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 1	99.57 24	98.96 3	99.39 5	98.93 36	97.38 17	99.41 3	99.54 1	96.66 6	99.84 42	98.86 2	99.85 2	99.87 1

SteuartSystems-ACMMP		98.90 2	98.75 2	99.36 12	99.22 72	98.43 17	99.10 44	98.87 49	97.38 17	99.35 5	99.40 6	97.78 1	99.87 35	97.77 39	99.85 2	99.78 7
Skip Steuart: Steuart Systems R&D Blog.
TSAR-MVS + MP.		98.78 3	98.62 4	99.24 25	99.69 17	98.28 28	99.14 37	98.66 107	96.84 43	99.56 2	99.31 21	96.34 11	99.70 91	98.32 20	99.73 35	99.73 28

CNVR-MVS		98.78 3	98.56 6	99.45 8	99.32 46	98.87 6	98.47 155	98.81 61	97.72 4	98.76 34	99.16 42	97.05 3	99.78 74	98.06 25	99.66 43	99.69 36

HSP-MVS		98.70 5	98.52 8	99.24 25	99.75 3	98.23 29	99.26 17	98.58 120	97.52 7	99.41 3	98.78 85	96.00 24	99.79 69	97.79 38	99.59 53	99.69 36

XVS		98.70 5	98.49 12	99.34 13	99.70 15	98.35 23	99.29 14	98.88 47	97.40 14	98.46 46	99.20 35	95.90 30	99.89 27	97.85 34	99.74 33	99.78 7

Regformer-2		98.69 7	98.52 8	99.19 28	99.35 38	98.01 42	98.37 164	98.81 61	97.48 11	99.21 10	99.21 32	96.13 17	99.80 57	98.40 18	99.73 35	99.75 21

Regformer-1		98.66 8	98.51 10	99.12 40	99.35 38	97.81 51	98.37 164	98.76 75	97.49 10	99.20 11	99.21 32	96.08 20	99.79 69	98.42 16	99.73 35	99.75 21

MCST-MVS		98.65 9	98.37 17	99.48 5	99.60 23	98.87 6	98.41 161	98.68 97	97.04 38	98.52 45	98.80 84	96.78 5	99.83 43	97.93 28	99.61 49	99.74 26

Regformer-4		98.64 10	98.53 7	98.99 47	99.43 36	97.37 64	98.40 162	98.79 69	97.46 12	99.09 14	99.31 21	95.86 32	99.80 57	98.64 4	99.76 24	99.79 4

SD-MVS		98.64 10	98.68 3	98.53 73	99.33 43	98.36 22	98.90 66	98.85 53	97.28 21	99.72 1	99.39 7	96.63 8	97.60 286	98.17 23	99.85 2	99.64 54

HFP-MVS		98.63 12	98.40 14	99.32 16	99.72 11	98.29 26	99.23 21	98.96 31	96.10 65	98.94 22	99.17 39	96.06 21	99.92 13	97.62 45	99.78 14	99.75 21

ACMMP_Plus		98.61 13	98.30 25	99.55 1	99.62 22	98.95 4	98.82 85	98.81 61	95.80 72	99.16 13	99.47 4	95.37 41	99.92 13	97.89 32	99.75 30	99.79 4

region2R		98.61 13	98.38 16	99.29 18	99.74 7	98.16 35	99.23 21	98.93 36	96.15 60	98.94 22	99.17 39	95.91 29	99.94 3	97.55 50	99.79 10	99.78 7

NCCC		98.61 13	98.35 20	99.38 10	99.28 61	98.61 11	98.45 156	98.76 75	97.82 3	98.45 49	98.93 73	96.65 7	99.83 43	97.38 57	99.41 77	99.71 33

Regformer-3		98.59 16	98.50 11	98.86 57	99.43 36	97.05 75	98.40 162	98.68 97	97.43 13	99.06 15	99.31 21	95.80 33	99.77 79	98.62 6	99.76 24	99.78 7

ACMMPR		98.59 16	98.36 18	99.29 18	99.74 7	98.15 36	99.23 21	98.95 33	96.10 65	98.93 26	99.19 38	95.70 34	99.94 3	97.62 45	99.79 10	99.78 7

MTAPA		98.58 18	98.29 26	99.46 6	99.76 1	98.64 9	98.90 66	98.74 79	97.27 25	98.02 65	99.39 7	94.81 55	99.96 1	97.91 29	99.79 10	99.77 14

HPM-MVS++		98.58 18	98.25 29	99.55 1	99.50 28	99.08 2	98.72 115	98.66 107	97.51 8	98.15 56	98.83 81	95.70 34	99.92 13	97.53 52	99.67 40	99.66 49

CP-MVS		98.57 20	98.36 18	99.19 28	99.66 19	97.86 47	99.34 11	98.87 49	95.96 68	98.60 42	99.13 44	96.05 23	99.94 3	97.77 39	99.86 1	99.77 14

MSLP-MVS++		98.56 21	98.57 5	98.55 71	99.26 64	96.80 84	98.71 116	99.05 23	97.28 21	98.84 28	99.28 25	96.47 10	99.40 131	98.52 14	99.70 38	99.47 78

MPTG		98.55 22	98.25 29	99.46 6	99.76 1	98.64 9	98.55 144	98.74 79	97.27 25	98.02 65	99.39 7	94.81 55	99.96 1	97.91 29	99.79 10	99.77 14

DeepC-MVS_fast	96.70 1	98.55 22	98.34 21	99.18 32	99.25 65	98.04 40	98.50 152	98.78 71	97.72 4	98.92 27	99.28 25	95.27 45	99.82 48	97.55 50	99.77 18	99.69 36
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
#test#		98.54 24	98.27 27	99.32 16	99.72 11	98.29 26	98.98 59	98.96 31	95.65 78	98.94 22	99.17 39	96.06 21	99.92 13	97.21 60	99.78 14	99.75 21

APD-MVS_3200maxsize		98.53 25	98.33 24	99.15 37	99.50 28	97.92 46	99.15 36	98.81 61	96.24 58	99.20 11	99.37 12	95.30 44	99.80 57	97.73 41	99.67 40	99.72 31

mPP-MVS		98.51 26	98.26 28	99.25 24	99.75 3	98.04 40	99.28 16	98.81 61	96.24 58	98.35 53	99.23 29	95.46 39	99.94 3	97.42 55	99.81 8	99.77 14

PGM-MVS		98.49 27	98.23 32	99.27 23	99.72 11	98.08 39	98.99 56	99.49 5	95.43 86	99.03 16	99.32 20	95.56 36	99.94 3	96.80 79	99.77 18	99.78 7

EI-MVSNet-Vis-set		98.47 28	98.39 15	98.69 62	99.46 33	96.49 97	98.30 175	98.69 94	97.21 28	98.84 28	99.36 16	95.41 40	99.78 74	98.62 6	99.65 44	99.80 3

MVS_111021_HR		98.47 28	98.34 21	98.88 56	99.22 72	97.32 65	97.91 218	99.58 3	97.20 29	98.33 54	99.00 63	95.99 25	99.64 100	98.05 26	99.76 24	99.69 36

EI-MVSNet-UG-set		98.41 30	98.34 21	98.61 67	99.45 34	96.32 104	98.28 177	98.68 97	97.17 31	98.74 35	99.37 12	95.25 46	99.79 69	98.57 8	99.54 65	99.73 28

DELS-MVS		98.40 31	98.20 34	98.99 47	99.00 87	97.66 53	97.75 235	98.89 44	97.71 6	98.33 54	98.97 65	94.97 53	99.88 34	98.42 16	99.76 24	99.42 86
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
TSAR-MVS + GP.		98.38 32	98.24 31	98.81 58	99.22 72	97.25 70	98.11 198	98.29 167	97.19 30	98.99 21	99.02 58	96.22 12	99.67 96	98.52 14	98.56 111	99.51 70

HPM-MVS_fast		98.38 32	98.13 35	99.12 40	99.75 3	97.86 47	99.44 4	98.82 58	94.46 134	98.94 22	99.20 35	95.16 49	99.74 85	97.58 47	99.85 2	99.77 14

HPM-MVS		98.36 34	98.10 36	99.13 38	99.74 7	97.82 50	99.53 1	98.80 68	94.63 127	98.61 41	98.97 65	95.13 50	99.77 79	97.65 44	99.83 7	99.79 4

APD-MVS		98.35 35	98.00 40	99.42 9	99.51 27	98.72 8	98.80 94	98.82 58	94.52 130	99.23 9	99.25 28	95.54 38	99.80 57	96.52 89	99.77 18	99.74 26
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MVS_111021_LR		98.34 36	98.23 32	98.67 64	99.27 62	96.90 81	97.95 213	99.58 3	97.14 33	98.44 50	99.01 62	95.03 52	99.62 105	97.91 29	99.75 30	99.50 72

PHI-MVS		98.34 36	98.06 37	99.18 32	99.15 79	98.12 38	99.04 52	99.09 19	93.32 180	98.83 30	99.10 48	96.54 9	99.83 43	97.70 43	99.76 24	99.59 62

MP-MVS		98.33 38	98.01 39	99.28 20	99.75 3	98.18 34	99.22 27	98.79 69	96.13 62	97.92 74	99.23 29	94.54 60	99.94 3	96.74 81	99.78 14	99.73 28

MP-MVS-pluss		98.31 39	97.92 42	99.49 4	99.72 11	98.88 5	98.43 159	98.78 71	94.10 140	97.69 86	99.42 5	95.25 46	99.92 13	98.09 24	99.80 9	99.67 47
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
abl_6		98.30 40	98.03 38	99.13 38	99.56 25	97.76 52	99.13 40	98.82 58	96.14 61	99.26 7	99.37 12	93.33 77	99.93 9	96.96 67	99.67 40	99.69 36

ACMMP		98.23 41	97.95 41	99.09 42	99.74 7	97.62 56	99.03 53	99.41 6	95.98 67	97.60 92	99.36 16	94.45 65	99.93 9	97.14 61	98.85 98	99.70 35
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
test_prior3		98.22 42	97.90 43	99.19 28	99.31 48	98.22 31	97.80 231	98.84 54	96.12 63	97.89 76	98.69 92	95.96 26	99.70 91	96.89 71	99.60 50	99.65 51

CANet		98.05 43	97.76 45	98.90 55	98.73 108	97.27 67	98.35 166	98.78 71	97.37 19	97.72 84	98.96 69	91.53 111	99.92 13	98.79 3	99.65 44	99.51 70

train_agg		97.97 44	97.52 54	99.33 15	99.31 48	98.50 13	97.92 215	98.73 84	92.98 191	97.74 82	98.68 94	96.20 13	99.80 57	96.59 85	99.57 56	99.68 42

UA-Net		97.96 45	97.62 48	98.98 49	98.86 100	97.47 61	98.89 70	99.08 20	96.67 49	98.72 36	99.54 1	93.15 80	99.81 50	94.87 134	98.83 99	99.65 51

agg_prior1		97.95 46	97.51 55	99.28 20	99.30 53	98.38 18	97.81 230	98.72 86	93.16 185	97.57 94	98.66 97	96.14 16	99.81 50	96.63 84	99.56 62	99.66 49

CDPH-MVS		97.94 47	97.49 56	99.28 20	99.47 32	98.44 15	97.91 218	98.67 104	92.57 204	98.77 33	98.85 79	95.93 28	99.72 86	95.56 118	99.69 39	99.68 42

DeepPCF-MVS	96.37 2	97.93 48	98.48 13	96.30 222	99.00 87	89.54 284	97.43 254	98.87 49	98.16 2	99.26 7	99.38 11	96.12 18	99.64 100	98.30 21	99.77 18	99.72 31

DeepC-MVS	95.98 3	97.88 49	97.58 50	98.77 59	99.25 65	96.93 79	98.83 83	98.75 78	96.96 41	96.89 116	99.50 3	90.46 125	99.87 35	97.84 36	99.76 24	99.52 67
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
agg_prior3		97.87 50	97.42 60	99.23 27	99.29 56	98.23 29	97.92 215	98.72 86	92.38 217	97.59 93	98.64 99	96.09 19	99.79 69	96.59 85	99.57 56	99.68 42

DP-MVS Recon		97.86 51	97.46 58	99.06 45	99.53 26	98.35 23	98.33 168	98.89 44	92.62 201	98.05 61	98.94 72	95.34 43	99.65 98	96.04 100	99.42 76	99.19 105

CSCG		97.85 52	97.74 46	98.20 92	99.67 18	95.16 152	99.22 27	99.32 7	93.04 188	97.02 108	98.92 75	95.36 42	99.91 22	97.43 54	99.64 46	99.52 67

MG-MVS		97.81 53	97.60 49	98.44 80	99.12 81	95.97 116	97.75 235	98.78 71	96.89 42	98.46 46	99.22 31	93.90 74	99.68 95	94.81 137	99.52 67	99.67 47

VNet		97.79 54	97.40 61	98.96 51	98.88 98	97.55 58	98.63 131	98.93 36	96.74 46	99.02 17	98.84 80	90.33 128	99.83 43	98.53 10	96.66 157	99.50 72

PS-MVSNAJ		97.73 55	97.77 44	97.62 128	98.68 114	95.58 136	97.34 263	98.51 132	97.29 20	98.66 38	97.88 161	94.51 61	99.90 25	97.87 33	99.17 87	97.39 190

CPTT-MVS		97.72 56	97.32 63	98.92 53	99.64 20	97.10 74	99.12 42	98.81 61	92.34 218	98.09 59	99.08 54	93.01 81	99.92 13	96.06 99	99.77 18	99.75 21

MVS_0304		97.70 57	97.25 65	99.07 43	98.90 95	97.83 49	98.20 183	98.74 79	97.51 8	98.03 64	99.06 56	86.12 224	99.93 9	99.02 1	99.64 46	99.44 85

PVSNet_Blended_VisFu		97.70 57	97.46 58	98.44 80	99.27 62	95.91 126	98.63 131	99.16 17	94.48 133	97.67 87	98.88 77	92.80 83	99.91 22	97.11 62	99.12 88	99.50 72

canonicalmvs		97.67 59	97.23 67	98.98 49	98.70 111	98.38 18	99.34 11	98.39 154	96.76 45	97.67 87	97.40 196	92.26 90	99.49 125	98.28 22	96.28 178	99.08 119

xiu_mvs_v2_base		97.66 60	97.70 47	97.56 135	98.61 120	95.46 142	97.44 252	98.46 142	97.15 32	98.65 39	98.15 141	94.33 67	99.80 57	97.84 36	98.66 107	97.41 188

xiu_mvs_v1_base_debu		97.60 61	97.56 51	97.72 119	98.35 127	95.98 112	97.86 226	98.51 132	97.13 34	99.01 18	98.40 117	91.56 107	99.80 57	98.53 10	98.68 103	97.37 192

xiu_mvs_v1_base		97.60 61	97.56 51	97.72 119	98.35 127	95.98 112	97.86 226	98.51 132	97.13 34	99.01 18	98.40 117	91.56 107	99.80 57	98.53 10	98.68 103	97.37 192

xiu_mvs_v1_base_debi		97.60 61	97.56 51	97.72 119	98.35 127	95.98 112	97.86 226	98.51 132	97.13 34	99.01 18	98.40 117	91.56 107	99.80 57	98.53 10	98.68 103	97.37 192

MVSFormer		97.57 64	97.49 56	97.84 112	98.07 147	95.76 132	99.47 2	98.40 152	94.98 113	98.79 31	98.83 81	92.34 87	98.41 243	96.91 69	99.59 53	99.34 89

alignmvs		97.56 65	97.07 74	99.01 46	98.66 115	98.37 21	98.83 83	98.06 215	96.74 46	98.00 69	97.65 182	90.80 122	99.48 129	98.37 19	96.56 161	99.19 105

OMC-MVS		97.55 66	97.34 62	98.20 92	99.33 43	95.92 124	98.28 177	98.59 115	95.52 83	97.97 70	99.10 48	93.28 79	99.49 125	95.09 132	98.88 95	99.19 105

PAPM_NR		97.46 67	97.11 71	98.50 75	99.50 28	96.41 100	98.63 131	98.60 114	95.18 104	97.06 106	98.06 147	94.26 69	99.57 113	93.80 163	98.87 97	99.52 67

EPP-MVSNet		97.46 67	97.28 64	97.99 106	98.64 117	95.38 144	99.33 13	98.31 162	93.61 171	97.19 100	99.07 55	94.05 71	99.23 142	96.89 71	98.43 118	99.37 88

3Dnovator	94.51 5	97.46 67	96.93 78	99.07 43	97.78 164	97.64 54	99.35 10	99.06 21	97.02 39	93.75 220	99.16 42	89.25 140	99.92 13	97.22 59	99.75 30	99.64 54

CNLPA		97.45 70	97.03 75	98.73 60	99.05 82	97.44 63	98.07 202	98.53 128	95.32 98	96.80 122	98.53 107	93.32 78	99.72 86	94.31 150	99.31 83	99.02 122

lupinMVS		97.44 71	97.22 68	98.12 98	98.07 147	95.76 132	97.68 240	97.76 227	94.50 131	98.79 31	98.61 100	92.34 87	99.30 137	97.58 47	99.59 53	99.31 92

3Dnovator+	94.38 6	97.43 72	96.78 85	99.38 10	97.83 162	98.52 12	99.37 7	98.71 91	97.09 37	92.99 241	99.13 44	89.36 137	99.89 27	96.97 65	99.57 56	99.71 33

Vis-MVSNet		97.42 73	97.11 71	98.34 86	98.66 115	96.23 107	99.22 27	99.00 26	96.63 51	98.04 63	99.21 32	88.05 186	99.35 136	96.01 102	99.21 85	99.45 84
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
API-MVS		97.41 74	97.25 65	97.91 109	98.70 111	96.80 84	98.82 85	98.69 94	94.53 129	98.11 58	98.28 131	94.50 64	99.57 113	94.12 155	99.49 68	97.37 192

sss		97.39 75	96.98 77	98.61 67	98.60 121	96.61 92	98.22 181	98.93 36	93.97 147	98.01 67	98.48 112	91.98 100	99.85 40	96.45 91	98.15 127	99.39 87

PVSNet_Blended		97.38 76	97.12 70	98.14 95	99.25 65	95.35 147	97.28 267	99.26 8	93.13 186	97.94 72	98.21 138	92.74 84	99.81 50	96.88 74	99.40 79	99.27 99

1121		97.37 77	96.77 87	99.16 35	99.34 40	97.99 45	98.19 187	98.68 97	90.14 266	98.01 67	98.97 65	94.80 57	99.87 35	93.36 172	99.46 73	99.61 57

WTY-MVS		97.37 77	96.92 79	98.72 61	98.86 100	96.89 83	98.31 173	98.71 91	95.26 100	97.67 87	98.56 106	92.21 93	99.78 74	95.89 104	96.85 154	99.48 77

jason		97.32 79	97.08 73	98.06 104	97.45 186	95.59 135	97.87 225	97.91 223	94.79 120	98.55 44	98.83 81	91.12 115	99.23 142	97.58 47	99.60 50	99.34 89
jason: jason.
MVS_Test		97.28 80	97.00 76	98.13 97	98.33 131	95.97 116	98.74 110	98.07 213	94.27 137	98.44 50	98.07 146	92.48 86	99.26 139	96.43 92	98.19 126	99.16 110

EPNet		97.28 80	96.87 81	98.51 74	94.98 302	96.14 109	98.90 66	97.02 283	98.28 1	95.99 153	99.11 46	91.36 112	99.89 27	96.98 64	99.19 86	99.50 72
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
IS-MVSNet		97.22 82	96.88 80	98.25 90	98.85 102	96.36 102	99.19 33	97.97 220	95.39 88	97.23 99	98.99 64	91.11 116	98.93 179	94.60 141	98.59 109	99.47 78

PLC	95.07 4	97.20 83	96.78 85	98.44 80	99.29 56	96.31 106	98.14 193	98.76 75	92.41 215	96.39 144	98.31 130	94.92 54	99.78 74	94.06 156	98.77 102	99.23 103
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CHOSEN 280x420		97.18 84	97.18 69	97.20 149	98.81 104	93.27 236	95.78 310	99.15 18	95.25 101	96.79 123	98.11 144	92.29 89	99.07 161	98.56 9	99.85 2	99.25 101

LS3D		97.16 85	96.66 92	98.68 63	98.53 125	97.19 72	98.93 64	98.90 42	92.83 198	95.99 153	99.37 12	92.12 96	99.87 35	93.67 166	99.57 56	98.97 127

AdaColmap		97.15 86	96.70 88	98.48 77	99.16 77	96.69 89	98.01 207	98.89 44	94.44 135	96.83 118	98.68 94	90.69 123	99.76 81	94.36 147	99.29 84	98.98 126

Effi-MVS+		97.12 87	96.69 89	98.39 84	98.19 140	96.72 88	97.37 259	98.43 149	93.71 162	97.65 90	98.02 149	92.20 94	99.25 140	96.87 77	97.79 139	99.19 105

CHOSEN 1792x2688		97.12 87	96.80 82	98.08 101	99.30 53	94.56 203	98.05 203	99.71 1	93.57 172	97.09 102	98.91 76	88.17 181	99.89 27	96.87 77	99.56 62	99.81 2

F-COLMAP		97.09 89	96.80 82	97.97 107	99.45 34	94.95 164	98.55 144	98.62 113	93.02 189	96.17 148	98.58 105	94.01 72	99.81 50	93.95 158	98.90 94	99.14 113

TAMVS		97.02 90	96.79 84	97.70 122	98.06 149	95.31 149	98.52 147	98.31 162	93.95 148	97.05 107	98.61 100	93.49 76	98.52 219	95.33 124	97.81 138	99.29 97

CDS-MVSNet		96.99 91	96.69 89	97.90 110	98.05 150	95.98 112	98.20 183	98.33 161	93.67 169	96.95 109	98.49 111	93.54 75	98.42 236	95.24 130	97.74 142	99.31 92
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
CANet_DTU		96.96 92	96.55 95	98.21 91	98.17 144	96.07 111	97.98 210	98.21 178	97.24 27	97.13 101	98.93 73	86.88 213	99.91 22	95.00 133	99.37 81	98.66 146

114514_t		96.93 93	96.27 104	98.92 53	99.50 28	97.63 55	98.85 79	98.90 42	84.80 313	97.77 79	99.11 46	92.84 82	99.66 97	94.85 135	99.77 18	99.47 78

MAR-MVS		96.91 94	96.40 100	98.45 79	98.69 113	96.90 81	98.66 129	98.68 97	92.40 216	97.07 105	97.96 154	91.54 110	99.75 83	93.68 165	98.92 93	98.69 143
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
HyFIR lowres test		96.90 95	96.49 98	98.14 95	99.33 43	95.56 138	97.38 257	99.65 2	92.34 218	97.61 91	98.20 139	89.29 139	99.10 158	96.97 65	97.60 145	99.77 14

Vis-MVSNet (Re-imp)		96.87 96	96.55 95	97.83 113	98.73 108	95.46 142	99.20 31	98.30 165	94.96 115	96.60 129	98.87 78	90.05 132	98.59 208	93.67 166	98.60 108	99.46 82

PAPR		96.84 97	96.24 106	98.65 65	98.72 110	96.92 80	97.36 261	98.57 121	93.33 179	96.67 125	97.57 189	94.30 68	99.56 115	91.05 233	98.59 109	99.47 78

HY-MVS	93.96 8	96.82 98	96.23 107	98.57 69	98.46 126	97.00 76	98.14 193	98.21 178	93.95 148	96.72 124	97.99 153	91.58 106	99.76 81	94.51 145	96.54 162	98.95 131

UGNet		96.78 99	96.30 103	98.19 94	98.24 135	95.89 128	98.88 72	98.93 36	97.39 16	96.81 121	97.84 165	82.60 274	99.90 25	96.53 88	99.49 68	98.79 138
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
PVSNet_BlendedMVS		96.73 100	96.60 93	97.12 155	99.25 65	95.35 147	98.26 179	99.26 8	94.28 136	97.94 72	97.46 193	92.74 84	99.81 50	96.88 74	93.32 223	96.20 278

mvs_anonymous		96.70 101	96.53 97	97.18 151	98.19 140	93.78 224	98.31 173	98.19 182	94.01 143	94.47 177	98.27 134	92.08 98	98.46 228	97.39 56	97.91 133	99.31 92

1112_ss		96.63 102	96.00 113	98.50 75	98.56 122	96.37 101	98.18 191	98.10 208	92.92 193	94.84 166	98.43 115	92.14 95	99.58 112	94.35 148	96.51 163	99.56 66

mvs-test1		96.60 103	96.68 91	96.37 216	97.89 159	91.81 255	98.56 142	98.10 208	96.57 52	96.52 136	97.94 156	90.81 120	99.45 130	95.72 111	98.01 130	97.86 177

PMMVS		96.60 103	96.33 102	97.41 141	97.90 158	93.93 220	97.35 262	98.41 150	92.84 197	97.76 80	97.45 195	91.10 117	99.20 144	96.26 95	97.91 133	99.11 115

DP-MVS		96.59 105	95.93 114	98.57 69	99.34 40	96.19 108	98.70 119	98.39 154	89.45 285	94.52 175	99.35 18	91.85 102	99.85 40	92.89 191	98.88 95	99.68 42

PatchMatch-RL		96.59 105	96.03 112	98.27 88	99.31 48	96.51 96	97.91 218	99.06 21	93.72 161	96.92 114	98.06 147	88.50 176	99.65 98	91.77 218	99.00 91	98.66 146

XVG-OURS		96.55 107	96.41 99	96.99 161	98.75 107	93.76 225	97.50 251	98.52 130	95.67 76	96.83 118	99.30 24	88.95 151	99.53 122	95.88 105	96.26 179	97.69 183

FIs		96.51 108	96.12 109	97.67 125	97.13 207	97.54 59	99.36 8	99.22 14	95.89 69	94.03 211	98.35 123	91.98 100	98.44 233	96.40 93	92.76 230	97.01 201

XVG-OURS-SEG-HR		96.51 108	96.34 101	97.02 160	98.77 106	93.76 225	97.79 233	98.50 137	95.45 85	96.94 111	99.09 52	87.87 192	99.55 121	96.76 80	95.83 189	97.74 180

PS-MVSNAJss		96.43 110	96.26 105	96.92 169	95.84 284	95.08 156	99.16 35	98.50 137	95.87 70	93.84 218	98.34 127	94.51 61	98.61 205	96.88 74	93.45 220	97.06 198

FC-MVSNet-test		96.42 111	96.05 110	97.53 136	96.95 214	97.27 67	99.36 8	99.23 12	95.83 71	93.93 213	98.37 121	92.00 99	98.32 252	96.02 101	92.72 231	97.00 202

ab-mvs		96.42 111	95.71 123	98.55 71	98.63 118	96.75 87	97.88 224	98.74 79	93.84 153	96.54 134	98.18 140	85.34 238	99.75 83	95.93 103	96.35 171	99.15 111

PVSNet	91.96 18	96.35 113	96.15 108	96.96 164	99.17 76	92.05 252	96.08 302	98.68 97	93.69 165	97.75 81	97.80 171	88.86 154	99.69 94	94.26 152	99.01 90	99.15 111

Test_1112_low_res		96.34 114	95.66 127	98.36 85	98.56 122	95.94 120	97.71 237	98.07 213	92.10 224	94.79 170	97.29 205	91.75 103	99.56 115	94.17 153	96.50 164	99.58 64

diffmvs		96.32 115	95.74 118	98.07 103	98.26 134	96.14 109	98.53 146	98.23 176	90.10 267	96.88 117	97.73 174	90.16 131	99.15 147	93.90 160	97.85 137	98.91 133

Effi-MVS+-dtu		96.29 116	96.56 94	95.51 247	97.89 159	90.22 278	98.80 94	98.10 208	96.57 52	96.45 143	96.66 255	90.81 120	98.91 181	95.72 111	97.99 131	97.40 189

QAPM		96.29 116	95.40 129	98.96 51	97.85 161	97.60 57	99.23 21	98.93 36	89.76 277	93.11 238	99.02 58	89.11 144	99.93 9	91.99 212	99.62 48	99.34 89

Fast-Effi-MVS+		96.28 118	95.70 124	98.03 105	98.29 133	95.97 116	98.58 137	98.25 173	91.74 232	95.29 160	97.23 208	91.03 119	99.15 147	92.90 189	97.96 132	98.97 127

nrg030		96.28 118	95.72 120	97.96 108	96.90 219	98.15 36	99.39 5	98.31 162	95.47 84	94.42 186	98.35 123	92.09 97	98.69 199	97.50 53	89.05 265	97.04 200

1314		96.25 120	95.73 119	97.79 116	97.13 207	95.55 140	98.19 187	98.59 115	93.47 175	92.03 263	97.82 169	91.33 113	99.49 125	94.62 140	98.44 116	98.32 167

HQP_MVS		96.14 121	95.90 115	96.85 170	97.42 187	94.60 201	98.80 94	98.56 122	97.28 21	95.34 157	98.28 131	87.09 208	99.03 167	96.07 97	94.27 197	96.92 207

MVSTER		96.06 122	95.72 120	97.08 158	98.23 136	95.93 123	98.73 113	98.27 168	94.86 119	95.07 161	98.09 145	88.21 180	98.54 212	96.59 85	93.46 218	96.79 225

test_djsdf		96.00 123	95.69 125	96.93 167	95.72 288	95.49 141	99.47 2	98.40 152	94.98 113	94.58 173	97.86 162	89.16 143	98.41 243	96.91 69	94.12 205	96.88 217

EI-MVSNet		95.96 124	95.83 117	96.36 217	97.93 156	93.70 229	98.12 196	98.27 168	93.70 164	95.07 161	99.02 58	92.23 92	98.54 212	94.68 138	93.46 218	96.84 221

BH-untuned		95.95 125	95.72 120	96.65 187	98.55 124	92.26 249	98.23 180	97.79 226	93.73 160	94.62 172	98.01 151	88.97 150	99.00 170	93.04 182	98.51 112	98.68 144

MSDG		95.93 126	95.30 139	97.83 113	98.90 95	95.36 145	96.83 289	98.37 157	91.32 247	94.43 185	98.73 91	90.27 129	99.60 106	90.05 248	98.82 100	98.52 152

BH-RMVSNet		95.92 127	95.32 137	97.69 123	98.32 132	94.64 195	98.19 187	97.45 256	94.56 128	96.03 151	98.61 100	85.02 241	99.12 151	90.68 237	99.06 89	99.30 95

Fast-Effi-MVS+-dtu		95.87 128	95.85 116	95.91 235	97.74 166	91.74 259	98.69 120	98.15 193	95.56 81	94.92 164	97.68 181	88.98 149	98.79 196	93.19 177	97.78 140	97.20 196

LFMVS		95.86 129	94.98 150	98.47 78	98.87 99	96.32 104	98.84 82	96.02 312	93.40 177	98.62 40	99.20 35	74.99 312	99.63 103	97.72 42	97.20 149	99.46 82

OpenMVS	93.04 13	95.83 130	95.00 148	98.32 87	97.18 204	97.32 65	99.21 30	98.97 29	89.96 270	91.14 269	99.05 57	86.64 216	99.92 13	93.38 171	99.47 70	97.73 181

VDD-MVS		95.82 131	95.23 141	97.61 133	98.84 103	93.98 219	98.68 124	97.40 261	95.02 112	97.95 71	99.34 19	74.37 317	99.78 74	98.64 4	96.80 155	99.08 119

UniMVSNet (Re)		95.78 132	95.19 143	97.58 134	96.99 213	97.47 61	98.79 99	99.18 16	95.60 79	93.92 214	97.04 226	91.68 104	98.48 223	95.80 109	87.66 287	96.79 225

VPA-MVSNet		95.75 133	95.11 145	97.69 123	97.24 197	97.27 67	98.94 63	99.23 12	95.13 106	95.51 156	97.32 203	85.73 230	98.91 181	97.33 58	89.55 259	96.89 215

HQP-MVS		95.72 134	95.40 129	96.69 179	97.20 201	94.25 214	98.05 203	98.46 142	96.43 54	94.45 178	97.73 174	86.75 214	98.96 174	95.30 125	94.18 201	96.86 220

UniMVSNet_NR-MVSNet		95.71 135	95.15 144	97.40 143	96.84 222	96.97 77	98.74 110	99.24 10	95.16 105	93.88 215	97.72 177	91.68 104	98.31 254	95.81 107	87.25 292	96.92 207

PatchmatchNet		95.71 135	95.52 128	96.29 223	97.58 175	90.72 271	96.84 288	97.52 241	94.06 141	97.08 103	96.96 234	89.24 141	98.90 184	92.03 211	98.37 119	99.26 100
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
OPM-MVS		95.69 137	95.33 136	96.76 174	96.16 271	94.63 196	98.43 159	98.39 154	96.64 50	95.02 163	98.78 85	85.15 240	99.05 162	95.21 131	94.20 200	96.60 255

ACMM	93.85 9	95.69 137	95.38 133	96.61 193	97.61 172	93.84 223	98.91 65	98.44 146	95.25 101	94.28 196	98.47 113	86.04 228	99.12 151	95.50 120	93.95 210	96.87 218
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
tpmrst		95.63 139	95.69 125	95.44 253	97.54 178	88.54 300	96.97 277	97.56 235	93.50 174	97.52 96	96.93 241	89.49 134	99.16 146	95.25 129	96.42 166	98.64 148

LPG-MVS_test		95.62 140	95.34 134	96.47 209	97.46 183	93.54 230	98.99 56	98.54 125	94.67 123	94.36 188	98.77 87	85.39 235	99.11 155	95.71 113	94.15 203	96.76 228

CLD-MVS		95.62 140	95.34 134	96.46 212	97.52 180	93.75 227	97.27 268	98.46 142	95.53 82	94.42 186	98.00 152	86.21 222	98.97 171	96.25 96	94.37 195	96.66 246
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
view600		95.60 142	94.93 154	97.62 128	99.05 82	94.85 170	99.09 45	97.01 285	95.36 92	96.52 136	97.37 197	84.55 249	99.59 107	89.07 267	96.39 167	98.40 158

view800		95.60 142	94.93 154	97.62 128	99.05 82	94.85 170	99.09 45	97.01 285	95.36 92	96.52 136	97.37 197	84.55 249	99.59 107	89.07 267	96.39 167	98.40 158

conf0.05thres1000		95.60 142	94.93 154	97.62 128	99.05 82	94.85 170	99.09 45	97.01 285	95.36 92	96.52 136	97.37 197	84.55 249	99.59 107	89.07 267	96.39 167	98.40 158

tfpn		95.60 142	94.93 154	97.62 128	99.05 82	94.85 170	99.09 45	97.01 285	95.36 92	96.52 136	97.37 197	84.55 249	99.59 107	89.07 267	96.39 167	98.40 158

tfpn_ndepth		95.53 146	94.90 159	97.39 146	98.96 92	95.88 129	99.05 50	95.27 320	93.80 156	96.95 109	96.93 241	85.53 233	99.40 131	91.54 223	96.10 185	96.89 215

thres600view7		95.49 147	94.77 162	97.67 125	98.98 89	95.02 157	98.85 79	96.90 293	95.38 89	96.63 126	96.90 243	84.29 256	99.59 107	88.65 276	96.33 172	98.40 158

PatchFormer-LS_test		95.47 148	95.27 140	96.08 231	97.59 174	90.66 272	98.10 200	97.34 265	93.98 146	96.08 149	96.15 275	87.65 200	99.12 151	95.27 128	95.24 193	98.44 157

IterMVS-LS		95.46 149	95.21 142	96.22 225	98.12 145	93.72 228	98.32 172	98.13 196	93.71 162	94.26 197	97.31 204	92.24 91	98.10 265	94.63 139	90.12 251	96.84 221
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
jajsoiax		95.45 150	95.03 147	96.73 175	95.42 297	94.63 196	99.14 37	98.52 130	95.74 73	93.22 232	98.36 122	83.87 268	98.65 203	96.95 68	94.04 206	96.91 212

CVMVSNet		95.43 151	96.04 111	93.57 293	97.93 156	83.62 316	98.12 196	98.59 115	95.68 75	96.56 130	99.02 58	87.51 202	97.51 289	93.56 169	97.44 146	99.60 60

anonymousdsp		95.42 152	94.91 158	96.94 166	95.10 301	95.90 127	99.14 37	98.41 150	93.75 157	93.16 234	97.46 193	87.50 204	98.41 243	95.63 117	94.03 207	96.50 268

DU-MVS		95.42 152	94.76 163	97.40 143	96.53 236	96.97 77	98.66 129	98.99 28	95.43 86	93.88 215	97.69 178	88.57 171	98.31 254	95.81 107	87.25 292	96.92 207

mvs_tets		95.41 154	95.00 148	96.65 187	95.58 292	94.42 206	99.00 55	98.55 124	95.73 74	93.21 233	98.38 120	83.45 271	98.63 204	97.09 63	94.00 208	96.91 212

conf200view11		95.40 155	94.70 165	97.50 137	98.98 89	94.92 165	98.87 73	96.90 293	95.38 89	96.61 127	96.88 246	84.29 256	99.56 115	88.11 282	96.29 174	98.02 173

thres100view900		95.38 156	94.70 165	97.41 141	98.98 89	94.92 165	98.87 73	96.90 293	95.38 89	96.61 127	96.88 246	84.29 256	99.56 115	88.11 282	96.29 174	97.76 178

thres400		95.38 156	94.62 168	97.65 127	98.94 93	94.98 161	98.68 124	96.93 291	95.33 96	96.55 132	96.53 260	84.23 260	99.56 115	88.11 282	96.29 174	98.40 158

BH-w/o		95.38 156	95.08 146	96.26 224	98.34 130	91.79 256	97.70 238	97.43 258	92.87 196	94.24 199	97.22 209	88.66 169	98.84 190	91.55 222	97.70 143	98.16 170

VDDNet		95.36 159	94.53 172	97.86 111	98.10 146	95.13 154	98.85 79	97.75 228	90.46 259	98.36 52	99.39 7	73.27 319	99.64 100	97.98 27	96.58 160	98.81 137

TAPA-MVS	93.98 7	95.35 160	94.56 171	97.74 118	99.13 80	94.83 181	98.33 168	98.64 112	86.62 301	96.29 146	98.61 100	94.00 73	99.29 138	80.00 313	99.41 77	99.09 116
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP	93.49 10	95.34 161	94.98 150	96.43 213	97.67 168	93.48 232	98.73 113	98.44 146	94.94 118	92.53 251	98.53 107	84.50 254	99.14 149	95.48 121	94.00 208	96.66 246
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
COLMAP_ROB	93.27 12	95.33 162	94.87 160	96.71 176	99.29 56	93.24 238	98.58 137	98.11 203	89.92 273	93.57 223	99.10 48	86.37 220	99.79 69	90.78 235	98.10 129	97.09 197
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
tfpn200view9		95.32 163	94.62 168	97.43 140	98.94 93	94.98 161	98.68 124	96.93 291	95.33 96	96.55 132	96.53 260	84.23 260	99.56 115	88.11 282	96.29 174	97.76 178

Patchmatch-test1		95.32 163	94.97 152	96.35 218	97.67 168	91.29 264	97.33 264	97.60 233	94.68 122	96.92 114	96.95 235	83.97 265	98.50 222	91.33 228	98.32 122	99.25 101

thres200		95.25 165	94.57 170	97.28 147	98.81 104	94.92 165	98.20 183	97.11 277	95.24 103	96.54 134	96.22 273	84.58 248	99.53 122	87.93 286	96.50 164	97.39 190

AllTest		95.24 166	94.65 167	96.99 161	99.25 65	93.21 239	98.59 135	98.18 185	91.36 243	93.52 225	98.77 87	84.67 246	99.72 86	89.70 256	97.87 135	98.02 173

LCM-MVSNet-Re		95.22 167	95.32 137	94.91 270	98.18 142	87.85 307	98.75 106	95.66 318	95.11 107	88.96 288	96.85 248	90.26 130	97.65 284	95.65 116	98.44 116	99.22 104

EPNet_dtu		95.21 168	94.95 153	95.99 232	96.17 268	90.45 276	98.16 192	97.27 272	96.77 44	93.14 237	98.33 128	90.34 127	98.42 236	85.57 300	98.81 101	99.09 116
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
XXY-MVS		95.20 169	94.45 177	97.46 138	96.75 227	96.56 94	98.86 78	98.65 111	93.30 182	93.27 231	98.27 134	84.85 245	98.87 187	94.82 136	91.26 247	96.96 204

WR-MVS		95.15 170	94.46 175	97.22 148	96.67 232	96.45 98	98.21 182	98.81 61	94.15 138	93.16 234	97.69 178	87.51 202	98.30 256	95.29 127	88.62 276	96.90 214

TranMVSNet+NR-MVSNet		95.14 171	94.48 173	97.11 156	96.45 241	96.36 102	99.03 53	99.03 24	95.04 111	93.58 222	97.93 157	88.27 179	98.03 270	94.13 154	86.90 297	96.95 206

test-LLR		95.10 172	94.87 160	95.80 240	96.77 224	89.70 282	96.91 281	95.21 321	95.11 107	94.83 168	95.72 286	87.71 196	98.97 171	93.06 180	98.50 113	98.72 140

WR-MVS_H		95.05 173	94.46 175	96.81 172	96.86 221	95.82 131	99.24 20	99.24 10	93.87 152	92.53 251	96.84 249	90.37 126	98.24 260	93.24 175	87.93 282	96.38 273

ADS-MVSNet		95.00 174	94.45 177	96.63 190	98.00 151	91.91 254	96.04 303	97.74 229	90.15 264	96.47 141	96.64 257	87.89 190	98.96 174	90.08 246	97.06 150	99.02 122

VPNet		94.99 175	94.19 188	97.40 143	97.16 205	96.57 93	98.71 116	98.97 29	95.67 76	94.84 166	98.24 137	80.36 289	98.67 202	96.46 90	87.32 290	96.96 204

EPMVS		94.99 175	94.48 173	96.52 205	97.22 199	91.75 258	97.23 269	91.66 338	94.11 139	97.28 98	96.81 250	85.70 231	98.84 190	93.04 182	97.28 148	98.97 127

NR-MVSNet		94.98 177	94.16 189	97.44 139	96.53 236	97.22 71	98.74 110	98.95 33	94.96 115	89.25 286	97.69 178	89.32 138	98.18 262	94.59 142	87.40 289	96.92 207

FMVSNet3		94.97 178	94.26 183	97.11 156	98.18 142	96.62 90	98.56 142	98.26 172	93.67 169	94.09 207	97.10 214	84.25 259	98.01 271	92.08 207	92.14 234	96.70 237

CostFormer		94.95 179	94.73 164	95.60 246	97.28 195	89.06 291	97.53 249	96.89 296	89.66 281	96.82 120	96.72 253	86.05 226	98.95 178	95.53 119	96.13 184	98.79 138

PAPM		94.95 179	94.00 200	97.78 117	97.04 210	95.65 134	96.03 305	98.25 173	91.23 252	94.19 202	97.80 171	91.27 114	98.86 189	82.61 308	97.61 144	98.84 136

CP-MVSNet		94.94 181	94.30 182	96.83 171	96.72 229	95.56 138	99.11 43	98.95 33	93.89 150	92.42 256	97.90 159	87.19 207	98.12 264	94.32 149	88.21 279	96.82 224

TR-MVS		94.94 181	94.20 187	97.17 152	97.75 165	94.14 216	97.59 246	97.02 283	92.28 222	95.75 155	97.64 184	83.88 267	98.96 174	89.77 252	96.15 183	98.40 158

RPSCF		94.87 183	95.40 129	93.26 297	98.89 97	82.06 322	98.33 168	98.06 215	90.30 263	96.56 130	99.26 27	87.09 208	99.49 125	93.82 162	96.32 173	98.24 168

v1neww		94.83 184	94.22 184	96.68 182	96.39 244	94.85 170	98.87 73	98.11 203	92.45 210	94.45 178	97.06 221	88.82 159	98.54 212	92.93 186	88.91 269	96.65 248

v7new		94.83 184	94.22 184	96.68 182	96.39 244	94.85 170	98.87 73	98.11 203	92.45 210	94.45 178	97.06 221	88.82 159	98.54 212	92.93 186	88.91 269	96.65 248

v6		94.83 184	94.21 186	96.69 179	96.36 248	94.85 170	98.87 73	98.11 203	92.46 205	94.44 184	97.05 225	88.76 165	98.57 210	92.95 185	88.92 268	96.65 248

DWT-MVSNet_test		94.82 187	94.36 180	96.20 226	97.35 192	90.79 269	98.34 167	96.57 307	92.91 194	95.33 159	96.44 265	82.00 276	99.12 151	94.52 144	95.78 190	98.70 142

GA-MVS		94.81 188	94.03 198	97.14 153	97.15 206	93.86 222	96.76 290	97.58 234	94.00 144	94.76 171	97.04 226	80.91 282	98.48 223	91.79 217	96.25 180	99.09 116

V42		94.78 189	94.14 191	96.70 178	96.33 255	95.22 151	98.97 60	98.09 211	92.32 220	94.31 192	97.06 221	88.39 177	98.55 211	92.90 189	88.87 271	96.34 275

divwei89l23v2f112		94.76 190	94.12 194	96.67 185	96.28 261	94.85 170	98.69 120	98.12 198	92.44 212	94.29 195	96.94 237	88.85 156	98.48 223	92.67 194	88.79 275	96.67 243

CR-MVSNet		94.76 190	94.15 190	96.59 195	97.00 211	93.43 233	94.96 316	97.56 235	92.46 205	96.93 112	96.24 269	88.15 182	97.88 281	87.38 288	96.65 158	98.46 155

v1141		94.75 192	94.11 195	96.67 185	96.27 263	94.86 169	98.69 120	98.12 198	92.43 213	94.31 192	96.94 237	88.78 164	98.48 223	92.63 196	88.85 273	96.67 243

v1		94.75 192	94.11 195	96.69 179	96.27 263	94.87 168	98.69 120	98.12 198	92.43 213	94.32 191	96.94 237	88.71 168	98.54 212	92.66 195	88.84 274	96.67 243

DI_MVS_plusplus_test		94.74 194	93.62 224	98.09 100	95.34 298	95.92 124	98.09 201	97.34 265	94.66 125	85.89 300	95.91 280	80.49 288	99.38 134	96.66 83	98.22 124	98.97 127

test_normal		94.72 195	93.59 226	98.11 99	95.30 299	95.95 119	97.91 218	97.39 263	94.64 126	85.70 303	95.88 281	80.52 287	99.36 135	96.69 82	98.30 123	99.01 125

v7		94.69 196	94.04 197	96.62 192	96.41 243	94.79 189	98.78 101	98.13 196	91.89 228	94.30 194	97.16 211	88.13 184	98.45 230	91.96 214	89.65 256	96.61 253

v2v482		94.69 196	94.03 198	96.65 187	96.17 268	94.79 189	98.67 127	98.08 212	92.72 199	94.00 212	97.16 211	87.69 199	98.45 230	92.91 188	88.87 271	96.72 233

pmmvs4		94.69 196	93.99 202	96.81 172	95.74 286	95.94 120	97.40 255	97.67 231	90.42 261	93.37 229	97.59 187	89.08 145	98.20 261	92.97 184	91.67 242	96.30 277

PCF-MVS	93.45 11	94.68 199	93.43 235	98.42 83	98.62 119	96.77 86	95.48 312	98.20 181	84.63 314	93.34 230	98.32 129	88.55 173	99.81 50	84.80 304	98.96 92	98.68 144
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MVS		94.67 200	93.54 229	98.08 101	96.88 220	96.56 94	98.19 187	98.50 137	78.05 327	92.69 246	98.02 149	91.07 118	99.63 103	90.09 245	98.36 120	98.04 172

PS-CasMVS		94.67 200	93.99 202	96.71 176	96.68 231	95.26 150	99.13 40	99.03 24	93.68 167	92.33 257	97.95 155	85.35 237	98.10 265	93.59 168	88.16 281	96.79 225

cascas		94.63 202	93.86 209	96.93 167	96.91 218	94.27 213	96.00 306	98.51 132	85.55 309	94.54 174	96.23 271	84.20 262	98.87 187	95.80 109	96.98 153	97.66 184

tpmvs		94.60 203	94.36 180	95.33 262	97.46 183	88.60 298	96.88 286	97.68 230	91.29 249	93.80 219	96.42 266	88.58 170	99.24 141	91.06 231	96.04 186	98.17 169

LTVRE_ROB	92.95 15	94.60 203	93.90 207	96.68 182	97.41 190	94.42 206	98.52 147	98.59 115	91.69 233	91.21 268	98.35 123	84.87 244	99.04 166	91.06 231	93.44 221	96.60 255
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
v1144		94.59 205	93.92 205	96.60 194	96.21 265	94.78 191	98.59 135	98.14 195	91.86 231	94.21 201	97.02 228	87.97 187	98.41 243	91.72 219	89.57 257	96.61 253

ADS-MVSNet2		94.58 206	94.40 179	95.11 267	98.00 151	88.74 295	96.04 303	97.30 269	90.15 264	96.47 141	96.64 257	87.89 190	97.56 288	90.08 246	97.06 150	99.02 122

ACMH	92.88 16	94.55 207	93.95 204	96.34 220	97.63 170	93.26 237	98.81 91	98.49 141	93.43 176	89.74 281	98.53 107	81.91 277	99.08 160	93.69 164	93.30 224	96.70 237
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
XVG-ACMP-BASELINE		94.54 208	94.14 191	95.75 243	96.55 235	91.65 260	98.11 198	98.44 146	94.96 115	94.22 200	97.90 159	79.18 295	99.11 155	94.05 157	93.85 211	96.48 270

GBi-Net		94.49 209	93.80 212	96.56 200	98.21 137	95.00 158	98.82 85	98.18 185	92.46 205	94.09 207	97.07 218	81.16 279	97.95 274	92.08 207	92.14 234	96.72 233

test1		94.49 209	93.80 212	96.56 200	98.21 137	95.00 158	98.82 85	98.18 185	92.46 205	94.09 207	97.07 218	81.16 279	97.95 274	92.08 207	92.14 234	96.72 233

v8		94.47 211	93.77 215	96.57 199	96.36 248	94.83 181	99.05 50	98.19 182	91.92 227	93.16 234	96.97 233	88.82 159	98.48 223	91.69 220	87.79 285	96.39 272

FMVSNet2		94.47 211	93.61 225	97.04 159	98.21 137	96.43 99	98.79 99	98.27 168	92.46 205	93.50 227	97.09 216	81.16 279	98.00 272	91.09 229	91.93 238	96.70 237

Patchmatch-test		94.42 213	93.68 222	96.63 190	97.60 173	91.76 257	94.83 320	97.49 253	89.45 285	94.14 205	97.10 214	88.99 146	98.83 192	85.37 303	98.13 128	99.29 97

PEN-MVS		94.42 213	93.73 219	96.49 207	96.28 261	94.84 179	99.17 34	99.00 26	93.51 173	92.23 259	97.83 168	86.10 225	97.90 277	92.55 199	86.92 296	96.74 230

v144192		94.39 215	93.70 220	96.48 208	96.06 274	94.35 210	98.58 137	98.16 192	91.45 238	94.33 190	97.02 228	87.50 204	98.45 230	91.08 230	89.11 264	96.63 251

Baseline_NR-MVSNet		94.35 216	93.81 211	95.96 233	96.20 266	94.05 218	98.61 134	96.67 304	91.44 239	93.85 217	97.60 186	88.57 171	98.14 263	94.39 146	86.93 295	95.68 291

v1192		94.32 217	93.58 227	96.53 204	96.10 272	94.45 205	98.50 152	98.17 190	91.54 236	94.19 202	97.06 221	86.95 212	98.43 235	90.14 244	89.57 257	96.70 237

ACMH+	92.99 14	94.30 218	93.77 215	95.88 237	97.81 163	92.04 253	98.71 116	98.37 157	93.99 145	90.60 276	98.47 113	80.86 284	99.05 162	92.75 193	92.40 233	96.55 262

v148		94.29 219	93.76 217	95.91 235	96.10 272	92.93 243	98.58 137	97.97 220	92.59 203	93.47 228	96.95 235	88.53 174	98.32 252	92.56 198	87.06 294	96.49 269

v10		94.29 219	93.55 228	96.51 206	96.39 244	94.80 186	98.99 56	98.19 182	91.35 245	93.02 240	96.99 231	88.09 185	98.41 243	90.50 241	88.41 278	96.33 276

MVP-Stereo		94.28 221	93.92 205	95.35 261	94.95 303	92.60 247	97.97 211	97.65 232	91.61 234	90.68 275	97.09 216	86.32 221	98.42 236	89.70 256	99.34 82	95.02 301
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
OurMVSNet-221017-0		94.21 222	94.00 200	94.85 273	95.60 291	89.22 289	98.89 70	97.43 258	95.29 99	92.18 261	98.52 110	82.86 273	98.59 208	93.46 170	91.76 241	96.74 230

v1921920		94.20 223	93.47 234	96.40 215	95.98 277	94.08 217	98.52 147	98.15 193	91.33 246	94.25 198	97.20 210	86.41 219	98.42 236	90.04 249	89.39 262	96.69 242

v7n		94.19 224	93.43 235	96.47 209	95.90 280	94.38 209	99.26 17	98.34 160	91.99 226	92.76 245	97.13 213	88.31 178	98.52 219	89.48 261	87.70 286	96.52 265

tpm2		94.19 224	93.76 217	95.46 251	97.23 198	89.04 292	97.31 266	96.85 299	87.08 300	96.21 147	96.79 251	83.75 270	98.74 198	92.43 203	96.23 181	98.59 150

v52		94.18 226	93.52 230	96.13 229	95.95 279	94.29 212	99.23 21	98.21 178	91.42 240	92.84 243	96.89 244	87.85 193	98.53 218	91.51 224	87.81 283	95.57 294

V4		94.18 226	93.52 230	96.13 229	95.89 281	94.31 211	99.23 21	98.22 177	91.42 240	92.82 244	96.89 244	87.93 189	98.52 219	91.51 224	87.81 283	95.58 293

TESTMET0.1,1		94.18 226	93.69 221	95.63 245	96.92 216	89.12 290	96.91 281	94.78 326	93.17 184	94.88 165	96.45 264	78.52 296	98.92 180	93.09 179	98.50 113	98.85 134

dp		94.15 229	93.90 207	94.90 271	97.31 194	86.82 312	96.97 277	97.19 276	91.22 253	96.02 152	96.61 259	85.51 234	99.02 169	90.00 250	94.30 196	98.85 134

tpm		94.13 230	93.80 212	95.12 266	96.50 238	87.91 306	97.44 252	95.89 317	92.62 201	96.37 145	96.30 268	84.13 263	98.30 256	93.24 175	91.66 243	99.14 113

IterMVS		94.09 231	93.85 210	94.80 276	97.99 153	90.35 277	97.18 272	98.12 198	93.68 167	92.46 255	97.34 201	84.05 264	97.41 291	92.51 201	91.33 244	96.62 252
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test-mter		94.08 232	93.51 232	95.80 240	96.77 224	89.70 282	96.91 281	95.21 321	92.89 195	94.83 168	95.72 286	77.69 300	98.97 171	93.06 180	98.50 113	98.72 140

test0.0.03 1		94.08 232	93.51 232	95.80 240	95.53 294	92.89 244	97.38 257	95.97 314	95.11 107	92.51 253	96.66 255	87.71 196	96.94 297	87.03 291	93.67 213	97.57 185

v1240		94.06 234	93.29 238	96.34 220	96.03 276	93.90 221	98.44 157	98.17 190	91.18 254	94.13 206	97.01 230	86.05 226	98.42 236	89.13 266	89.50 260	96.70 237

X-MVStestdata		94.06 234	92.30 252	99.34 13	99.70 15	98.35 23	99.29 14	98.88 47	97.40 14	98.46 46	43.50 341	95.90 30	99.89 27	97.85 34	99.74 33	99.78 7

DTE-MVSNet		93.98 236	93.26 239	96.14 228	96.06 274	94.39 208	99.20 31	98.86 52	93.06 187	91.78 264	97.81 170	85.87 229	97.58 287	90.53 240	86.17 301	96.46 271

pm-mvs1		93.94 237	93.06 240	96.59 195	96.49 239	95.16 152	98.95 62	98.03 219	92.32 220	91.08 270	97.84 165	84.54 253	98.41 243	92.16 205	86.13 303	96.19 279

tpmp4_e23		93.91 238	93.42 237	95.38 259	97.62 171	88.59 299	97.52 250	97.34 265	87.94 296	94.17 204	96.79 251	82.91 272	99.05 162	90.62 239	95.91 187	98.50 153

MS-PatchMatch		93.84 239	93.63 223	94.46 285	96.18 267	89.45 285	97.76 234	98.27 168	92.23 223	92.13 262	97.49 191	79.50 292	98.69 199	89.75 254	99.38 80	95.25 296

v748		93.75 240	93.06 240	95.82 239	95.73 287	92.64 246	99.25 19	98.24 175	91.60 235	92.22 260	96.52 262	87.60 201	98.46 228	90.64 238	85.72 304	96.36 274

tfpnnormal		93.66 241	92.70 247	96.55 203	96.94 215	95.94 120	98.97 60	99.19 15	91.04 255	91.38 267	97.34 201	84.94 243	98.61 205	85.45 302	89.02 267	95.11 298

EU-MVSNet		93.66 241	94.14 191	92.25 302	95.96 278	83.38 317	98.52 147	98.12 198	94.69 121	92.61 248	98.13 143	87.36 206	96.39 315	91.82 216	90.00 253	96.98 203

pmmvs5		93.65 243	92.97 242	95.68 244	95.49 295	92.37 248	98.20 183	97.28 271	89.66 281	92.58 249	97.26 206	82.14 275	98.09 267	93.18 178	90.95 248	96.58 257

tpm cat1		93.36 244	92.80 244	95.07 268	97.58 175	87.97 305	96.76 290	97.86 224	82.17 321	93.53 224	96.04 278	86.13 223	99.13 150	89.24 264	95.87 188	98.10 171

JIA-IIPM		93.35 245	92.49 249	95.92 234	96.48 240	90.65 273	95.01 315	96.96 289	85.93 307	96.08 149	87.33 328	87.70 198	98.78 197	91.35 227	95.58 191	98.34 165

SixPastTwentyTwo		93.34 246	92.86 243	94.75 277	95.67 289	89.41 287	98.75 106	96.67 304	93.89 150	90.15 279	98.25 136	80.87 283	98.27 259	90.90 234	90.64 249	96.57 259

USDC		93.33 247	92.71 246	95.21 263	96.83 223	90.83 268	96.91 281	97.50 247	93.84 153	90.72 274	98.14 142	77.69 300	98.82 193	89.51 260	93.21 227	95.97 284

IB-MVS	91.98 17	93.27 248	91.97 255	97.19 150	97.47 182	93.41 235	97.09 275	95.99 313	93.32 180	92.47 254	95.73 284	78.06 298	99.53 122	94.59 142	82.98 309	98.62 149
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
MIMVSNet		93.26 249	92.21 253	96.41 214	97.73 167	93.13 241	95.65 311	97.03 282	91.27 251	94.04 210	96.06 277	75.33 310	97.19 294	86.56 293	96.23 181	98.92 132

Patchmtry		93.22 250	92.35 251	95.84 238	96.77 224	93.09 242	94.66 322	97.56 235	87.37 299	92.90 242	96.24 269	88.15 182	97.90 277	87.37 289	90.10 252	96.53 264

FMVSNet1		93.19 251	92.07 254	96.56 200	97.54 178	95.00 158	98.82 85	98.18 185	90.38 262	92.27 258	97.07 218	73.68 318	97.95 274	89.36 263	91.30 245	96.72 233

LF4IMVS		93.14 252	92.79 245	94.20 288	95.88 282	88.67 297	97.66 242	97.07 279	93.81 155	91.71 265	97.65 182	77.96 299	98.81 194	91.47 226	91.92 239	95.12 297

testgi		93.06 253	92.45 250	94.88 272	96.43 242	89.90 279	98.75 106	97.54 240	95.60 79	91.63 266	97.91 158	74.46 316	97.02 296	86.10 296	93.67 213	97.72 182

PatchT		93.06 253	91.97 255	96.35 218	96.69 230	92.67 245	94.48 323	97.08 278	86.62 301	97.08 103	92.23 323	87.94 188	97.90 277	78.89 317	96.69 156	98.49 154

TransMVSNet (Re)		92.67 255	91.51 259	96.15 227	96.58 234	94.65 194	98.90 66	96.73 300	90.86 257	89.46 284	97.86 162	85.62 232	98.09 267	86.45 294	81.12 314	95.71 290

K. test v3		92.55 256	91.91 257	94.48 283	95.64 290	89.24 288	99.07 49	94.88 325	94.04 142	86.78 296	97.59 187	77.64 303	97.64 285	92.08 207	89.43 261	96.57 259

DSMNet-mixed		92.52 257	92.58 248	92.33 301	94.15 310	82.65 320	98.30 175	94.26 331	89.08 290	92.65 247	95.73 284	85.01 242	95.76 318	86.24 295	97.76 141	98.59 150

RPMNet		92.52 257	91.17 260	96.59 195	97.00 211	93.43 233	94.96 316	97.26 273	82.27 320	96.93 112	92.12 324	86.98 211	97.88 281	76.32 322	96.65 158	98.46 155

TinyColmap		92.31 259	91.53 258	94.65 279	96.92 216	89.75 281	96.92 279	96.68 303	90.45 260	89.62 282	97.85 164	76.06 308	98.81 194	86.74 292	92.51 232	95.41 295

gg-mvs-nofinetune		92.21 260	90.58 274	97.13 154	96.75 227	95.09 155	95.85 308	89.40 341	85.43 310	94.50 176	81.98 332	80.80 285	98.40 249	92.16 205	98.33 121	97.88 176

Test4		92.21 260	90.34 276	97.82 115	92.83 316	95.87 130	97.94 214	98.05 218	94.50 131	82.12 319	94.48 297	59.54 334	98.54 212	95.39 123	98.22 124	99.06 121

v18		92.10 262	90.97 262	95.50 248	96.34 251	94.85 170	98.82 85	97.52 241	89.99 269	85.31 307	93.26 305	88.90 153	96.92 298	88.82 272	79.77 318	94.73 304

v17		92.08 263	90.94 263	95.48 250	96.34 251	94.83 181	98.81 91	97.52 241	89.95 271	85.32 305	93.24 306	88.91 152	96.91 299	88.76 273	79.63 319	94.71 306

v16		92.08 263	90.94 263	95.49 249	96.38 247	94.84 179	98.81 91	97.51 244	89.94 272	85.25 308	93.28 304	88.86 154	96.91 299	88.70 274	79.78 317	94.72 305

v15		91.94 265	90.77 267	95.43 255	96.31 259	94.83 181	98.77 102	97.50 247	89.92 273	85.13 309	93.08 309	88.76 165	96.86 301	88.40 277	79.10 321	94.61 310

V14		91.93 266	90.76 268	95.42 258	96.33 255	94.81 185	98.77 102	97.51 244	89.86 275	85.09 310	93.13 307	88.80 163	96.83 303	88.32 278	79.06 323	94.60 311

V9		91.91 267	90.73 269	95.45 252	96.32 258	94.80 186	98.77 102	97.50 247	89.81 276	85.03 312	93.08 309	88.76 165	96.86 301	88.24 279	79.03 324	94.69 307

v12		91.89 268	90.70 270	95.43 255	96.31 259	94.80 186	98.76 105	97.50 247	89.76 277	84.95 313	93.00 312	88.82 159	96.82 305	88.23 280	79.00 325	94.68 309

v13		91.88 269	90.69 271	95.43 255	96.33 255	94.78 191	98.75 106	97.50 247	89.68 280	84.93 314	92.98 313	88.84 157	96.83 303	88.14 281	79.09 322	94.69 307

v11		91.85 270	90.68 272	95.36 260	96.34 251	94.74 193	98.80 94	97.43 258	89.60 283	85.09 310	93.03 311	88.53 174	96.75 306	87.37 289	79.96 316	94.58 312

FMVSNet5		91.81 271	90.92 265	94.49 282	97.21 200	92.09 251	98.00 209	97.55 239	89.31 288	90.86 273	95.61 289	74.48 315	95.32 320	85.57 300	89.70 255	96.07 282

pmmvs6		91.77 272	90.63 273	95.17 265	94.69 308	91.24 265	98.67 127	97.92 222	86.14 304	89.62 282	97.56 190	75.79 309	98.34 250	90.75 236	84.56 308	95.94 285

Anonymous20231206		91.66 273	91.10 261	93.33 295	94.02 312	87.35 309	98.58 137	97.26 273	90.48 258	90.16 278	96.31 267	83.83 269	96.53 313	79.36 315	89.90 254	96.12 280

Patchmatch-RL test		91.49 274	90.85 266	93.41 294	91.37 320	84.40 314	92.81 328	95.93 316	91.87 230	87.25 294	94.87 294	88.99 146	96.53 313	92.54 200	82.00 311	99.30 95

test_0402		91.32 275	90.27 277	94.48 283	96.60 233	91.12 266	98.50 152	97.22 275	86.10 305	88.30 291	96.98 232	77.65 302	97.99 273	78.13 319	92.94 229	94.34 314

PVSNet_0	88.72 19	91.28 276	90.03 279	95.00 269	97.99 153	87.29 310	94.84 319	98.50 137	92.06 225	89.86 280	95.19 290	79.81 291	99.39 133	92.27 204	69.79 333	98.33 166

EG-PatchMatch MVS		91.13 277	90.12 278	94.17 290	94.73 307	89.00 293	98.13 195	97.81 225	89.22 289	85.32 305	96.46 263	67.71 327	98.42 236	87.89 287	93.82 212	95.08 299

LP		91.12 278	89.99 280	94.53 281	96.35 250	88.70 296	93.86 327	97.35 264	84.88 312	90.98 271	94.77 295	84.40 255	97.43 290	75.41 325	91.89 240	97.47 186

TDRefinement		91.06 279	89.68 282	95.21 263	85.35 332	91.49 261	98.51 151	97.07 279	91.47 237	88.83 289	97.84 165	77.31 304	99.09 159	92.79 192	77.98 326	95.04 300

UnsupCasMVSNet_eth		90.99 280	89.92 281	94.19 289	94.08 311	89.83 280	97.13 274	98.67 104	93.69 165	85.83 302	96.19 274	75.15 311	96.74 307	89.14 265	79.41 320	96.00 283

test20.03		90.89 281	90.38 275	92.43 300	93.48 313	88.14 304	98.33 168	97.56 235	93.40 177	87.96 292	96.71 254	80.69 286	94.13 324	79.15 316	86.17 301	95.01 302

MDA-MVSNet_test_wron		90.71 282	89.38 285	94.68 278	94.83 305	90.78 270	97.19 271	97.46 254	87.60 297	72.41 331	95.72 286	86.51 217	96.71 310	85.92 298	86.80 298	96.56 261

YYNet1		90.70 283	89.39 284	94.62 280	94.79 306	90.65 273	97.20 270	97.46 254	87.54 298	72.54 330	95.74 283	86.51 217	96.66 311	86.00 297	86.76 299	96.54 263

testing_2		90.61 284	88.50 291	96.95 165	90.08 324	95.57 137	97.69 239	98.06 215	93.02 189	76.55 326	92.48 321	61.18 333	98.44 233	95.45 122	91.98 237	96.84 221

pmmvs-eth3d		90.36 285	89.05 288	94.32 287	91.10 321	92.12 250	97.63 245	96.95 290	88.86 291	84.91 315	93.13 307	78.32 297	96.74 307	88.70 274	81.81 313	94.09 318

new_pmnet		90.06 286	89.00 289	93.22 298	94.18 309	88.32 303	96.42 301	96.89 296	86.19 303	85.67 304	93.62 302	77.18 305	97.10 295	81.61 310	89.29 263	94.23 315

MDA-MVSNet-bldmvs		89.97 287	88.35 293	94.83 275	95.21 300	91.34 262	97.64 243	97.51 244	88.36 294	71.17 332	96.13 276	79.22 294	96.63 312	83.65 305	86.27 300	96.52 265

CMPMVS	66.06 21	89.70 288	89.67 283	89.78 307	93.19 314	76.56 327	97.00 276	98.35 159	80.97 323	81.57 321	97.75 173	74.75 314	98.61 205	89.85 251	93.63 215	94.17 316
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MIMVSNet1		89.67 289	88.28 294	93.82 291	92.81 317	91.08 267	98.01 207	97.45 256	87.95 295	87.90 293	95.87 282	67.63 328	94.56 323	78.73 318	88.18 280	95.83 287

MVS-HIRNet		89.46 290	88.40 292	92.64 299	97.58 175	82.15 321	94.16 326	93.05 337	75.73 329	90.90 272	82.52 331	79.42 293	98.33 251	83.53 306	98.68 103	97.43 187

OpenMVS_ROB	86.42 20	89.00 291	87.43 297	93.69 292	93.08 315	89.42 286	97.91 218	96.89 296	78.58 326	85.86 301	94.69 296	69.48 324	98.29 258	77.13 320	93.29 225	93.36 323

testus		88.91 292	89.08 287	88.40 310	91.39 319	76.05 328	96.56 296	96.48 308	89.38 287	89.39 285	95.17 292	70.94 322	93.56 327	77.04 321	95.41 192	95.61 292

testpf		88.74 293	89.09 286	87.69 311	95.78 285	83.16 319	84.05 338	94.13 334	85.22 311	90.30 277	94.39 299	74.92 313	95.80 317	89.77 252	93.28 226	84.10 333

test2356		88.68 294	88.61 290	88.87 309	89.90 325	78.23 325	95.11 314	96.66 306	88.66 293	89.06 287	94.33 301	73.14 320	92.56 331	75.56 324	95.11 194	95.81 288

new-patchmatchnet		88.50 295	87.45 296	91.67 304	90.31 323	85.89 313	97.16 273	97.33 268	89.47 284	83.63 317	92.77 317	76.38 306	95.06 322	82.70 307	77.29 327	94.06 319

PM-MVS		87.77 296	86.55 298	91.40 305	91.03 322	83.36 318	96.92 279	95.18 323	91.28 250	86.48 299	93.42 303	53.27 335	96.74 307	89.43 262	81.97 312	94.11 317

UnsupCasMVSNet_bld		87.17 297	85.12 300	93.31 296	91.94 318	88.77 294	94.92 318	98.30 165	84.30 315	82.30 318	90.04 325	63.96 332	97.25 293	85.85 299	74.47 332	93.93 321

N_pmnet		87.12 298	87.77 295	85.17 318	95.46 296	61.92 341	97.37 259	70.66 349	85.83 308	88.73 290	96.04 278	85.33 239	97.76 283	80.02 312	90.48 250	95.84 286

pmmvs3		86.67 299	84.86 301	92.11 303	88.16 327	87.19 311	96.63 293	94.75 327	79.88 325	87.22 295	92.75 318	66.56 329	95.20 321	81.24 311	76.56 329	93.96 320

test1235678		86.26 300	85.81 299	87.62 312	86.97 330	75.00 332	96.55 298	96.32 311	86.08 306	81.32 322	92.98 313	73.10 321	92.05 332	71.64 328	87.32 290	95.81 288

1111		84.94 301	84.30 302	86.86 313	87.59 328	75.10 330	96.63 293	96.43 309	82.53 318	80.75 323	92.91 315	68.94 325	93.79 325	68.24 331	84.66 307	91.70 325

Anonymous20231211		83.69 302	81.50 304	90.26 306	89.23 326	80.10 324	97.97 211	97.06 281	72.79 331	82.05 320	92.57 319	50.28 336	96.32 316	76.15 323	75.38 330	94.37 313

test12356		83.47 303	83.37 303	83.78 319	84.43 333	70.09 337	95.12 313	95.60 319	82.98 316	78.89 325	92.43 322	64.99 330	91.41 334	70.36 329	85.55 306	89.82 327

testmv		78.74 304	77.35 305	82.89 321	78.16 341	69.30 338	95.87 307	94.65 328	81.11 322	70.98 333	87.11 329	46.31 337	90.42 335	65.28 334	76.72 328	88.95 328

LCM-MVSNet		78.70 305	76.24 309	86.08 315	77.26 342	71.99 335	94.34 324	96.72 301	61.62 335	76.53 327	89.33 326	33.91 345	92.78 330	81.85 309	74.60 331	93.46 322

Gipuma		78.40 306	76.75 307	83.38 320	95.54 293	80.43 323	79.42 339	97.40 261	64.67 333	73.46 329	80.82 334	45.65 339	93.14 329	66.32 333	87.43 288	76.56 338
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMMVS2		77.95 307	75.44 310	85.46 316	82.54 334	74.95 333	94.23 325	93.08 336	72.80 330	74.68 328	87.38 327	36.36 343	91.56 333	73.95 326	63.94 334	89.87 326

FPMVS		77.62 308	77.14 306	79.05 323	79.25 338	60.97 342	95.79 309	95.94 315	65.96 332	67.93 334	94.40 298	37.73 342	88.88 337	68.83 330	88.46 277	87.29 329

no-one		74.41 309	70.76 311	85.35 317	79.88 337	76.83 326	94.68 321	94.22 332	80.33 324	63.81 335	79.73 335	35.45 344	93.36 328	71.78 327	36.99 341	85.86 332

.test1245		73.05 310	76.31 308	63.27 331	87.59 328	75.10 330	96.63 293	96.43 309	82.53 318	80.75 323	92.91 315	68.94 325	93.79 325	68.24 331	12.72 344	20.91 342

ANet_high		69.08 311	65.37 313	80.22 322	65.99 345	71.96 336	90.91 332	90.09 340	82.62 317	49.93 341	78.39 336	29.36 346	81.75 340	62.49 337	38.52 340	86.95 331

tmp_tt		68.90 312	66.97 312	74.68 327	50.78 347	59.95 343	87.13 334	83.47 347	38.80 341	62.21 336	96.23 271	64.70 331	76.91 344	88.91 271	30.49 342	87.19 330

PNet_i23d		67.70 313	65.07 314	75.60 325	78.61 339	59.61 344	89.14 333	88.24 343	61.83 334	52.37 339	80.89 333	18.91 347	84.91 339	62.70 336	52.93 336	82.28 334

PMVS	61.03 23	65.95 314	63.57 316	73.09 328	57.90 346	51.22 347	85.05 337	93.93 335	54.45 337	44.32 342	83.57 330	13.22 348	89.15 336	58.68 338	81.00 315	78.91 337
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
E-PMN		64.94 315	64.25 315	67.02 329	82.28 335	59.36 345	91.83 331	85.63 345	52.69 338	60.22 337	77.28 337	41.06 341	80.12 342	46.15 340	41.14 338	61.57 340

EMVS		64.07 316	63.26 317	66.53 330	81.73 336	58.81 346	91.85 330	84.75 346	51.93 340	59.09 338	75.13 338	43.32 340	79.09 343	42.03 341	39.47 339	61.69 339

wuykxyi23d		63.73 317	58.86 319	78.35 324	67.62 344	67.90 339	86.56 335	87.81 344	58.26 336	42.49 343	70.28 340	11.55 350	85.05 338	63.66 335	41.50 337	82.11 335

MVE	62.14 22	63.28 318	59.38 318	74.99 326	74.33 343	65.47 340	85.55 336	80.50 348	52.02 339	51.10 340	75.00 339	10.91 352	80.50 341	51.60 339	53.40 335	78.99 336
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
pcd1.5k->3k		39.42 319	41.78 320	32.35 332	96.17 268	0.00 351	0.00 341	98.54 125	0.00 345	0.00 347	0.00 347	87.78 195	0.00 348	0.00 345	93.56 217	97.06 198

wuyk23d		30.17 320	30.18 322	30.16 333	78.61 339	43.29 348	66.79 340	14.21 350	17.31 342	14.82 346	11.93 346	11.55 350	41.43 345	37.08 342	19.30 343	5.76 344

cdsmvs_eth3d_5k		23.98 321	31.98 321	0.00 336	0.00 350	0.00 351	0.00 341	98.59 115	0.00 345	0.00 347	98.61 100	90.60 124	0.00 348	0.00 345	0.00 347	0.00 345

testmvs		21.48 322	24.95 323	11.09 335	14.89 348	6.47 350	96.56 296	9.87 351	7.55 343	17.93 344	39.02 342	9.43 353	5.90 347	16.56 344	12.72 344	20.91 342

test123		20.95 323	23.72 324	12.64 334	13.54 349	8.19 349	96.55 298	6.13 352	7.48 344	16.74 345	37.98 343	12.97 349	6.05 346	16.69 343	5.43 346	23.68 341

ab-mvs-re		8.20 324	10.94 325	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	98.43 115	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

pcd_1.5k_mvsjas		7.88 325	10.50 326	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	94.51 61	0.00 348	0.00 345	0.00 347	0.00 345

sosnet-low-res		0.00 326	0.00 327	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

sosnet		0.00 326	0.00 327	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

uncertanet		0.00 326	0.00 327	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

Regformer		0.00 326	0.00 327	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

uanet		0.00 326	0.00 327	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

test_part2					99.63 21	99.18 1				99.27 6

test_part1								98.84 54				97.38 2			99.78 14	99.76 20

test11111								98.84 54

sam_mvs1												89.45 135

sam_mvs												88.99 146

semantic-postprocess				94.85 273	97.98 155	90.56 275		98.11 203	93.75 157	92.58 249	97.48 192	83.91 266	97.41 291	92.48 202	91.30 245	96.58 257

ambc				89.49 308	86.66 331	75.78 329	92.66 329	96.72 301		86.55 298	92.50 320	46.01 338	97.90 277	90.32 242	82.09 310	94.80 303

MTGPA								98.74 79

test_post1							96.68 292				30.43 345	87.85 193	98.69 199	92.59 197

test_post											31.83 344	88.83 158	98.91 181

patchmatchnet-post											95.10 293	89.42 136	98.89 185

GG-mvs-BLEND				96.59 195	96.34 251	94.98 161	96.51 300	88.58 342		93.10 239	94.34 300	80.34 290	98.05 269	89.53 259	96.99 152	96.74 230

MTMP								94.14 333

gm-plane-assit					95.88 282	87.47 308			89.74 279		96.94 237		99.19 145	93.32 174

test9_res														96.39 94	99.57 56	99.69 36

TEST9					99.31 48	98.50 13	97.92 215	98.73 84	92.63 200	97.74 82	98.68 94	96.20 13	99.80 57

test_8					99.29 56	98.44 15	97.89 223	98.72 86	92.98 191	97.70 85	98.66 97	96.20 13	99.80 57

agg_prior2														95.87 106	99.57 56	99.68 42

agg_prior					99.30 53	98.38 18		98.72 86		97.57 94			99.81 50

TestCases				96.99 161	99.25 65	93.21 239		98.18 185	91.36 243	93.52 225	98.77 87	84.67 246	99.72 86	89.70 256	97.87 135	98.02 173

test_prior4						98.01 42	97.86 226

test_prior2							97.80 231		96.12 63	97.89 76	98.69 92	95.96 26		96.89 71	99.60 50

test_prior				99.19 28	99.31 48	98.22 31		98.84 54					99.70 91			99.65 51

旧先验2							97.57 248		91.30 248	98.67 37			99.80 57	95.70 115

新几何2							97.64 243

新几何1				99.16 35	99.34 40	98.01 42		98.69 94	90.06 268	98.13 57	98.95 71	94.60 59	99.89 27	91.97 213	99.47 70	99.59 62

旧先验1					99.29 56	97.48 60		98.70 93			99.09 52	95.56 36			99.47 70	99.61 57

无先验							97.58 247	98.72 86	91.38 242				99.87 35	93.36 172		99.60 60

原ACMM2							97.67 241

原ACMM1				98.65 65	99.32 46	96.62 90		98.67 104	93.27 183	97.81 78	98.97 65	95.18 48	99.83 43	93.84 161	99.46 73	99.50 72

test222					99.23 71	97.17 73	97.40 255	98.66 107	88.68 292	98.05 61	98.96 69	94.14 70			99.53 66	99.61 57

testdata2													99.89 27	91.65 221

segment_acmp												96.85 4

testdata				98.26 89	99.20 75	95.36 145		98.68 97	91.89 228	98.60 42	99.10 48	94.44 66	99.82 48	94.27 151	99.44 75	99.58 64

testdata1							97.32 265		96.34 57

test12				99.18 32	99.16 77	98.19 33		98.53 128		98.07 60		95.13 50	99.72 86		99.56 62	99.63 56

plane_prior7					97.42 187	94.63 196

plane_prior6					97.35 192	94.61 199						87.09 208

plane_prior5								98.56 122					99.03 167	96.07 97	94.27 197	96.92 207

plane_prior4											98.28 131

plane_prior3						94.61 199			97.02 39	95.34 157

plane_prior2							98.80 94		97.28 21

plane_prior1					97.37 191

plane_prior						94.60 201	98.44 157		96.74 46						94.22 199

n2								0.00 353

nn								0.00 353

door-mid								94.37 330

lessismore_v0				94.45 286	94.93 304	88.44 301		91.03 339		86.77 297	97.64 184	76.23 307	98.42 236	90.31 243	85.64 305	96.51 267

LGP-MVS_train				96.47 209	97.46 183	93.54 230		98.54 125	94.67 123	94.36 188	98.77 87	85.39 235	99.11 155	95.71 113	94.15 203	96.76 228

test11								98.66 107

door								94.64 329

HQP5-MVS						94.25 214

HQP-NCC					97.20 201		98.05 203		96.43 54	94.45 178

ACMP_Plane					97.20 201		98.05 203		96.43 54	94.45 178

BP-MVS														95.30 125

HQP4-MVS										94.45 178			98.96 174			96.87 218

HQP3-MVS								98.46 142							94.18 201

HQP2-MVS												86.75 214

NP-MVS					97.28 195	94.51 204					97.73 174

MDTV_nov1_ep13_2view						84.26 315	96.89 285		90.97 256	97.90 75		89.89 133		93.91 159		99.18 109

MDTV_nov1_ep13			95.40 129		97.48 181	88.34 302	96.85 287	97.29 270	93.74 159	97.48 97	97.26 206	89.18 142	99.05 162	91.92 215	97.43 147

ACMMP++_ref															92.97 228

ACMMP++															93.61 216

Test By Simon												94.64 58

ITE_SJBPF				95.44 253	97.42 187	91.32 263		97.50 247	95.09 110	93.59 221	98.35 123	81.70 278	98.88 186	89.71 255	93.39 222	96.12 280

DeepMVS_CX				86.78 314	97.09 209	72.30 334		95.17 324	75.92 328	84.34 316	95.19 290	70.58 323	95.35 319	79.98 314	89.04 266	92.68 324

High-resolution multi-view benchmark