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	courty.	delive.	electro	facade	kicker	meadow	office	pipes	playgr.	relief	relief.	terrace	terrai.

SMA-MVS		98.47 5	99.06 6	97.77 8	99.48 1	99.78 9	99.37 7	96.14 5	99.29 10	93.03 16	97.59 25	99.97 2	99.03 6	98.94 7	98.30 8	99.60 28	99.58 61

CNVR-MVS		98.73 1	99.17 4	98.22 1	99.47 2	99.85 2	99.57 2	96.23 1	99.30 9	94.90 5	98.65 10	98.93 14	99.36 1	99.46 3	98.21 10	99.81 6	99.80 36

HPM-MVS++		98.16 10	98.87 11	97.32 14	99.39 3	99.70 16	99.18 16	96.10 8	99.09 16	91.14 23	98.02 20	99.89 3	98.44 19	98.75 12	97.03 43	99.67 18	99.63 54

APDe-MVS		98.60 4	98.97 8	98.18 2	99.38 4	99.78 9	99.35 10	96.14 5	99.24 12	95.66 3	98.19 17	99.01 12	98.66 13	98.77 11	97.80 23	99.86 2	99.97 5

ESAPD		98.61 3	99.15 5	97.97 5	99.36 5	99.80 5	99.56 3	96.18 2	99.26 11	93.88 12	98.64 11	99.98 1	99.04 5	98.89 9	97.49 30	99.79 9	99.98 3

NCCC		98.41 6	99.18 2	97.52 12	99.36 5	99.84 3	99.55 4	96.08 11	99.33 8	91.77 21	98.79 6	99.46 7	98.59 15	99.15 6	98.07 19	99.73 12	99.64 50

ACMMP_Plus		97.51 20	98.27 22	96.63 23	99.34 7	99.72 13	99.25 14	95.94 12	98.11 39	87.10 43	96.98 27	98.50 19	98.61 14	98.58 14	96.83 48	99.56 45	99.14 95

PGM-MVS		97.03 26	98.14 27	95.73 27	99.34 7	99.61 26	99.34 11	89.99 40	97.70 49	87.67 39	99.44 2	96.45 39	98.44 19	97.65 36	97.09 40	99.58 35	99.06 103

APD-MVS		98.28 8	98.69 12	97.80 6	99.31 9	99.62 24	99.31 13	96.15 4	99.19 14	93.60 13	97.28 26	98.35 21	98.72 12	98.27 17	98.22 9	99.73 12	99.89 23
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MSLP-MVS++		98.12 11	98.23 24	97.99 4	99.28 10	99.72 13	99.59 1	95.27 23	98.61 26	94.79 6	96.11 30	97.79 30	99.27 2	96.62 54	98.96 4	99.77 10	99.80 36

MCST-MVS		98.20 9	99.18 2	97.06 18	99.27 11	99.87 1	99.37 7	96.11 7	99.37 5	89.29 29	98.76 8	99.50 6	98.37 21	99.23 5	97.64 26	99.95 1	99.87 29

HSP-MVS		98.70 2	99.28 1	98.03 3	99.21 12	99.82 4	99.17 17	96.09 9	99.54 2	94.79 6	98.79 6	99.55 5	99.05 4	99.54 1	98.19 13	99.84 3	99.52 66

zzz-MVS		97.93 14	98.05 28	97.80 6	99.20 13	99.64 20	99.40 6	95.76 14	98.01 45	94.31 10	96.54 29	98.49 20	98.58 16	98.22 20	96.23 54	99.54 53	99.23 87

AdaColmap		97.54 19	97.35 34	97.77 8	99.17 14	99.55 30	98.57 26	95.76 14	99.04 18	94.66 8	97.94 21	94.39 49	98.82 9	96.21 60	94.78 74	99.62 25	99.52 66

CSCG		95.77 37	95.35 48	96.26 25	99.13 15	99.60 27	98.14 32	91.89 37	96.57 65	92.61 17	89.65 61	91.74 64	96.96 35	93.69 119	96.58 52	98.86 129	99.63 54

HFP-MVS		98.02 12	98.55 16	97.40 13	99.11 16	99.69 17	99.41 5	95.41 21	98.79 24	91.86 20	98.61 12	98.16 23	99.02 7	97.87 28	97.40 32	99.60 28	99.35 79

X-MVS		97.20 24	98.42 19	95.77 26	99.04 17	99.64 20	98.95 25	95.10 28	98.16 37	83.97 61	98.27 16	98.08 26	97.95 24	97.89 25	97.46 31	99.58 35	99.47 72

ACMMPR		97.78 17	98.28 21	97.20 17	99.03 18	99.68 18	99.37 7	95.24 24	98.86 23	91.16 22	97.86 23	97.26 33	98.79 10	97.64 38	97.40 32	99.60 28	99.25 86

CP-MVS		97.81 16	98.26 23	97.28 15	99.00 19	99.65 19	99.10 20	95.32 22	98.38 34	92.21 19	98.33 15	97.74 31	98.50 18	97.66 35	96.55 53	99.57 40	99.48 71

DeepC-MVS_fast	95.01 1	97.67 18	98.22 25	97.02 19	99.00 19	99.79 6	99.10 20	95.82 13	99.05 17	89.53 28	93.54 44	96.77 36	98.83 8	99.34 4	99.44 1	99.82 4	99.63 54
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MP-MVS		97.46 21	98.30 20	96.48 24	98.93 21	99.43 40	99.20 15	95.42 20	98.43 30	87.60 40	98.19 17	98.01 29	98.09 23	98.05 23	96.67 51	99.64 21	99.35 79
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
SteuartSystems-ACMMP		97.86 15	98.91 9	96.64 22	98.89 22	99.79 6	99.34 11	95.20 25	98.48 28	89.91 27	98.58 13	98.69 16	96.84 41	98.92 8	98.16 15	99.66 19	99.74 39
Skip Steuart: Steuart Systems R&D Blog.
PLC	94.37 2	97.03 26	96.54 37	97.60 10	98.84 23	98.64 70	98.17 31	94.99 29	99.01 19	96.80 1	93.21 48	95.64 41	97.36 30	96.37 57	94.79 73	99.41 81	98.12 140
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
mPP-MVS					98.66 24							97.11 34

3Dnovator	90.31 8	95.67 40	96.16 41	95.11 34	98.59 25	99.37 48	97.50 40	87.98 53	98.02 44	89.09 30	85.36 92	94.62 46	97.66 25	97.10 47	98.90 5	99.82 4	99.73 41

QAPM		95.17 42	96.05 42	94.14 41	98.55 26	99.49 33	97.41 42	87.88 54	97.72 48	84.21 59	84.59 96	95.60 42	97.21 33	97.10 47	98.19 13	99.57 40	99.65 48

CNLPA		96.14 31	95.43 46	96.98 21	98.55 26	99.41 44	95.91 53	95.15 27	99.00 20	95.71 2	84.21 102	94.55 47	97.25 32	95.50 89	96.23 54	99.28 98	99.09 102

OMC-MVS		95.75 38	95.84 43	95.64 29	98.52 28	99.34 49	97.15 46	92.02 36	98.94 22	90.45 25	88.31 64	94.64 45	96.35 49	96.02 67	95.99 62	99.34 91	97.65 149

train_agg		97.42 22	98.88 10	95.71 28	98.46 29	99.60 27	99.05 22	95.16 26	99.10 15	84.38 55	98.47 14	98.85 15	97.61 27	98.54 15	97.66 25	99.62 25	99.93 15

OpenMVS	88.43 11	93.49 51	93.62 66	93.34 47	98.46 29	99.39 45	97.00 48	87.66 58	95.37 81	81.21 82	75.96 129	91.58 65	96.21 52	96.37 57	97.10 39	99.52 54	99.54 65

MAR-MVS		94.18 48	95.12 51	93.09 51	98.40 31	99.17 55	94.20 79	81.92 102	98.47 29	86.52 44	90.92 57	84.21 93	98.12 22	95.88 70	97.59 28	99.40 82	99.58 61
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
CPTT-MVS		97.32 23	97.60 33	96.99 20	98.29 32	99.31 51	99.04 23	94.67 30	97.99 46	93.12 14	98.03 19	98.26 22	98.77 11	96.08 64	94.26 82	98.07 188	99.27 85

CDPH-MVS		95.90 36	97.77 32	93.72 46	98.28 33	99.43 40	98.40 27	91.30 38	98.34 35	78.62 100	94.80 36	95.74 40	96.11 54	97.86 29	98.67 6	99.59 31	99.56 63

abl_6				95.40 31	98.18 34	99.45 38	97.39 43	89.27 44	99.48 3	90.52 24	94.52 41	98.63 17	97.32 31			99.73 12	99.82 34

3Dnovator+	90.72 7	95.99 34	96.42 39	95.50 30	98.18 34	99.33 50	97.44 41	87.73 56	97.93 47	92.36 18	84.67 95	97.33 32	97.55 28	97.32 41	98.47 7	99.72 16	99.88 24

TSAR-MVS + ACMM		96.90 28	98.64 14	94.88 35	98.12 36	99.47 35	99.01 24	95.43 19	99.23 13	81.98 78	95.95 31	99.16 11	95.13 67	98.61 13	98.11 17	99.58 35	99.93 15

ACMMP		96.05 33	96.70 36	95.29 32	98.01 37	99.43 40	97.60 38	94.33 32	97.62 53	86.17 46	98.92 4	92.81 57	96.10 55	95.67 78	93.33 102	99.55 50	99.12 98
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
PHI-MVS		97.09 25	98.69 12	95.22 33	97.99 38	99.59 29	97.56 39	92.16 34	98.41 32	87.11 42	98.70 9	99.42 8	96.95 37	96.88 51	98.16 15	99.56 45	99.70 44

MVS_111021_LR		96.07 32	97.94 29	93.88 43	97.86 39	99.43 40	95.70 56	89.65 43	98.73 25	84.86 53	99.38 3	94.08 51	95.78 64	97.81 31	96.73 50	99.43 79	99.42 74

TAPA-MVS	92.04 6	94.72 44	95.13 50	94.24 39	97.72 40	99.17 55	97.61 37	92.16 34	97.66 51	81.99 77	87.84 71	93.94 52	96.50 47	95.74 75	94.27 81	99.46 75	97.31 157
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
EPNet		96.23 30	97.89 30	94.29 38	97.62 41	99.44 39	97.14 47	88.63 47	98.16 37	88.14 35	99.46 1	94.15 50	94.61 76	97.20 44	97.23 36	99.57 40	99.59 59
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MVS_111021_HR		95.70 39	98.16 26	92.83 53	97.57 42	99.77 11	94.78 70	88.05 51	98.61 26	82.29 71	98.85 5	94.66 44	94.63 75	97.80 32	97.63 27	99.64 21	99.79 38

DeepPCF-MVS	94.02 3	95.92 35	98.47 17	92.95 52	97.57 42	99.79 6	91.45 115	94.42 31	99.76 1	86.48 45	92.88 50	98.12 25	92.62 93	99.49 2	99.32 2	95.15 218	99.95 9

MSDG		91.93 70	90.28 116	93.85 44	97.36 44	97.12 103	95.88 54	94.07 33	94.52 92	84.13 60	76.74 124	80.89 105	92.54 94	93.97 115	93.61 97	99.14 106	95.10 191

SD-MVS		98.33 7	99.01 7	97.54 11	97.17 45	99.77 11	99.14 19	96.09 9	99.34 7	94.06 11	97.91 22	99.89 3	99.18 3	97.99 24	98.21 10	99.63 23	99.95 9

TSAR-MVS + MP.		97.98 13	98.62 15	97.23 16	97.08 46	99.55 30	99.17 17	95.69 16	99.40 4	93.04 15	96.68 28	98.96 13	98.58 16	98.82 10	96.95 45	99.81 6	99.96 6

EPNet_dtu		89.82 98	94.18 60	84.74 124	96.87 47	95.54 129	92.65 98	86.91 61	96.99 61	54.17 204	92.41 51	88.54 73	78.35 194	96.15 62	96.05 60	99.47 64	93.60 199
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DeepC-MVS	92.23 5	94.53 45	94.26 59	94.86 36	96.73 48	99.50 32	97.85 34	95.45 18	96.22 73	82.73 68	80.68 112	88.02 75	96.92 38	97.49 40	98.20 12	99.47 64	99.69 46
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PatchMatch-RL		92.54 59	92.82 80	92.21 58	96.57 49	98.74 61	91.85 111	86.30 67	96.23 72	85.18 52	95.21 33	73.58 129	94.22 80	95.40 93	93.08 106	99.14 106	97.49 155

DELS-MVS		93.82 50	93.82 63	93.81 45	96.34 50	99.47 35	97.26 45	88.53 49	92.13 119	87.80 38	79.67 114	88.01 76	93.14 85	98.28 16	99.22 3	99.80 8	99.98 3
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
CANet		95.40 41	96.27 40	94.40 37	96.25 51	99.62 24	98.37 28	88.59 48	98.09 40	87.58 41	84.57 97	95.54 43	95.87 61	98.12 21	98.03 21	99.73 12	99.90 21

LS3D		92.70 56	92.23 87	93.26 48	96.24 52	98.72 62	97.93 33	96.17 3	96.41 66	72.46 115	81.39 110	80.76 106	97.66 25	95.69 77	95.62 65	99.07 113	97.02 166

PCF-MVS	92.56 4	93.95 49	93.82 63	94.10 42	96.07 53	99.25 53	96.82 49	95.51 17	92.00 121	81.51 81	82.97 107	93.88 54	95.63 66	94.24 107	94.71 76	99.09 111	99.70 44
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
COLMAP_ROB	84.42 15	88.24 119	87.32 140	89.32 93	95.83 54	95.82 122	92.81 94	87.68 57	92.09 120	72.64 114	72.34 142	79.96 110	88.79 122	89.54 156	89.46 153	98.16 185	92.00 205
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
PVSNet_BlendedMVS		93.30 52	93.46 71	93.10 49	95.60 55	99.38 46	93.59 86	88.70 45	98.09 40	88.10 36	86.96 77	75.02 125	93.08 86	97.89 25	96.90 46	99.56 45	100.00 1

PVSNet_Blended		93.30 52	93.46 71	93.10 49	95.60 55	99.38 46	93.59 86	88.70 45	98.09 40	88.10 36	86.96 77	75.02 125	93.08 86	97.89 25	96.90 46	99.56 45	100.00 1

CHOSEN 280x420		94.51 46	97.78 31	90.70 76	95.54 57	99.49 33	94.14 80	74.91 157	98.43 30	85.32 51	94.78 37	99.19 10	94.95 71	97.02 49	96.18 57	99.35 87	99.36 78

CHOSEN 1792x2688		88.63 113	89.01 127	88.19 101	94.83 58	99.21 54	92.66 97	79.85 120	92.40 117	72.18 116	56.38 206	80.22 108	90.24 113	97.64 38	97.28 35	99.37 83	99.94 12

MVS_0304		94.35 47	95.66 45	92.83 53	94.82 59	99.46 37	98.19 30	87.75 55	97.32 58	81.83 80	83.50 104	93.19 56	94.71 73	98.24 19	98.07 19	99.68 17	99.83 32

HyFIR lowres test		87.86 122	88.25 131	87.40 103	94.67 60	98.54 74	90.33 125	76.51 148	89.60 140	70.89 120	51.43 221	85.69 87	92.79 90	96.59 55	95.96 63	99.22 104	99.94 12

TSAR-MVS + COLMAP		92.56 58	92.44 84	92.71 55	94.61 61	97.69 92	97.69 36	91.09 39	98.96 21	76.71 104	94.68 38	69.41 152	96.91 39	95.80 73	94.18 83	99.26 100	96.33 180

OPM-MVS		89.33 105	87.45 139	91.53 68	94.49 62	96.20 117	96.47 50	89.72 42	82.77 168	75.43 106	80.53 113	70.86 146	93.80 82	94.00 113	91.85 133	99.29 97	95.91 184

HQP-MVS		91.94 69	93.03 76	90.66 78	93.69 63	96.48 114	95.92 52	89.73 41	97.33 57	72.65 113	95.37 32	73.56 130	92.75 92	94.85 102	94.12 84	99.23 103	99.51 68

XVS					93.63 64	99.64 20	94.32 77			83.97 61		98.08 26				99.59 31

X-MVStestdata					93.63 64	99.64 20	94.32 77			83.97 61		98.08 26				99.59 31

PVSNet_Blended_VisFu		91.20 82	92.89 78	89.23 94	93.41 66	98.61 72	89.80 127	85.39 83	92.84 113	82.80 67	74.21 134	91.38 67	84.64 146	97.22 43	96.04 61	99.34 91	99.93 15

LGP-MVS_train		90.34 94	91.63 92	88.83 98	93.31 67	96.14 118	95.49 59	85.24 86	93.91 97	68.71 129	93.96 43	71.63 135	91.12 107	93.82 117	92.79 120	99.07 113	99.16 94

ACMM	89.40 10	90.58 90	90.02 119	91.23 72	93.30 68	94.75 136	90.69 122	88.22 50	95.20 83	82.70 69	88.54 63	71.40 137	93.48 83	93.64 120	90.94 139	98.99 121	95.72 188
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CMPMVS	58.73 17	76.78 207	74.27 216	79.70 173	93.26 69	95.58 127	82.74 195	77.44 141	71.46 223	56.29 192	53.58 217	59.13 172	77.33 198	79.20 221	79.71 222	91.14 227	81.24 224
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
RPSCF		89.81 99	89.75 121	89.88 87	93.22 70	93.99 143	94.78 70	85.23 87	94.01 96	82.52 70	95.00 35	87.23 79	92.01 98	85.16 209	83.48 217	91.54 224	89.38 214

MS-PatchMatch		87.19 126	88.59 129	85.55 119	93.15 71	96.58 112	92.35 102	74.19 165	91.97 122	70.33 124	71.42 146	85.89 85	84.28 149	93.12 122	89.16 159	99.00 120	91.99 206

IB-MVS	84.67 14	88.34 116	90.61 112	85.70 117	92.99 72	98.62 71	78.85 206	86.07 74	94.35 94	88.64 34	85.99 88	75.69 122	68.09 216	88.21 164	91.43 136	99.55 50	99.96 6
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
UGNet		91.71 71	94.43 54	88.53 100	92.72 73	98.00 85	90.22 126	84.81 88	94.45 93	83.05 66	87.65 73	92.74 58	81.04 182	94.51 106	94.45 79	99.32 96	99.21 91
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
ACMP	89.80 9	90.72 89	91.15 103	90.21 82	92.55 74	96.52 113	92.63 99	85.71 78	94.65 90	81.06 83	93.32 45	70.56 148	90.52 111	92.68 130	91.05 138	98.76 138	99.31 83
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
UA-Net		89.56 101	93.03 76	85.52 120	92.46 75	97.55 96	91.92 110	81.91 103	85.24 157	71.39 117	83.57 103	96.56 38	76.01 203	96.81 52	97.04 42	99.46 75	94.41 194

CANet_DTU		91.36 77	95.75 44	86.23 113	92.31 76	98.71 63	95.60 58	78.41 133	98.20 36	56.48 191	94.38 42	87.96 77	95.11 68	96.89 50	96.07 58	99.48 60	98.01 144

TSAR-MVS + GP.		96.47 29	98.45 18	94.17 40	92.12 77	99.29 52	97.76 35	88.05 51	99.36 6	90.26 26	97.82 24	99.21 9	97.21 33	96.78 53	96.74 49	99.63 23	99.94 12

ACMH	85.22 13	85.40 136	85.73 146	85.02 122	91.76 78	94.46 141	84.97 184	81.54 109	85.18 158	65.22 137	76.92 123	64.22 160	88.58 126	90.17 145	90.25 149	98.03 189	98.90 107
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
conf0.002		92.80 55	93.55 70	91.93 60	91.66 79	98.85 58	95.03 64	86.42 64	93.24 105	82.20 74	92.98 49	79.35 115	96.80 42	95.83 71	94.67 78	99.48 60	99.91 19

conf0.01		92.41 63	92.86 79	91.90 61	91.65 80	98.84 59	95.03 64	86.38 66	93.24 105	82.03 76	91.90 56	77.54 118	96.80 42	95.78 74	92.82 114	99.48 60	99.90 21

tfpn111		91.99 68	92.28 86	91.65 64	91.61 81	98.69 64	95.03 64	86.17 68	93.24 105	80.82 84	94.67 39	71.15 138	96.80 42	95.53 82	92.82 114	99.47 64	99.88 24

conf200view11		91.47 75	91.31 97	91.65 64	91.61 81	98.69 64	95.03 64	86.17 68	93.24 105	80.82 84	87.90 67	71.15 138	96.80 42	95.53 82	92.82 114	99.47 64	99.88 24

thres100view900		91.69 72	91.52 94	91.88 62	91.61 81	98.89 57	95.49 59	86.96 60	93.24 105	80.82 84	87.90 67	71.15 138	96.88 40	96.00 68	93.51 99	99.51 55	99.95 9

tfpn200view9		91.47 75	91.31 97	91.65 64	91.61 81	98.69 64	95.03 64	86.17 68	93.24 105	80.82 84	87.90 67	71.15 138	96.80 42	95.53 82	92.82 114	99.47 64	99.88 24

thres200		91.36 77	91.19 102	91.55 67	91.60 85	98.69 64	94.98 69	86.17 68	92.16 118	80.76 88	87.66 72	71.15 138	96.35 49	95.53 82	93.23 105	99.47 64	99.92 18

thres400		91.24 81	91.01 107	91.50 69	91.56 86	98.77 60	94.66 74	86.41 65	91.87 123	80.56 89	87.05 76	71.01 143	96.35 49	95.67 78	92.82 114	99.48 60	99.88 24

view600		90.97 85	90.70 109	91.30 70	91.53 87	98.69 64	94.33 75	86.17 68	91.75 125	80.19 91	86.06 86	70.90 144	96.10 55	95.53 82	92.08 128	99.47 64	99.86 30

thres600view7		90.97 85	90.70 109	91.30 70	91.53 87	98.69 64	94.33 75	86.17 68	91.75 125	80.19 91	86.06 86	70.90 144	96.10 55	95.53 82	92.08 128	99.47 64	99.86 30

view800		90.79 87	90.54 113	91.09 74	91.50 89	98.58 73	94.09 81	85.92 75	91.57 128	79.68 94	85.29 93	70.72 147	95.91 59	95.40 93	92.39 124	99.47 64	99.83 32

tfpn		91.26 79	91.55 93	90.92 75	91.47 90	98.50 76	93.85 85	85.72 77	91.40 130	79.30 98	84.78 94	77.33 119	95.70 65	95.29 95	93.73 89	99.47 64	99.82 34

tfpn_ndepth		92.26 65	93.84 62	90.42 79	91.45 91	97.91 88	92.73 96	85.80 76	96.69 64	82.22 72	91.92 55	83.42 95	90.76 110	95.51 88	93.28 103	99.58 35	98.14 136

canonicalmvs		92.54 59	93.28 73	91.68 63	91.44 92	98.24 80	95.45 61	81.84 106	95.98 77	84.85 54	90.69 59	78.53 116	96.96 35	92.97 126	97.06 41	99.57 40	99.47 72

PMMVS		93.05 54	95.40 47	90.31 81	91.41 93	97.54 97	92.62 100	83.25 96	98.08 43	79.44 97	95.18 34	88.52 74	96.43 48	95.70 76	93.88 87	98.68 157	98.91 106

tfpn1000		91.48 74	93.17 75	89.51 91	91.27 94	97.71 91	92.08 105	85.28 85	96.13 74	80.20 90	90.77 58	82.52 98	88.64 125	95.17 98	92.35 125	99.56 45	97.52 154

DWT-MVSNet_training		92.09 67	93.58 69	90.35 80	91.27 94	97.94 87	92.05 106	78.82 129	97.40 56	88.83 33	87.91 66	86.76 84	91.99 99	90.03 147	95.25 70	99.13 108	99.73 41

CLD-MVS		91.67 73	91.30 100	92.10 59	91.25 96	96.59 111	95.93 51	87.25 59	96.86 63	85.55 50	87.08 74	73.01 132	93.26 84	93.07 124	92.84 111	99.34 91	99.68 47
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
IS_MVSNet		92.67 57	94.99 52	89.96 86	91.17 97	98.54 74	92.77 95	84.00 90	92.72 115	81.90 79	85.67 90	92.47 59	90.39 112	97.82 30	97.81 22	99.51 55	99.91 19

thresconf0.02		92.16 66	95.16 49	88.67 99	91.10 98	97.63 94	92.93 93	86.58 63	96.29 70	73.55 111	94.67 39	88.63 72	88.29 129	96.14 63	95.40 69	99.58 35	97.33 156

EPMVS		89.31 106	93.70 65	84.18 129	91.10 98	98.10 82	89.17 136	62.71 211	96.24 71	70.21 126	86.46 82	92.37 61	92.79 90	91.95 136	93.59 98	99.10 110	97.19 158

Vis-MVSNet (Re-imp)		91.05 84	94.43 54	87.11 106	91.05 100	97.99 86	92.53 101	83.82 92	92.71 116	76.28 105	84.50 98	92.43 60	79.52 188	97.24 42	97.68 24	99.43 79	98.45 120

TDRefinement		81.49 157	80.08 180	83.13 139	91.02 101	94.53 139	91.66 113	82.43 99	81.70 176	62.12 149	62.30 165	59.32 171	73.93 210	87.31 174	85.29 209	97.61 200	90.14 211

conf0.05thres1000		88.28 117	87.54 137	89.15 96	91.00 102	97.50 99	92.18 104	84.70 89	85.15 159	73.91 110	73.77 136	70.50 151	94.01 81	93.99 114	92.21 126	99.11 109	99.64 50

tfpnview11		90.36 93	92.74 81	87.59 102	90.93 103	97.30 102	92.28 103	85.63 79	95.88 78	70.44 121	92.30 52	79.50 112	86.76 139	95.26 97	92.83 113	99.51 55	96.09 181

Anonymous20240521		90.11 97	88.25 131	92.28 57	90.91 104	98.16 81	94.78 70	86.87 62	90.82 133	84.37 56	67.60 155	73.12 131	97.40 29	93.33 121	95.42 68	99.37 83	99.30 84

MVSTER		94.75 43	96.50 38	92.70 56	90.91 104	94.51 140	97.37 44	83.37 94	98.40 33	89.04 31	93.23 47	97.04 35	95.91 59	97.73 33	95.59 66	99.61 27	99.01 104

tfpn_n400		90.13 95	92.47 82	87.40 103	90.89 106	97.37 100	92.05 106	85.47 80	93.43 102	70.44 121	92.30 52	79.50 112	86.50 140	94.84 103	93.93 85	99.07 113	95.91 184

tfpnconf		90.13 95	92.47 82	87.40 103	90.89 106	97.37 100	92.05 106	85.47 80	93.43 102	70.44 121	92.30 52	79.50 112	86.50 140	94.84 103	93.93 85	99.07 113	95.91 184

ACMH+	85.62 12	85.27 138	84.96 148	85.64 118	90.84 108	94.78 135	87.46 143	81.30 112	86.94 145	67.35 131	74.56 133	64.09 161	88.70 123	88.14 165	89.00 160	98.22 184	97.19 158

Anonymous202405211			87.54 137		90.72 109	97.10 104	93.40 88	85.30 84	91.41 129		60.23 171	80.69 107	95.80 63	91.33 139	92.60 122	98.38 178	99.40 76

casdiffmvs		92.52 61	94.57 53	90.13 84	90.72 109	98.26 78	95.06 63	81.08 113	97.65 52	78.18 102	85.79 89	85.40 88	96.16 53	97.65 36	98.10 18	99.57 40	99.18 93

MVS_Test		92.42 62	94.43 54	90.08 85	90.69 111	98.26 78	94.78 70	80.81 115	97.27 59	78.76 99	87.06 75	84.25 92	95.84 62	97.67 34	97.56 29	99.59 31	98.93 105

tpmrst		86.78 131	90.29 115	82.69 143	90.55 112	96.95 107	88.49 138	62.58 212	95.09 85	63.52 144	76.67 126	84.00 94	92.05 97	87.93 168	91.89 132	98.98 122	99.50 70

FC-MVSNet-train		89.37 104	89.62 123	89.08 97	90.48 113	94.16 142	89.45 131	83.99 91	91.09 131	80.09 93	82.84 108	74.52 128	91.44 104	93.79 118	91.57 135	99.01 119	99.35 79

ADS-MVSNet		86.68 133	90.79 108	81.88 147	90.38 114	96.81 109	86.90 151	60.50 223	96.01 76	63.93 141	81.67 109	84.72 90	90.78 109	87.03 181	91.67 134	98.77 135	97.63 150

EPP-MVSNet		92.29 64	94.35 58	89.88 87	90.36 115	97.69 92	90.89 119	83.31 95	93.39 104	83.47 65	85.56 91	93.92 53	91.93 100	95.49 90	94.77 75	99.34 91	99.62 57

tmp_tt				71.24 214	90.29 116	76.39 229	65.81 227	59.43 226	97.62 53	79.65 95	90.60 60	68.71 154	49.71 228	72.71 227	65.70 229	82.54 233

Anonymous20231211		89.22 108	87.56 136	91.16 73	90.23 117	96.62 110	93.22 90	85.44 82	92.89 112	84.37 56	60.13 173	81.25 103	96.02 58	90.61 143	92.01 130	97.70 199	99.41 75

DI_MVS_plusplus_trai		91.11 83	91.47 95	90.68 77	90.01 118	97.77 89	95.87 55	83.56 93	94.72 89	82.12 75	68.46 151	87.46 78	93.07 88	96.46 56	95.73 64	99.47 64	99.71 43

CostFormer		89.42 103	91.67 91	86.80 109	89.99 119	96.33 116	90.75 120	64.79 207	95.17 84	83.62 64	86.20 84	82.15 100	92.96 89	89.22 161	92.94 107	98.68 157	99.65 48

tpmp4_e23		88.10 120	90.02 119	85.86 115	89.94 120	95.73 126	91.83 112	64.92 205	94.79 88	78.25 101	81.03 111	78.34 117	92.33 96	88.10 166	92.82 114	97.90 195	99.34 82

dps		88.66 112	90.19 117	86.88 108	89.94 120	96.48 114	89.56 129	64.08 209	94.12 95	89.00 32	83.39 105	82.56 97	90.16 115	86.81 195	89.26 157	98.53 173	98.71 111

diffmvs		90.73 88	92.06 90	89.17 95	89.83 122	98.03 84	93.32 89	80.32 116	95.23 82	77.63 103	86.49 81	75.24 124	94.65 74	95.47 91	95.54 67	99.27 99	98.40 123

tpm cat1		87.34 125	88.52 130	85.95 114	89.83 122	95.80 123	90.73 121	64.91 206	92.99 111	82.21 73	71.19 148	82.68 96	90.13 116	86.38 199	90.87 141	97.90 195	99.74 39

USDC		85.11 139	85.35 147	84.83 123	89.45 124	94.93 134	92.98 92	77.30 142	90.53 135	61.80 154	76.69 125	59.62 170	88.90 121	92.78 129	90.79 145	98.53 173	92.12 203

PatchmatchNet		88.67 111	94.10 61	82.34 145	89.38 125	97.72 90	87.24 146	62.18 216	97.00 60	64.79 138	87.97 65	94.43 48	91.55 102	91.21 141	92.77 121	98.90 125	97.60 151
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Vis-MVSNet		87.60 123	91.31 97	83.27 137	89.14 126	98.04 83	90.35 124	79.42 121	87.23 144	66.92 132	79.10 117	84.63 91	74.34 209	95.81 72	96.06 59	99.46 75	98.32 130
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Effi-MVS+		88.96 109	91.13 104	86.43 111	89.12 127	97.62 95	93.15 91	75.52 152	93.90 98	66.40 133	86.23 83	70.51 149	95.03 69	95.89 69	94.28 80	99.37 83	99.51 68

TinyColmap		83.03 148	82.24 158	83.95 132	88.88 128	93.22 147	89.48 130	76.89 145	87.53 143	62.12 149	68.46 151	55.03 205	88.43 128	90.87 142	89.65 151	97.89 197	90.91 209

RPMNet		87.35 124	92.41 85	81.45 149	88.85 129	96.06 119	89.42 134	59.59 225	93.57 100	61.81 153	76.48 127	91.48 66	90.18 114	96.32 59	93.37 101	98.87 128	99.59 59

IterMVS-LS		87.95 121	89.40 125	86.26 112	88.79 130	90.93 185	91.23 117	76.05 149	90.87 132	71.07 119	75.51 131	81.18 104	91.21 106	94.11 112	95.01 72	99.20 105	98.23 134
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MDTV_nov1_ep13		89.63 100	94.38 57	84.09 130	88.76 131	97.53 98	89.37 135	68.46 201	96.95 62	70.27 125	87.88 70	93.67 55	91.04 108	93.12 122	93.83 88	96.62 210	97.68 148

CR-MVSNet		86.73 132	91.47 95	81.20 155	88.56 132	96.06 119	89.43 132	61.37 219	93.57 100	60.81 158	72.89 139	88.85 71	88.13 131	96.03 65	93.64 93	98.89 126	99.22 89

CVMVSNet		84.01 143	86.91 141	80.61 162	88.39 133	93.29 146	86.06 163	82.29 100	83.13 165	54.29 201	72.68 141	79.59 111	75.11 205	91.23 140	92.91 108	97.54 203	95.58 189

test-LLR		89.31 106	93.60 67	84.30 127	88.08 134	96.98 105	88.10 139	78.00 136	94.83 86	62.43 147	84.29 100	90.96 68	89.70 117	95.63 80	92.86 109	99.51 55	99.64 50

test0.0.03 1		88.71 110	92.22 88	84.63 125	88.08 134	94.71 138	85.91 173	78.00 136	95.54 80	72.96 112	86.10 85	85.88 86	83.59 156	92.95 128	93.24 104	99.25 102	97.09 162

gg-mvs-nofinetune		81.27 159	84.65 151	77.32 198	87.96 136	98.48 77	95.64 57	56.36 230	59.35 229	32.80 234	47.96 224	92.11 62	91.49 103	98.12 21	97.00 44	99.65 20	99.56 63

PatchT		84.89 141	90.67 111	78.13 195	87.83 137	94.99 133	72.46 219	60.22 224	91.74 127	60.81 158	72.16 143	86.95 80	88.13 131	96.03 65	93.64 93	99.36 86	99.22 89

tpm		83.97 144	87.97 133	79.31 184	87.35 138	93.21 148	86.00 168	61.90 217	90.69 134	54.01 206	79.42 116	75.61 123	88.65 124	87.18 176	90.48 147	97.95 193	99.21 91

IterMVS		85.02 140	88.98 128	80.41 165	87.03 139	90.34 195	89.78 128	69.45 194	89.77 139	54.04 205	73.71 137	82.05 101	83.44 161	95.11 99	93.64 93	98.75 143	98.22 135
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Fast-Effi-MVS+		86.94 129	87.88 134	85.84 116	86.99 140	95.80 123	91.24 116	73.48 171	92.75 114	69.22 127	72.70 140	65.71 159	94.84 72	94.98 101	94.71 76	99.26 100	98.48 119

CDS-MVSNet		88.59 115	90.13 118	86.79 110	86.98 141	95.43 130	92.03 109	81.33 111	85.54 154	74.51 109	77.07 121	85.14 89	87.03 137	93.90 116	95.18 71	98.88 127	98.67 113
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
LP		77.20 203	79.14 197	74.92 208	86.71 142	90.62 188	77.97 207	57.87 227	85.88 151	50.75 212	55.29 213	66.34 157	79.39 189	80.75 220	85.03 210	96.86 206	90.09 212

Effi-MVS+-dtu		87.18 127	90.48 114	83.32 136	86.51 143	95.76 125	91.16 118	74.28 164	90.44 137	61.31 156	86.72 80	72.68 133	91.25 105	95.01 100	93.64 93	95.45 217	99.12 98

Fast-Effi-MVS+-dtu		86.94 129	91.27 101	81.89 146	86.27 144	95.06 131	90.68 123	68.93 198	91.76 124	57.18 189	89.56 62	75.85 121	89.19 119	94.56 105	92.84 111	99.07 113	99.23 87

testgi		82.88 149	86.14 144	79.08 188	86.05 145	92.20 164	81.23 203	74.77 160	88.70 141	57.63 187	86.73 79	61.53 164	76.83 201	90.33 144	89.43 156	97.99 190	94.05 196

testpf		81.62 156	87.82 135	74.38 210	85.88 146	89.26 201	74.45 217	48.92 235	95.87 79	60.31 166	76.95 122	80.17 109	80.07 187	85.72 206	88.77 162	96.67 209	98.01 144

FMVSNet3		91.25 80	92.13 89	90.21 82	85.64 147	93.14 149	95.29 62	80.09 117	96.40 67	85.74 47	77.13 118	86.81 81	94.98 70	97.19 45	97.11 38	99.55 50	97.13 161

GA-MVS		83.83 145	86.63 142	80.58 163	85.40 148	94.73 137	87.27 145	78.76 131	86.49 147	49.57 214	74.21 134	67.67 155	83.38 163	95.28 96	90.92 140	99.08 112	97.09 162

FC-MVSNet-test		85.51 135	89.08 126	81.35 150	85.31 149	93.35 145	87.65 141	77.55 139	90.01 138	64.07 140	79.63 115	81.83 102	74.94 206	92.08 133	90.83 143	98.55 170	95.81 187

GBi-Net		90.49 91	91.12 105	89.75 89	84.99 150	92.73 152	93.94 82	80.09 117	96.40 67	85.74 47	77.13 118	86.81 81	94.42 77	94.12 109	93.73 89	99.35 87	96.90 170

test1		90.49 91	91.12 105	89.75 89	84.99 150	92.73 152	93.94 82	80.09 117	96.40 67	85.74 47	77.13 118	86.81 81	94.42 77	94.12 109	93.73 89	99.35 87	96.90 170

FMVSNet2		89.51 102	89.63 122	89.38 92	84.99 150	92.73 152	93.94 82	79.28 123	93.73 99	84.28 58	69.36 150	82.32 99	94.42 77	96.16 61	96.22 56	99.35 87	96.90 170

TAMVS		85.35 137	86.00 145	84.59 126	84.97 153	95.57 128	88.98 137	77.29 143	81.44 179	71.36 118	71.48 145	75.00 127	87.03 137	91.92 137	92.21 126	97.92 194	94.40 195

tfpnnormal		81.11 160	79.33 193	83.19 138	84.23 154	92.29 159	86.76 153	82.27 101	72.67 217	62.02 151	56.10 208	53.86 213	85.35 144	92.06 134	89.23 158	98.49 175	99.11 100

MVS-HIRNet		79.34 189	82.56 155	75.57 205	84.11 155	95.02 132	75.03 216	57.28 228	85.50 155	55.88 193	53.00 218	70.51 149	83.05 170	92.12 132	91.96 131	98.09 187	89.83 213

TESTMET0.1,1		88.63 113	93.60 67	82.84 142	84.07 156	96.98 105	88.10 139	73.22 173	94.83 86	62.43 147	84.29 100	90.96 68	89.70 117	95.63 80	92.86 109	99.51 55	99.64 50

test-mter		88.25 118	93.27 74	82.38 144	83.89 157	96.86 108	87.10 150	72.80 175	94.58 91	61.85 152	83.21 106	90.65 70	89.18 120	95.43 92	92.58 123	99.46 75	99.61 58

TransMVSNet (Re)		79.51 187	78.36 203	80.84 160	83.17 158	89.72 198	84.22 189	81.45 110	73.98 215	60.79 161	57.20 202	56.05 199	77.11 200	89.88 149	88.86 161	98.30 183	92.83 201

EG-PatchMatch MVS		78.32 198	79.42 192	77.03 202	83.03 159	93.77 144	84.47 187	69.26 196	75.85 212	53.69 208	55.68 211	60.23 168	73.20 211	89.69 153	88.22 173	98.55 170	92.54 202

LTVRE_ROB	79.45 16	79.66 182	80.55 174	78.61 192	83.01 160	92.19 165	87.18 147	73.69 170	71.70 220	43.22 225	71.22 147	50.85 219	87.82 133	89.47 157	90.43 148	96.75 207	98.00 146
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
pmmvs4		84.88 142	84.67 150	85.13 121	82.80 161	92.37 157	87.29 144	79.08 124	90.51 136	74.94 108	70.37 149	62.49 163	88.17 130	92.01 135	88.51 166	98.49 175	96.44 177

FMVSNet1		85.85 134	84.91 149	86.96 107	82.70 162	91.39 179	91.54 114	77.45 140	85.29 156	79.56 96	60.70 167	72.68 133	92.37 95	94.12 109	93.73 89	98.12 186	96.44 177

pm-mvs1		81.68 155	81.70 162	81.65 148	82.61 163	92.26 160	85.54 180	78.95 125	76.29 211	63.81 142	58.43 197	66.33 158	80.63 185	92.30 131	89.93 150	98.37 180	96.39 179

NR-MVSNet		82.37 152	81.95 161	82.85 141	82.56 164	92.24 161	87.49 142	81.91 103	86.41 148	65.51 136	63.95 162	52.93 215	80.80 184	89.41 158	89.61 152	98.85 130	99.10 101

our_test_3					81.94 165	90.26 196	75.39 213

UniMVSNet (Re)		83.28 147	83.16 154	83.42 135	81.93 166	93.12 150	86.27 157	80.83 114	85.88 151	68.23 130	64.56 161	60.58 165	84.25 150	89.13 162	89.44 155	99.04 118	99.40 76

SixPastTwentyTwo		80.28 174	82.06 160	78.21 194	81.89 167	92.35 158	77.72 208	74.48 161	83.04 167	54.22 202	76.06 128	56.40 197	83.55 157	86.83 192	84.83 212	97.38 204	94.93 192

v18		80.16 175	80.01 184	80.34 167	81.72 168	85.71 210	86.58 154	70.68 185	83.23 164	60.78 162	60.39 169	58.50 176	83.49 158	87.03 181	88.19 175	98.79 132	97.06 164

v16		80.03 176	79.95 185	80.13 169	81.64 169	85.63 212	86.17 158	70.42 188	83.12 166	60.34 165	60.11 174	58.61 174	83.45 160	86.98 187	88.12 185	98.75 143	97.05 165

v17		79.95 177	79.87 186	80.05 170	81.55 170	85.65 211	86.10 162	70.44 187	82.59 169	60.02 167	60.26 170	58.53 175	83.41 162	86.98 187	88.09 187	98.76 138	97.02 166

v8		80.61 170	80.61 173	80.62 161	81.51 171	91.00 184	86.06 163	74.07 167	81.78 175	59.93 168	60.10 176	58.42 177	83.35 166	86.99 185	88.11 186	98.79 132	97.83 147

pmmvs5		80.48 171	81.43 163	79.36 182	81.50 172	92.24 161	82.07 199	74.08 166	78.10 202	55.86 194	67.72 154	54.35 210	83.91 155	92.97 126	88.65 164	98.77 135	96.01 182

v1neww		81.04 162	80.86 167	81.25 152	81.48 173	92.14 166	86.06 163	78.41 133	82.02 172	59.43 172	60.09 177	58.30 180	83.37 164	87.02 183	88.15 179	98.76 138	98.33 128

v7new		81.04 162	80.86 167	81.25 152	81.48 173	92.14 166	86.06 163	78.41 133	82.02 172	59.43 172	60.09 177	58.30 180	83.37 164	87.02 183	88.15 179	98.76 138	98.33 128

v6		81.06 161	80.87 166	81.28 151	81.47 175	92.12 168	86.14 159	78.42 132	81.99 174	59.68 170	60.14 172	58.36 178	83.22 169	86.99 185	88.14 181	98.76 138	98.32 130

UniMVSNet_NR-MVSNet		83.83 145	83.70 153	83.98 131	81.41 176	92.56 156	86.54 155	82.96 97	85.98 150	66.27 134	66.16 158	63.63 162	87.78 134	87.65 171	90.81 144	98.94 123	99.13 96

WR-MVS_H		79.76 180	80.07 181	79.40 180	81.25 177	91.73 175	82.77 194	74.82 159	79.02 201	62.55 146	59.41 182	57.32 192	76.27 202	87.61 172	87.30 201	98.78 134	98.09 141

v7		80.74 166	80.95 165	80.50 164	81.23 178	91.58 176	86.12 160	74.83 158	82.30 171	57.64 186	58.74 193	57.45 186	84.48 147	89.75 151	88.27 171	98.72 148	98.57 116

v10		80.38 172	80.73 170	79.96 172	81.22 179	90.40 194	86.11 161	71.63 179	82.42 170	57.65 185	58.74 193	57.47 184	84.44 148	89.75 151	88.28 170	98.71 152	98.06 143

V42		80.88 164	80.74 169	81.05 156	81.21 180	92.01 172	85.96 169	77.75 138	81.62 177	59.73 169	59.93 179	58.35 179	82.98 171	86.90 189	88.06 190	98.69 155	98.32 130

v1141		80.70 167	80.42 176	81.02 158	81.14 181	92.03 170	85.94 171	78.92 127	80.59 187	58.40 182	59.32 184	57.41 189	82.97 172	87.10 177	88.16 177	98.72 148	98.37 125

divwei89l23v2f112		80.69 168	80.42 176	81.02 158	81.13 182	92.04 169	85.95 170	78.92 127	80.45 189	58.43 180	59.34 183	57.46 185	82.92 173	87.09 178	88.16 177	98.75 143	98.36 127

v1		80.69 168	80.38 178	81.05 156	81.13 182	92.02 171	86.02 167	78.93 126	80.32 195	58.65 176	59.29 185	57.45 186	82.83 176	87.07 179	88.14 181	98.74 146	98.37 125

gm-plane-assit		77.20 203	82.26 157	71.30 213	81.10 184	82.00 225	54.33 231	64.41 208	63.80 228	40.93 227	59.04 189	76.57 120	87.30 136	98.26 18	97.36 34	99.74 11	98.76 110

v15		79.35 188	79.20 195	79.54 177	81.08 185	85.48 213	85.92 172	70.02 190	80.60 186	58.63 177	59.14 188	57.40 190	82.87 175	86.89 190	87.95 191	98.70 154	96.92 169

v148		79.66 182	79.13 198	80.27 168	81.02 186	91.76 174	81.90 200	79.32 122	79.24 199	63.79 143	58.07 200	54.34 211	77.17 199	84.42 211	87.52 200	98.40 177	98.59 115

V14		79.33 190	79.18 196	79.51 178	81.00 187	85.46 215	85.88 174	69.79 191	80.52 188	58.76 175	59.16 187	57.52 183	82.91 174	86.86 191	87.90 192	98.72 148	96.87 174

v11		79.54 186	79.71 189	79.35 183	80.96 188	85.36 219	85.81 176	69.10 197	81.49 178	57.63 187	58.90 191	57.07 195	83.94 153	90.09 146	88.08 189	98.66 162	96.97 168

N_pmnet		76.83 205	77.97 208	75.50 206	80.96 188	88.23 205	72.81 218	76.83 146	80.87 182	50.55 213	56.94 204	60.09 169	75.70 204	83.28 217	84.23 214	96.14 214	92.12 203

V9		79.23 191	79.09 199	79.39 181	80.95 190	85.40 216	85.85 175	69.63 192	80.42 190	58.45 179	58.94 190	57.42 188	82.77 177	86.79 196	87.85 194	98.69 155	96.83 175

v13		79.09 193	78.98 201	79.22 187	80.88 191	85.34 220	85.50 181	69.40 195	80.36 193	58.14 183	58.62 195	57.30 193	82.70 178	86.72 198	87.75 197	98.67 161	96.76 176

v12		79.16 192	79.04 200	79.30 185	80.88 191	85.37 218	85.45 182	69.52 193	80.39 191	58.57 178	58.90 191	57.17 194	82.68 179	86.76 197	87.82 195	98.68 157	96.88 173

v1144		80.36 173	80.63 172	80.05 170	80.86 193	91.56 177	85.78 177	75.22 154	80.73 184	55.83 195	58.51 196	56.99 196	83.93 154	89.79 150	88.25 172	98.68 157	98.56 117

v2v482		80.86 165	80.52 175	81.25 152	80.79 194	91.85 173	85.68 178	78.78 130	81.05 180	58.09 184	60.46 168	56.08 198	85.45 143	87.27 175	88.53 165	98.73 147	98.38 124

DU-MVS		82.87 150	82.16 159	83.70 134	80.77 195	92.24 161	86.54 155	81.91 103	86.41 148	66.27 134	63.95 162	55.66 203	87.78 134	86.83 192	90.86 142	98.94 123	99.13 96

Baseline_NR-MVSNet		82.08 153	80.64 171	83.77 133	80.77 195	88.50 203	86.88 152	81.71 107	85.58 153	68.80 128	58.20 198	57.75 182	86.16 142	86.83 192	88.68 163	98.33 181	98.90 107

CP-MVSNet		79.90 178	79.49 190	80.38 166	80.72 197	90.83 186	82.98 193	75.17 155	79.70 197	61.39 155	59.74 180	51.98 218	83.31 167	87.37 173	88.38 168	98.71 152	98.45 120

WR-MVS		79.67 181	80.25 179	79.00 190	80.65 198	91.16 181	83.31 191	76.57 147	80.97 181	60.50 164	59.20 186	58.66 173	74.38 208	85.85 204	87.76 196	98.61 165	98.14 136

PS-CasMVS		79.06 194	78.58 202	79.63 174	80.59 199	90.55 191	82.54 197	75.04 156	77.76 203	58.84 174	58.16 199	50.11 223	82.09 181	87.05 180	88.18 176	98.66 162	98.27 133

v1192		79.84 179	80.05 183	79.61 175	80.49 200	91.04 183	85.56 179	74.37 163	80.73 184	54.35 200	57.07 203	54.54 209	84.23 151	89.94 148	88.38 168	98.63 164	98.61 114

TranMVSNet+NR-MVSNet		82.07 154	81.36 164	82.90 140	80.43 201	91.39 179	87.16 148	82.75 98	84.28 163	62.98 145	62.28 166	56.01 200	85.30 145	86.06 202	90.69 146	98.80 131	98.80 109

v144192		79.61 184	79.77 187	79.41 179	80.28 202	91.06 182	84.87 186	73.86 168	79.65 198	55.38 196	57.76 201	55.20 204	83.46 159	88.42 163	87.89 193	98.61 165	98.42 122

v1921920		79.55 185	79.77 187	79.30 185	80.24 203	90.77 187	85.37 183	73.75 169	80.38 192	53.78 207	56.89 205	54.18 212	84.05 152	89.55 155	88.13 184	98.59 167	98.52 118

v1240		78.97 195	79.27 194	78.63 191	80.04 204	90.61 189	84.25 188	72.95 174	79.22 200	52.70 209	56.22 207	52.88 217	83.28 168	89.60 154	88.20 174	98.56 169	98.14 136

PEN-MVS		78.80 197	78.13 205	79.58 176	80.03 205	89.67 199	83.61 190	75.83 150	77.71 205	58.41 181	60.11 174	50.00 224	81.02 183	84.08 212	88.14 181	98.59 167	97.18 160

EU-MVSNet		76.76 208	79.47 191	73.60 211	79.99 206	87.47 206	77.39 209	75.43 153	77.62 206	47.83 217	64.78 160	60.44 167	64.80 217	86.28 200	86.53 204	96.17 213	93.19 200

pmmvs6		76.79 206	75.69 215	78.09 196	79.95 207	89.57 200	80.92 204	74.46 162	64.79 226	60.74 163	45.71 227	60.55 166	78.37 193	88.04 167	86.00 208	94.07 220	95.15 190

FMVSNet5		87.06 128	89.52 124	84.20 128	79.92 208	86.57 208	87.11 149	72.37 177	96.06 75	75.41 107	84.33 99	91.76 63	91.60 101	91.51 138	91.22 137	98.77 135	85.16 221

anonymousdsp		81.29 158	84.52 152	77.52 197	79.83 209	92.62 155	82.61 196	70.88 184	80.76 183	50.82 211	68.35 153	68.76 153	82.45 180	93.00 125	89.45 154	98.55 170	98.69 112

DTE-MVSNet		77.92 199	77.42 209	78.51 193	79.34 210	89.00 202	83.05 192	75.60 151	76.89 207	56.58 190	59.63 181	50.31 221	78.09 197	82.57 219	87.56 199	98.38 178	95.95 183

v748		76.68 209	76.82 212	76.51 203	78.70 211	90.06 197	77.12 210	73.40 172	73.32 216	59.57 171	55.00 215	50.71 220	72.48 212	83.71 216	86.78 203	97.81 198	98.13 139

MDTV_nov1_ep13_2view		78.83 196	82.35 156	74.73 209	78.65 212	91.51 178	79.18 205	62.52 213	84.51 161	52.51 210	67.49 156	67.29 156	78.90 192	85.52 207	86.34 205	96.62 210	93.76 197

v7n		77.71 200	78.25 204	77.09 201	78.49 213	90.55 191	82.15 198	71.11 183	76.79 208	54.18 203	55.63 212	50.20 222	78.28 195	89.36 160	87.15 202	98.33 181	98.07 142

test20.03		72.81 214	76.24 213	68.80 216	78.31 214	85.40 216	71.04 220	71.20 182	71.85 219	43.40 224	65.31 159	54.71 208	51.27 227	85.92 203	84.18 215	97.58 202	86.35 220

FPMVS		63.27 222	61.31 227	65.57 223	78.25 215	74.42 231	75.23 214	68.92 199	72.33 218	43.87 221	49.01 223	43.94 227	48.64 229	61.15 231	58.81 233	78.51 235	69.49 233

Anonymous20231206		74.59 212	77.00 211	71.78 212	77.89 216	87.45 207	75.14 215	72.29 178	77.76 203	46.65 219	52.14 219	52.93 215	61.10 222	89.37 159	88.09 187	97.59 201	91.30 208

V4		77.67 202	78.01 207	77.28 200	77.82 217	90.56 190	81.70 202	71.63 179	76.33 210	55.38 196	55.74 209	55.83 202	79.20 191	84.02 213	86.01 207	97.97 191	97.55 153

v52		77.69 201	78.04 206	77.29 199	77.79 218	90.54 193	81.76 201	71.62 181	76.52 209	55.34 198	55.70 210	55.91 201	79.27 190	84.02 213	86.03 206	97.96 192	97.56 152

MIMVSNet		82.87 150	86.17 143	79.02 189	77.23 219	92.88 151	84.88 185	60.62 222	86.72 146	64.16 139	73.58 138	71.48 136	88.51 127	94.14 108	93.50 100	98.72 148	90.87 210

PM-MVS		75.81 210	76.11 214	75.46 207	73.81 220	85.48 213	76.42 212	70.57 186	80.05 196	54.75 199	62.33 164	39.56 231	80.59 186	87.71 170	82.81 218	96.61 212	94.81 193

test2356		74.04 213	80.07 181	67.01 221	73.77 221	80.65 226	67.82 225	66.87 203	84.93 160	37.70 231	75.45 132	57.40 190	60.26 223	86.28 200	88.47 167	95.64 216	87.33 218

testus		72.50 215	77.19 210	67.04 219	73.69 222	80.06 227	67.65 226	68.24 202	84.46 162	37.48 233	75.90 130	40.07 230	59.40 224	85.45 208	87.69 198	95.76 215	86.70 219

pmmvs-eth3d		75.17 211	74.09 217	76.43 204	72.92 223	84.49 221	76.61 211	72.42 176	74.33 213	61.28 157	54.71 216	39.42 232	78.20 196	87.77 169	84.25 213	97.17 205	93.63 198

new-patchmatchnet		67.66 221	68.07 222	67.18 218	72.85 224	82.86 224	63.09 230	68.61 200	66.60 225	42.64 226	49.28 222	38.68 233	61.21 221	75.84 224	75.22 227	94.67 219	88.00 217

new_pmnet		71.86 216	73.67 218	69.75 215	72.56 225	84.20 222	70.95 222	66.81 204	80.34 194	43.62 223	51.60 220	53.81 214	71.24 214	82.91 218	80.93 219	93.35 222	81.92 223

testmv		60.16 224	62.42 225	57.53 225	67.85 226	69.87 234	48.47 233	62.44 214	54.75 232	29.08 235	46.99 225	31.77 235	45.97 230	74.85 225	79.08 224	91.39 225	79.62 226

test1235678		60.16 224	62.41 226	57.53 225	67.85 226	69.86 235	48.47 233	62.43 215	54.73 233	29.08 235	46.99 225	31.76 236	45.97 230	74.84 226	79.07 225	91.39 225	79.61 227

pmmvs3		69.04 218	70.75 219	67.04 219	66.83 228	78.54 228	64.99 229	60.92 221	64.67 227	40.61 228	55.08 214	40.29 229	74.89 207	83.76 215	84.01 216	93.98 221	88.88 215

1111		61.69 223	63.75 224	59.29 224	64.35 229	70.45 232	48.44 235	48.86 236	55.76 230	39.40 229	39.25 230	54.73 206	62.55 218	77.84 222	80.37 221	92.16 223	67.84 234

.test1245		51.60 229	57.21 229	45.06 231	64.35 229	70.45 232	48.44 235	48.86 236	55.76 230	39.40 229	39.25 230	54.73 206	62.55 218	77.84 222	27.11 237	6.75 241	75.30 231

test12356		57.24 226	59.66 228	54.43 228	64.26 231	66.14 236	49.96 232	61.73 218	54.37 234	28.80 237	44.89 228	25.68 238	32.36 235	70.23 229	79.19 223	89.46 229	77.11 228

PMVS	49.05 18	51.88 228	50.56 232	53.42 229	64.21 232	43.30 241	42.64 239	62.93 210	50.56 235	43.72 222	37.44 232	42.95 228	35.05 234	58.76 234	54.58 234	71.95 237	66.33 236
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MDA-MVSNet-bldmvs		69.61 217	70.36 220	68.74 217	62.88 233	88.50 203	65.40 228	77.01 144	71.60 222	43.93 220	66.71 157	35.33 234	72.47 213	61.01 232	80.63 220	90.73 228	88.75 216

ambc			64.61 223		61.80 234	75.31 230	71.00 221		74.16 214	48.83 215	36.02 234	13.22 243	58.66 225	85.80 205	76.26 226	88.01 230	91.53 207

Gipuma		54.59 227	53.98 230	55.30 227	59.03 235	52.63 239	47.17 238	56.08 231	71.68 221	37.54 232	20.90 237	19.00 239	52.33 226	71.69 228	75.20 228	79.64 234	66.79 235
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MIMVSNet1		68.63 219	70.24 221	66.76 222	56.86 236	83.26 223	67.93 224	70.26 189	68.05 224	46.80 218	40.44 229	48.15 225	62.01 220	84.96 210	84.86 211	96.69 208	81.93 222

no-one		41.64 231	41.19 233	42.16 232	52.35 237	58.34 238	27.46 241	57.21 229	28.41 241	21.09 239	19.65 238	17.04 240	21.39 240	39.74 236	61.20 232	73.45 236	63.95 238

PMMVS2		50.69 230	52.33 231	48.78 230	51.24 238	64.81 237	47.91 237	53.79 234	44.95 236	21.75 238	29.98 235	25.90 237	31.98 237	59.95 233	65.37 230	86.00 232	75.36 230

EMVS		36.45 233	33.63 236	39.74 234	48.47 239	35.73 242	23.59 243	55.11 233	35.61 238	12.88 242	17.49 239	14.62 241	41.04 232	29.33 238	43.00 236	57.32 239	59.62 240

E-PMN		37.15 232	34.82 235	39.86 233	47.53 240	35.42 243	23.79 242	55.26 232	35.18 239	14.12 241	17.38 241	14.13 242	39.73 233	32.24 237	46.98 235	58.76 238	62.39 239

MVE	42.40 19	36.00 234	38.65 234	32.92 236	29.16 241	46.17 240	22.61 244	44.21 238	26.44 242	18.88 240	17.41 240	9.36 244	32.29 236	45.75 235	61.38 231	50.35 240	64.03 237
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
testmvs		21.55 235	30.91 237	10.62 237	2.78 242	11.66 244	18.51 245	4.82 239	38.21 237	4.06 243	36.35 233	4.47 245	26.81 238	23.27 239	27.11 237	6.75 241	75.30 231

GG-mvs-BLEND		67.99 220	97.35 34	33.72 235	1.22 243	99.72 13	98.30 29	0.57 241	97.61 55	1.18 244	93.26 46	96.63 37	1.74 241	97.15 46	97.14 37	99.34 91	99.96 6

test123		16.81 236	24.80 238	7.48 238	0.82 244	8.38 245	11.92 246	2.60 240	28.96 240	1.12 245	28.39 236	1.26 246	24.51 239	8.93 240	22.19 239	3.90 243	75.49 229

sosnet-low-res		0.00 237	0.00 239	0.00 239	0.00 245	0.00 246	0.00 247	0.00 242	0.00 243	0.00 246	0.00 242	0.00 247	0.00 242	0.00 241	0.00 240	0.00 244	0.00 241

sosnet		0.00 237	0.00 239	0.00 239	0.00 245	0.00 246	0.00 247	0.00 242	0.00 243	0.00 246	0.00 242	0.00 247	0.00 242	0.00 241	0.00 240	0.00 244	0.00 241

MTAPA										94.58 9		98.56 18

MTMP										95.24 4		98.13 24

Patchmatch-RL test							37.05 240

NP-MVS									97.69 50

Patchmtry						95.86 121	89.43 132	61.37 219		60.81 158

DeepMVS_CX						85.88 209	69.83 223	81.56 108	87.99 142	48.22 216	71.85 144	45.52 226	68.67 215	63.21 230		86.64 231	80.03 225

High-resolution multi-view benchmark