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 44	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 43	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 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 10	93.88 12	98.64 11	99.98 1	99.04 5	98.89 8	97.49 30	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 19	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 48	99.56 44	99.14 93

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 40	99.58 34	99.06 101

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 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 85

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 16	89.65 61	91.74 64	96.96 35	93.69 119	96.58 52	98.86 129	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 32	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 31	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 38	97.40 32	99.60 28	99.25 84

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 53	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 51	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 41	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 30	96.37 57	94.79 73	99.41 81	98.12 138
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 57	84.59 96	95.60 42	97.21 33	97.10 47	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	84.21 102	94.55 47	97.25 32	95.50 89	96.23 54	99.28 98	99.09 100

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	97.65 147

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 80	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	81.92 100	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 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 64	94.26 82	98.07 187	99.27 83

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 98	94.80 36	95.74 40	96.11 54	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 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 17	84.67 95	97.33 32	97.55 28	97.32 41	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 76	95.95 31	99.16 11	95.13 65	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 53	86.17 46	98.92 4	92.81 57	96.10 55	95.67 78	93.33 102	99.55 50	99.12 96
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 44	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 62	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 75	87.84 71	93.94 52	96.50 47	95.74 75	94.27 81	99.46 75	97.31 155
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 73	97.20 44	97.23 36	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 70	88.05 51	98.61 26	82.29 69	98.85 5	94.66 44	94.63 72	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	91.45 113	94.42 31	99.76 1	86.48 45	92.88 50	98.12 25	92.62 91	99.49 2	99.32 2	95.15 216	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 58	76.74 124	80.89 104	92.54 92	93.97 115	93.61 97	99.14 105	95.10 189

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 45	99.81 6	99.96 6

EPNet_dtu		89.82 97	94.18 60	84.74 123	96.87 47	95.54 127	92.65 95	86.91 61	96.99 61	54.17 204	92.41 51	88.54 73	78.35 192	96.15 62	96.05 60	99.47 64	93.60 197
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	80.68 112	88.02 75	96.92 38	97.49 40	98.20 12	99.47 64	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 59	92.82 80	92.21 57	96.57 49	98.74 61	91.85 109	86.30 67	96.23 72	85.18 52	95.21 33	73.58 127	94.22 77	95.40 92	93.08 106	99.14 105	97.49 153

DELS-MVS		93.82 50	93.82 63	93.81 45	96.34 50	99.47 35	97.26 45	88.53 49	92.13 118	87.80 38	79.67 114	88.01 76	93.14 83	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 60	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	72.46 113	81.39 110	80.76 105	97.66 25	95.69 77	95.62 65	99.07 113	97.02 164

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	92.00 120	81.51 79	82.97 107	93.88 54	95.63 64	94.24 107	94.71 76	99.09 111	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	88.24 118	87.32 138	89.32 92	95.83 54	95.82 120	92.81 91	87.68 57	92.09 119	72.64 112	72.34 142	79.96 108	88.79 120	89.54 154	89.46 151	98.16 184	92.00 203
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	75.02 123	93.08 84	97.89 25	96.90 46	99.56 44	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	75.02 123	93.08 84	97.89 25	96.90 46	99.56 44	100.00 1

CHOSEN 280x420		94.51 46	97.78 31	90.70 74	95.54 57	99.49 33	94.14 80	74.91 155	98.43 30	85.32 51	94.78 37	99.19 10	94.95 69	97.02 49	96.18 57	99.35 87	99.36 76

CHOSEN 1792x2688		88.63 112	89.01 127	88.19 100	94.83 58	99.21 54	92.66 94	79.85 117	92.40 116	72.18 114	56.38 204	80.22 106	90.24 111	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 78	83.50 104	93.19 56	94.71 71	98.24 19	98.07 19	99.68 17	99.83 32

HyFIR lowres test		87.86 121	88.25 131	87.40 102	94.67 60	98.54 74	90.33 123	76.51 146	89.60 138	70.89 119	51.43 219	85.69 87	92.79 88	96.59 55	95.96 63	99.22 103	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	76.71 102	94.68 38	69.41 150	96.91 39	95.80 73	94.18 83	99.26 99	96.33 178

OPM-MVS		89.33 104	87.45 137	91.53 67	94.49 62	96.20 115	96.47 50	89.72 42	82.77 166	75.43 104	80.53 113	70.86 144	93.80 80	94.00 113	91.85 131	99.29 97	95.91 182

HQP-MVS		91.94 69	93.03 76	90.66 76	93.69 63	96.48 112	95.92 52	89.73 41	97.33 57	72.65 111	95.37 32	73.56 128	92.75 90	94.85 101	94.12 84	99.23 102	99.51 68

XVS					93.63 64	99.64 20	94.32 77			83.97 59		98.08 26				99.59 30

X-MVStestdata					93.63 64	99.64 20	94.32 77			83.97 59		98.08 26				99.59 30

PVSNet_Blended_VisFu		91.20 82	92.89 78	89.23 93	93.41 66	98.61 72	89.80 125	85.39 82	92.84 112	82.80 65	74.21 134	91.38 67	84.64 144	97.22 43	96.04 61	99.34 91	99.93 15

LGP-MVS_train		90.34 94	91.63 92	88.83 96	93.31 67	96.14 116	95.49 59	85.24 84	93.91 97	68.71 128	93.96 43	71.63 133	91.12 105	93.82 117	92.79 120	99.07 113	99.16 92

ACMM	89.40 10	90.58 89	90.02 119	91.23 71	93.30 68	94.75 134	90.69 120	88.22 50	95.20 83	82.70 67	88.54 63	71.40 135	93.48 81	93.64 120	90.94 137	98.99 121	95.72 186
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CMPMVS	58.73 17	76.78 206	74.27 214	79.70 172	93.26 69	95.58 125	82.74 193	77.44 139	71.46 221	56.29 192	53.58 215	59.13 170	77.33 196	79.20 219	79.71 220	91.14 225	81.24 223
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
RPSCF		89.81 98	89.75 121	89.88 86	93.22 70	93.99 141	94.78 70	85.23 85	94.01 96	82.52 68	95.00 35	87.23 79	92.01 96	85.16 207	83.48 215	91.54 222	89.38 213

MS-PatchMatch		87.19 125	88.59 129	85.55 118	93.15 71	96.58 110	92.35 100	74.19 163	91.97 121	70.33 123	71.42 146	85.89 85	84.28 147	93.12 122	89.16 157	99.00 120	91.99 204

IB-MVS	84.67 14	88.34 115	90.61 112	85.70 116	92.99 72	98.62 71	78.85 204	86.07 74	94.35 94	88.64 34	85.99 88	75.69 120	68.09 214	88.21 162	91.43 134	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 99	92.72 73	98.00 85	90.22 124	84.81 86	94.45 93	83.05 64	87.65 73	92.74 58	81.04 180	94.51 106	94.45 79	99.32 96	99.21 89
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	91.15 103	90.21 80	92.55 74	96.52 111	92.63 96	85.71 78	94.65 90	81.06 81	93.32 45	70.56 146	90.52 109	92.68 130	91.05 136	98.76 138	99.31 81
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
UA-Net		89.56 100	93.03 76	85.52 119	92.46 75	97.55 96	91.92 108	81.91 101	85.24 155	71.39 115	83.57 103	96.56 38	76.01 201	96.81 52	97.04 42	99.46 75	94.41 192

CANet_DTU		91.36 77	95.75 44	86.23 112	92.31 76	98.71 63	95.60 58	78.41 131	98.20 36	56.48 191	94.38 42	87.96 77	95.11 66	96.89 50	96.07 58	99.48 60	98.01 142

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	85.40 135	85.73 144	85.02 121	91.76 78	94.46 139	84.97 182	81.54 107	85.18 156	65.22 137	76.92 123	64.22 158	88.58 124	90.17 143	90.25 147	98.03 188	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 64	86.42 64	93.24 105	82.20 72	92.98 49	79.35 113	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 60	91.65 80	98.84 59	95.03 64	86.38 66	93.24 105	82.03 74	91.90 56	77.54 116	96.80 42	95.78 74	92.82 114	99.48 60	99.90 21

tfpn111		91.99 68	92.28 86	91.65 63	91.61 81	98.69 64	95.03 64	86.17 68	93.24 105	80.82 82	94.67 39	71.15 136	96.80 42	95.53 82	92.82 114	99.47 64	99.88 24

conf200view11		91.47 75	91.31 97	91.65 63	91.61 81	98.69 64	95.03 64	86.17 68	93.24 105	80.82 82	87.90 67	71.15 136	96.80 42	95.53 82	92.82 114	99.47 64	99.88 24

thres100view900		91.69 72	91.52 94	91.88 61	91.61 81	98.89 57	95.49 59	86.96 60	93.24 105	80.82 82	87.90 67	71.15 136	96.88 40	96.00 68	93.51 99	99.51 55	99.95 9

tfpn200view9		91.47 75	91.31 97	91.65 63	91.61 81	98.69 64	95.03 64	86.17 68	93.24 105	80.82 82	87.90 67	71.15 136	96.80 42	95.53 82	92.82 114	99.47 64	99.88 24

thres200		91.36 77	91.19 102	91.55 66	91.60 85	98.69 64	94.98 69	86.17 68	92.16 117	80.76 86	87.66 72	71.15 136	96.35 49	95.53 82	93.23 105	99.47 64	99.92 18

thres400		91.24 81	91.01 107	91.50 68	91.56 86	98.77 60	94.66 74	86.41 65	91.87 122	80.56 87	87.05 76	71.01 141	96.35 49	95.67 78	92.82 114	99.48 60	99.88 24

view600		90.97 85	90.70 109	91.30 69	91.53 87	98.69 64	94.33 75	86.17 68	91.75 124	80.19 89	86.06 86	70.90 142	96.10 55	95.53 82	92.08 127	99.47 64	99.86 30

thres600view7		90.97 85	90.70 109	91.30 69	91.53 87	98.69 64	94.33 75	86.17 68	91.75 124	80.19 89	86.06 86	70.90 142	96.10 55	95.53 82	92.08 127	99.47 64	99.86 30

view800		90.79 87	90.54 113	91.09 72	91.50 89	98.58 73	94.09 81	85.92 75	91.57 127	79.68 92	85.29 93	70.72 145	95.91 58	95.40 92	92.39 123	99.47 64	99.83 32

tfpn		91.26 79	91.55 93	90.92 73	91.47 90	98.50 76	93.85 85	85.72 77	91.40 128	79.30 96	84.78 94	77.33 117	95.70 63	95.29 94	93.73 89	99.47 64	99.82 34

tfpn_ndepth		92.26 65	93.84 62	90.42 77	91.45 91	97.91 88	92.73 93	85.80 76	96.69 64	82.22 70	91.92 55	83.42 95	90.76 108	95.51 88	93.28 103	99.58 34	98.14 134

canonicalmvs		92.54 59	93.28 73	91.68 62	91.44 92	98.24 80	95.45 61	81.84 104	95.98 77	84.85 54	90.69 59	78.53 114	96.96 35	92.97 126	97.06 41	99.57 39	99.47 72

PMMVS		93.05 54	95.40 47	90.31 79	91.41 93	97.54 97	92.62 97	83.25 94	98.08 43	79.44 95	95.18 34	88.52 74	96.43 48	95.70 76	93.88 87	98.68 157	98.91 104

tfpn1000		91.48 74	93.17 75	89.51 90	91.27 94	97.71 91	92.08 103	85.28 83	96.13 74	80.20 88	90.77 58	82.52 98	88.64 123	95.17 97	92.35 124	99.56 44	97.52 152

DWT-MVSNet_training		92.09 67	93.58 69	90.35 78	91.27 94	97.94 87	92.05 104	78.82 127	97.40 56	88.83 33	87.91 66	86.76 84	91.99 97	90.03 145	95.25 69	99.13 108	99.73 41

CLD-MVS		91.67 73	91.30 100	92.10 58	91.25 96	96.59 109	95.93 51	87.25 59	96.86 63	85.55 50	87.08 74	73.01 130	93.26 82	93.07 124	92.84 111	99.34 91	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 57	94.99 52	89.96 85	91.17 97	98.54 74	92.77 92	84.00 88	92.72 114	81.90 77	85.67 90	92.47 59	90.39 110	97.82 30	97.81 22	99.51 55	99.91 19

thresconf0.02		92.16 66	95.16 49	88.67 97	91.10 98	97.63 94	92.93 90	86.58 63	96.29 70	73.55 109	94.67 39	88.63 72	88.29 127	96.14 63	95.40 68	99.58 34	97.33 154

EPMVS		89.31 105	93.70 65	84.18 128	91.10 98	98.10 83	89.17 134	62.71 210	96.24 71	70.21 125	86.46 81	92.37 61	92.79 88	91.95 136	93.59 98	99.10 110	97.19 156

Vis-MVSNet (Re-imp)		91.05 84	94.43 54	87.11 105	91.05 100	97.99 86	92.53 98	83.82 90	92.71 115	76.28 103	84.50 98	92.43 60	79.52 186	97.24 42	97.68 24	99.43 79	98.45 119

TDRefinement		81.49 156	80.08 178	83.13 138	91.02 101	94.53 137	91.66 111	82.43 97	81.70 174	62.12 149	62.30 165	59.32 169	73.93 208	87.31 172	85.29 207	97.61 198	90.14 210

conf0.05thres1000		88.28 116	87.54 136	89.15 94	91.00 102	97.50 99	92.18 102	84.70 87	85.15 157	73.91 108	73.77 136	70.50 149	94.01 78	93.99 114	92.21 125	99.11 109	99.64 51

tfpnview11		90.36 93	92.74 81	87.59 101	90.93 103	97.30 102	92.28 101	85.63 79	95.88 78	70.44 120	92.30 52	79.50 110	86.76 137	95.26 96	92.83 113	99.51 55	96.09 179

Anonymous20240521		89.08 107	88.25 131	90.05 84	90.91 104	98.16 81	94.78 70	86.87 62	90.82 131	70.94 118	67.60 155	73.12 129	97.40 29	93.33 121	95.42 67	99.37 83	99.30 82

MVSTER		94.75 43	96.50 38	92.70 56	90.91 104	94.51 138	97.37 44	83.37 92	98.40 33	89.04 31	93.23 47	97.04 35	95.91 58	97.73 33	95.59 66	99.61 27	99.01 102

tfpn_n400		90.13 95	92.47 82	87.40 102	90.89 106	97.37 100	92.05 104	85.47 80	93.43 102	70.44 120	92.30 52	79.50 110	86.50 138	94.84 102	93.93 85	99.07 113	95.91 182

tfpnconf		90.13 95	92.47 82	87.40 102	90.89 106	97.37 100	92.05 104	85.47 80	93.43 102	70.44 120	92.30 52	79.50 110	86.50 138	94.84 102	93.93 85	99.07 113	95.91 182

ACMH+	85.62 12	85.27 137	84.96 146	85.64 117	90.84 108	94.78 133	87.46 141	81.30 110	86.94 143	67.35 131	74.56 133	64.09 159	88.70 121	88.14 163	89.00 158	98.22 183	97.19 156

casdiffmvs		92.52 61	94.57 53	90.13 82	90.72 109	98.26 78	95.06 63	81.08 111	97.65 52	78.18 100	85.79 89	85.40 88	96.16 53	97.65 36	98.10 18	99.57 39	99.18 91

MVS_Test		92.42 62	94.43 54	90.08 83	90.69 110	98.26 78	94.78 70	80.81 113	97.27 59	78.76 97	87.06 75	84.25 92	95.84 61	97.67 34	97.56 29	99.59 30	98.93 103

tpmrst		86.78 130	90.29 115	82.69 142	90.55 111	96.95 106	88.49 136	62.58 211	95.09 85	63.52 144	76.67 126	84.00 94	92.05 95	87.93 166	91.89 130	98.98 122	99.50 70

FC-MVSNet-train		89.37 103	89.62 123	89.08 95	90.48 112	94.16 140	89.45 129	83.99 89	91.09 129	80.09 91	82.84 108	74.52 126	91.44 102	93.79 118	91.57 133	99.01 119	99.35 77

ADS-MVSNet		86.68 132	90.79 108	81.88 146	90.38 113	96.81 108	86.90 149	60.50 222	96.01 76	63.93 141	81.67 109	84.72 90	90.78 107	87.03 179	91.67 132	98.77 135	97.63 148

EPP-MVSNet		92.29 64	94.35 58	89.88 86	90.36 114	97.69 92	90.89 117	83.31 93	93.39 104	83.47 63	85.56 91	93.92 53	91.93 98	95.49 90	94.77 75	99.34 91	99.62 58

tmp_tt				71.24 213	90.29 115	76.39 228	65.81 225	59.43 225	97.62 53	79.65 93	90.60 60	68.71 152	49.71 227	72.71 226	65.70 228	82.54 232

diffmvs		90.43 92	92.02 90	88.58 98	90.16 116	98.12 82	92.37 99	78.97 122	95.32 82	76.88 101	86.37 82	75.69 120	93.98 79	94.82 104	95.22 70	99.14 105	98.58 114

DI_MVS_plusplus_trai		91.11 83	91.47 95	90.68 75	90.01 117	97.77 89	95.87 55	83.56 91	94.72 89	82.12 73	68.46 151	87.46 78	93.07 86	96.46 56	95.73 64	99.47 64	99.71 44

CostFormer		89.42 102	91.67 91	86.80 108	89.99 118	96.33 114	90.75 118	64.79 206	95.17 84	83.62 62	86.20 84	82.15 100	92.96 87	89.22 159	92.94 107	98.68 157	99.65 49

tpmp4_e23		88.10 119	90.02 119	85.86 114	89.94 119	95.73 124	91.83 110	64.92 204	94.79 88	78.25 99	81.03 111	78.34 115	92.33 94	88.10 164	92.82 114	97.90 194	99.34 80

dps		88.66 111	90.19 117	86.88 107	89.94 119	96.48 112	89.56 127	64.08 208	94.12 95	89.00 32	83.39 105	82.56 97	90.16 113	86.81 193	89.26 155	98.53 173	98.71 109

tpm cat1		87.34 124	88.52 130	85.95 113	89.83 121	95.80 121	90.73 119	64.91 205	92.99 111	82.21 71	71.19 148	82.68 96	90.13 114	86.38 197	90.87 139	97.90 194	99.74 39

USDC		85.11 138	85.35 145	84.83 122	89.45 122	94.93 132	92.98 89	77.30 140	90.53 133	61.80 154	76.69 125	59.62 168	88.90 119	92.78 129	90.79 143	98.53 173	92.12 201

PatchmatchNet		88.67 110	94.10 61	82.34 144	89.38 123	97.72 90	87.24 144	62.18 215	97.00 60	64.79 138	87.97 65	94.43 48	91.55 100	91.21 140	92.77 121	98.90 125	97.60 149
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Vis-MVSNet		87.60 122	91.31 97	83.27 136	89.14 124	98.04 84	90.35 122	79.42 118	87.23 142	66.92 132	79.10 117	84.63 91	74.34 207	95.81 72	96.06 59	99.46 75	98.32 128
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Effi-MVS+		88.96 108	91.13 104	86.43 110	89.12 125	97.62 95	93.15 88	75.52 150	93.90 98	66.40 133	86.23 83	70.51 147	95.03 67	95.89 69	94.28 80	99.37 83	99.51 68

TinyColmap		83.03 147	82.24 156	83.95 131	88.88 126	93.22 145	89.48 128	76.89 143	87.53 141	62.12 149	68.46 151	55.03 203	88.43 126	90.87 141	89.65 149	97.89 196	90.91 208

RPMNet		87.35 123	92.41 85	81.45 148	88.85 127	96.06 117	89.42 132	59.59 224	93.57 100	61.81 153	76.48 127	91.48 66	90.18 112	96.32 59	93.37 101	98.87 128	99.59 60

IterMVS-LS		87.95 120	89.40 125	86.26 111	88.79 128	90.93 183	91.23 115	76.05 147	90.87 130	71.07 117	75.51 131	81.18 103	91.21 104	94.11 112	95.01 72	99.20 104	98.23 132
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MDTV_nov1_ep13		89.63 99	94.38 57	84.09 129	88.76 129	97.53 98	89.37 133	68.46 199	96.95 62	70.27 124	87.88 70	93.67 55	91.04 106	93.12 122	93.83 88	96.62 208	97.68 146

CR-MVSNet		86.73 131	91.47 95	81.20 154	88.56 130	96.06 117	89.43 130	61.37 218	93.57 100	60.81 158	72.89 139	88.85 71	88.13 129	96.03 65	93.64 93	98.89 126	99.22 87

CVMVSNet		84.01 142	86.91 139	80.61 161	88.39 131	93.29 144	86.06 161	82.29 98	83.13 163	54.29 201	72.68 141	79.59 109	75.11 203	91.23 139	92.91 108	97.54 201	95.58 187

test-LLR		89.31 105	93.60 67	84.30 126	88.08 132	96.98 104	88.10 137	78.00 134	94.83 86	62.43 147	84.29 100	90.96 68	89.70 115	95.63 80	92.86 109	99.51 55	99.64 51

test0.0.03 1		88.71 109	92.22 88	84.63 124	88.08 132	94.71 136	85.91 171	78.00 134	95.54 80	72.96 110	86.10 85	85.88 86	83.59 154	92.95 128	93.24 104	99.25 101	97.09 160

gg-mvs-nofinetune		81.27 158	84.65 149	77.32 197	87.96 134	98.48 77	95.64 57	56.36 229	59.35 227	32.80 234	47.96 222	92.11 62	91.49 101	98.12 21	97.00 44	99.65 20	99.56 63

PatchT		84.89 140	90.67 111	78.13 194	87.83 135	94.99 131	72.46 217	60.22 223	91.74 126	60.81 158	72.16 143	86.95 80	88.13 129	96.03 65	93.64 93	99.36 86	99.22 87

tpm		83.97 143	87.97 133	79.31 183	87.35 136	93.21 146	86.00 166	61.90 216	90.69 132	54.01 206	79.42 116	75.61 122	88.65 122	87.18 174	90.48 145	97.95 192	99.21 89

IterMVS		85.02 139	88.98 128	80.41 164	87.03 137	90.34 193	89.78 126	69.45 192	89.77 137	54.04 205	73.71 137	82.05 101	83.44 159	95.11 98	93.64 93	98.75 143	98.22 133
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Fast-Effi-MVS+		86.94 128	87.88 134	85.84 115	86.99 138	95.80 121	91.24 114	73.48 169	92.75 113	69.22 126	72.70 140	65.71 157	94.84 70	94.98 100	94.71 76	99.26 99	98.48 118

CDS-MVSNet		88.59 114	90.13 118	86.79 109	86.98 139	95.43 128	92.03 107	81.33 109	85.54 152	74.51 107	77.07 121	85.14 89	87.03 135	93.90 116	95.18 71	98.88 127	98.67 111
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
LP		77.20 202	79.14 195	74.92 207	86.71 140	90.62 186	77.97 205	57.87 226	85.88 149	50.75 212	55.29 211	66.34 155	79.39 187	80.75 218	85.03 208	96.86 204	90.09 211

Effi-MVS+-dtu		87.18 126	90.48 114	83.32 135	86.51 141	95.76 123	91.16 116	74.28 162	90.44 135	61.31 156	86.72 80	72.68 131	91.25 103	95.01 99	93.64 93	95.45 215	99.12 96

Fast-Effi-MVS+-dtu		86.94 128	91.27 101	81.89 145	86.27 142	95.06 129	90.68 121	68.93 196	91.76 123	57.18 189	89.56 62	75.85 119	89.19 117	94.56 105	92.84 111	99.07 113	99.23 85

testgi		82.88 148	86.14 142	79.08 187	86.05 143	92.20 162	81.23 201	74.77 158	88.70 139	57.63 187	86.73 79	61.53 162	76.83 199	90.33 142	89.43 154	97.99 189	94.05 194

testpf		81.62 155	87.82 135	74.38 209	85.88 144	89.26 199	74.45 215	48.92 234	95.87 79	60.31 166	76.95 122	80.17 107	80.07 185	85.72 204	88.77 160	96.67 207	98.01 142

FMVSNet3		91.25 80	92.13 89	90.21 80	85.64 145	93.14 147	95.29 62	80.09 114	96.40 67	85.74 47	77.13 118	86.81 81	94.98 68	97.19 45	97.11 38	99.55 50	97.13 159

GA-MVS		83.83 144	86.63 140	80.58 162	85.40 146	94.73 135	87.27 143	78.76 129	86.49 145	49.57 214	74.21 134	67.67 153	83.38 161	95.28 95	90.92 138	99.08 112	97.09 160

FC-MVSNet-test		85.51 134	89.08 126	81.35 149	85.31 147	93.35 143	87.65 139	77.55 137	90.01 136	64.07 140	79.63 115	81.83 102	74.94 204	92.08 133	90.83 141	98.55 170	95.81 185

GBi-Net		90.49 90	91.12 105	89.75 88	84.99 148	92.73 150	93.94 82	80.09 114	96.40 67	85.74 47	77.13 118	86.81 81	94.42 74	94.12 109	93.73 89	99.35 87	96.90 168

test1		90.49 90	91.12 105	89.75 88	84.99 148	92.73 150	93.94 82	80.09 114	96.40 67	85.74 47	77.13 118	86.81 81	94.42 74	94.12 109	93.73 89	99.35 87	96.90 168

FMVSNet2		89.51 101	89.63 122	89.38 91	84.99 148	92.73 150	93.94 82	79.28 120	93.73 99	84.28 56	69.36 150	82.32 99	94.42 74	96.16 61	96.22 56	99.35 87	96.90 168

TAMVS		85.35 136	86.00 143	84.59 125	84.97 151	95.57 126	88.98 135	77.29 141	81.44 177	71.36 116	71.48 145	75.00 125	87.03 135	91.92 137	92.21 125	97.92 193	94.40 193

tfpnnormal		81.11 159	79.33 191	83.19 137	84.23 152	92.29 157	86.76 151	82.27 99	72.67 215	62.02 151	56.10 206	53.86 211	85.35 142	92.06 134	89.23 156	98.49 175	99.11 98

MVS-HIRNet		79.34 188	82.56 153	75.57 204	84.11 153	95.02 130	75.03 214	57.28 227	85.50 153	55.88 193	53.00 216	70.51 147	83.05 168	92.12 132	91.96 129	98.09 186	89.83 212

TESTMET0.1,1		88.63 112	93.60 67	82.84 141	84.07 154	96.98 104	88.10 137	73.22 171	94.83 86	62.43 147	84.29 100	90.96 68	89.70 115	95.63 80	92.86 109	99.51 55	99.64 51

test-mter		88.25 117	93.27 74	82.38 143	83.89 155	96.86 107	87.10 148	72.80 173	94.58 91	61.85 152	83.21 106	90.65 70	89.18 118	95.43 91	92.58 122	99.46 75	99.61 59

TransMVSNet (Re)		79.51 186	78.36 201	80.84 159	83.17 156	89.72 196	84.22 187	81.45 108	73.98 213	60.79 161	57.20 200	56.05 197	77.11 198	89.88 147	88.86 159	98.30 182	92.83 199

EG-PatchMatch MVS		78.32 197	79.42 190	77.03 201	83.03 157	93.77 142	84.47 185	69.26 194	75.85 210	53.69 208	55.68 209	60.23 166	73.20 209	89.69 151	88.22 171	98.55 170	92.54 200

LTVRE_ROB	79.45 16	79.66 181	80.55 172	78.61 191	83.01 158	92.19 163	87.18 145	73.69 168	71.70 218	43.22 225	71.22 147	50.85 217	87.82 131	89.47 155	90.43 146	96.75 205	98.00 144
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		84.88 141	84.67 148	85.13 120	82.80 159	92.37 155	87.29 142	79.08 121	90.51 134	74.94 106	70.37 149	62.49 161	88.17 128	92.01 135	88.51 164	98.49 175	96.44 175

FMVSNet1		85.85 133	84.91 147	86.96 106	82.70 160	91.39 177	91.54 112	77.45 138	85.29 154	79.56 94	60.70 167	72.68 131	92.37 93	94.12 109	93.73 89	98.12 185	96.44 175

pm-mvs1		81.68 154	81.70 160	81.65 147	82.61 161	92.26 158	85.54 178	78.95 123	76.29 209	63.81 142	58.43 195	66.33 156	80.63 183	92.30 131	89.93 148	98.37 179	96.39 177

NR-MVSNet		82.37 151	81.95 159	82.85 140	82.56 162	92.24 159	87.49 140	81.91 101	86.41 146	65.51 136	63.95 162	52.93 213	80.80 182	89.41 156	89.61 150	98.85 130	99.10 99

our_test_3					81.94 163	90.26 194	75.39 211

UniMVSNet (Re)		83.28 146	83.16 152	83.42 134	81.93 164	93.12 148	86.27 155	80.83 112	85.88 149	68.23 129	64.56 161	60.58 163	84.25 148	89.13 160	89.44 153	99.04 118	99.40 75

SixPastTwentyTwo		80.28 173	82.06 158	78.21 193	81.89 165	92.35 156	77.72 206	74.48 159	83.04 165	54.22 202	76.06 128	56.40 195	83.55 155	86.83 190	84.83 210	97.38 202	94.93 190

v18		80.16 174	80.01 182	80.34 166	81.72 166	85.71 208	86.58 152	70.68 183	83.23 162	60.78 162	60.39 169	58.50 174	83.49 156	87.03 179	88.19 173	98.79 132	97.06 162

v16		80.03 175	79.95 183	80.13 168	81.64 167	85.63 210	86.17 156	70.42 186	83.12 164	60.34 165	60.11 172	58.61 172	83.45 158	86.98 185	88.12 183	98.75 143	97.05 163

v17		79.95 176	79.87 184	80.05 169	81.55 168	85.65 209	86.10 160	70.44 185	82.59 167	60.02 167	60.26 170	58.53 173	83.41 160	86.98 185	88.09 185	98.76 138	97.02 164

v8		80.61 169	80.61 171	80.62 160	81.51 169	91.00 182	86.06 161	74.07 165	81.78 173	59.93 168	60.10 174	58.42 175	83.35 164	86.99 183	88.11 184	98.79 132	97.83 145

pmmvs5		80.48 170	81.43 161	79.36 181	81.50 170	92.24 159	82.07 197	74.08 164	78.10 200	55.86 194	67.72 154	54.35 208	83.91 153	92.97 126	88.65 162	98.77 135	96.01 180

v1neww		81.04 161	80.86 165	81.25 151	81.48 171	92.14 164	86.06 161	78.41 131	82.02 170	59.43 172	60.09 175	58.30 178	83.37 162	87.02 181	88.15 177	98.76 138	98.33 126

v7new		81.04 161	80.86 165	81.25 151	81.48 171	92.14 164	86.06 161	78.41 131	82.02 170	59.43 172	60.09 175	58.30 178	83.37 162	87.02 181	88.15 177	98.76 138	98.33 126

v6		81.06 160	80.87 164	81.28 150	81.47 173	92.12 166	86.14 157	78.42 130	81.99 172	59.68 170	60.14 171	58.36 176	83.22 167	86.99 183	88.14 179	98.76 138	98.32 128

UniMVSNet_NR-MVSNet		83.83 144	83.70 151	83.98 130	81.41 174	92.56 154	86.54 153	82.96 95	85.98 148	66.27 134	66.16 158	63.63 160	87.78 132	87.65 169	90.81 142	98.94 123	99.13 94

WR-MVS_H		79.76 179	80.07 179	79.40 179	81.25 175	91.73 173	82.77 192	74.82 157	79.02 199	62.55 146	59.41 180	57.32 190	76.27 200	87.61 170	87.30 199	98.78 134	98.09 139

v7		80.74 165	80.95 163	80.50 163	81.23 176	91.58 174	86.12 158	74.83 156	82.30 169	57.64 186	58.74 191	57.45 184	84.48 145	89.75 149	88.27 169	98.72 148	98.57 115

v10		80.38 171	80.73 168	79.96 171	81.22 177	90.40 192	86.11 159	71.63 177	82.42 168	57.65 185	58.74 191	57.47 182	84.44 146	89.75 149	88.28 168	98.71 152	98.06 141

V42		80.88 163	80.74 167	81.05 155	81.21 178	92.01 170	85.96 167	77.75 136	81.62 175	59.73 169	59.93 177	58.35 177	82.98 169	86.90 187	88.06 188	98.69 155	98.32 128

v1141		80.70 166	80.42 174	81.02 157	81.14 179	92.03 168	85.94 169	78.92 125	80.59 185	58.40 182	59.32 182	57.41 187	82.97 170	87.10 175	88.16 175	98.72 148	98.37 123

divwei89l23v2f112		80.69 167	80.42 174	81.02 157	81.13 180	92.04 167	85.95 168	78.92 125	80.45 187	58.43 180	59.34 181	57.46 183	82.92 171	87.09 176	88.16 175	98.75 143	98.36 125

v1		80.69 167	80.38 176	81.05 155	81.13 180	92.02 169	86.02 165	78.93 124	80.32 193	58.65 176	59.29 183	57.45 184	82.83 174	87.07 177	88.14 179	98.74 146	98.37 123

gm-plane-assit		77.20 202	82.26 155	71.30 212	81.10 182	82.00 223	54.33 230	64.41 207	63.80 226	40.93 227	59.04 187	76.57 118	87.30 134	98.26 18	97.36 34	99.74 11	98.76 108

v15		79.35 187	79.20 193	79.54 176	81.08 183	85.48 211	85.92 170	70.02 188	80.60 184	58.63 177	59.14 186	57.40 188	82.87 173	86.89 188	87.95 189	98.70 154	96.92 167

v148		79.66 181	79.13 196	80.27 167	81.02 184	91.76 172	81.90 198	79.32 119	79.24 197	63.79 143	58.07 198	54.34 209	77.17 197	84.42 209	87.52 198	98.40 177	98.59 113

V14		79.33 189	79.18 194	79.51 177	81.00 185	85.46 213	85.88 172	69.79 189	80.52 186	58.76 175	59.16 185	57.52 181	82.91 172	86.86 189	87.90 190	98.72 148	96.87 172

v11		79.54 185	79.71 187	79.35 182	80.96 186	85.36 217	85.81 174	69.10 195	81.49 176	57.63 187	58.90 189	57.07 193	83.94 151	90.09 144	88.08 187	98.66 162	96.97 166

N_pmnet		76.83 204	77.97 206	75.50 205	80.96 186	88.23 203	72.81 216	76.83 144	80.87 180	50.55 213	56.94 202	60.09 167	75.70 202	83.28 215	84.23 212	96.14 212	92.12 201

V9		79.23 190	79.09 197	79.39 180	80.95 188	85.40 214	85.85 173	69.63 190	80.42 188	58.45 179	58.94 188	57.42 186	82.77 175	86.79 194	87.85 192	98.69 155	96.83 173

v13		79.09 192	78.98 199	79.22 186	80.88 189	85.34 218	85.50 179	69.40 193	80.36 191	58.14 183	58.62 193	57.30 191	82.70 176	86.72 196	87.75 195	98.67 161	96.76 174

v12		79.16 191	79.04 198	79.30 184	80.88 189	85.37 216	85.45 180	69.52 191	80.39 189	58.57 178	58.90 189	57.17 192	82.68 177	86.76 195	87.82 193	98.68 157	96.88 171

v1144		80.36 172	80.63 170	80.05 169	80.86 191	91.56 175	85.78 175	75.22 152	80.73 182	55.83 195	58.51 194	56.99 194	83.93 152	89.79 148	88.25 170	98.68 157	98.56 116

v2v482		80.86 164	80.52 173	81.25 151	80.79 192	91.85 171	85.68 176	78.78 128	81.05 178	58.09 184	60.46 168	56.08 196	85.45 141	87.27 173	88.53 163	98.73 147	98.38 122

DU-MVS		82.87 149	82.16 157	83.70 133	80.77 193	92.24 159	86.54 153	81.91 101	86.41 146	66.27 134	63.95 162	55.66 201	87.78 132	86.83 190	90.86 140	98.94 123	99.13 94

Baseline_NR-MVSNet		82.08 152	80.64 169	83.77 132	80.77 193	88.50 201	86.88 150	81.71 105	85.58 151	68.80 127	58.20 196	57.75 180	86.16 140	86.83 190	88.68 161	98.33 180	98.90 105

CP-MVSNet		79.90 177	79.49 188	80.38 165	80.72 195	90.83 184	82.98 191	75.17 153	79.70 195	61.39 155	59.74 178	51.98 216	83.31 165	87.37 171	88.38 166	98.71 152	98.45 119

WR-MVS		79.67 180	80.25 177	79.00 189	80.65 196	91.16 179	83.31 189	76.57 145	80.97 179	60.50 164	59.20 184	58.66 171	74.38 206	85.85 202	87.76 194	98.61 165	98.14 134

PS-CasMVS		79.06 193	78.58 200	79.63 173	80.59 197	90.55 189	82.54 195	75.04 154	77.76 201	58.84 174	58.16 197	50.11 221	82.09 179	87.05 178	88.18 174	98.66 162	98.27 131

v1192		79.84 178	80.05 181	79.61 174	80.49 198	91.04 181	85.56 177	74.37 161	80.73 182	54.35 200	57.07 201	54.54 207	84.23 149	89.94 146	88.38 166	98.63 164	98.61 112

TranMVSNet+NR-MVSNet		82.07 153	81.36 162	82.90 139	80.43 199	91.39 177	87.16 146	82.75 96	84.28 161	62.98 145	62.28 166	56.01 198	85.30 143	86.06 200	90.69 144	98.80 131	98.80 107

v144192		79.61 183	79.77 185	79.41 178	80.28 200	91.06 180	84.87 184	73.86 166	79.65 196	55.38 196	57.76 199	55.20 202	83.46 157	88.42 161	87.89 191	98.61 165	98.42 121

v1921920		79.55 184	79.77 185	79.30 184	80.24 201	90.77 185	85.37 181	73.75 167	80.38 190	53.78 207	56.89 203	54.18 210	84.05 150	89.55 153	88.13 182	98.59 167	98.52 117

v1240		78.97 194	79.27 192	78.63 190	80.04 202	90.61 187	84.25 186	72.95 172	79.22 198	52.70 209	56.22 205	52.88 215	83.28 166	89.60 152	88.20 172	98.56 169	98.14 134

PEN-MVS		78.80 196	78.13 203	79.58 175	80.03 203	89.67 197	83.61 188	75.83 148	77.71 203	58.41 181	60.11 172	50.00 222	81.02 181	84.08 210	88.14 179	98.59 167	97.18 158

EU-MVSNet		76.76 207	79.47 189	73.60 210	79.99 204	87.47 204	77.39 207	75.43 151	77.62 204	47.83 217	64.78 160	60.44 165	64.80 215	86.28 198	86.53 202	96.17 211	93.19 198

pmmvs6		76.79 205	75.69 213	78.09 195	79.95 205	89.57 198	80.92 202	74.46 160	64.79 224	60.74 163	45.71 225	60.55 164	78.37 191	88.04 165	86.00 206	94.07 218	95.15 188

FMVSNet5		87.06 127	89.52 124	84.20 127	79.92 206	86.57 206	87.11 147	72.37 175	96.06 75	75.41 105	84.33 99	91.76 63	91.60 99	91.51 138	91.22 135	98.77 135	85.16 220

anonymousdsp		81.29 157	84.52 150	77.52 196	79.83 207	92.62 153	82.61 194	70.88 182	80.76 181	50.82 211	68.35 153	68.76 151	82.45 178	93.00 125	89.45 152	98.55 170	98.69 110

DTE-MVSNet		77.92 198	77.42 207	78.51 192	79.34 208	89.00 200	83.05 190	75.60 149	76.89 205	56.58 190	59.63 179	50.31 219	78.09 195	82.57 217	87.56 197	98.38 178	95.95 181

v748		76.68 208	76.82 210	76.51 202	78.70 209	90.06 195	77.12 208	73.40 170	73.32 214	59.57 171	55.00 213	50.71 218	72.48 210	83.71 214	86.78 201	97.81 197	98.13 137

MDTV_nov1_ep13_2view		78.83 195	82.35 154	74.73 208	78.65 210	91.51 176	79.18 203	62.52 212	84.51 159	52.51 210	67.49 156	67.29 154	78.90 190	85.52 205	86.34 203	96.62 208	93.76 195

v7n		77.71 199	78.25 202	77.09 200	78.49 211	90.55 189	82.15 196	71.11 181	76.79 206	54.18 203	55.63 210	50.20 220	78.28 193	89.36 158	87.15 200	98.33 180	98.07 140

test20.03		72.81 213	76.24 211	68.80 216	78.31 212	85.40 214	71.04 218	71.20 180	71.85 217	43.40 224	65.31 159	54.71 206	51.27 226	85.92 201	84.18 213	97.58 200	86.35 219

FPMVS		63.27 222	61.31 226	65.57 223	78.25 213	74.42 230	75.23 212	68.92 197	72.33 216	43.87 221	49.01 221	43.94 225	48.64 228	61.15 230	58.81 232	78.51 234	69.49 232

Anonymous20231206		74.59 211	77.00 209	71.78 211	77.89 214	87.45 205	75.14 213	72.29 176	77.76 201	46.65 219	52.14 217	52.93 213	61.10 220	89.37 157	88.09 185	97.59 199	91.30 206

V4		77.67 201	78.01 205	77.28 199	77.82 215	90.56 188	81.70 200	71.63 177	76.33 208	55.38 196	55.74 207	55.83 200	79.20 189	84.02 211	86.01 205	97.97 190	97.55 151

v52		77.69 200	78.04 204	77.29 198	77.79 216	90.54 191	81.76 199	71.62 179	76.52 207	55.34 198	55.70 208	55.91 199	79.27 188	84.02 211	86.03 204	97.96 191	97.56 150

MIMVSNet		82.87 149	86.17 141	79.02 188	77.23 217	92.88 149	84.88 183	60.62 221	86.72 144	64.16 139	73.58 138	71.48 134	88.51 125	94.14 108	93.50 100	98.72 148	90.87 209

PM-MVS		75.81 209	76.11 212	75.46 206	73.81 218	85.48 211	76.42 210	70.57 184	80.05 194	54.75 199	62.33 164	39.56 229	80.59 184	87.71 168	82.81 216	96.61 210	94.81 191

test2356		74.04 212	80.07 179	67.01 221	73.77 219	80.65 224	67.82 223	66.87 202	84.93 158	37.70 231	75.45 132	57.40 188	60.26 221	86.28 198	88.47 165	95.64 214	87.33 217

testus		72.50 214	77.19 208	67.04 219	73.69 220	80.06 225	67.65 224	68.24 200	84.46 160	37.48 233	75.90 130	40.07 228	59.40 222	85.45 206	87.69 196	95.76 213	86.70 218

pmmvs-eth3d		75.17 210	74.09 215	76.43 203	72.92 221	84.49 219	76.61 209	72.42 174	74.33 211	61.28 157	54.71 214	39.42 230	78.20 194	87.77 167	84.25 211	97.17 203	93.63 196

new-patchmatchnet		67.66 220	68.07 220	67.18 218	72.85 222	82.86 222	63.09 229	68.61 198	66.60 223	42.64 226	49.28 220	38.68 231	61.21 219	75.84 222	75.22 226	94.67 217	88.00 216

new_pmnet		71.86 215	73.67 216	69.75 214	72.56 223	84.20 220	70.95 220	66.81 203	80.34 192	43.62 223	51.60 218	53.81 212	71.24 212	82.91 216	80.93 217	93.35 220	81.92 222

Anonymous20231211		65.42 221	62.24 225	69.13 215	68.68 224	78.21 227	65.79 226	68.17 201	49.86 234	67.57 130	29.67 234	34.65 233	55.41 224	75.07 223	76.98 224	89.18 228	91.26 207

testmv		60.16 224	62.42 223	57.53 225	67.85 225	69.87 233	48.47 232	62.44 213	54.75 230	29.08 235	46.99 223	31.77 234	45.97 229	74.85 224	79.08 222	91.39 223	79.62 225

test1235678		60.16 224	62.41 224	57.53 225	67.85 225	69.86 234	48.47 232	62.43 214	54.73 231	29.08 235	46.99 223	31.76 235	45.97 229	74.84 225	79.07 223	91.39 223	79.61 226

pmmvs3		69.04 217	70.75 217	67.04 219	66.83 227	78.54 226	64.99 228	60.92 220	64.67 225	40.61 228	55.08 212	40.29 227	74.89 205	83.76 213	84.01 214	93.98 219	88.88 214

1111		61.69 223	63.75 222	59.29 224	64.35 228	70.45 231	48.44 234	48.86 235	55.76 228	39.40 229	39.25 228	54.73 204	62.55 216	77.84 220	80.37 219	92.16 221	67.84 233

.test1245		51.60 229	57.21 228	45.06 231	64.35 228	70.45 231	48.44 234	48.86 235	55.76 228	39.40 229	39.25 228	54.73 204	62.55 216	77.84 220	27.11 236	6.75 240	75.30 230

test12356		57.24 226	59.66 227	54.43 228	64.26 230	66.14 235	49.96 231	61.73 217	54.37 232	28.80 237	44.89 226	25.68 237	32.36 234	70.23 228	79.19 221	89.46 227	77.11 227

PMVS	49.05 18	51.88 228	50.56 231	53.42 229	64.21 231	43.30 240	42.64 238	62.93 209	50.56 233	43.72 222	37.44 230	42.95 226	35.05 233	58.76 233	54.58 233	71.95 236	66.33 235
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MDA-MVSNet-bldmvs		69.61 216	70.36 218	68.74 217	62.88 232	88.50 201	65.40 227	77.01 142	71.60 220	43.93 220	66.71 157	35.33 232	72.47 211	61.01 231	80.63 218	90.73 226	88.75 215

ambc			64.61 221		61.80 233	75.31 229	71.00 219		74.16 212	48.83 215	36.02 232	13.22 242	58.66 223	85.80 203	76.26 225	88.01 229	91.53 205

Gipuma		54.59 227	53.98 229	55.30 227	59.03 234	52.63 238	47.17 237	56.08 230	71.68 219	37.54 232	20.90 236	19.00 238	52.33 225	71.69 227	75.20 227	79.64 233	66.79 234
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MIMVSNet1		68.63 218	70.24 219	66.76 222	56.86 235	83.26 221	67.93 222	70.26 187	68.05 222	46.80 218	40.44 227	48.15 223	62.01 218	84.96 208	84.86 209	96.69 206	81.93 221

no-one		41.64 231	41.19 232	42.16 232	52.35 236	58.34 237	27.46 240	57.21 228	28.41 240	21.09 239	19.65 237	17.04 239	21.39 239	39.74 235	61.20 231	73.45 235	63.95 237

PMMVS2		50.69 230	52.33 230	48.78 230	51.24 237	64.81 236	47.91 236	53.79 233	44.95 235	21.75 238	29.98 233	25.90 236	31.98 236	59.95 232	65.37 229	86.00 231	75.36 229

EMVS		36.45 233	33.63 235	39.74 234	48.47 238	35.73 241	23.59 242	55.11 232	35.61 237	12.88 242	17.49 238	14.62 240	41.04 231	29.33 237	43.00 235	57.32 238	59.62 239

E-PMN		37.15 232	34.82 234	39.86 233	47.53 239	35.42 242	23.79 241	55.26 231	35.18 238	14.12 241	17.38 240	14.13 241	39.73 232	32.24 236	46.98 234	58.76 237	62.39 238

MVE	42.40 19	36.00 234	38.65 233	32.92 236	29.16 240	46.17 239	22.61 243	44.21 237	26.44 241	18.88 240	17.41 239	9.36 243	32.29 235	45.75 234	61.38 230	50.35 239	64.03 236
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
testmvs		21.55 235	30.91 236	10.62 237	2.78 241	11.66 243	18.51 244	4.82 238	38.21 236	4.06 243	36.35 231	4.47 244	26.81 237	23.27 238	27.11 236	6.75 240	75.30 230

GG-mvs-BLEND		67.99 219	97.35 34	33.72 235	1.22 242	99.72 13	98.30 29	0.57 240	97.61 55	1.18 244	93.26 46	96.63 37	1.74 240	97.15 46	97.14 37	99.34 91	99.96 6

test123		16.81 236	24.80 237	7.48 238	0.82 243	8.38 244	11.92 245	2.60 239	28.96 239	1.12 245	28.39 235	1.26 245	24.51 238	8.93 239	22.19 238	3.90 242	75.49 228

sosnet-low-res		0.00 237	0.00 238	0.00 239	0.00 244	0.00 245	0.00 246	0.00 241	0.00 242	0.00 246	0.00 241	0.00 246	0.00 241	0.00 240	0.00 239	0.00 243	0.00 240

sosnet		0.00 237	0.00 238	0.00 239	0.00 244	0.00 245	0.00 246	0.00 241	0.00 242	0.00 246	0.00 241	0.00 246	0.00 241	0.00 240	0.00 239	0.00 243	0.00 240

MTAPA										94.58 9		98.56 18

MTMP										95.24 4		98.13 24

Patchmatch-RL test							37.05 239

NP-MVS									97.69 50

Patchmtry						95.86 119	89.43 130	61.37 218		60.81 158

DeepMVS_CX						85.88 207	69.83 221	81.56 106	87.99 140	48.22 216	71.85 144	45.52 224	68.67 213	63.21 229		86.64 230	80.03 224

High-resolution multi-view benchmark