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.

CNVR-MVS		98.73 1	99.17 4	98.22 1	99.47 1	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

SMA-MVS		98.26 8	98.97 7	97.44 12	99.42 2	99.79 6	99.33 12	96.12 6	99.25 11	91.26 21	96.72 27	99.96 2	98.95 7	98.81 10	98.52 7	99.56 43	99.72 43

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 42	99.67 18	99.63 55

APDe-MVS		98.60 4	98.97 7	98.18 2	99.38 4	99.78 10	99.35 9	96.14 5	99.24 12	95.66 3	98.19 17	99.01 12	98.66 13	98.77 11	97.80 22	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 10	93.88 12	98.64 11	99.98 1	99.04 5	98.89 8	97.49 29	99.79 9	99.98 3

NCCC		98.41 5	99.18 2	97.52 11	99.36 5	99.84 3	99.55 4	96.08 11	99.33 8	91.77 20	98.79 6	99.46 7	98.59 15	99.15 6	98.07 18	99.73 12	99.64 51

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 26	98.50 19	98.61 14	98.58 14	96.83 47	99.56 43	99.14 91

PGM-MVS		97.03 26	98.14 27	95.73 27	99.34 7	99.61 26	99.34 10	89.99 40	97.70 49	87.67 39	99.44 2	96.45 39	98.44 19	97.65 36	97.09 39	99.58 34	99.06 100

APD-MVS		98.28 7	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 25	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 53	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 25	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 53	99.54 52	99.23 84

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 59	94.78 72	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 16	89.65 61	91.74 65	96.96 34	93.69 118	96.58 51	98.86 127	99.63 55

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 19	98.61 12	98.16 23	99.02 6	97.87 28	97.40 31	99.60 28	99.35 77

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 59	98.27 16	98.08 26	97.95 24	97.89 25	97.46 30	99.58 34	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 37	97.40 31	99.60 28	99.25 83

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 18	98.33 15	97.74 31	98.50 18	97.66 35	96.55 52	99.57 39	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 55
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 50	99.64 21	99.35 77
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 10	95.20 25	98.48 28	89.91 27	98.58 13	98.69 16	96.84 40	98.92 7	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 9	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 29	96.37 56	94.79 71	99.41 81	98.12 137
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 90	94.62 46	97.66 25	97.10 46	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 57	84.59 95	95.60 42	97.21 32	97.10 46	98.19 13	99.57 39	99.65 49

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	84.21 101	94.55 47	97.25 31	95.50 88	96.23 53	99.28 97	99.09 99

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 48	96.02 66	95.99 62	99.34 90	97.65 146

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 24	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 81	75.96 128	91.58 66	96.21 51	96.37 56	97.10 38	99.52 53	99.54 65

MAR-MVS		94.18 48	95.12 51	93.09 51	98.40 31	99.17 55	94.20 78	81.92 99	98.47 29	86.52 44	90.92 57	84.21 93	98.12 22	95.88 69	97.59 27	99.40 82	99.58 62
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 63	94.26 80	98.07 186	99.27 82

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 99	94.80 36	95.74 40	96.11 52	97.86 29	98.67 6	99.59 30	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 30			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 17	84.67 94	97.33 32	97.55 28	97.32 40	98.47 8	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 77	95.95 31	99.16 11	95.13 63	98.61 13	98.11 17	99.58 34	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 52	86.17 46	98.92 4	92.81 58	96.10 53	95.67 77	93.33 100	99.55 49	99.12 94
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 36	96.88 50	98.16 15	99.56 43	99.70 45

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 60	97.81 31	96.73 49	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 76	87.84 71	93.94 52	96.50 46	95.74 74	94.27 79	99.46 74	97.31 154
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 71	97.20 43	97.23 35	99.57 39	99.59 60
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 69	88.05 51	98.61 26	82.29 70	98.85 5	94.66 44	94.63 70	97.80 32	97.63 26	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	91.45 111	94.42 31	99.76 1	86.48 45	92.88 50	98.12 25	92.62 89	99.49 2	99.32 2	95.15 215	99.95 9

MSDG		91.93 70	90.28 115	93.85 44	97.36 44	97.12 101	95.88 54	94.07 33	94.52 91	84.13 58	76.74 123	80.89 104	92.54 90	93.97 114	93.61 95	99.14 104	95.10 188

SD-MVS		98.33 6	99.01 6	97.54 10	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 9	96.95 44	99.81 6	99.96 6

EPNet_dtu		89.82 96	94.18 60	84.74 121	96.87 47	95.54 125	92.65 94	86.91 61	96.99 60	54.17 202	92.41 51	88.54 74	78.35 190	96.15 61	96.05 60	99.47 63	93.60 196
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 66	80.68 111	88.02 76	96.92 37	97.49 39	98.20 12	99.47 63	99.69 47
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 60	92.82 80	92.21 57	96.57 49	98.74 61	91.85 107	86.30 66	96.23 72	85.18 52	95.21 33	73.58 126	94.22 75	95.40 91	93.08 104	99.14 104	97.49 152

DELS-MVS		93.82 50	93.82 63	93.81 45	96.34 50	99.47 35	97.26 45	88.53 49	92.13 117	87.80 38	79.67 113	88.01 77	93.14 81	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 96	95.54 43	95.87 58	98.12 21	98.03 20	99.73 12	99.90 21

LS3D		92.70 57	92.23 87	93.26 48	96.24 52	98.72 62	97.93 33	96.17 3	96.41 66	72.46 112	81.39 109	80.76 105	97.66 25	95.69 76	95.62 65	99.07 111	97.02 163

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	92.00 119	81.51 80	82.97 106	93.88 54	95.63 62	94.24 106	94.71 74	99.09 109	99.70 45
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
COLMAP_ROB	84.42 15	88.24 116	87.32 136	89.32 91	95.83 54	95.82 118	92.81 90	87.68 57	92.09 118	72.64 111	72.34 141	79.96 108	88.79 118	89.54 153	89.46 149	98.16 183	92.00 202
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 85	88.70 45	98.09 40	88.10 36	86.96 77	75.02 122	93.08 82	97.89 25	96.90 45	99.56 43	100.00 1

PVSNet_Blended		93.30 52	93.46 71	93.10 49	95.60 55	99.38 46	93.59 85	88.70 45	98.09 40	88.10 36	86.96 77	75.02 122	93.08 82	97.89 25	96.90 45	99.56 43	100.00 1

CHOSEN 280x420		94.51 46	97.78 31	90.70 74	95.54 57	99.49 33	94.14 79	74.91 154	98.43 30	85.32 51	94.78 37	99.19 10	94.95 67	97.02 48	96.18 57	99.35 86	99.36 76

CHOSEN 1792x2688		88.63 110	89.01 126	88.19 98	94.83 58	99.21 54	92.66 93	79.85 116	92.40 115	72.18 113	56.38 203	80.22 106	90.24 109	97.64 37	97.28 34	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 57	81.83 79	83.50 103	93.19 56	94.71 69	98.24 19	98.07 18	99.68 17	99.83 32

HyFIR lowres test		87.86 119	88.25 130	87.40 100	94.67 60	98.54 74	90.33 121	76.51 144	89.60 136	70.89 117	51.43 218	85.69 88	92.79 86	96.59 54	95.96 63	99.22 102	99.94 12

TSAR-MVS + COLMAP		92.56 59	92.44 84	92.71 55	94.61 61	97.69 90	97.69 36	91.09 39	98.96 21	76.71 101	94.68 38	69.41 148	96.91 38	95.80 72	94.18 81	99.26 98	96.33 177

OPM-MVS		89.33 103	87.45 135	91.53 67	94.49 62	96.20 113	96.47 50	89.72 42	82.77 164	75.43 103	80.53 112	70.86 142	93.80 78	94.00 112	91.85 129	99.29 96	95.91 181

HQP-MVS		91.94 69	93.03 76	90.66 76	93.69 63	96.48 110	95.92 52	89.73 41	97.33 56	72.65 110	95.37 32	73.56 127	92.75 88	94.85 100	94.12 82	99.23 101	99.51 68

XVS					93.63 64	99.64 20	94.32 76			83.97 59		98.08 26				99.59 30

X-MVStestdata					93.63 64	99.64 20	94.32 76			83.97 59		98.08 26				99.59 30

PVSNet_Blended_VisFu		91.20 82	92.89 78	89.23 92	93.41 66	98.61 72	89.80 123	85.39 81	92.84 111	82.80 65	74.21 133	91.38 68	84.64 142	97.22 42	96.04 61	99.34 90	99.93 15

LGP-MVS_train		90.34 93	91.63 91	88.83 95	93.31 67	96.14 114	95.49 59	85.24 83	93.91 96	68.71 126	93.96 43	71.63 131	91.12 103	93.82 116	92.79 118	99.07 111	99.16 90

ACMM	89.40 10	90.58 89	90.02 118	91.23 71	93.30 68	94.75 132	90.69 118	88.22 50	95.20 82	82.70 67	88.54 63	71.40 133	93.48 79	93.64 119	90.94 135	98.99 119	95.72 185
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CMPMVS	58.73 17	76.78 205	74.27 213	79.70 170	93.26 69	95.58 123	82.74 192	77.44 137	71.46 220	56.29 190	53.58 214	59.13 169	77.33 194	79.20 218	79.71 219	91.14 224	81.24 222
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
RPSCF		89.81 97	89.75 120	89.88 85	93.22 70	93.99 139	94.78 69	85.23 84	94.01 95	82.52 68	95.00 35	87.23 80	92.01 94	85.16 206	83.48 214	91.54 221	89.38 212

MS-PatchMatch		87.19 123	88.59 128	85.55 116	93.15 71	96.58 108	92.35 98	74.19 162	91.97 120	70.33 121	71.42 145	85.89 86	84.28 145	93.12 120	89.16 155	99.00 118	91.99 203

IB-MVS	84.67 14	88.34 113	90.61 111	85.70 114	92.99 72	98.62 71	78.85 203	86.07 73	94.35 93	88.64 34	85.99 87	75.69 120	68.09 213	88.21 161	91.43 132	99.55 49	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 97	92.72 73	98.00 83	90.22 122	84.81 85	94.45 92	83.05 64	87.65 73	92.74 59	81.04 178	94.51 105	94.45 77	99.32 95	99.21 88
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 88	91.15 102	90.21 81	92.55 74	96.52 109	92.63 95	85.71 77	94.65 89	81.06 82	93.32 45	70.56 144	90.52 107	92.68 128	91.05 134	98.76 137	99.31 81
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
UA-Net		89.56 99	93.03 76	85.52 117	92.46 75	97.55 94	91.92 106	81.91 100	85.24 153	71.39 114	83.57 102	96.56 38	76.01 200	96.81 51	97.04 41	99.46 74	94.41 191

CANet_DTU		91.36 77	95.75 44	86.23 110	92.31 76	98.71 63	95.60 58	78.41 129	98.20 36	56.48 189	94.38 42	87.96 78	95.11 64	96.89 49	96.07 58	99.48 59	98.01 141

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 32	96.78 52	96.74 48	99.63 23	99.94 12

ACMH	85.22 13	85.40 133	85.73 142	85.02 119	91.76 78	94.46 137	84.97 180	81.54 106	85.18 154	65.22 134	76.92 122	64.22 156	88.58 122	90.17 142	90.25 145	98.03 187	98.90 105
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 59	91.66 79	98.85 58	95.03 63	86.42 63	93.24 104	82.20 73	92.98 49	79.35 113	96.80 41	95.83 70	94.67 76	99.48 59	99.91 19

conf0.01		92.41 63	92.86 79	91.90 60	91.65 80	98.84 59	95.03 63	86.38 65	93.24 104	82.03 75	91.90 56	77.54 116	96.80 41	95.78 73	92.82 112	99.48 59	99.90 21

tfpn111		91.99 68	92.28 86	91.65 63	91.61 81	98.69 64	95.03 63	86.17 67	93.24 104	80.82 83	94.67 39	71.15 134	96.80 41	95.53 81	92.82 112	99.47 63	99.88 24

conf200view11		91.47 75	91.31 96	91.65 63	91.61 81	98.69 64	95.03 63	86.17 67	93.24 104	80.82 83	87.90 67	71.15 134	96.80 41	95.53 81	92.82 112	99.47 63	99.88 24

thres100view900		91.69 72	91.52 93	91.88 61	91.61 81	98.89 57	95.49 59	86.96 60	93.24 104	80.82 83	87.90 67	71.15 134	96.88 39	96.00 67	93.51 97	99.51 54	99.95 9

tfpn200view9		91.47 75	91.31 96	91.65 63	91.61 81	98.69 64	95.03 63	86.17 67	93.24 104	80.82 83	87.90 67	71.15 134	96.80 41	95.53 81	92.82 112	99.47 63	99.88 24

thres200		91.36 77	91.19 101	91.55 66	91.60 85	98.69 64	94.98 68	86.17 67	92.16 116	80.76 87	87.66 72	71.15 134	96.35 48	95.53 81	93.23 103	99.47 63	99.92 18

thres400		91.24 81	91.01 106	91.50 68	91.56 86	98.77 60	94.66 73	86.41 64	91.87 121	80.56 88	87.05 76	71.01 139	96.35 48	95.67 77	92.82 112	99.48 59	99.88 24

view600		90.97 85	90.70 108	91.30 69	91.53 87	98.69 64	94.33 74	86.17 67	91.75 123	80.19 90	86.06 85	70.90 140	96.10 53	95.53 81	92.08 125	99.47 63	99.86 30

thres600view7		90.97 85	90.70 108	91.30 69	91.53 87	98.69 64	94.33 74	86.17 67	91.75 123	80.19 90	86.06 85	70.90 140	96.10 53	95.53 81	92.08 125	99.47 63	99.86 30

view800		90.79 87	90.54 112	91.09 72	91.50 89	98.58 73	94.09 80	85.92 74	91.57 126	79.68 93	85.29 91	70.72 143	95.91 56	95.40 91	92.39 121	99.47 63	99.83 32

tfpn		91.26 79	91.55 92	90.92 73	91.47 90	98.50 76	93.85 84	85.72 76	91.40 127	79.30 97	84.78 93	77.33 117	95.70 61	95.29 93	93.73 87	99.47 63	99.82 34

tfpn_ndepth		92.26 65	93.84 62	90.42 77	91.45 91	97.91 86	92.73 92	85.80 75	96.69 64	82.22 71	91.92 55	83.42 95	90.76 106	95.51 87	93.28 101	99.58 34	98.14 133

canonicalmvs		92.54 60	93.28 73	91.68 62	91.44 92	98.24 79	95.45 61	81.84 103	95.98 77	84.85 54	90.69 59	78.53 114	96.96 34	92.97 124	97.06 40	99.57 39	99.47 72

PMMVS		93.05 54	95.40 47	90.31 80	91.41 93	97.54 95	92.62 96	83.25 93	98.08 43	79.44 96	95.18 34	88.52 75	96.43 47	95.70 75	93.88 85	98.68 156	98.91 104

tfpn1000		91.48 74	93.17 75	89.51 89	91.27 94	97.71 89	92.08 101	85.28 82	96.13 74	80.20 89	90.77 58	82.52 98	88.64 121	95.17 96	92.35 122	99.56 43	97.52 151

DWT-MVSNet_training		92.09 67	93.58 69	90.35 79	91.27 94	97.94 85	92.05 102	78.82 125	97.40 55	88.83 33	87.91 66	86.76 85	91.99 95	90.03 144	95.25 68	99.13 106	99.73 41

CLD-MVS		91.67 73	91.30 99	92.10 58	91.25 96	96.59 107	95.93 51	87.25 59	96.86 63	85.55 50	87.08 74	73.01 128	93.26 80	93.07 122	92.84 109	99.34 90	99.68 48
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 58	94.99 52	89.96 84	91.17 97	98.54 74	92.77 91	84.00 87	92.72 113	81.90 78	85.67 88	92.47 60	90.39 108	97.82 30	97.81 21	99.51 54	99.91 19

thresconf0.02		92.16 66	95.16 49	88.67 96	91.10 98	97.63 92	92.93 89	86.58 62	96.29 70	73.55 108	94.67 39	88.63 73	88.29 125	96.14 62	95.40 67	99.58 34	97.33 153

EPMVS		89.31 104	93.70 65	84.18 126	91.10 98	98.10 81	89.17 132	62.71 209	96.24 71	70.21 123	86.46 81	92.37 62	92.79 86	91.95 134	93.59 96	99.10 108	97.19 155

Vis-MVSNet (Re-imp)		91.05 84	94.43 54	87.11 103	91.05 100	97.99 84	92.53 97	83.82 89	92.71 114	76.28 102	84.50 97	92.43 61	79.52 184	97.24 41	97.68 23	99.43 79	98.45 118

TDRefinement		81.49 154	80.08 177	83.13 136	91.02 101	94.53 135	91.66 109	82.43 96	81.70 172	62.12 147	62.30 163	59.32 168	73.93 207	87.31 171	85.29 206	97.61 197	90.14 209

conf0.05thres1000		88.28 114	87.54 134	89.15 93	91.00 102	97.50 97	92.18 100	84.70 86	85.15 155	73.91 107	73.77 135	70.50 147	94.01 76	93.99 113	92.21 123	99.11 107	99.64 51

tfpnview11		90.36 92	92.74 81	87.59 99	90.93 103	97.30 100	92.28 99	85.63 78	95.88 78	70.44 118	92.30 52	79.50 110	86.76 135	95.26 95	92.83 111	99.51 54	96.09 178

MVSTER		94.75 43	96.50 38	92.70 56	90.91 104	94.51 136	97.37 44	83.37 91	98.40 33	89.04 31	93.23 47	97.04 35	95.91 56	97.73 33	95.59 66	99.61 27	99.01 102

tfpn_n400		90.13 94	92.47 82	87.40 100	90.89 105	97.37 98	92.05 102	85.47 79	93.43 101	70.44 118	92.30 52	79.50 110	86.50 136	94.84 101	93.93 83	99.07 111	95.91 181

tfpnconf		90.13 94	92.47 82	87.40 100	90.89 105	97.37 98	92.05 102	85.47 79	93.43 101	70.44 118	92.30 52	79.50 110	86.50 136	94.84 101	93.93 83	99.07 111	95.91 181

ACMH+	85.62 12	85.27 135	84.96 144	85.64 115	90.84 107	94.78 131	87.46 139	81.30 109	86.94 141	67.35 128	74.56 132	64.09 157	88.70 119	88.14 162	89.00 156	98.22 182	97.19 155

diffmvs		92.73 56	94.75 53	90.37 78	90.81 108	98.11 80	94.69 72	80.93 110	96.91 62	82.50 69	85.28 92	92.99 57	93.84 77	94.67 103	96.19 56	99.44 78	99.12 94

MVS_Test		92.42 62	94.43 54	90.08 83	90.69 109	98.26 78	94.78 69	80.81 112	97.27 58	78.76 98	87.06 75	84.25 92	95.84 59	97.67 34	97.56 28	99.59 30	98.93 103

tpmrst		86.78 128	90.29 114	82.69 140	90.55 110	96.95 104	88.49 134	62.58 210	95.09 84	63.52 142	76.67 125	84.00 94	92.05 93	87.93 165	91.89 128	98.98 120	99.50 70

FC-MVSNet-train		89.37 102	89.62 122	89.08 94	90.48 111	94.16 138	89.45 127	83.99 88	91.09 128	80.09 92	82.84 107	74.52 125	91.44 100	93.79 117	91.57 131	99.01 117	99.35 77

ADS-MVSNet		86.68 130	90.79 107	81.88 144	90.38 112	96.81 106	86.90 147	60.50 221	96.01 76	63.93 138	81.67 108	84.72 90	90.78 105	87.03 178	91.67 130	98.77 134	97.63 147

EPP-MVSNet		92.29 64	94.35 58	89.88 85	90.36 113	97.69 90	90.89 115	83.31 92	93.39 103	83.47 63	85.56 89	93.92 53	91.93 96	95.49 89	94.77 73	99.34 90	99.62 58

tmp_tt				71.24 212	90.29 114	76.39 227	65.81 224	59.43 224	97.62 52	79.65 94	90.60 60	68.71 150	49.71 226	72.71 225	65.70 227	82.54 231

DI_MVS_plusplus_trai		91.11 83	91.47 94	90.68 75	90.01 115	97.77 87	95.87 55	83.56 90	94.72 88	82.12 74	68.46 150	87.46 79	93.07 84	96.46 55	95.73 64	99.47 63	99.71 44

CostFormer		89.42 101	91.67 90	86.80 106	89.99 116	96.33 112	90.75 116	64.79 205	95.17 83	83.62 62	86.20 83	82.15 100	92.96 85	89.22 158	92.94 105	98.68 156	99.65 49

tpmp4_e23		88.10 117	90.02 118	85.86 112	89.94 117	95.73 122	91.83 108	64.92 203	94.79 87	78.25 100	81.03 110	78.34 115	92.33 92	88.10 163	92.82 112	97.90 193	99.34 80

dps		88.66 109	90.19 116	86.88 105	89.94 117	96.48 110	89.56 125	64.08 207	94.12 94	89.00 32	83.39 104	82.56 97	90.16 111	86.81 192	89.26 153	98.53 172	98.71 109

tpm cat1		87.34 122	88.52 129	85.95 111	89.83 119	95.80 119	90.73 117	64.91 204	92.99 110	82.21 72	71.19 147	82.68 96	90.13 112	86.38 196	90.87 137	97.90 193	99.74 39

USDC		85.11 136	85.35 143	84.83 120	89.45 120	94.93 130	92.98 88	77.30 138	90.53 131	61.80 152	76.69 124	59.62 167	88.90 117	92.78 127	90.79 141	98.53 172	92.12 200

PatchmatchNet		88.67 108	94.10 61	82.34 142	89.38 121	97.72 88	87.24 142	62.18 214	97.00 59	64.79 135	87.97 65	94.43 48	91.55 98	91.21 138	92.77 119	98.90 123	97.60 148
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Vis-MVSNet		87.60 120	91.31 96	83.27 134	89.14 122	98.04 82	90.35 120	79.42 117	87.23 140	66.92 129	79.10 116	84.63 91	74.34 206	95.81 71	96.06 59	99.46 74	98.32 127
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Effi-MVS+		88.96 106	91.13 103	86.43 108	89.12 123	97.62 93	93.15 87	75.52 148	93.90 97	66.40 130	86.23 82	70.51 145	95.03 65	95.89 68	94.28 78	99.37 83	99.51 68

TinyColmap		83.03 145	82.24 154	83.95 129	88.88 124	93.22 143	89.48 126	76.89 141	87.53 139	62.12 147	68.46 150	55.03 202	88.43 124	90.87 140	89.65 147	97.89 195	90.91 207

RPMNet		87.35 121	92.41 85	81.45 146	88.85 125	96.06 115	89.42 130	59.59 223	93.57 99	61.81 151	76.48 126	91.48 67	90.18 110	96.32 58	93.37 99	98.87 126	99.59 60

IterMVS-LS		87.95 118	89.40 124	86.26 109	88.79 126	90.93 182	91.23 113	76.05 145	90.87 129	71.07 116	75.51 130	81.18 103	91.21 102	94.11 111	95.01 70	99.20 103	98.23 131
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MDTV_nov1_ep13		89.63 98	94.38 57	84.09 127	88.76 127	97.53 96	89.37 131	68.46 198	96.95 61	70.27 122	87.88 70	93.67 55	91.04 104	93.12 120	93.83 86	96.62 207	97.68 145

CR-MVSNet		86.73 129	91.47 94	81.20 152	88.56 128	96.06 115	89.43 128	61.37 217	93.57 99	60.81 156	72.89 138	88.85 72	88.13 127	96.03 64	93.64 91	98.89 124	99.22 86

CVMVSNet		84.01 140	86.91 137	80.61 159	88.39 129	93.29 142	86.06 159	82.29 97	83.13 161	54.29 199	72.68 140	79.59 109	75.11 202	91.23 137	92.91 106	97.54 200	95.58 186

test-LLR		89.31 104	93.60 67	84.30 124	88.08 130	96.98 102	88.10 135	78.00 132	94.83 85	62.43 145	84.29 99	90.96 69	89.70 113	95.63 79	92.86 107	99.51 54	99.64 51

test0.0.03 1		88.71 107	92.22 88	84.63 122	88.08 130	94.71 134	85.91 169	78.00 132	95.54 80	72.96 109	86.10 84	85.88 87	83.59 152	92.95 126	93.24 102	99.25 100	97.09 159

gg-mvs-nofinetune		81.27 156	84.65 147	77.32 196	87.96 132	98.48 77	95.64 57	56.36 228	59.35 226	32.80 233	47.96 221	92.11 63	91.49 99	98.12 21	97.00 43	99.65 20	99.56 63

PatchT		84.89 138	90.67 110	78.13 193	87.83 133	94.99 129	72.46 216	60.22 222	91.74 125	60.81 156	72.16 142	86.95 81	88.13 127	96.03 64	93.64 91	99.36 85	99.22 86

tpm		83.97 141	87.97 131	79.31 182	87.35 134	93.21 144	86.00 164	61.90 215	90.69 130	54.01 204	79.42 115	75.61 121	88.65 120	87.18 173	90.48 143	97.95 191	99.21 88

IterMVS		85.02 137	88.98 127	80.41 162	87.03 135	90.34 192	89.78 124	69.45 191	89.77 135	54.04 203	73.71 136	82.05 101	83.44 157	95.11 97	93.64 91	98.75 142	98.22 132
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Fast-Effi-MVS+		86.94 126	87.88 132	85.84 113	86.99 136	95.80 119	91.24 112	73.48 168	92.75 112	69.22 124	72.70 139	65.71 155	94.84 68	94.98 99	94.71 74	99.26 98	98.48 117

CDS-MVSNet		88.59 112	90.13 117	86.79 107	86.98 137	95.43 126	92.03 105	81.33 108	85.54 150	74.51 106	77.07 120	85.14 89	87.03 133	93.90 115	95.18 69	98.88 125	98.67 111
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
LP		77.20 201	79.14 194	74.92 206	86.71 138	90.62 185	77.97 204	57.87 225	85.88 147	50.75 210	55.29 210	66.34 153	79.39 185	80.75 217	85.03 207	96.86 203	90.09 210

Effi-MVS+-dtu		87.18 124	90.48 113	83.32 133	86.51 139	95.76 121	91.16 114	74.28 161	90.44 133	61.31 154	86.72 80	72.68 129	91.25 101	95.01 98	93.64 91	95.45 214	99.12 94

Fast-Effi-MVS+-dtu		86.94 126	91.27 100	81.89 143	86.27 140	95.06 127	90.68 119	68.93 195	91.76 122	57.18 187	89.56 62	75.85 119	89.19 115	94.56 104	92.84 109	99.07 111	99.23 84

testgi		82.88 146	86.14 140	79.08 186	86.05 141	92.20 161	81.23 200	74.77 157	88.70 137	57.63 185	86.73 79	61.53 160	76.83 197	90.33 141	89.43 152	97.99 188	94.05 193

testpf		81.62 153	87.82 133	74.38 208	85.88 142	89.26 198	74.45 214	48.92 233	95.87 79	60.31 164	76.95 121	80.17 107	80.07 183	85.72 203	88.77 159	96.67 206	98.01 141

FMVSNet3		91.25 80	92.13 89	90.21 81	85.64 143	93.14 145	95.29 62	80.09 113	96.40 67	85.74 47	77.13 117	86.81 82	94.98 66	97.19 44	97.11 37	99.55 49	97.13 158

GA-MVS		83.83 142	86.63 138	80.58 160	85.40 144	94.73 133	87.27 141	78.76 127	86.49 143	49.57 212	74.21 133	67.67 151	83.38 159	95.28 94	90.92 136	99.08 110	97.09 159

FC-MVSNet-test		85.51 132	89.08 125	81.35 147	85.31 145	93.35 141	87.65 137	77.55 135	90.01 134	64.07 137	79.63 114	81.83 102	74.94 203	92.08 131	90.83 139	98.55 169	95.81 184

GBi-Net		90.49 90	91.12 104	89.75 87	84.99 146	92.73 149	93.94 81	80.09 113	96.40 67	85.74 47	77.13 117	86.81 82	94.42 72	94.12 108	93.73 87	99.35 86	96.90 167

test1		90.49 90	91.12 104	89.75 87	84.99 146	92.73 149	93.94 81	80.09 113	96.40 67	85.74 47	77.13 117	86.81 82	94.42 72	94.12 108	93.73 87	99.35 86	96.90 167

FMVSNet2		89.51 100	89.63 121	89.38 90	84.99 146	92.73 149	93.94 81	79.28 119	93.73 98	84.28 56	69.36 149	82.32 99	94.42 72	96.16 60	96.22 55	99.35 86	96.90 167

TAMVS		85.35 134	86.00 141	84.59 123	84.97 149	95.57 124	88.98 133	77.29 139	81.44 175	71.36 115	71.48 144	75.00 124	87.03 133	91.92 135	92.21 123	97.92 192	94.40 192

tfpnnormal		81.11 157	79.33 190	83.19 135	84.23 150	92.29 156	86.76 149	82.27 98	72.67 214	62.02 149	56.10 205	53.86 210	85.35 140	92.06 132	89.23 154	98.49 174	99.11 97

MVS-HIRNet		79.34 187	82.56 151	75.57 203	84.11 151	95.02 128	75.03 213	57.28 226	85.50 151	55.88 191	53.00 215	70.51 145	83.05 166	92.12 130	91.96 127	98.09 185	89.83 211

TESTMET0.1,1		88.63 110	93.60 67	82.84 139	84.07 152	96.98 102	88.10 135	73.22 170	94.83 85	62.43 145	84.29 99	90.96 69	89.70 113	95.63 79	92.86 107	99.51 54	99.64 51

test-mter		88.25 115	93.27 74	82.38 141	83.89 153	96.86 105	87.10 146	72.80 172	94.58 90	61.85 150	83.21 105	90.65 71	89.18 116	95.43 90	92.58 120	99.46 74	99.61 59

TransMVSNet (Re)		79.51 185	78.36 200	80.84 157	83.17 154	89.72 195	84.22 185	81.45 107	73.98 212	60.79 159	57.20 199	56.05 196	77.11 196	89.88 146	88.86 157	98.30 181	92.83 198

EG-PatchMatch MVS		78.32 196	79.42 189	77.03 200	83.03 155	93.77 140	84.47 183	69.26 193	75.85 209	53.69 206	55.68 208	60.23 165	73.20 208	89.69 150	88.22 170	98.55 169	92.54 199

LTVRE_ROB	79.45 16	79.66 180	80.55 171	78.61 190	83.01 156	92.19 162	87.18 143	73.69 167	71.70 217	43.22 223	71.22 146	50.85 216	87.82 129	89.47 154	90.43 144	96.75 204	98.00 143
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		84.88 139	84.67 146	85.13 118	82.80 157	92.37 154	87.29 140	79.08 120	90.51 132	74.94 105	70.37 148	62.49 159	88.17 126	92.01 133	88.51 163	98.49 174	96.44 174

FMVSNet1		85.85 131	84.91 145	86.96 104	82.70 158	91.39 176	91.54 110	77.45 136	85.29 152	79.56 95	60.70 166	72.68 129	92.37 91	94.12 108	93.73 87	98.12 184	96.44 174

pm-mvs1		81.68 152	81.70 159	81.65 145	82.61 159	92.26 157	85.54 176	78.95 121	76.29 208	63.81 140	58.43 194	66.33 154	80.63 181	92.30 129	89.93 146	98.37 178	96.39 176

NR-MVSNet		82.37 149	81.95 158	82.85 138	82.56 160	92.24 158	87.49 138	81.91 100	86.41 144	65.51 133	63.95 160	52.93 212	80.80 180	89.41 155	89.61 148	98.85 128	99.10 98

our_test_3					81.94 161	90.26 193	75.39 210

UniMVSNet (Re)		83.28 144	83.16 150	83.42 132	81.93 162	93.12 146	86.27 153	80.83 111	85.88 147	68.23 127	64.56 159	60.58 162	84.25 146	89.13 159	89.44 151	99.04 116	99.40 75

SixPastTwentyTwo		80.28 172	82.06 157	78.21 192	81.89 163	92.35 155	77.72 205	74.48 158	83.04 163	54.22 200	76.06 127	56.40 194	83.55 153	86.83 189	84.83 209	97.38 201	94.93 189

v18		80.16 173	80.01 181	80.34 164	81.72 164	85.71 207	86.58 150	70.68 182	83.23 160	60.78 160	60.39 168	58.50 173	83.49 154	87.03 178	88.19 172	98.79 130	97.06 161

v16		80.03 174	79.95 182	80.13 166	81.64 165	85.63 209	86.17 154	70.42 185	83.12 162	60.34 163	60.11 171	58.61 171	83.45 156	86.98 184	88.12 182	98.75 142	97.05 162

v17		79.95 175	79.87 183	80.05 167	81.55 166	85.65 208	86.10 158	70.44 184	82.59 165	60.02 165	60.26 169	58.53 172	83.41 158	86.98 184	88.09 184	98.76 137	97.02 163

v8		80.61 168	80.61 170	80.62 158	81.51 167	91.00 181	86.06 159	74.07 164	81.78 171	59.93 166	60.10 173	58.42 174	83.35 162	86.99 182	88.11 183	98.79 130	97.83 144

pmmvs5		80.48 169	81.43 160	79.36 180	81.50 168	92.24 158	82.07 196	74.08 163	78.10 199	55.86 192	67.72 153	54.35 207	83.91 151	92.97 124	88.65 161	98.77 134	96.01 179

v1neww		81.04 159	80.86 164	81.25 149	81.48 169	92.14 163	86.06 159	78.41 129	82.02 168	59.43 170	60.09 174	58.30 177	83.37 160	87.02 180	88.15 176	98.76 137	98.33 125

v7new		81.04 159	80.86 164	81.25 149	81.48 169	92.14 163	86.06 159	78.41 129	82.02 168	59.43 170	60.09 174	58.30 177	83.37 160	87.02 180	88.15 176	98.76 137	98.33 125

v6		81.06 158	80.87 163	81.28 148	81.47 171	92.12 165	86.14 155	78.42 128	81.99 170	59.68 168	60.14 170	58.36 175	83.22 165	86.99 182	88.14 178	98.76 137	98.32 127

UniMVSNet_NR-MVSNet		83.83 142	83.70 149	83.98 128	81.41 172	92.56 153	86.54 151	82.96 94	85.98 146	66.27 131	66.16 156	63.63 158	87.78 130	87.65 168	90.81 140	98.94 121	99.13 92

WR-MVS_H		79.76 178	80.07 178	79.40 178	81.25 173	91.73 172	82.77 191	74.82 156	79.02 198	62.55 144	59.41 179	57.32 189	76.27 199	87.61 169	87.30 198	98.78 133	98.09 138

v7		80.74 164	80.95 162	80.50 161	81.23 174	91.58 173	86.12 156	74.83 155	82.30 167	57.64 184	58.74 190	57.45 183	84.48 143	89.75 148	88.27 168	98.72 147	98.57 114

v10		80.38 170	80.73 167	79.96 169	81.22 175	90.40 191	86.11 157	71.63 176	82.42 166	57.65 183	58.74 190	57.47 181	84.44 144	89.75 148	88.28 167	98.71 151	98.06 140

V42		80.88 162	80.74 166	81.05 153	81.21 176	92.01 169	85.96 165	77.75 134	81.62 173	59.73 167	59.93 176	58.35 176	82.98 167	86.90 186	88.06 187	98.69 154	98.32 127

v1141		80.70 165	80.42 173	81.02 155	81.14 177	92.03 167	85.94 167	78.92 123	80.59 183	58.40 180	59.32 181	57.41 186	82.97 168	87.10 174	88.16 174	98.72 147	98.37 122

divwei89l23v2f112		80.69 166	80.42 173	81.02 155	81.13 178	92.04 166	85.95 166	78.92 123	80.45 185	58.43 178	59.34 180	57.46 182	82.92 169	87.09 175	88.16 174	98.75 142	98.36 124

v1		80.69 166	80.38 175	81.05 153	81.13 178	92.02 168	86.02 163	78.93 122	80.32 191	58.65 174	59.29 182	57.45 183	82.83 172	87.07 176	88.14 178	98.74 145	98.37 122

gm-plane-assit		77.20 201	82.26 153	71.30 211	81.10 180	82.00 222	54.33 229	64.41 206	63.80 225	40.93 226	59.04 186	76.57 118	87.30 132	98.26 18	97.36 33	99.74 11	98.76 108

v15		79.35 186	79.20 192	79.54 174	81.08 181	85.48 210	85.92 168	70.02 187	80.60 182	58.63 175	59.14 185	57.40 187	82.87 171	86.89 187	87.95 188	98.70 153	96.92 166

v148		79.66 180	79.13 195	80.27 165	81.02 182	91.76 171	81.90 197	79.32 118	79.24 196	63.79 141	58.07 197	54.34 208	77.17 195	84.42 208	87.52 197	98.40 176	98.59 113

V14		79.33 188	79.18 193	79.51 176	81.00 183	85.46 212	85.88 170	69.79 188	80.52 184	58.76 173	59.16 184	57.52 180	82.91 170	86.86 188	87.90 189	98.72 147	96.87 171

v11		79.54 184	79.71 186	79.35 181	80.96 184	85.36 216	85.81 172	69.10 194	81.49 174	57.63 185	58.90 188	57.07 192	83.94 149	90.09 143	88.08 186	98.66 161	96.97 165

N_pmnet		76.83 203	77.97 205	75.50 204	80.96 184	88.23 202	72.81 215	76.83 142	80.87 178	50.55 211	56.94 201	60.09 166	75.70 201	83.28 214	84.23 211	96.14 211	92.12 200

V9		79.23 189	79.09 196	79.39 179	80.95 186	85.40 213	85.85 171	69.63 189	80.42 186	58.45 177	58.94 187	57.42 185	82.77 173	86.79 193	87.85 191	98.69 154	96.83 172

v13		79.09 191	78.98 198	79.22 185	80.88 187	85.34 217	85.50 177	69.40 192	80.36 189	58.14 181	58.62 192	57.30 190	82.70 174	86.72 195	87.75 194	98.67 160	96.76 173

v12		79.16 190	79.04 197	79.30 183	80.88 187	85.37 215	85.45 178	69.52 190	80.39 187	58.57 176	58.90 188	57.17 191	82.68 175	86.76 194	87.82 192	98.68 156	96.88 170

v1144		80.36 171	80.63 169	80.05 167	80.86 189	91.56 174	85.78 173	75.22 151	80.73 180	55.83 193	58.51 193	56.99 193	83.93 150	89.79 147	88.25 169	98.68 156	98.56 115

v2v482		80.86 163	80.52 172	81.25 149	80.79 190	91.85 170	85.68 174	78.78 126	81.05 176	58.09 182	60.46 167	56.08 195	85.45 139	87.27 172	88.53 162	98.73 146	98.38 121

DU-MVS		82.87 147	82.16 156	83.70 131	80.77 191	92.24 158	86.54 151	81.91 100	86.41 144	66.27 131	63.95 160	55.66 200	87.78 130	86.83 189	90.86 138	98.94 121	99.13 92

Baseline_NR-MVSNet		82.08 150	80.64 168	83.77 130	80.77 191	88.50 200	86.88 148	81.71 104	85.58 149	68.80 125	58.20 195	57.75 179	86.16 138	86.83 189	88.68 160	98.33 179	98.90 105

CP-MVSNet		79.90 176	79.49 187	80.38 163	80.72 193	90.83 183	82.98 189	75.17 152	79.70 194	61.39 153	59.74 177	51.98 215	83.31 163	87.37 170	88.38 165	98.71 151	98.45 118

WR-MVS		79.67 179	80.25 176	79.00 188	80.65 194	91.16 178	83.31 187	76.57 143	80.97 177	60.50 162	59.20 183	58.66 170	74.38 205	85.85 201	87.76 193	98.61 164	98.14 133

PS-CasMVS		79.06 192	78.58 199	79.63 171	80.59 195	90.55 188	82.54 194	75.04 153	77.76 200	58.84 172	58.16 196	50.11 220	82.09 177	87.05 177	88.18 173	98.66 161	98.27 130

v1192		79.84 177	80.05 180	79.61 172	80.49 196	91.04 180	85.56 175	74.37 160	80.73 180	54.35 198	57.07 200	54.54 206	84.23 147	89.94 145	88.38 165	98.63 163	98.61 112

TranMVSNet+NR-MVSNet		82.07 151	81.36 161	82.90 137	80.43 197	91.39 176	87.16 144	82.75 95	84.28 159	62.98 143	62.28 164	56.01 197	85.30 141	86.06 199	90.69 142	98.80 129	98.80 107

v144192		79.61 182	79.77 184	79.41 177	80.28 198	91.06 179	84.87 182	73.86 165	79.65 195	55.38 194	57.76 198	55.20 201	83.46 155	88.42 160	87.89 190	98.61 164	98.42 120

v1921920		79.55 183	79.77 184	79.30 183	80.24 199	90.77 184	85.37 179	73.75 166	80.38 188	53.78 205	56.89 202	54.18 209	84.05 148	89.55 152	88.13 181	98.59 166	98.52 116

v1240		78.97 193	79.27 191	78.63 189	80.04 200	90.61 186	84.25 184	72.95 171	79.22 197	52.70 207	56.22 204	52.88 214	83.28 164	89.60 151	88.20 171	98.56 168	98.14 133

PEN-MVS		78.80 195	78.13 202	79.58 173	80.03 201	89.67 196	83.61 186	75.83 146	77.71 202	58.41 179	60.11 171	50.00 221	81.02 179	84.08 209	88.14 178	98.59 166	97.18 157

EU-MVSNet		76.76 206	79.47 188	73.60 209	79.99 202	87.47 203	77.39 206	75.43 149	77.62 203	47.83 215	64.78 158	60.44 164	64.80 214	86.28 197	86.53 201	96.17 210	93.19 197

pmmvs6		76.79 204	75.69 212	78.09 194	79.95 203	89.57 197	80.92 201	74.46 159	64.79 223	60.74 161	45.71 224	60.55 163	78.37 189	88.04 164	86.00 205	94.07 217	95.15 187

FMVSNet5		87.06 125	89.52 123	84.20 125	79.92 204	86.57 205	87.11 145	72.37 174	96.06 75	75.41 104	84.33 98	91.76 64	91.60 97	91.51 136	91.22 133	98.77 134	85.16 219

anonymousdsp		81.29 155	84.52 148	77.52 195	79.83 205	92.62 152	82.61 193	70.88 181	80.76 179	50.82 209	68.35 152	68.76 149	82.45 176	93.00 123	89.45 150	98.55 169	98.69 110

Anonymous20240521		80.95 161	82.17 155	79.53 175	79.69 206	92.77 148	82.89 190	75.40 150	80.29 192	63.89 139	61.97 165	61.30 161	76.51 198	91.01 139	88.79 158	98.79 130	99.06 100

DTE-MVSNet		77.92 197	77.42 206	78.51 191	79.34 207	89.00 199	83.05 188	75.60 147	76.89 204	56.58 188	59.63 178	50.31 218	78.09 193	82.57 216	87.56 196	98.38 177	95.95 180

v748		76.68 207	76.82 209	76.51 201	78.70 208	90.06 194	77.12 207	73.40 169	73.32 213	59.57 169	55.00 212	50.71 217	72.48 209	83.71 213	86.78 200	97.81 196	98.13 136

MDTV_nov1_ep13_2view		78.83 194	82.35 152	74.73 207	78.65 209	91.51 175	79.18 202	62.52 211	84.51 157	52.51 208	67.49 154	67.29 152	78.90 188	85.52 204	86.34 202	96.62 207	93.76 194

v7n		77.71 198	78.25 201	77.09 199	78.49 210	90.55 188	82.15 195	71.11 180	76.79 205	54.18 201	55.63 209	50.20 219	78.28 191	89.36 157	87.15 199	98.33 179	98.07 139

test20.03		72.81 212	76.24 210	68.80 214	78.31 211	85.40 213	71.04 217	71.20 179	71.85 216	43.40 222	65.31 157	54.71 205	51.27 225	85.92 200	84.18 212	97.58 199	86.35 218

FPMVS		63.27 221	61.31 225	65.57 221	78.25 212	74.42 229	75.23 211	68.92 196	72.33 215	43.87 219	49.01 220	43.94 224	48.64 227	61.15 229	58.81 231	78.51 233	69.49 231

Anonymous20231206		74.59 210	77.00 208	71.78 210	77.89 213	87.45 204	75.14 212	72.29 175	77.76 200	46.65 217	52.14 216	52.93 212	61.10 219	89.37 156	88.09 184	97.59 198	91.30 205

V4		77.67 200	78.01 204	77.28 198	77.82 214	90.56 187	81.70 199	71.63 176	76.33 207	55.38 194	55.74 206	55.83 199	79.20 187	84.02 210	86.01 204	97.97 189	97.55 150

v52		77.69 199	78.04 203	77.29 197	77.79 215	90.54 190	81.76 198	71.62 178	76.52 206	55.34 196	55.70 207	55.91 198	79.27 186	84.02 210	86.03 203	97.96 190	97.56 149

MIMVSNet		82.87 147	86.17 139	79.02 187	77.23 216	92.88 147	84.88 181	60.62 220	86.72 142	64.16 136	73.58 137	71.48 132	88.51 123	94.14 107	93.50 98	98.72 147	90.87 208

PM-MVS		75.81 208	76.11 211	75.46 205	73.81 217	85.48 210	76.42 209	70.57 183	80.05 193	54.75 197	62.33 162	39.56 228	80.59 182	87.71 167	82.81 215	96.61 209	94.81 190

test2356		74.04 211	80.07 178	67.01 219	73.77 218	80.65 223	67.82 222	66.87 201	84.93 156	37.70 230	75.45 131	57.40 187	60.26 220	86.28 197	88.47 164	95.64 213	87.33 216

testus		72.50 213	77.19 207	67.04 217	73.69 219	80.06 224	67.65 223	68.24 199	84.46 158	37.48 232	75.90 129	40.07 227	59.40 221	85.45 205	87.69 195	95.76 212	86.70 217

pmmvs-eth3d		75.17 209	74.09 214	76.43 202	72.92 220	84.49 218	76.61 208	72.42 173	74.33 210	61.28 155	54.71 213	39.42 229	78.20 192	87.77 166	84.25 210	97.17 202	93.63 195

new-patchmatchnet		67.66 219	68.07 219	67.18 216	72.85 221	82.86 221	63.09 228	68.61 197	66.60 222	42.64 225	49.28 219	38.68 230	61.21 218	75.84 221	75.22 225	94.67 216	88.00 215

new_pmnet		71.86 214	73.67 215	69.75 213	72.56 222	84.20 219	70.95 219	66.81 202	80.34 190	43.62 221	51.60 217	53.81 211	71.24 211	82.91 215	80.93 216	93.35 219	81.92 221

Anonymous20231211		63.52 220	62.24 224	65.02 222	68.68 223	78.21 226	65.79 225	68.17 200	49.86 233	42.89 224	29.67 233	34.65 232	55.41 223	75.07 222	76.98 223	89.18 227	91.26 206

testmv		60.16 223	62.42 222	57.53 224	67.85 224	69.87 232	48.47 231	62.44 212	54.75 229	29.08 234	46.99 222	31.77 233	45.97 228	74.85 223	79.08 221	91.39 222	79.62 224

test1235678		60.16 223	62.41 223	57.53 224	67.85 224	69.86 233	48.47 231	62.43 213	54.73 230	29.08 234	46.99 222	31.76 234	45.97 228	74.84 224	79.07 222	91.39 222	79.61 225

pmmvs3		69.04 216	70.75 216	67.04 217	66.83 226	78.54 225	64.99 227	60.92 219	64.67 224	40.61 227	55.08 211	40.29 226	74.89 204	83.76 212	84.01 213	93.98 218	88.88 213

1111		61.69 222	63.75 221	59.29 223	64.35 227	70.45 230	48.44 233	48.86 234	55.76 227	39.40 228	39.25 227	54.73 203	62.55 215	77.84 219	80.37 218	92.16 220	67.84 232

.test1245		51.60 228	57.21 227	45.06 230	64.35 227	70.45 230	48.44 233	48.86 234	55.76 227	39.40 228	39.25 227	54.73 203	62.55 215	77.84 219	27.11 235	6.75 239	75.30 229

test12356		57.24 225	59.66 226	54.43 227	64.26 229	66.14 234	49.96 230	61.73 216	54.37 231	28.80 236	44.89 225	25.68 236	32.36 233	70.23 227	79.19 220	89.46 226	77.11 226

PMVS	49.05 18	51.88 227	50.56 230	53.42 228	64.21 230	43.30 239	42.64 237	62.93 208	50.56 232	43.72 220	37.44 229	42.95 225	35.05 232	58.76 232	54.58 232	71.95 235	66.33 234
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MDA-MVSNet-bldmvs		69.61 215	70.36 217	68.74 215	62.88 231	88.50 200	65.40 226	77.01 140	71.60 219	43.93 218	66.71 155	35.33 231	72.47 210	61.01 230	80.63 217	90.73 225	88.75 214

ambc			64.61 220		61.80 232	75.31 228	71.00 218		74.16 211	48.83 213	36.02 231	13.22 241	58.66 222	85.80 202	76.26 224	88.01 228	91.53 204

Gipuma		54.59 226	53.98 228	55.30 226	59.03 233	52.63 237	47.17 236	56.08 229	71.68 218	37.54 231	20.90 235	19.00 237	52.33 224	71.69 226	75.20 226	79.64 232	66.79 233
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MIMVSNet1		68.63 217	70.24 218	66.76 220	56.86 234	83.26 220	67.93 221	70.26 186	68.05 221	46.80 216	40.44 226	48.15 222	62.01 217	84.96 207	84.86 208	96.69 205	81.93 220

no-one		41.64 230	41.19 231	42.16 231	52.35 235	58.34 236	27.46 239	57.21 227	28.41 239	21.09 238	19.65 236	17.04 238	21.39 238	39.74 234	61.20 230	73.45 234	63.95 236

PMMVS2		50.69 229	52.33 229	48.78 229	51.24 236	64.81 235	47.91 235	53.79 232	44.95 234	21.75 237	29.98 232	25.90 235	31.98 235	59.95 231	65.37 228	86.00 230	75.36 228

EMVS		36.45 232	33.63 234	39.74 233	48.47 237	35.73 240	23.59 241	55.11 231	35.61 236	12.88 241	17.49 237	14.62 239	41.04 230	29.33 236	43.00 234	57.32 237	59.62 238

E-PMN		37.15 231	34.82 233	39.86 232	47.53 238	35.42 241	23.79 240	55.26 230	35.18 237	14.12 240	17.38 239	14.13 240	39.73 231	32.24 235	46.98 233	58.76 236	62.39 237

MVE	42.40 19	36.00 233	38.65 232	32.92 235	29.16 239	46.17 238	22.61 242	44.21 236	26.44 240	18.88 239	17.41 238	9.36 242	32.29 234	45.75 233	61.38 229	50.35 238	64.03 235
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
testmvs		21.55 234	30.91 235	10.62 236	2.78 240	11.66 242	18.51 243	4.82 237	38.21 235	4.06 242	36.35 230	4.47 243	26.81 236	23.27 237	27.11 235	6.75 239	75.30 229

GG-mvs-BLEND		67.99 218	97.35 34	33.72 234	1.22 241	99.72 13	98.30 29	0.57 239	97.61 54	1.18 243	93.26 46	96.63 37	1.74 239	97.15 45	97.14 36	99.34 90	99.96 6

test123		16.81 235	24.80 236	7.48 237	0.82 242	8.38 243	11.92 244	2.60 238	28.96 238	1.12 244	28.39 234	1.26 244	24.51 237	8.93 238	22.19 237	3.90 241	75.49 227

sosnet-low-res		0.00 236	0.00 237	0.00 238	0.00 243	0.00 244	0.00 245	0.00 240	0.00 241	0.00 245	0.00 240	0.00 245	0.00 240	0.00 239	0.00 238	0.00 242	0.00 239

sosnet		0.00 236	0.00 237	0.00 238	0.00 243	0.00 244	0.00 245	0.00 240	0.00 241	0.00 245	0.00 240	0.00 245	0.00 240	0.00 239	0.00 238	0.00 242	0.00 239

MTAPA										94.58 9		98.56 18

MTMP										95.24 4		98.13 24

Patchmatch-RL test							37.05 238

NP-MVS									97.69 50

Patchmtry						95.86 117	89.43 128	61.37 217		60.81 156

DeepMVS_CX						85.88 206	69.83 220	81.56 105	87.99 138	48.22 214	71.85 143	45.52 223	68.67 212	63.21 228		86.64 229	80.03 223

High-resolution multi-view benchmark