07 128	95.51 135	97.78 123	98.41 143	94.84 195	99.28 17	94.33 351	94.26 146	97.64 97	98.64 104	84.05 281	99.47 136	95.34 133	97.60 150	99.03 132

MDTV_nov1_ep13			95.40 136		97.48 201	88.34 324	96.85 308	97.29 281	93.74 169	97.48 105	97.26 219	89.18 149	99.05 180	91.92 227	97.43 153

HQP-MVS		95.72 141	95.40 136	96.69 198	97.20 221	94.25 233	98.05 223	98.46 146	96.43 55	94.45 197	97.73 185	86.75 222	98.96 192	95.30 135	94.18 218	96.86 240

QAPM		96.29 122	95.40 136	98.96 53	97.85 181	97.60 59	99.23 24	98.93 36	89.76 298	93.11 257	99.02 61	89.11 151	99.93 10	91.99 224	99.62 49	99.34 91

RPSCF		94.87 201	95.40 136	93.26 319	98.89 111	82.06 344	98.33 188	98.06 224	90.30 285	96.56 142	99.26 30	87.09 216	99.49 131	93.82 173	96.32 180	98.24 179

ACMM	93.85 9	95.69 145	95.38 140	96.61 212	97.61 192	93.84 242	98.91 78	98.44 150	95.25 105	94.28 215	98.47 119	86.04 242	99.12 169	95.50 129	93.95 227	96.87 238
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LPG-MVS_test		95.62 148	95.34 141	96.47 229	97.46 203	93.54 250	98.99 68	98.54 129	94.67 131	94.36 207	98.77 92	85.39 250	99.11 173	95.71 122	94.15 220	96.76 248

CLD-MVS		95.62 148	95.34 141	96.46 232	97.52 200	93.75 246	97.27 287	98.46 146	95.53 84	94.42 205	98.00 162	86.21 230	98.97 189	96.25 103	94.37 212	96.66 266
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
OPM-MVS		95.69 145	95.33 143	96.76 193	96.16 292	94.63 213	98.43 178	98.39 159	96.64 51	95.02 182	98.78 90	85.15 255	99.05 180	95.21 141	94.20 217	96.60 275

LCM-MVSNet-Re		95.22 184	95.32 144	94.91 291	98.18 160	87.85 329	98.75 122	95.66 336	95.11 113	88.96 311	96.85 271	90.26 136	97.65 306	95.65 125	98.44 117	99.22 108

BH-RMVSNet		95.92 134	95.32 144	97.69 134	98.32 150	94.64 212	98.19 207	97.45 267	94.56 136	96.03 170	98.61 106	85.02 256	99.12 169	90.68 250	99.06 90	99.30 99

MSDG		95.93 133	95.30 146	97.83 119	98.90 103	95.36 158	96.83 310	98.37 162	91.32 267	94.43 204	98.73 96	90.27 135	99.60 111	90.05 267	98.82 101	98.52 163

PatchFormer-LS_test		95.47 163	95.27 147	96.08 251	97.59 194	90.66 293	98.10 220	97.34 276	93.98 156	96.08 168	96.15 298	87.65 208	99.12 169	95.27 138	95.24 209	98.44 168

VDD-MVS		95.82 138	95.23 148	97.61 145	98.84 117	93.98 238	98.68 141	97.40 272	95.02 118	97.95 76	99.34 21	74.37 338	99.78 78	98.64 4	96.80 161	99.08 129

IterMVS-LS		95.46 164	95.21 149	96.22 245	98.12 165	93.72 248	98.32 192	98.13 204	93.71 172	94.26 216	97.31 217	92.24 95	98.10 285	94.63 150	90.12 270	96.84 241
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
UniMVSNet (Re)		95.78 139	95.19 150	97.58 146	96.99 233	97.47 63	98.79 115	99.18 16	95.60 81	93.92 233	97.04 246	91.68 109	98.48 243	95.80 118	87.66 308	96.79 245

UniMVSNet_NR-MVSNet		95.71 143	95.15 151	97.40 161	96.84 242	96.97 79	98.74 126	99.24 10	95.16 110	93.88 234	97.72 187	91.68 109	98.31 274	95.81 116	87.25 313	96.92 226

tfpn1000		95.72 141	95.11 152	97.58 146	99.00 92	95.73 146	99.24 22	95.49 338	94.08 150	96.87 127	97.45 206	85.81 244	99.30 145	91.78 230	96.22 191	97.71 197

VPA-MVSNet		95.75 140	95.11 152	97.69 134	97.24 217	97.27 69	98.94 76	99.23 12	95.13 112	95.51 175	97.32 216	85.73 245	98.91 199	97.33 62	89.55 278	96.89 234

BH-w/o		95.38 172	95.08 154	96.26 244	98.34 148	91.79 276	97.70 257	97.43 269	92.87 214	94.24 218	97.22 223	88.66 176	98.84 208	91.55 235	97.70 148	98.16 181

jajsoiax		95.45 165	95.03 155	96.73 194	95.42 320	94.63 213	99.14 46	98.52 134	95.74 75	93.22 251	98.36 129	83.87 286	98.65 222	96.95 72	94.04 223	96.91 231

mvs_tets		95.41 170	95.00 156	96.65 206	95.58 313	94.42 223	99.00 67	98.55 128	95.73 76	93.21 252	98.38 127	83.45 289	98.63 223	97.09 67	94.00 225	96.91 231

OpenMVS	93.04 13	95.83 137	95.00 156	98.32 91	97.18 224	97.32 67	99.21 33	98.97 29	89.96 291	91.14 292	99.05 60	86.64 224	99.92 14	93.38 182	99.47 71	97.73 195

LFMVS		95.86 136	94.98 158	98.47 81	98.87 113	96.32 110	98.84 98	96.02 324	93.40 194	98.62 43	99.20 38	74.99 333	99.63 108	97.72 44	97.20 155	99.46 83

ACMP	93.49 10	95.34 177	94.98 158	96.43 233	97.67 188	93.48 252	98.73 129	98.44 150	94.94 125	92.53 271	98.53 113	84.50 270	99.14 167	95.48 130	94.00 225	96.66 266
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
Patchmatch-test1		95.32 179	94.97 160	96.35 238	97.67 188	91.29 284	97.33 283	97.60 244	94.68 130	96.92 124	96.95 256	83.97 283	98.50 242	91.33 241	98.32 123	99.25 105

EPNet_dtu		95.21 185	94.95 161	95.99 252	96.17 289	90.45 297	98.16 212	97.27 283	96.77 45	93.14 256	98.33 135	90.34 133	98.42 256	85.57 321	98.81 102	99.09 126
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
view600		95.60 151	94.93 162	97.62 140	99.05 86	94.85 186	99.09 55	97.01 296	95.36 96	96.52 148	97.37 210	84.55 265	99.59 112	89.07 286	96.39 174	98.40 169

view800		95.60 151	94.93 162	97.62 140	99.05 86	94.85 186	99.09 55	97.01 296	95.36 96	96.52 148	97.37 210	84.55 265	99.59 112	89.07 286	96.39 174	98.40 169

conf0.05thres1000		95.60 151	94.93 162	97.62 140	99.05 86	94.85 186	99.09 55	97.01 296	95.36 96	96.52 148	97.37 210	84.55 265	99.59 112	89.07 286	96.39 174	98.40 169

tfpn		95.60 151	94.93 162	97.62 140	99.05 86	94.85 186	99.09 55	97.01 296	95.36 96	96.52 148	97.37 210	84.55 265	99.59 112	89.07 286	96.39 174	98.40 169

anonymousdsp		95.42 168	94.91 166	96.94 185	95.10 324	95.90 139	99.14 46	98.41 155	93.75 167	93.16 253	97.46 204	87.50 212	98.41 263	95.63 126	94.03 224	96.50 288

tfpn_ndepth		95.53 157	94.90 167	97.39 164	98.96 100	95.88 141	99.05 60	95.27 339	93.80 166	96.95 119	96.93 262	85.53 248	99.40 139	91.54 236	96.10 194	96.89 234

thisisatest0515		95.61 150	94.89 168	97.76 125	98.15 163	95.15 168	96.77 311	94.41 349	92.95 210	97.18 109	97.43 208	84.78 261	99.45 137	94.63 150	97.73 147	98.68 154

test-LLR		95.10 189	94.87 169	95.80 260	96.77 244	89.70 303	96.91 300	95.21 340	95.11 113	94.83 187	95.72 309	87.71 204	98.97 189	93.06 191	98.50 114	98.72 150

COLMAP_ROB	93.27 12	95.33 178	94.87 169	96.71 195	99.29 59	93.24 258	98.58 155	98.11 212	89.92 294	93.57 242	99.10 51	86.37 228	99.79 73	90.78 248	98.10 132	97.09 216
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
conf0.01		95.56 155	94.84 171	97.72 128	98.90 103	95.93 129	99.17 37	95.70 330	93.42 188	96.50 153	97.16 225	86.12 232	99.22 155	90.51 254	96.06 195	98.02 184

conf0.002		95.56 155	94.84 171	97.72 128	98.90 103	95.93 129	99.17 37	95.70 330	93.42 188	96.50 153	97.16 225	86.12 232	99.22 155	90.51 254	96.06 195	98.02 184

thresconf0.02		95.50 158	94.84 171	97.51 150	98.90 103	95.93 129	99.17 37	95.70 330	93.42 188	96.50 153	97.16 225	86.12 232	99.22 155	90.51 254	96.06 195	97.37 207

tfpn_n400		95.50 158	94.84 171	97.51 150	98.90 103	95.93 129	99.17 37	95.70 330	93.42 188	96.50 153	97.16 225	86.12 232	99.22 155	90.51 254	96.06 195	97.37 207

tfpnconf		95.50 158	94.84 171	97.51 150	98.90 103	95.93 129	99.17 37	95.70 330	93.42 188	96.50 153	97.16 225	86.12 232	99.22 155	90.51 254	96.06 195	97.37 207

tfpnview11		95.50 158	94.84 171	97.51 150	98.90 103	95.93 129	99.17 37	95.70 330	93.42 188	96.50 153	97.16 225	86.12 232	99.22 155	90.51 254	96.06 195	97.37 207

thres600view7		95.49 162	94.77 177	97.67 136	98.98 96	95.02 172	98.85 95	96.90 304	95.38 92	96.63 137	96.90 264	84.29 272	99.59 112	88.65 295	96.33 179	98.40 169

DU-MVS		95.42 168	94.76 178	97.40 161	96.53 257	96.97 79	98.66 146	98.99 28	95.43 89	93.88 234	97.69 188	88.57 178	98.31 274	95.81 116	87.25 313	96.92 226

tfpn111		95.43 166	94.74 179	97.51 150	98.98 96	94.92 180	98.87 87	96.90 304	95.38 92	96.61 138	96.88 267	84.29 272	99.59 112	88.43 296	96.32 180	98.02 184

CostFormer		94.95 197	94.73 180	95.60 266	97.28 215	89.06 313	97.53 268	96.89 308	89.66 302	96.82 130	96.72 276	86.05 240	98.95 196	95.53 128	96.13 193	98.79 148

conf200view11		95.40 171	94.70 181	97.50 155	98.98 96	94.92 180	98.87 87	96.90 304	95.38 92	96.61 138	96.88 267	84.29 272	99.56 121	88.11 302	96.29 182	98.02 184

thres100view900		95.38 172	94.70 181	97.41 159	98.98 96	94.92 180	98.87 87	96.90 304	95.38 92	96.61 138	96.88 267	84.29 272	99.56 121	88.11 302	96.29 182	97.76 192

AllTest		95.24 183	94.65 183	96.99 180	99.25 68	93.21 259	98.59 153	98.18 193	91.36 263	93.52 244	98.77 92	84.67 262	99.72 90	89.70 275	97.87 139	98.02 184

tfpn200view9		95.32 179	94.62 184	97.43 158	98.94 101	94.98 176	98.68 141	96.93 302	95.33 100	96.55 144	96.53 283	84.23 277	99.56 121	88.11 302	96.29 182	97.76 192

thres400		95.38 172	94.62 184	97.65 139	98.94 101	94.98 176	98.68 141	96.93 302	95.33 100	96.55 144	96.53 283	84.23 277	99.56 121	88.11 302	96.29 182	98.40 169

thres200		95.25 182	94.57 186	97.28 165	98.81 118	94.92 180	98.20 203	97.11 288	95.24 107	96.54 146	96.22 296	84.58 264	99.53 128	87.93 307	96.50 171	97.39 205

TAPA-MVS	93.98 7	95.35 176	94.56 187	97.74 127	99.13 83	94.83 198	98.33 188	98.64 116	86.62 322	96.29 165	98.61 106	94.00 74	99.29 149	80.00 335	99.41 78	99.09 126
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
VDDNet		95.36 175	94.53 188	97.86 117	98.10 166	95.13 169	98.85 95	97.75 238	90.46 281	98.36 56	99.39 9	73.27 340	99.64 105	97.98 29	96.58 167	98.81 147

Anonymous202405211		95.28 181	94.49 189	97.67 136	99.00 92	93.75 246	98.70 135	97.04 292	90.66 278	96.49 159	98.80 88	78.13 318	99.83 46	96.21 104	95.36 208	99.44 86

TranMVSNet+NR-MVSNet		95.14 188	94.48 190	97.11 174	96.45 262	96.36 108	99.03 64	99.03 24	95.04 117	93.58 241	97.93 168	88.27 186	98.03 290	94.13 166	86.90 318	96.95 225

EPMVS		94.99 193	94.48 190	96.52 225	97.22 219	91.75 278	97.23 288	91.66 359	94.11 148	97.28 106	96.81 273	85.70 246	98.84 208	93.04 193	97.28 154	98.97 138

WR-MVS_H		95.05 191	94.46 192	96.81 191	96.86 241	95.82 143	99.24 22	99.24 10	93.87 162	92.53 271	96.84 272	90.37 132	98.24 280	93.24 186	87.93 303	96.38 294

WR-MVS		95.15 187	94.46 192	97.22 166	96.67 252	96.45 104	98.21 202	98.81 64	94.15 147	93.16 253	97.69 188	87.51 210	98.30 276	95.29 137	88.62 297	96.90 233

ADS-MVSNet		95.00 192	94.45 194	96.63 209	98.00 171	91.91 274	96.04 325	97.74 239	90.15 286	96.47 160	96.64 280	87.89 198	98.96 192	90.08 265	97.06 156	99.02 133

XXY-MVS		95.20 186	94.45 194	97.46 156	96.75 247	96.56 98	98.86 94	98.65 115	93.30 199	93.27 250	98.27 142	84.85 260	98.87 205	94.82 147	91.26 265	96.96 223

ADS-MVSNet2		94.58 225	94.40 196	95.11 287	98.00 171	88.74 317	96.04 325	97.30 280	90.15 286	96.47 160	96.64 280	87.89 198	97.56 310	90.08 265	97.06 156	99.02 133

tpmvs		94.60 222	94.36 197	95.33 282	97.46 203	88.60 320	96.88 306	97.68 240	91.29 269	93.80 238	96.42 289	88.58 177	99.24 152	91.06 244	96.04 201	98.17 180

DWT-MVSNet_test		94.82 205	94.36 197	96.20 246	97.35 212	90.79 290	98.34 187	96.57 319	92.91 212	95.33 178	96.44 288	82.00 294	99.12 169	94.52 156	95.78 205	98.70 152

CP-MVSNet		94.94 199	94.30 199	96.83 190	96.72 249	95.56 151	99.11 53	98.95 33	93.89 160	92.42 276	97.90 170	87.19 215	98.12 284	94.32 161	88.21 300	96.82 244

FMVSNet3		94.97 196	94.26 200	97.11 174	98.18 160	96.62 93	98.56 160	98.26 180	93.67 179	94.09 226	97.10 234	84.25 276	98.01 291	92.08 218	92.14 251	96.70 257

Anonymous20240529		95.10 189	94.22 201	97.75 126	99.01 91	94.26 232	98.87 87	98.83 60	85.79 331	96.64 136	98.97 68	78.73 315	99.85 42	96.27 101	94.89 211	99.12 123

v1neww		94.83 202	94.22 201	96.68 201	96.39 265	94.85 186	98.87 87	98.11 212	92.45 229	94.45 197	97.06 241	88.82 166	98.54 232	92.93 197	88.91 290	96.65 268

v7new		94.83 202	94.22 201	96.68 201	96.39 265	94.85 186	98.87 87	98.11 212	92.45 229	94.45 197	97.06 241	88.82 166	98.54 232	92.93 197	88.91 290	96.65 268

v6		94.83 202	94.21 204	96.69 198	96.36 269	94.85 186	98.87 87	98.11 212	92.46 224	94.44 203	97.05 245	88.76 172	98.57 230	92.95 196	88.92 289	96.65 268

TR-MVS		94.94 199	94.20 205	97.17 170	97.75 185	94.14 235	97.59 265	97.02 294	92.28 241	95.75 174	97.64 194	83.88 285	98.96 192	89.77 271	96.15 192	98.40 169

VPNet		94.99 193	94.19 206	97.40 161	97.16 225	96.57 97	98.71 132	98.97 29	95.67 78	94.84 185	98.24 145	80.36 308	98.67 221	96.46 95	87.32 311	96.96 223

NR-MVSNet		94.98 195	94.16 207	97.44 157	96.53 257	97.22 73	98.74 126	98.95 33	94.96 122	89.25 309	97.69 188	89.32 145	98.18 282	94.59 154	87.40 310	96.92 226

CR-MVSNet		94.76 209	94.15 208	96.59 215	97.00 231	93.43 253	94.96 338	97.56 246	92.46 224	96.93 122	96.24 292	88.15 189	97.88 302	87.38 309	96.65 165	98.46 166

V42		94.78 208	94.14 209	96.70 197	96.33 276	95.22 165	98.97 72	98.09 220	92.32 239	94.31 211	97.06 241	88.39 184	98.55 231	92.90 200	88.87 292	96.34 296

EU-MVSNet		93.66 261	94.14 209	92.25 324	95.96 299	83.38 339	98.52 165	98.12 207	94.69 129	92.61 268	98.13 151	87.36 214	96.39 337	91.82 228	90.00 272	96.98 222

XVG-ACMP-BASELINE		94.54 227	94.14 209	95.75 263	96.55 256	91.65 280	98.11 218	98.44 150	94.96 122	94.22 219	97.90 170	79.18 314	99.11 173	94.05 169	93.85 228	96.48 290

divwei89l23v2f112		94.76 209	94.12 212	96.67 204	96.28 282	94.85 186	98.69 137	98.12 207	92.44 231	94.29 214	96.94 258	88.85 163	98.48 243	92.67 205	88.79 296	96.67 263

v1141		94.75 211	94.11 213	96.67 204	96.27 284	94.86 185	98.69 137	98.12 207	92.43 232	94.31 211	96.94 258	88.78 171	98.48 243	92.63 207	88.85 294	96.67 263

v1		94.75 211	94.11 213	96.69 198	96.27 284	94.87 184	98.69 137	98.12 207	92.43 232	94.32 210	96.94 258	88.71 175	98.54 232	92.66 206	88.84 295	96.67 263

v7		94.69 215	94.04 215	96.62 211	96.41 264	94.79 206	98.78 117	98.13 204	91.89 248	94.30 213	97.16 225	88.13 191	98.45 250	91.96 226	89.65 275	96.61 273

Anonymous20240521		94.80 207	94.03 216	97.11 174	96.56 255	96.46 103	99.30 14	98.44 150	92.86 215	91.21 290	97.01 250	89.59 140	98.58 229	92.03 222	89.23 283	96.30 298

v2v482		94.69 215	94.03 216	96.65 206	96.17 289	94.79 206	98.67 144	98.08 221	92.72 218	94.00 231	97.16 225	87.69 207	98.45 250	92.91 199	88.87 292	96.72 253

GA-MVS		94.81 206	94.03 216	97.14 171	97.15 226	93.86 241	96.76 312	97.58 245	94.00 154	94.76 190	97.04 246	80.91 301	98.48 243	91.79 229	96.25 188	99.09 126

OurMVSNet-221017-0		94.21 241	94.00 219	94.85 294	95.60 312	89.22 311	98.89 83	97.43 269	95.29 103	92.18 281	98.52 116	82.86 291	98.59 227	93.46 181	91.76 258	96.74 250

PAPM		94.95 197	94.00 219	97.78 123	97.04 230	95.65 147	96.03 327	98.25 181	91.23 272	94.19 221	97.80 182	91.27 119	98.86 207	82.61 330	97.61 149	98.84 146

pmmvs4		94.69 215	93.99 221	96.81 191	95.74 307	95.94 126	97.40 274	97.67 241	90.42 283	93.37 248	97.59 197	89.08 152	98.20 281	92.97 195	91.67 259	96.30 298

PS-CasMVS		94.67 219	93.99 221	96.71 195	96.68 251	95.26 163	99.13 50	99.03 24	93.68 177	92.33 277	97.95 165	85.35 252	98.10 285	93.59 179	88.16 302	96.79 245

ACMH	92.88 16	94.55 226	93.95 223	96.34 240	97.63 190	93.26 257	98.81 107	98.49 145	93.43 187	89.74 304	98.53 113	81.91 295	99.08 178	93.69 175	93.30 241	96.70 257
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVP-Stereo		94.28 240	93.92 224	95.35 281	94.95 326	92.60 267	97.97 231	97.65 242	91.61 254	90.68 298	97.09 236	86.32 229	98.42 256	89.70 275	99.34 83	95.02 324
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
v1144		94.59 224	93.92 224	96.60 214	96.21 286	94.78 208	98.59 153	98.14 203	91.86 251	94.21 220	97.02 248	87.97 195	98.41 263	91.72 232	89.57 276	96.61 273

dp		94.15 248	93.90 226	94.90 292	97.31 214	86.82 334	96.97 296	97.19 287	91.22 273	96.02 171	96.61 282	85.51 249	99.02 187	90.00 269	94.30 213	98.85 144

LTVRE_ROB	92.95 15	94.60 222	93.90 226	96.68 201	97.41 210	94.42 223	98.52 165	98.59 119	91.69 253	91.21 290	98.35 130	84.87 259	99.04 184	91.06 244	93.44 238	96.60 275
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
cascas		94.63 221	93.86 228	96.93 186	96.91 238	94.27 231	96.00 328	98.51 136	85.55 332	94.54 193	96.23 294	84.20 279	98.87 205	95.80 118	96.98 159	97.66 199

IterMVS		94.09 251	93.85 229	94.80 297	97.99 173	90.35 298	97.18 291	98.12 207	93.68 177	92.46 275	97.34 214	84.05 281	97.41 313	92.51 212	91.33 262	96.62 272
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Baseline_NR-MVSNet		94.35 235	93.81 230	95.96 253	96.20 287	94.05 237	98.61 151	96.67 316	91.44 259	93.85 236	97.60 196	88.57 178	98.14 283	94.39 158	86.93 316	95.68 314

tpm		94.13 249	93.80 231	95.12 286	96.50 259	87.91 328	97.44 271	95.89 329	92.62 220	96.37 164	96.30 291	84.13 280	98.30 276	93.24 186	91.66 260	99.14 121

GBi-Net		94.49 228	93.80 231	96.56 220	98.21 155	95.00 173	98.82 101	98.18 193	92.46 224	94.09 226	97.07 238	81.16 298	97.95 294	92.08 218	92.14 251	96.72 253

test1		94.49 228	93.80 231	96.56 220	98.21 155	95.00 173	98.82 101	98.18 193	92.46 224	94.09 226	97.07 238	81.16 298	97.95 294	92.08 218	92.14 251	96.72 253

v8		94.47 230	93.77 234	96.57 219	96.36 269	94.83 198	99.05 60	98.19 190	91.92 247	93.16 253	96.97 254	88.82 166	98.48 243	91.69 233	87.79 306	96.39 293

ACMH+	92.99 14	94.30 237	93.77 234	95.88 257	97.81 183	92.04 273	98.71 132	98.37 162	93.99 155	90.60 299	98.47 119	80.86 303	99.05 180	92.75 204	92.40 250	96.55 282

v148		94.29 238	93.76 236	95.91 255	96.10 293	92.93 263	98.58 155	97.97 229	92.59 222	93.47 247	96.95 256	88.53 181	98.32 272	92.56 209	87.06 315	96.49 289

tpm2		94.19 243	93.76 236	95.46 271	97.23 218	89.04 314	97.31 285	96.85 311	87.08 321	96.21 166	96.79 274	83.75 288	98.74 216	92.43 214	96.23 189	98.59 161

PEN-MVS		94.42 232	93.73 238	96.49 227	96.28 282	94.84 195	99.17 37	99.00 26	93.51 184	92.23 279	97.83 179	86.10 239	97.90 298	92.55 210	86.92 317	96.74 250

v144192		94.39 234	93.70 239	96.48 228	96.06 295	94.35 227	98.58 155	98.16 200	91.45 258	94.33 209	97.02 248	87.50 212	98.45 250	91.08 243	89.11 284	96.63 271

TESTMET0.1,1		94.18 245	93.69 240	95.63 265	96.92 236	89.12 312	96.91 300	94.78 345	93.17 201	94.88 184	96.45 287	78.52 316	98.92 198	93.09 190	98.50 114	98.85 144

Patchmatch-test		94.42 232	93.68 241	96.63 209	97.60 193	91.76 277	94.83 342	97.49 264	89.45 306	94.14 224	97.10 234	88.99 153	98.83 210	85.37 324	98.13 131	99.29 101

MS-PatchMatch		93.84 259	93.63 242	94.46 307	96.18 288	89.45 307	97.76 253	98.27 176	92.23 242	92.13 282	97.49 202	79.50 311	98.69 217	89.75 273	99.38 81	95.25 319

DI_MVS_plusplus_test		94.74 213	93.62 243	98.09 106	95.34 321	95.92 136	98.09 221	97.34 276	94.66 133	85.89 323	95.91 303	80.49 307	99.38 142	96.66 88	98.22 127	98.97 138

FMVSNet2		94.47 230	93.61 244	97.04 178	98.21 155	96.43 105	98.79 115	98.27 176	92.46 224	93.50 246	97.09 236	81.16 298	98.00 292	91.09 242	91.93 255	96.70 257

test_normal		94.72 214	93.59 245	98.11 105	95.30 322	95.95 125	97.91 237	97.39 274	94.64 134	85.70 326	95.88 304	80.52 306	99.36 143	96.69 87	98.30 124	99.01 136

v1192		94.32 236	93.58 246	96.53 224	96.10 293	94.45 222	98.50 170	98.17 198	91.54 256	94.19 221	97.06 241	86.95 220	98.43 255	90.14 263	89.57 276	96.70 257

v10		94.29 238	93.55 247	96.51 226	96.39 265	94.80 203	98.99 68	98.19 190	91.35 265	93.02 259	96.99 252	88.09 192	98.41 263	90.50 260	88.41 299	96.33 297

MVS		94.67 219	93.54 248	98.08 107	96.88 240	96.56 98	98.19 207	98.50 141	78.05 350	92.69 266	98.02 158	91.07 123	99.63 108	90.09 264	98.36 121	98.04 183

v52		94.18 245	93.52 249	96.13 249	95.95 300	94.29 229	99.23 24	98.21 185	91.42 260	92.84 262	96.89 265	87.85 201	98.53 238	91.51 237	87.81 304	95.57 317

V4		94.18 245	93.52 249	96.13 249	95.89 302	94.31 228	99.23 24	98.22 184	91.42 260	92.82 263	96.89 265	87.93 197	98.52 239	91.51 237	87.81 304	95.58 316

test-mter		94.08 252	93.51 251	95.80 260	96.77 244	89.70 303	96.91 300	95.21 340	92.89 213	94.83 187	95.72 309	77.69 321	98.97 189	93.06 191	98.50 114	98.72 150

test0.0.03 1		94.08 252	93.51 251	95.80 260	95.53 315	92.89 264	97.38 276	95.97 326	95.11 113	92.51 273	96.66 278	87.71 204	96.94 319	87.03 312	93.67 230	97.57 200

v1921920		94.20 242	93.47 253	96.40 235	95.98 298	94.08 236	98.52 165	98.15 201	91.33 266	94.25 217	97.20 224	86.41 227	98.42 256	90.04 268	89.39 281	96.69 262

v7n		94.19 243	93.43 254	96.47 229	95.90 301	94.38 226	99.26 19	98.34 165	91.99 245	92.76 265	97.13 233	88.31 185	98.52 239	89.48 280	87.70 307	96.52 285

PCF-MVS	93.45 11	94.68 218	93.43 254	98.42 86	98.62 134	96.77 88	95.48 334	98.20 188	84.63 337	93.34 249	98.32 136	88.55 180	99.81 54	84.80 326	98.96 93	98.68 154
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
tpmp4_e23		93.91 258	93.42 256	95.38 279	97.62 191	88.59 321	97.52 269	97.34 276	87.94 317	94.17 223	96.79 274	82.91 290	99.05 180	90.62 252	95.91 202	98.50 164

our_test_3		93.65 263	93.30 257	94.69 299	95.45 318	89.68 305	96.91 300	97.65 242	91.97 246	91.66 287	96.88 267	89.67 139	97.93 297	88.02 306	91.49 261	96.48 290

v1240		94.06 254	93.29 258	96.34 240	96.03 297	93.90 240	98.44 176	98.17 198	91.18 274	94.13 225	97.01 250	86.05 240	98.42 256	89.13 285	89.50 279	96.70 257

Anonymous20231211		94.10 250	93.26 259	96.61 212	99.11 85	94.28 230	99.01 66	98.88 48	86.43 324	92.81 264	97.57 199	81.66 297	98.68 220	94.83 146	89.02 287	96.88 236

DTE-MVSNet		93.98 256	93.26 259	96.14 248	96.06 295	94.39 225	99.20 34	98.86 54	93.06 204	91.78 285	97.81 181	85.87 243	97.58 309	90.53 253	86.17 322	96.46 292

v748		93.75 260	93.06 261	95.82 259	95.73 308	92.64 266	99.25 21	98.24 183	91.60 255	92.22 280	96.52 285	87.60 209	98.46 248	90.64 251	85.72 325	96.36 295

pm-mvs1		93.94 257	93.06 261	96.59 215	96.49 260	95.16 166	98.95 74	98.03 228	92.32 239	91.08 293	97.84 176	84.54 269	98.41 263	92.16 216	86.13 324	96.19 302

pmmvs5		93.65 263	92.97 263	95.68 264	95.49 316	92.37 268	98.20 203	97.28 282	89.66 302	92.58 269	97.26 219	82.14 293	98.09 287	93.18 189	90.95 266	96.58 277

SixPastTwentyTwo		93.34 267	92.86 264	94.75 298	95.67 310	89.41 309	98.75 122	96.67 316	93.89 160	90.15 302	98.25 144	80.87 302	98.27 279	90.90 247	90.64 267	96.57 279

tpm cat1		93.36 265	92.80 265	95.07 288	97.58 195	87.97 327	96.76 312	97.86 234	82.17 344	93.53 243	96.04 301	86.13 231	99.13 168	89.24 283	95.87 203	98.10 182

LF4IMVS		93.14 274	92.79 266	94.20 310	95.88 303	88.67 319	97.66 261	97.07 290	93.81 165	91.71 286	97.65 192	77.96 320	98.81 212	91.47 239	91.92 256	95.12 320

USDC		93.33 268	92.71 267	95.21 283	96.83 243	90.83 289	96.91 300	97.50 258	93.84 163	90.72 297	98.14 150	77.69 321	98.82 211	89.51 279	93.21 244	95.97 307

tfpnnormal		93.66 261	92.70 268	96.55 223	96.94 235	95.94 126	98.97 72	99.19 15	91.04 275	91.38 289	97.34 214	84.94 258	98.61 224	85.45 323	89.02 287	95.11 321

ppachtmachnet_test		93.22 271	92.63 269	94.97 290	95.45 318	90.84 288	96.88 306	97.88 233	90.60 279	92.08 283	97.26 219	88.08 193	97.86 304	85.12 325	90.33 269	96.22 300

DSMNet-mixed		92.52 279	92.58 270	92.33 323	94.15 333	82.65 342	98.30 195	94.26 352	89.08 311	92.65 267	95.73 307	85.01 257	95.76 339	86.24 316	97.76 145	98.59 161

JIA-IIPM		93.35 266	92.49 271	95.92 254	96.48 261	90.65 294	95.01 337	96.96 300	85.93 329	96.08 168	87.33 350	87.70 206	98.78 215	91.35 240	95.58 206	98.34 176

testgi		93.06 275	92.45 272	94.88 293	96.43 263	89.90 300	98.75 122	97.54 251	95.60 81	91.63 288	97.91 169	74.46 337	97.02 318	86.10 317	93.67 230	97.72 196

Patchmtry		93.22 271	92.35 273	95.84 258	96.77 244	93.09 262	94.66 344	97.56 246	87.37 320	92.90 261	96.24 292	88.15 189	97.90 298	87.37 310	90.10 271	96.53 284

X-MVStestdata		94.06 254	92.30 274	99.34 15	99.70 15	98.35 25	99.29 15	98.88 48	97.40 15	98.46 49	43.50 363	95.90 31	99.89 28	97.85 36	99.74 34	99.78 8

MIMVSNet		93.26 270	92.21 275	96.41 234	97.73 187	93.13 261	95.65 333	97.03 293	91.27 271	94.04 229	96.06 300	75.33 331	97.19 316	86.56 314	96.23 189	98.92 143

FMVSNet1		93.19 273	92.07 276	96.56 220	97.54 198	95.00 173	98.82 101	98.18 193	90.38 284	92.27 278	97.07 238	73.68 339	97.95 294	89.36 282	91.30 263	96.72 253

PatchT		93.06 275	91.97 277	96.35 238	96.69 250	92.67 265	94.48 345	97.08 289	86.62 322	97.08 112	92.23 345	87.94 196	97.90 298	78.89 339	96.69 163	98.49 165

IB-MVS	91.98 17	93.27 269	91.97 277	97.19 168	97.47 202	93.41 255	97.09 294	95.99 325	93.32 197	92.47 274	95.73 307	78.06 319	99.53 128	94.59 154	82.98 330	98.62 160
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
K. test v3		92.55 278	91.91 279	94.48 305	95.64 311	89.24 310	99.07 59	94.88 344	94.04 152	86.78 319	97.59 197	77.64 324	97.64 307	92.08 218	89.43 280	96.57 279

TinyColmap		92.31 281	91.53 280	94.65 301	96.92 236	89.75 302	96.92 298	96.68 315	90.45 282	89.62 305	97.85 175	76.06 329	98.81 212	86.74 313	92.51 249	95.41 318

TransMVSNet (Re)		92.67 277	91.51 281	96.15 247	96.58 254	94.65 211	98.90 79	96.73 312	90.86 277	89.46 307	97.86 173	85.62 247	98.09 287	86.45 315	81.12 335	95.71 313

RPMNet		92.52 279	91.17 282	96.59 215	97.00 231	93.43 253	94.96 338	97.26 284	82.27 343	96.93 122	92.12 346	86.98 219	97.88 302	76.32 344	96.65 165	98.46 166

Anonymous20231206		91.66 295	91.10 283	93.33 317	94.02 335	87.35 331	98.58 155	97.26 284	90.48 280	90.16 301	96.31 290	83.83 287	96.53 335	79.36 337	89.90 273	96.12 303

v18		92.10 284	90.97 284	95.50 268	96.34 272	94.85 186	98.82 101	97.52 252	89.99 290	85.31 330	93.26 328	88.90 160	96.92 320	88.82 291	79.77 339	94.73 327

v17		92.08 285	90.94 285	95.48 270	96.34 272	94.83 198	98.81 107	97.52 252	89.95 292	85.32 328	93.24 329	88.91 159	96.91 321	88.76 292	79.63 340	94.71 329

v16		92.08 285	90.94 285	95.49 269	96.38 268	94.84 195	98.81 107	97.51 255	89.94 293	85.25 331	93.28 327	88.86 161	96.91 321	88.70 293	79.78 338	94.72 328

FMVSNet5		91.81 293	90.92 287	94.49 304	97.21 220	92.09 271	98.00 229	97.55 250	89.31 309	90.86 296	95.61 312	74.48 336	95.32 341	85.57 321	89.70 274	96.07 305

Patchmatch-RL test		91.49 296	90.85 288	93.41 316	91.37 343	84.40 336	92.81 350	95.93 328	91.87 250	87.25 317	94.87 317	88.99 153	96.53 335	92.54 211	82.00 332	99.30 99

v15		91.94 287	90.77 289	95.43 275	96.31 280	94.83 198	98.77 118	97.50 258	89.92 294	85.13 332	93.08 332	88.76 172	96.86 323	88.40 297	79.10 342	94.61 333

V14		91.93 288	90.76 290	95.42 278	96.33 276	94.81 202	98.77 118	97.51 255	89.86 296	85.09 333	93.13 330	88.80 170	96.83 325	88.32 298	79.06 344	94.60 334

V9		91.91 289	90.73 291	95.45 272	96.32 279	94.80 203	98.77 118	97.50 258	89.81 297	85.03 335	93.08 332	88.76 172	96.86 323	88.24 299	79.03 345	94.69 330

v12		91.89 290	90.70 292	95.43 275	96.31 280	94.80 203	98.76 121	97.50 258	89.76 298	84.95 336	93.00 335	88.82 166	96.82 327	88.23 300	79.00 346	94.68 332

v13		91.88 291	90.69 293	95.43 275	96.33 276	94.78 208	98.75 122	97.50 258	89.68 301	84.93 337	92.98 336	88.84 164	96.83 325	88.14 301	79.09 343	94.69 330

v11		91.85 292	90.68 294	95.36 280	96.34 272	94.74 210	98.80 110	97.43 269	89.60 304	85.09 333	93.03 334	88.53 181	96.75 328	87.37 310	79.96 337	94.58 335

pmmvs6		91.77 294	90.63 295	95.17 285	94.69 331	91.24 285	98.67 144	97.92 231	86.14 326	89.62 305	97.56 201	75.79 330	98.34 270	90.75 249	84.56 329	95.94 308

gg-mvs-nofinetune		92.21 282	90.58 296	97.13 172	96.75 247	95.09 170	95.85 330	89.40 362	85.43 333	94.50 195	81.98 354	80.80 304	98.40 269	92.16 216	98.33 122	97.88 190

test20.03		90.89 303	90.38 297	92.43 322	93.48 336	88.14 326	98.33 188	97.56 246	93.40 194	87.96 315	96.71 277	80.69 305	94.13 345	79.15 338	86.17 322	95.01 325

Test4		92.21 282	90.34 298	97.82 121	92.83 339	95.87 142	97.94 233	98.05 227	94.50 139	82.12 342	94.48 320	59.54 355	98.54 232	95.39 132	98.22 127	99.06 131

test_0402		91.32 297	90.27 299	94.48 305	96.60 253	91.12 286	98.50 170	97.22 286	86.10 327	88.30 314	96.98 253	77.65 323	97.99 293	78.13 341	92.94 246	94.34 336

EG-PatchMatch MVS		91.13 299	90.12 300	94.17 312	94.73 330	89.00 315	98.13 215	97.81 235	89.22 310	85.32 328	96.46 286	67.71 348	98.42 256	87.89 308	93.82 229	95.08 322

PVSNet_0	88.72 19	91.28 298	90.03 301	95.00 289	97.99 173	87.29 332	94.84 341	98.50 141	92.06 244	89.86 303	95.19 313	79.81 310	99.39 141	92.27 215	69.79 353	98.33 177

LP		91.12 300	89.99 302	94.53 303	96.35 271	88.70 318	93.86 349	97.35 275	84.88 335	90.98 294	94.77 318	84.40 271	97.43 312	75.41 346	91.89 257	97.47 201

UnsupCasMVSNet_eth		90.99 302	89.92 303	94.19 311	94.08 334	89.83 301	97.13 293	98.67 108	93.69 175	85.83 325	96.19 297	75.15 332	96.74 329	89.14 284	79.41 341	96.00 306

TDRefinement		91.06 301	89.68 304	95.21 283	85.35 354	91.49 281	98.51 169	97.07 290	91.47 257	88.83 312	97.84 176	77.31 325	99.09 177	92.79 203	77.98 347	95.04 323

CMPMVS	66.06 21	89.70 310	89.67 305	89.78 328	93.19 337	76.56 348	97.00 295	98.35 164	80.97 346	81.57 343	97.75 184	74.75 335	98.61 224	89.85 270	93.63 232	94.17 338
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
YYNet1		90.70 305	89.39 306	94.62 302	94.79 329	90.65 294	97.20 289	97.46 265	87.54 319	72.54 352	95.74 306	86.51 225	96.66 333	86.00 318	86.76 320	96.54 283

MDA-MVSNet_test_wron		90.71 304	89.38 307	94.68 300	94.83 328	90.78 291	97.19 290	97.46 265	87.60 318	72.41 353	95.72 309	86.51 225	96.71 332	85.92 319	86.80 319	96.56 281

testpf		88.74 315	89.09 308	87.69 332	95.78 306	83.16 341	84.05 360	94.13 355	85.22 334	90.30 300	94.39 322	74.92 334	95.80 338	89.77 271	93.28 243	84.10 355

testus		88.91 314	89.08 309	88.40 331	91.39 342	76.05 349	96.56 318	96.48 320	89.38 308	89.39 308	95.17 315	70.94 343	93.56 348	77.04 343	95.41 207	95.61 315

pmmvs-eth3d		90.36 307	89.05 310	94.32 309	91.10 344	92.12 270	97.63 264	96.95 301	88.86 312	84.91 338	93.13 330	78.32 317	96.74 329	88.70 293	81.81 334	94.09 340

new_pmnet		90.06 308	89.00 311	93.22 320	94.18 332	88.32 325	96.42 323	96.89 308	86.19 325	85.67 327	93.62 325	77.18 326	97.10 317	81.61 332	89.29 282	94.23 337

test2356		88.68 316	88.61 312	88.87 330	89.90 348	78.23 346	95.11 336	96.66 318	88.66 314	89.06 310	94.33 324	73.14 341	92.56 352	75.56 345	95.11 210	95.81 311

testing_2		90.61 306	88.50 313	96.95 184	90.08 347	95.57 150	97.69 258	98.06 224	93.02 206	76.55 348	92.48 343	61.18 354	98.44 253	95.45 131	91.98 254	96.84 241

MVS-HIRNet		89.46 312	88.40 314	92.64 321	97.58 195	82.15 343	94.16 348	93.05 358	75.73 352	90.90 295	82.52 353	79.42 312	98.33 271	83.53 328	98.68 104	97.43 202

MDA-MVSNet-bldmvs		89.97 309	88.35 315	94.83 296	95.21 323	91.34 282	97.64 262	97.51 255	88.36 315	71.17 354	96.13 299	79.22 313	96.63 334	83.65 327	86.27 321	96.52 285

MIMVSNet1		89.67 311	88.28 316	93.82 313	92.81 340	91.08 287	98.01 227	97.45 267	87.95 316	87.90 316	95.87 305	67.63 349	94.56 344	78.73 340	88.18 301	95.83 310

N_pmnet		87.12 320	87.77 317	85.17 339	95.46 317	61.92 362	97.37 278	70.66 370	85.83 330	88.73 313	96.04 301	85.33 254	97.76 305	80.02 334	90.48 268	95.84 309

new-patchmatchnet		88.50 317	87.45 318	91.67 326	90.31 346	85.89 335	97.16 292	97.33 279	89.47 305	83.63 340	92.77 340	76.38 327	95.06 343	82.70 329	77.29 348	94.06 341

OpenMVS_ROB	86.42 20	89.00 313	87.43 319	93.69 314	93.08 338	89.42 308	97.91 237	96.89 308	78.58 349	85.86 324	94.69 319	69.48 345	98.29 278	77.13 342	93.29 242	93.36 345

PM-MVS		87.77 318	86.55 320	91.40 327	91.03 345	83.36 340	96.92 298	95.18 342	91.28 270	86.48 322	93.42 326	53.27 356	96.74 329	89.43 281	81.97 333	94.11 339

test1235678		86.26 322	85.81 321	87.62 333	86.97 352	75.00 353	96.55 320	96.32 323	86.08 328	81.32 344	92.98 336	73.10 342	92.05 353	71.64 349	87.32 311	95.81 311

UnsupCasMVSNet_bld		87.17 319	85.12 322	93.31 318	91.94 341	88.77 316	94.92 340	98.30 173	84.30 338	82.30 341	90.04 347	63.96 353	97.25 315	85.85 320	74.47 352	93.93 343

pmmvs3		86.67 321	84.86 323	92.11 325	88.16 349	87.19 333	96.63 315	94.75 346	79.88 348	87.22 318	92.75 341	66.56 350	95.20 342	81.24 333	76.56 350	93.96 342

1111		84.94 323	84.30 324	86.86 334	87.59 350	75.10 351	96.63 315	96.43 321	82.53 341	80.75 345	92.91 338	68.94 346	93.79 346	68.24 352	84.66 328	91.70 347

test12356		83.47 324	83.37 325	83.78 340	84.43 355	70.09 358	95.12 335	95.60 337	82.98 339	78.89 347	92.43 344	64.99 351	91.41 355	70.36 350	85.55 327	89.82 349

testmv		78.74 325	77.35 326	82.89 342	78.16 363	69.30 359	95.87 329	94.65 347	81.11 345	70.98 355	87.11 351	46.31 357	90.42 356	65.28 355	76.72 349	88.95 350

FPMVS		77.62 329	77.14 327	79.05 344	79.25 360	60.97 363	95.79 331	95.94 327	65.96 354	67.93 356	94.40 321	37.73 362	88.88 358	68.83 351	88.46 298	87.29 351

Gipuma		78.40 327	76.75 328	83.38 341	95.54 314	80.43 345	79.42 361	97.40 272	64.67 355	73.46 351	80.82 356	45.65 359	93.14 350	66.32 354	87.43 309	76.56 360
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
.test1245		73.05 331	76.31 329	63.27 352	87.59 350	75.10 351	96.63 315	96.43 321	82.53 341	80.75 345	92.91 338	68.94 346	93.79 346	68.24 352	12.72 364	20.91 364

LCM-MVSNet		78.70 326	76.24 330	86.08 336	77.26 364	71.99 356	94.34 346	96.72 313	61.62 357	76.53 349	89.33 348	33.91 365	92.78 351	81.85 331	74.60 351	93.46 344

PMMVS2		77.95 328	75.44 331	85.46 337	82.54 356	74.95 354	94.23 347	93.08 357	72.80 353	74.68 350	87.38 349	36.36 363	91.56 354	73.95 347	63.94 354	89.87 348

no-one		74.41 330	70.76 332	85.35 338	79.88 359	76.83 347	94.68 343	94.22 353	80.33 347	63.81 357	79.73 357	35.45 364	93.36 349	71.78 348	36.99 361	85.86 354

tmp_tt		68.90 333	66.97 333	74.68 348	50.78 369	59.95 364	87.13 356	83.47 368	38.80 363	62.21 358	96.23 294	64.70 352	76.91 365	88.91 290	30.49 362	87.19 352

ANet_high		69.08 332	65.37 334	80.22 343	65.99 367	71.96 357	90.91 354	90.09 361	82.62 340	49.93 363	78.39 358	29.36 366	81.75 361	62.49 358	38.52 360	86.95 353

PNet_i23d		67.70 334	65.07 335	75.60 346	78.61 361	59.61 365	89.14 355	88.24 364	61.83 356	52.37 361	80.89 355	18.91 367	84.91 360	62.70 357	52.93 356	82.28 356

E-PMN		64.94 336	64.25 336	67.02 350	82.28 357	59.36 366	91.83 353	85.63 366	52.69 360	60.22 359	77.28 359	41.06 361	80.12 363	46.15 361	41.14 358	61.57 362

PMVS	61.03 23	65.95 335	63.57 337	73.09 349	57.90 368	51.22 368	85.05 359	93.93 356	54.45 359	44.32 364	83.57 352	13.22 368	89.15 357	58.68 359	81.00 336	78.91 359
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
EMVS		64.07 337	63.26 338	66.53 351	81.73 358	58.81 367	91.85 352	84.75 367	51.93 362	59.09 360	75.13 360	43.32 360	79.09 364	42.03 362	39.47 359	61.69 361

MVE	62.14 22	63.28 339	59.38 339	74.99 347	74.33 365	65.47 361	85.55 358	80.50 369	52.02 361	51.10 362	75.00 361	10.91 372	80.50 362	51.60 360	53.40 355	78.99 358
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuykxyi23d		63.73 338	58.86 340	78.35 345	67.62 366	67.90 360	86.56 357	87.81 365	58.26 358	42.49 365	70.28 362	11.55 370	85.05 359	63.66 356	41.50 357	82.11 357

v1.0		41.12 340	54.83 341	0.00 357	99.63 21	0.00 372	0.00 363	98.84 56	96.40 58	99.27 8	99.31 23	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

pcd1.5k->3k		39.42 341	41.78 342	32.35 353	96.17 289	0.00 372	0.00 363	98.54 129	0.00 367	0.00 369	0.00 369	87.78 203	0.00 369	0.00 366	93.56 234	97.06 217

cdsmvs_eth3d_5k		23.98 343	31.98 343	0.00 357	0.00 372	0.00 372	0.00 363	98.59 119	0.00 367	0.00 369	98.61 106	90.60 130	0.00 369	0.00 366	0.00 367	0.00 367

wuyk23d		30.17 342	30.18 344	30.16 354	78.61 361	43.29 369	66.79 362	14.21 371	17.31 364	14.82 368	11.93 368	11.55 370	41.43 366	37.08 363	19.30 363	5.76 366

testmvs		21.48 344	24.95 345	11.09 356	14.89 370	6.47 371	96.56 318	9.87 372	7.55 365	17.93 366	39.02 364	9.43 373	5.90 368	16.56 365	12.72 364	20.91 364

test123		20.95 345	23.72 346	12.64 355	13.54 371	8.19 370	96.55 320	6.13 373	7.48 366	16.74 367	37.98 365	12.97 369	6.05 367	16.69 364	5.43 366	23.68 363

ab-mvs-re		8.20 346	10.94 347	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	98.43 121	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

pcd_1.5k_mvsjas		7.88 347	10.50 348	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	94.51 62	0.00 369	0.00 366	0.00 367	0.00 367

sosnet-low-res		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

sosnet		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

uncertanet		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

Regformer		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

uanet		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

GSMVS																99.20 109

test_part2					99.63 21	99.18 2				99.27 8

test_part1				0.00 357		0.00 372	0.00 363	98.84 56				0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

sam_mvs1												89.45 142				99.20 109

sam_mvs												88.99 153

semantic-postprocess				94.85 294	97.98 175	90.56 296		98.11 212	93.75 167	92.58 269	97.48 203	83.91 284	97.41 313	92.48 213	91.30 263	96.58 277

ambc				89.49 329	86.66 353	75.78 350	92.66 351	96.72 313		86.55 321	92.50 342	46.01 358	97.90 298	90.32 261	82.09 331	94.80 326

MTGPA								98.74 83

test_post1							96.68 314				30.43 367	87.85 201	98.69 217	92.59 208

test_post											31.83 366	88.83 165	98.91 199

patchmatchnet-post											95.10 316	89.42 143	98.89 203

GG-mvs-BLEND				96.59 215	96.34 272	94.98 176	96.51 322	88.58 363		93.10 258	94.34 323	80.34 309	98.05 289	89.53 278	96.99 158	96.74 250

MTMP							98.89 83	94.14 354

gm-plane-assit					95.88 303	87.47 330			89.74 300		96.94 258		99.19 163	93.32 185

test9_res														96.39 100	99.57 57	99.69 37

TEST9					99.31 51	98.50 15	97.92 234	98.73 88	92.63 219	97.74 87	98.68 99	96.20 14	99.80 61

test_8					99.29 59	98.44 17	97.89 242	98.72 90	92.98 208	97.70 90	98.66 102	96.20 14	99.80 61

agg_prior2														95.87 115	99.57 57	99.68 43

agg_prior					99.30 56	98.38 20		98.72 90		97.57 101			99.81 54

TestCases				96.99 180	99.25 68	93.21 259		98.18 193	91.36 263	93.52 244	98.77 92	84.67 262	99.72 90	89.70 275	97.87 139	98.02 184

test_prior4						98.01 44	97.86 245

test_prior2							97.80 250		96.12 65	97.89 81	98.69 97	95.96 27		96.89 75	99.60 51

test_prior				99.19 30	99.31 51	98.22 33		98.84 56					99.70 95			99.65 52

旧先验2							97.57 267		91.30 268	98.67 40			99.80 61	95.70 124

新几何2							97.64 262

新几何1				99.16 37	99.34 43	98.01 44		98.69 98	90.06 289	98.13 61	98.95 75	94.60 60	99.89 28	91.97 225	99.47 71	99.59 63

旧先验1					99.29 59	97.48 62		98.70 97			99.09 55	95.56 37			99.47 71	99.61 58

无先验							97.58 266	98.72 90	91.38 262				99.87 37	93.36 183		99.60 61

原ACMM2							97.67 260

原ACMM1				98.65 67	99.32 49	96.62 93		98.67 108	93.27 200	97.81 83	98.97 68	95.18 49	99.83 46	93.84 172	99.46 74	99.50 73

test222					99.23 74	97.17 75	97.40 274	98.66 111	88.68 313	98.05 65	98.96 73	94.14 71			99.53 67	99.61 58

testdata2													99.89 28	91.65 234

segment_acmp												96.85 4

testdata				98.26 94	99.20 78	95.36 158		98.68 101	91.89 248	98.60 45	99.10 51	94.44 67	99.82 52	94.27 163	99.44 76	99.58 65

testdata1							97.32 284		96.34 59

test12				99.18 34	99.16 80	98.19 35		98.53 132		98.07 64		95.13 51	99.72 90		99.56 63	99.63 57

plane_prior7					97.42 207	94.63 213

plane_prior6					97.35 212	94.61 216						87.09 216

plane_prior5								98.56 126					99.03 185	96.07 105	94.27 214	96.92 226

plane_prior4											98.28 139

plane_prior3						94.61 216			97.02 40	95.34 176

plane_prior2							98.80 110		97.28 22

plane_prior1					97.37 211

plane_prior						94.60 218	98.44 176		96.74 47						94.22 216

n2								0.00 374

nn								0.00 374

door-mid								94.37 350

lessismore_v0				94.45 308	94.93 327	88.44 323		91.03 360		86.77 320	97.64 194	76.23 328	98.42 256	90.31 262	85.64 326	96.51 287

LGP-MVS_train				96.47 229	97.46 203	93.54 250		98.54 129	94.67 131	94.36 207	98.77 92	85.39 250	99.11 173	95.71 122	94.15 220	96.76 248

test11								98.66 111

door								94.64 348

HQP5-MVS						94.25 233

HQP-NCC					97.20 221		98.05 223		96.43 55	94.45 197

ACMP_Plane					97.20 221		98.05 223		96.43 55	94.45 197

BP-MVS														95.30 135

HQP4-MVS										94.45 197			98.96 192			96.87 238

HQP3-MVS								98.46 146							94.18 218

HQP2-MVS												86.75 222

NP-MVS					97.28 215	94.51 221					97.73 185

MDTV_nov1_ep13_2view						84.26 337	96.89 305		90.97 276	97.90 80		89.89 138		93.91 171		99.18 115

ACMMP++_ref															92.97 245

ACMMP++															93.61 233

Test By Simon												94.64 59

ITE_SJBPF				95.44 273	97.42 207	91.32 283		97.50 258	95.09 116	93.59 240	98.35 130	81.70 296	98.88 204	89.71 274	93.39 239	96.12 303

DeepMVS_CX				86.78 335	97.09 229	72.30 355		95.17 343	75.92 351	84.34 339	95.19 313	70.58 344	95.35 340	79.98 336	89.04 286	92.68 346

High-resolution multi-view benchmark