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 94

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	99.06 102

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 86

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 78

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 60	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 85

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 78
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	98.12 139
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 58	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	99.09 101

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	97.65 148

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 81	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	81.92 101	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 84

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 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 77	95.95 31	99.16 11	95.13 66	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 97
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 63	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 76	87.84 71	93.94 52	96.50 47	95.74 75	94.27 81	99.46 75	97.31 156
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 75	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 70	98.85 5	94.66 44	94.63 74	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	91.45 114	94.42 31	99.76 1	86.48 45	92.88 50	98.12 25	92.62 92	99.49 2	99.32 2	95.15 217	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 59	76.74 124	80.89 104	92.54 93	93.97 115	93.61 97	99.14 106	95.10 190

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	84.74 123	96.87 47	95.54 128	92.65 97	86.91 61	96.99 61	54.17 204	92.41 51	88.54 73	78.35 193	96.15 62	96.05 60	99.47 64	93.60 198
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 67	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	91.85 110	86.30 67	96.23 72	85.18 52	95.21 33	73.58 128	94.22 79	95.40 93	93.08 106	99.14 106	97.49 154

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 84	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	72.46 114	81.39 110	80.76 105	97.66 25	95.69 77	95.62 65	99.07 113	97.02 165

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 80	82.97 107	93.88 54	95.63 65	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	88.24 118	87.32 139	89.32 92	95.83 54	95.82 121	92.81 93	87.68 57	92.09 119	72.64 113	72.34 142	79.96 109	88.79 121	89.54 155	89.46 152	98.16 185	92.00 204
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	75.02 124	93.08 85	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	75.02 124	93.08 85	97.89 25	96.90 46	99.56 45	100.00 1

CHOSEN 280x420		94.51 46	97.78 31	90.70 75	95.54 57	99.49 33	94.14 80	74.91 156	98.43 30	85.32 51	94.78 37	99.19 10	94.95 70	97.02 49	96.18 57	99.35 87	99.36 77

CHOSEN 1792x2688		88.63 112	89.01 127	88.19 100	94.83 58	99.21 54	92.66 96	79.85 119	92.40 116	72.18 115	56.38 205	80.22 107	90.24 112	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 79	83.50 104	93.19 56	94.71 72	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	90.33 124	76.51 147	89.60 139	70.89 119	51.43 220	85.69 87	92.79 89	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	76.71 103	94.68 38	69.41 151	96.91 39	95.80 73	94.18 83	99.26 100	96.33 179

OPM-MVS		89.33 105	87.45 138	91.53 68	94.49 62	96.20 116	96.47 50	89.72 42	82.77 167	75.43 105	80.53 113	70.86 145	93.80 81	94.00 113	91.85 132	99.29 97	95.91 183

HQP-MVS		91.94 69	93.03 76	90.66 77	93.69 63	96.48 113	95.92 52	89.73 41	97.33 57	72.65 112	95.37 32	73.56 129	92.75 91	94.85 102	94.12 84	99.23 103	99.51 68

XVS					93.63 64	99.64 20	94.32 77			83.97 60		98.08 26				99.59 31

X-MVStestdata					93.63 64	99.64 20	94.32 77			83.97 60		98.08 26				99.59 31

PVSNet_Blended_VisFu		91.20 82	92.89 78	89.23 93	93.41 66	98.61 72	89.80 126	85.39 82	92.84 112	82.80 66	74.21 134	91.38 67	84.64 145	97.22 43	96.04 61	99.34 91	99.93 15

LGP-MVS_train		90.34 94	91.63 92	88.83 97	93.31 67	96.14 117	95.49 59	85.24 85	93.91 97	68.71 128	93.96 43	71.63 134	91.12 106	93.82 117	92.79 120	99.07 113	99.16 93

ACMM	89.40 10	90.58 90	90.02 119	91.23 72	93.30 68	94.75 135	90.69 121	88.22 50	95.20 83	82.70 68	88.54 63	71.40 136	93.48 82	93.64 120	90.94 138	98.99 121	95.72 187
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CMPMVS	58.73 17	76.78 206	74.27 215	79.70 172	93.26 69	95.58 126	82.74 194	77.44 140	71.46 222	56.29 192	53.58 216	59.13 171	77.33 197	79.20 220	79.71 221	91.14 226	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 86	93.22 70	93.99 142	94.78 70	85.23 86	94.01 96	82.52 69	95.00 35	87.23 79	92.01 97	85.16 208	83.48 216	91.54 223	89.38 214

MS-PatchMatch		87.19 125	88.59 129	85.55 118	93.15 71	96.58 111	92.35 101	74.19 164	91.97 121	70.33 123	71.42 146	85.89 85	84.28 148	93.12 122	89.16 158	99.00 120	91.99 205

IB-MVS	84.67 14	88.34 115	90.61 112	85.70 116	92.99 72	98.62 71	78.85 205	86.07 74	94.35 94	88.64 34	85.99 88	75.69 121	68.09 215	88.21 163	91.43 135	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	90.22 125	84.81 87	94.45 93	83.05 65	87.65 73	92.74 58	81.04 181	94.51 106	94.45 79	99.32 96	99.21 90
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 81	92.55 74	96.52 112	92.63 98	85.71 78	94.65 90	81.06 82	93.32 45	70.56 147	90.52 110	92.68 130	91.05 137	98.76 138	99.31 82
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
UA-Net		89.56 101	93.03 76	85.52 119	92.46 75	97.55 96	91.92 109	81.91 102	85.24 156	71.39 116	83.57 103	96.56 38	76.01 202	96.81 52	97.04 42	99.46 75	94.41 193

CANet_DTU		91.36 77	95.75 44	86.23 112	92.31 76	98.71 63	95.60 58	78.41 132	98.20 36	56.48 191	94.38 42	87.96 77	95.11 67	96.89 50	96.07 58	99.48 60	98.01 143

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	85.73 145	85.02 121	91.76 78	94.46 140	84.97 183	81.54 108	85.18 157	65.22 137	76.92 123	64.22 159	88.58 125	90.17 144	90.25 148	98.03 189	98.90 106
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 73	92.98 49	79.35 114	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 75	91.90 56	77.54 117	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 83	94.67 39	71.15 137	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 83	87.90 67	71.15 137	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 83	87.90 67	71.15 137	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 83	87.90 67	71.15 137	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	92.16 117	80.76 87	87.66 72	71.15 137	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	91.87 122	80.56 88	87.05 76	71.01 142	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	91.75 124	80.19 90	86.06 86	70.90 143	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	91.75 124	80.19 90	86.06 86	70.90 143	96.10 55	95.53 82	92.08 128	99.47 64	99.86 30

view800		90.79 87	90.54 113	91.09 73	91.50 89	98.58 73	94.09 81	85.92 75	91.57 127	79.68 93	85.29 93	70.72 146	95.91 58	95.40 93	92.39 124	99.47 64	99.83 32

tfpn		91.26 79	91.55 93	90.92 74	91.47 90	98.50 76	93.85 85	85.72 77	91.40 129	79.30 97	84.78 94	77.33 118	95.70 64	95.29 95	93.73 89	99.47 64	99.82 34

tfpn_ndepth		92.26 65	93.84 62	90.42 78	91.45 91	97.91 88	92.73 95	85.80 76	96.69 64	82.22 71	91.92 55	83.42 95	90.76 109	95.51 88	93.28 103	99.58 35	98.14 135

canonicalmvs		92.54 59	93.28 73	91.68 63	91.44 92	98.24 80	95.45 61	81.84 105	95.98 77	84.85 54	90.69 59	78.53 115	96.96 35	92.97 126	97.06 41	99.57 40	99.47 72

PMMVS		93.05 54	95.40 47	90.31 80	91.41 93	97.54 97	92.62 99	83.25 95	98.08 43	79.44 96	95.18 34	88.52 74	96.43 48	95.70 76	93.88 87	98.68 157	98.91 105

tfpn1000		91.48 74	93.17 75	89.51 90	91.27 94	97.71 91	92.08 104	85.28 84	96.13 74	80.20 89	90.77 58	82.52 98	88.64 124	95.17 98	92.35 125	99.56 45	97.52 153

DWT-MVSNet_training		92.09 67	93.58 69	90.35 79	91.27 94	97.94 87	92.05 105	78.82 128	97.40 56	88.83 33	87.91 66	86.76 84	91.99 98	90.03 146	95.25 70	99.13 108	99.73 41

CLD-MVS		91.67 73	91.30 100	92.10 59	91.25 96	96.59 110	95.93 51	87.25 59	96.86 63	85.55 50	87.08 74	73.01 131	93.26 83	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 85	91.17 97	98.54 74	92.77 94	84.00 89	92.72 114	81.90 78	85.67 90	92.47 59	90.39 111	97.82 30	97.81 22	99.51 55	99.91 19

thresconf0.02		92.16 66	95.16 49	88.67 98	91.10 98	97.63 94	92.93 92	86.58 63	96.29 70	73.55 110	94.67 39	88.63 72	88.29 128	96.14 63	95.40 69	99.58 35	97.33 155

EPMVS		89.31 106	93.70 65	84.18 128	91.10 98	98.10 82	89.17 135	62.71 211	96.24 71	70.21 125	86.46 82	92.37 61	92.79 89	91.95 136	93.59 98	99.10 110	97.19 157

Vis-MVSNet (Re-imp)		91.05 84	94.43 54	87.11 105	91.05 100	97.99 86	92.53 100	83.82 91	92.71 115	76.28 104	84.50 98	92.43 60	79.52 187	97.24 42	97.68 24	99.43 79	98.45 119

TDRefinement		81.49 156	80.08 179	83.13 138	91.02 101	94.53 138	91.66 112	82.43 98	81.70 175	62.12 149	62.30 165	59.32 170	73.93 209	87.31 173	85.29 208	97.61 199	90.14 211

conf0.05thres1000		88.28 116	87.54 136	89.15 95	91.00 102	97.50 99	92.18 103	84.70 88	85.15 158	73.91 109	73.77 136	70.50 150	94.01 80	93.99 114	92.21 126	99.11 109	99.64 50

tfpnview11		90.36 93	92.74 81	87.59 101	90.93 103	97.30 102	92.28 102	85.63 79	95.88 78	70.44 120	92.30 52	79.50 111	86.76 138	95.26 97	92.83 113	99.51 55	96.09 180

Anonymous20240521		90.11 97	88.25 131	92.28 57	90.91 104	98.16 81	94.78 70	86.87 62	90.82 132	84.37 56	67.60 155	73.12 130	97.40 29	93.33 121	95.42 68	99.37 83	99.30 83

MVSTER		94.75 43	96.50 38	92.70 56	90.91 104	94.51 139	97.37 44	83.37 93	98.40 33	89.04 31	93.23 47	97.04 35	95.91 58	97.73 33	95.59 66	99.61 27	99.01 103

tfpn_n400		90.13 95	92.47 82	87.40 102	90.89 106	97.37 100	92.05 105	85.47 80	93.43 102	70.44 120	92.30 52	79.50 111	86.50 139	94.84 103	93.93 85	99.07 113	95.91 183

tfpnconf		90.13 95	92.47 82	87.40 102	90.89 106	97.37 100	92.05 105	85.47 80	93.43 102	70.44 120	92.30 52	79.50 111	86.50 139	94.84 103	93.93 85	99.07 113	95.91 183

ACMH+	85.62 12	85.27 137	84.96 147	85.64 117	90.84 108	94.78 134	87.46 142	81.30 111	86.94 144	67.35 131	74.56 133	64.09 160	88.70 122	88.14 164	89.00 159	98.22 184	97.19 157

Anonymous202405211			87.54 136		90.72 109	97.10 104	93.40 88	85.30 83	91.41 128		60.23 171	80.69 106	95.80 62	91.33 139	92.60 122	98.38 178	99.40 75

casdiffmvs		92.52 61	94.57 53	90.13 83	90.72 109	98.26 78	95.06 63	81.08 112	97.65 52	78.18 101	85.79 89	85.40 88	96.16 53	97.65 36	98.10 18	99.57 40	99.18 92

MVS_Test		92.42 62	94.43 54	90.08 84	90.69 111	98.26 78	94.78 70	80.81 114	97.27 59	78.76 98	87.06 75	84.25 92	95.84 61	97.67 34	97.56 29	99.59 31	98.93 104

tpmrst		86.78 130	90.29 115	82.69 142	90.55 112	96.95 107	88.49 137	62.58 212	95.09 85	63.52 144	76.67 126	84.00 94	92.05 96	87.93 167	91.89 131	98.98 122	99.50 70

FC-MVSNet-train		89.37 104	89.62 123	89.08 96	90.48 113	94.16 141	89.45 130	83.99 90	91.09 130	80.09 92	82.84 108	74.52 127	91.44 103	93.79 118	91.57 134	99.01 119	99.35 78

ADS-MVSNet		86.68 132	90.79 108	81.88 146	90.38 114	96.81 109	86.90 150	60.50 223	96.01 76	63.93 141	81.67 109	84.72 90	90.78 108	87.03 180	91.67 133	98.77 135	97.63 149

EPP-MVSNet		92.29 64	94.35 58	89.88 86	90.36 115	97.69 92	90.89 118	83.31 94	93.39 104	83.47 64	85.56 91	93.92 53	91.93 99	95.49 90	94.77 75	99.34 91	99.62 57

tmp_tt				71.24 213	90.29 116	76.39 229	65.81 226	59.43 226	97.62 53	79.65 94	90.60 60	68.71 153	49.71 228	72.71 227	65.70 229	82.54 233

DI_MVS_plusplus_trai		91.11 83	91.47 95	90.68 76	90.01 117	97.77 89	95.87 55	83.56 92	94.72 89	82.12 74	68.46 151	87.46 78	93.07 87	96.46 56	95.73 64	99.47 64	99.71 43

CostFormer		89.42 103	91.67 91	86.80 108	89.99 118	96.33 115	90.75 119	64.79 207	95.17 84	83.62 63	86.20 84	82.15 100	92.96 88	89.22 160	92.94 107	98.68 157	99.65 48

tpmp4_e23		88.10 119	90.02 119	85.86 114	89.94 119	95.73 125	91.83 111	64.92 205	94.79 88	78.25 100	81.03 111	78.34 116	92.33 95	88.10 165	92.82 114	97.90 195	99.34 81

dps		88.66 111	90.19 117	86.88 107	89.94 119	96.48 113	89.56 128	64.08 209	94.12 95	89.00 32	83.39 105	82.56 97	90.16 114	86.81 194	89.26 156	98.53 173	98.71 110

diffmvs		90.73 88	92.06 90	89.17 94	89.83 121	98.03 84	93.32 89	80.32 115	95.23 82	77.63 102	86.49 81	75.24 123	94.65 73	95.47 91	95.54 67	99.27 99	98.40 122

tpm cat1		87.34 124	88.52 130	85.95 113	89.83 121	95.80 122	90.73 120	64.91 206	92.99 111	82.21 72	71.19 148	82.68 96	90.13 115	86.38 198	90.87 140	97.90 195	99.74 39

USDC		85.11 138	85.35 146	84.83 122	89.45 123	94.93 133	92.98 91	77.30 141	90.53 134	61.80 154	76.69 125	59.62 169	88.90 120	92.78 129	90.79 144	98.53 173	92.12 202

PatchmatchNet		88.67 110	94.10 61	82.34 144	89.38 124	97.72 90	87.24 145	62.18 216	97.00 60	64.79 138	87.97 65	94.43 48	91.55 101	91.21 141	92.77 121	98.90 125	97.60 150
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	89.14 125	98.04 83	90.35 123	79.42 120	87.23 143	66.92 132	79.10 117	84.63 91	74.34 208	95.81 72	96.06 59	99.46 75	98.32 129
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	89.12 126	97.62 95	93.15 90	75.52 151	93.90 98	66.40 133	86.23 83	70.51 148	95.03 68	95.89 69	94.28 80	99.37 83	99.51 68

TinyColmap		83.03 147	82.24 157	83.95 131	88.88 127	93.22 146	89.48 129	76.89 144	87.53 142	62.12 149	68.46 151	55.03 204	88.43 127	90.87 142	89.65 150	97.89 197	90.91 209

RPMNet		87.35 123	92.41 85	81.45 148	88.85 128	96.06 118	89.42 133	59.59 225	93.57 100	61.81 153	76.48 127	91.48 66	90.18 113	96.32 59	93.37 101	98.87 128	99.59 59

IterMVS-LS		87.95 120	89.40 125	86.26 111	88.79 129	90.93 184	91.23 116	76.05 148	90.87 131	71.07 118	75.51 131	81.18 103	91.21 105	94.11 112	95.01 72	99.20 105	98.23 133
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	84.09 129	88.76 130	97.53 98	89.37 134	68.46 200	96.95 62	70.27 124	87.88 70	93.67 55	91.04 107	93.12 122	93.83 88	96.62 209	97.68 147

CR-MVSNet		86.73 131	91.47 95	81.20 154	88.56 131	96.06 118	89.43 131	61.37 219	93.57 100	60.81 158	72.89 139	88.85 71	88.13 130	96.03 65	93.64 93	98.89 126	99.22 88

CVMVSNet		84.01 142	86.91 140	80.61 161	88.39 132	93.29 145	86.06 162	82.29 99	83.13 164	54.29 201	72.68 141	79.59 110	75.11 204	91.23 140	92.91 108	97.54 202	95.58 188

test-LLR		89.31 106	93.60 67	84.30 126	88.08 133	96.98 105	88.10 138	78.00 135	94.83 86	62.43 147	84.29 100	90.96 68	89.70 116	95.63 80	92.86 109	99.51 55	99.64 50

test0.0.03 1		88.71 109	92.22 88	84.63 124	88.08 133	94.71 137	85.91 172	78.00 135	95.54 80	72.96 111	86.10 85	85.88 86	83.59 155	92.95 128	93.24 104	99.25 102	97.09 161

gg-mvs-nofinetune		81.27 158	84.65 150	77.32 197	87.96 135	98.48 77	95.64 57	56.36 230	59.35 228	32.80 234	47.96 223	92.11 62	91.49 102	98.12 21	97.00 44	99.65 20	99.56 63

PatchT		84.89 140	90.67 111	78.13 194	87.83 136	94.99 132	72.46 218	60.22 224	91.74 126	60.81 158	72.16 143	86.95 80	88.13 130	96.03 65	93.64 93	99.36 86	99.22 88

tpm		83.97 143	87.97 133	79.31 183	87.35 137	93.21 147	86.00 167	61.90 217	90.69 133	54.01 206	79.42 116	75.61 122	88.65 123	87.18 175	90.48 146	97.95 193	99.21 90

IterMVS		85.02 139	88.98 128	80.41 164	87.03 138	90.34 194	89.78 127	69.45 193	89.77 138	54.04 205	73.71 137	82.05 101	83.44 160	95.11 99	93.64 93	98.75 143	98.22 134
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	86.99 139	95.80 122	91.24 115	73.48 170	92.75 113	69.22 126	72.70 140	65.71 158	94.84 71	94.98 101	94.71 76	99.26 100	98.48 118

CDS-MVSNet		88.59 114	90.13 118	86.79 109	86.98 140	95.43 129	92.03 108	81.33 110	85.54 153	74.51 108	77.07 121	85.14 89	87.03 136	93.90 116	95.18 71	98.88 127	98.67 112
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
LP		77.20 202	79.14 196	74.92 207	86.71 141	90.62 187	77.97 206	57.87 227	85.88 150	50.75 212	55.29 212	66.34 156	79.39 188	80.75 219	85.03 209	96.86 205	90.09 212

Effi-MVS+-dtu		87.18 126	90.48 114	83.32 135	86.51 142	95.76 124	91.16 117	74.28 163	90.44 136	61.31 156	86.72 80	72.68 132	91.25 104	95.01 100	93.64 93	95.45 216	99.12 97

Fast-Effi-MVS+-dtu		86.94 128	91.27 101	81.89 145	86.27 143	95.06 130	90.68 122	68.93 197	91.76 123	57.18 189	89.56 62	75.85 120	89.19 118	94.56 105	92.84 111	99.07 113	99.23 86

testgi		82.88 148	86.14 143	79.08 187	86.05 144	92.20 163	81.23 202	74.77 159	88.70 140	57.63 187	86.73 79	61.53 163	76.83 200	90.33 143	89.43 155	97.99 190	94.05 195

testpf		81.62 155	87.82 135	74.38 209	85.88 145	89.26 200	74.45 216	48.92 235	95.87 79	60.31 166	76.95 122	80.17 108	80.07 186	85.72 205	88.77 161	96.67 208	98.01 143

FMVSNet3		91.25 80	92.13 89	90.21 81	85.64 146	93.14 148	95.29 62	80.09 116	96.40 67	85.74 47	77.13 118	86.81 81	94.98 69	97.19 45	97.11 38	99.55 50	97.13 160

GA-MVS		83.83 144	86.63 141	80.58 162	85.40 147	94.73 136	87.27 144	78.76 130	86.49 146	49.57 214	74.21 134	67.67 154	83.38 162	95.28 96	90.92 139	99.08 112	97.09 161

FC-MVSNet-test		85.51 134	89.08 126	81.35 149	85.31 148	93.35 144	87.65 140	77.55 138	90.01 137	64.07 140	79.63 115	81.83 102	74.94 205	92.08 133	90.83 142	98.55 170	95.81 186

GBi-Net		90.49 91	91.12 105	89.75 88	84.99 149	92.73 151	93.94 82	80.09 116	96.40 67	85.74 47	77.13 118	86.81 81	94.42 76	94.12 109	93.73 89	99.35 87	96.90 169

test1		90.49 91	91.12 105	89.75 88	84.99 149	92.73 151	93.94 82	80.09 116	96.40 67	85.74 47	77.13 118	86.81 81	94.42 76	94.12 109	93.73 89	99.35 87	96.90 169

FMVSNet2		89.51 102	89.63 122	89.38 91	84.99 149	92.73 151	93.94 82	79.28 122	93.73 99	84.28 57	69.36 150	82.32 99	94.42 76	96.16 61	96.22 56	99.35 87	96.90 169

TAMVS		85.35 136	86.00 144	84.59 125	84.97 152	95.57 127	88.98 136	77.29 142	81.44 178	71.36 117	71.48 145	75.00 126	87.03 136	91.92 137	92.21 126	97.92 194	94.40 194

tfpnnormal		81.11 159	79.33 192	83.19 137	84.23 153	92.29 158	86.76 152	82.27 100	72.67 216	62.02 151	56.10 207	53.86 212	85.35 143	92.06 134	89.23 157	98.49 175	99.11 99

MVS-HIRNet		79.34 188	82.56 154	75.57 204	84.11 154	95.02 131	75.03 215	57.28 228	85.50 154	55.88 193	53.00 217	70.51 148	83.05 169	92.12 132	91.96 130	98.09 187	89.83 213

TESTMET0.1,1		88.63 112	93.60 67	82.84 141	84.07 155	96.98 105	88.10 138	73.22 172	94.83 86	62.43 147	84.29 100	90.96 68	89.70 116	95.63 80	92.86 109	99.51 55	99.64 50

test-mter		88.25 117	93.27 74	82.38 143	83.89 156	96.86 108	87.10 149	72.80 174	94.58 91	61.85 152	83.21 106	90.65 70	89.18 119	95.43 92	92.58 123	99.46 75	99.61 58

TransMVSNet (Re)		79.51 186	78.36 202	80.84 159	83.17 157	89.72 197	84.22 188	81.45 109	73.98 214	60.79 161	57.20 201	56.05 198	77.11 199	89.88 148	88.86 160	98.30 183	92.83 200

EG-PatchMatch MVS		78.32 197	79.42 191	77.03 201	83.03 158	93.77 143	84.47 186	69.26 195	75.85 211	53.69 208	55.68 210	60.23 167	73.20 210	89.69 152	88.22 172	98.55 170	92.54 201

LTVRE_ROB	79.45 16	79.66 181	80.55 173	78.61 191	83.01 159	92.19 164	87.18 146	73.69 169	71.70 219	43.22 225	71.22 147	50.85 218	87.82 132	89.47 156	90.43 147	96.75 206	98.00 145
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	84.67 149	85.13 120	82.80 160	92.37 156	87.29 143	79.08 123	90.51 135	74.94 107	70.37 149	62.49 162	88.17 129	92.01 135	88.51 165	98.49 175	96.44 176

FMVSNet1		85.85 133	84.91 148	86.96 106	82.70 161	91.39 178	91.54 113	77.45 139	85.29 155	79.56 95	60.70 167	72.68 132	92.37 94	94.12 109	93.73 89	98.12 186	96.44 176

pm-mvs1		81.68 154	81.70 161	81.65 147	82.61 162	92.26 159	85.54 179	78.95 124	76.29 210	63.81 142	58.43 196	66.33 157	80.63 184	92.30 131	89.93 149	98.37 180	96.39 178

NR-MVSNet		82.37 151	81.95 160	82.85 140	82.56 163	92.24 160	87.49 141	81.91 102	86.41 147	65.51 136	63.95 162	52.93 214	80.80 183	89.41 157	89.61 151	98.85 130	99.10 100

our_test_3					81.94 164	90.26 195	75.39 212

UniMVSNet (Re)		83.28 146	83.16 153	83.42 134	81.93 165	93.12 149	86.27 156	80.83 113	85.88 150	68.23 129	64.56 161	60.58 164	84.25 149	89.13 161	89.44 154	99.04 118	99.40 75

SixPastTwentyTwo		80.28 173	82.06 159	78.21 193	81.89 166	92.35 157	77.72 207	74.48 160	83.04 166	54.22 202	76.06 128	56.40 196	83.55 156	86.83 191	84.83 211	97.38 203	94.93 191

v18		80.16 174	80.01 183	80.34 166	81.72 167	85.71 209	86.58 153	70.68 184	83.23 163	60.78 162	60.39 169	58.50 175	83.49 157	87.03 180	88.19 174	98.79 132	97.06 163

v16		80.03 175	79.95 184	80.13 168	81.64 168	85.63 211	86.17 157	70.42 187	83.12 165	60.34 165	60.11 173	58.61 173	83.45 159	86.98 186	88.12 184	98.75 143	97.05 164

v17		79.95 176	79.87 185	80.05 169	81.55 169	85.65 210	86.10 161	70.44 186	82.59 168	60.02 167	60.26 170	58.53 174	83.41 161	86.98 186	88.09 186	98.76 138	97.02 165

v8		80.61 169	80.61 172	80.62 160	81.51 170	91.00 183	86.06 162	74.07 166	81.78 174	59.93 168	60.10 175	58.42 176	83.35 165	86.99 184	88.11 185	98.79 132	97.83 146

pmmvs5		80.48 170	81.43 162	79.36 181	81.50 171	92.24 160	82.07 198	74.08 165	78.10 201	55.86 194	67.72 154	54.35 209	83.91 154	92.97 126	88.65 163	98.77 135	96.01 181

v1neww		81.04 161	80.86 166	81.25 151	81.48 172	92.14 165	86.06 162	78.41 132	82.02 171	59.43 172	60.09 176	58.30 179	83.37 163	87.02 182	88.15 178	98.76 138	98.33 127

v7new		81.04 161	80.86 166	81.25 151	81.48 172	92.14 165	86.06 162	78.41 132	82.02 171	59.43 172	60.09 176	58.30 179	83.37 163	87.02 182	88.15 178	98.76 138	98.33 127

v6		81.06 160	80.87 165	81.28 150	81.47 174	92.12 167	86.14 158	78.42 131	81.99 173	59.68 170	60.14 172	58.36 177	83.22 168	86.99 184	88.14 180	98.76 138	98.32 129

UniMVSNet_NR-MVSNet		83.83 144	83.70 152	83.98 130	81.41 175	92.56 155	86.54 154	82.96 96	85.98 149	66.27 134	66.16 158	63.63 161	87.78 133	87.65 170	90.81 143	98.94 123	99.13 95

WR-MVS_H		79.76 179	80.07 180	79.40 179	81.25 176	91.73 174	82.77 193	74.82 158	79.02 200	62.55 146	59.41 181	57.32 191	76.27 201	87.61 171	87.30 200	98.78 134	98.09 140

v7		80.74 165	80.95 164	80.50 163	81.23 177	91.58 175	86.12 159	74.83 157	82.30 170	57.64 186	58.74 192	57.45 185	84.48 146	89.75 150	88.27 170	98.72 148	98.57 115

v10		80.38 171	80.73 169	79.96 171	81.22 178	90.40 193	86.11 160	71.63 178	82.42 169	57.65 185	58.74 192	57.47 183	84.44 147	89.75 150	88.28 169	98.71 152	98.06 142

V42		80.88 163	80.74 168	81.05 155	81.21 179	92.01 171	85.96 168	77.75 137	81.62 176	59.73 169	59.93 178	58.35 178	82.98 170	86.90 188	88.06 189	98.69 155	98.32 129

v1141		80.70 166	80.42 175	81.02 157	81.14 180	92.03 169	85.94 170	78.92 126	80.59 186	58.40 182	59.32 183	57.41 188	82.97 171	87.10 176	88.16 176	98.72 148	98.37 124

divwei89l23v2f112		80.69 167	80.42 175	81.02 157	81.13 181	92.04 168	85.95 169	78.92 126	80.45 188	58.43 180	59.34 182	57.46 184	82.92 172	87.09 177	88.16 176	98.75 143	98.36 126

v1		80.69 167	80.38 177	81.05 155	81.13 181	92.02 170	86.02 166	78.93 125	80.32 194	58.65 176	59.29 184	57.45 185	82.83 175	87.07 178	88.14 180	98.74 146	98.37 124

gm-plane-assit		77.20 202	82.26 156	71.30 212	81.10 183	82.00 224	54.33 231	64.41 208	63.80 227	40.93 227	59.04 188	76.57 119	87.30 135	98.26 18	97.36 34	99.74 11	98.76 109

v15		79.35 187	79.20 194	79.54 176	81.08 184	85.48 212	85.92 171	70.02 189	80.60 185	58.63 177	59.14 187	57.40 189	82.87 174	86.89 189	87.95 190	98.70 154	96.92 168

v148		79.66 181	79.13 197	80.27 167	81.02 185	91.76 173	81.90 199	79.32 121	79.24 198	63.79 143	58.07 199	54.34 210	77.17 198	84.42 210	87.52 199	98.40 177	98.59 114

V14		79.33 189	79.18 195	79.51 177	81.00 186	85.46 214	85.88 173	69.79 190	80.52 187	58.76 175	59.16 186	57.52 182	82.91 173	86.86 190	87.90 191	98.72 148	96.87 173

v11		79.54 185	79.71 188	79.35 182	80.96 187	85.36 218	85.81 175	69.10 196	81.49 177	57.63 187	58.90 190	57.07 194	83.94 152	90.09 145	88.08 188	98.66 162	96.97 167

N_pmnet		76.83 204	77.97 207	75.50 205	80.96 187	88.23 204	72.81 217	76.83 145	80.87 181	50.55 213	56.94 203	60.09 168	75.70 203	83.28 216	84.23 213	96.14 213	92.12 202

V9		79.23 190	79.09 198	79.39 180	80.95 189	85.40 215	85.85 174	69.63 191	80.42 189	58.45 179	58.94 189	57.42 187	82.77 176	86.79 195	87.85 193	98.69 155	96.83 174

v13		79.09 192	78.98 200	79.22 186	80.88 190	85.34 219	85.50 180	69.40 194	80.36 192	58.14 183	58.62 194	57.30 192	82.70 177	86.72 197	87.75 196	98.67 161	96.76 175

v12		79.16 191	79.04 199	79.30 184	80.88 190	85.37 217	85.45 181	69.52 192	80.39 190	58.57 178	58.90 190	57.17 193	82.68 178	86.76 196	87.82 194	98.68 157	96.88 172

v1144		80.36 172	80.63 171	80.05 169	80.86 192	91.56 176	85.78 176	75.22 153	80.73 183	55.83 195	58.51 195	56.99 195	83.93 153	89.79 149	88.25 171	98.68 157	98.56 116

v2v482		80.86 164	80.52 174	81.25 151	80.79 193	91.85 172	85.68 177	78.78 129	81.05 179	58.09 184	60.46 168	56.08 197	85.45 142	87.27 174	88.53 164	98.73 147	98.38 123

DU-MVS		82.87 149	82.16 158	83.70 133	80.77 194	92.24 160	86.54 154	81.91 102	86.41 147	66.27 134	63.95 162	55.66 202	87.78 133	86.83 191	90.86 141	98.94 123	99.13 95

Baseline_NR-MVSNet		82.08 152	80.64 170	83.77 132	80.77 194	88.50 202	86.88 151	81.71 106	85.58 152	68.80 127	58.20 197	57.75 181	86.16 141	86.83 191	88.68 162	98.33 181	98.90 106

CP-MVSNet		79.90 177	79.49 189	80.38 165	80.72 196	90.83 185	82.98 192	75.17 154	79.70 196	61.39 155	59.74 179	51.98 217	83.31 166	87.37 172	88.38 167	98.71 152	98.45 119

WR-MVS		79.67 180	80.25 178	79.00 189	80.65 197	91.16 180	83.31 190	76.57 146	80.97 180	60.50 164	59.20 185	58.66 172	74.38 207	85.85 203	87.76 195	98.61 165	98.14 135

PS-CasMVS		79.06 193	78.58 201	79.63 173	80.59 198	90.55 190	82.54 196	75.04 155	77.76 202	58.84 174	58.16 198	50.11 222	82.09 180	87.05 179	88.18 175	98.66 162	98.27 132

v1192		79.84 178	80.05 182	79.61 174	80.49 199	91.04 182	85.56 178	74.37 162	80.73 183	54.35 200	57.07 202	54.54 208	84.23 150	89.94 147	88.38 167	98.63 164	98.61 113

TranMVSNet+NR-MVSNet		82.07 153	81.36 163	82.90 139	80.43 200	91.39 178	87.16 147	82.75 97	84.28 162	62.98 145	62.28 166	56.01 199	85.30 144	86.06 201	90.69 145	98.80 131	98.80 108

v144192		79.61 183	79.77 186	79.41 178	80.28 201	91.06 181	84.87 185	73.86 167	79.65 197	55.38 196	57.76 200	55.20 203	83.46 158	88.42 162	87.89 192	98.61 165	98.42 121

v1921920		79.55 184	79.77 186	79.30 184	80.24 202	90.77 186	85.37 182	73.75 168	80.38 191	53.78 207	56.89 204	54.18 211	84.05 151	89.55 154	88.13 183	98.59 167	98.52 117

v1240		78.97 194	79.27 193	78.63 190	80.04 203	90.61 188	84.25 187	72.95 173	79.22 199	52.70 209	56.22 206	52.88 216	83.28 167	89.60 153	88.20 173	98.56 169	98.14 135

PEN-MVS		78.80 196	78.13 204	79.58 175	80.03 204	89.67 198	83.61 189	75.83 149	77.71 204	58.41 181	60.11 173	50.00 223	81.02 182	84.08 211	88.14 180	98.59 167	97.18 159

EU-MVSNet		76.76 207	79.47 190	73.60 210	79.99 205	87.47 205	77.39 208	75.43 152	77.62 205	47.83 217	64.78 160	60.44 166	64.80 216	86.28 199	86.53 203	96.17 212	93.19 199

pmmvs6		76.79 205	75.69 214	78.09 195	79.95 206	89.57 199	80.92 203	74.46 161	64.79 225	60.74 163	45.71 226	60.55 165	78.37 192	88.04 166	86.00 207	94.07 219	95.15 189

FMVSNet5		87.06 127	89.52 124	84.20 127	79.92 207	86.57 207	87.11 148	72.37 176	96.06 75	75.41 106	84.33 99	91.76 63	91.60 100	91.51 138	91.22 136	98.77 135	85.16 221

anonymousdsp		81.29 157	84.52 151	77.52 196	79.83 208	92.62 154	82.61 195	70.88 183	80.76 182	50.82 211	68.35 153	68.76 152	82.45 179	93.00 125	89.45 153	98.55 170	98.69 111

DTE-MVSNet		77.92 198	77.42 208	78.51 192	79.34 209	89.00 201	83.05 191	75.60 150	76.89 206	56.58 190	59.63 180	50.31 220	78.09 196	82.57 218	87.56 198	98.38 178	95.95 182

v748		76.68 208	76.82 211	76.51 202	78.70 210	90.06 196	77.12 209	73.40 171	73.32 215	59.57 171	55.00 214	50.71 219	72.48 211	83.71 215	86.78 202	97.81 198	98.13 138

MDTV_nov1_ep13_2view		78.83 195	82.35 155	74.73 208	78.65 211	91.51 177	79.18 204	62.52 213	84.51 160	52.51 210	67.49 156	67.29 155	78.90 191	85.52 206	86.34 204	96.62 209	93.76 196

v7n		77.71 199	78.25 203	77.09 200	78.49 212	90.55 190	82.15 197	71.11 182	76.79 207	54.18 203	55.63 211	50.20 221	78.28 194	89.36 159	87.15 201	98.33 181	98.07 141

test20.03		72.81 213	76.24 212	68.80 216	78.31 213	85.40 215	71.04 219	71.20 181	71.85 218	43.40 224	65.31 159	54.71 207	51.27 227	85.92 202	84.18 214	97.58 201	86.35 220

FPMVS		63.27 222	61.31 227	65.57 223	78.25 214	74.42 231	75.23 213	68.92 198	72.33 217	43.87 221	49.01 222	43.94 226	48.64 229	61.15 231	58.81 233	78.51 235	69.49 233

Anonymous20231206		74.59 211	77.00 210	71.78 211	77.89 215	87.45 206	75.14 214	72.29 177	77.76 202	46.65 219	52.14 218	52.93 214	61.10 221	89.37 158	88.09 186	97.59 200	91.30 207

V4		77.67 201	78.01 206	77.28 199	77.82 216	90.56 189	81.70 201	71.63 178	76.33 209	55.38 196	55.74 208	55.83 201	79.20 190	84.02 212	86.01 206	97.97 191	97.55 152

v52		77.69 200	78.04 205	77.29 198	77.79 217	90.54 192	81.76 200	71.62 180	76.52 208	55.34 198	55.70 209	55.91 200	79.27 189	84.02 212	86.03 205	97.96 192	97.56 151

MIMVSNet		82.87 149	86.17 142	79.02 188	77.23 218	92.88 150	84.88 184	60.62 222	86.72 145	64.16 139	73.58 138	71.48 135	88.51 126	94.14 108	93.50 100	98.72 148	90.87 210

PM-MVS		75.81 209	76.11 213	75.46 206	73.81 219	85.48 212	76.42 211	70.57 185	80.05 195	54.75 199	62.33 164	39.56 230	80.59 185	87.71 169	82.81 217	96.61 211	94.81 192

test2356		74.04 212	80.07 180	67.01 221	73.77 220	80.65 225	67.82 224	66.87 203	84.93 159	37.70 231	75.45 132	57.40 189	60.26 222	86.28 199	88.47 166	95.64 215	87.33 218

testus		72.50 214	77.19 209	67.04 219	73.69 221	80.06 226	67.65 225	68.24 201	84.46 161	37.48 233	75.90 130	40.07 229	59.40 223	85.45 207	87.69 197	95.76 214	86.70 219

pmmvs-eth3d		75.17 210	74.09 216	76.43 203	72.92 222	84.49 220	76.61 210	72.42 175	74.33 212	61.28 157	54.71 215	39.42 231	78.20 195	87.77 168	84.25 212	97.17 204	93.63 197

new-patchmatchnet		67.66 220	68.07 221	67.18 218	72.85 223	82.86 223	63.09 230	68.61 199	66.60 224	42.64 226	49.28 221	38.68 232	61.21 220	75.84 223	75.22 227	94.67 218	88.00 217

new_pmnet		71.86 215	73.67 217	69.75 214	72.56 224	84.20 221	70.95 221	66.81 204	80.34 193	43.62 223	51.60 219	53.81 213	71.24 213	82.91 217	80.93 218	93.35 221	81.92 223

Anonymous20231211		65.42 221	62.24 226	69.13 215	68.68 225	78.21 228	65.79 227	68.17 202	49.86 235	67.57 130	29.67 235	34.65 234	55.41 225	75.07 224	76.98 225	89.18 229	91.26 208

testmv		60.16 224	62.42 224	57.53 225	67.85 226	69.87 234	48.47 233	62.44 214	54.75 231	29.08 235	46.99 224	31.77 235	45.97 230	74.85 225	79.08 223	91.39 224	79.62 226

test1235678		60.16 224	62.41 225	57.53 225	67.85 226	69.86 235	48.47 233	62.43 215	54.73 232	29.08 235	46.99 224	31.76 236	45.97 230	74.84 226	79.07 224	91.39 224	79.61 227

pmmvs3		69.04 217	70.75 218	67.04 219	66.83 228	78.54 227	64.99 229	60.92 221	64.67 226	40.61 228	55.08 213	40.29 228	74.89 206	83.76 214	84.01 215	93.98 220	88.88 215

1111		61.69 223	63.75 223	59.29 224	64.35 229	70.45 232	48.44 235	48.86 236	55.76 229	39.40 229	39.25 229	54.73 205	62.55 217	77.84 221	80.37 220	92.16 222	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	55.76 229	39.40 229	39.25 229	54.73 205	62.55 217	77.84 221	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	54.37 233	28.80 237	44.89 227	25.68 238	32.36 235	70.23 229	79.19 222	89.46 228	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	50.56 234	43.72 222	37.44 231	42.95 227	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		69.61 216	70.36 219	68.74 217	62.88 233	88.50 202	65.40 228	77.01 143	71.60 221	43.93 220	66.71 157	35.33 233	72.47 212	61.01 232	80.63 219	90.73 227	88.75 216

ambc			64.61 222		61.80 234	75.31 230	71.00 220		74.16 213	48.83 215	36.02 233	13.22 243	58.66 224	85.80 204	76.26 226	88.01 230	91.53 206

Gipuma		54.59 227	53.98 230	55.30 227	59.03 235	52.63 239	47.17 238	56.08 231	71.68 220	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		68.63 218	70.24 220	66.76 222	56.86 236	83.26 222	67.93 223	70.26 188	68.05 223	46.80 218	40.44 228	48.15 224	62.01 219	84.96 209	84.86 210	96.69 207	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	29.98 234	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	36.35 232	4.47 245	26.81 238	23.27 239	27.11 237	6.75 241	75.30 231

GG-mvs-BLEND		67.99 219	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						95.86 120	89.43 131	61.37 219		60.81 158

DeepMVS_CX						85.88 208	69.83 222	81.56 107	87.99 141	48.22 216	71.85 144	45.52 225	68.67 214	63.21 230		86.64 231	80.03 225

High-resolution multi-view benchmark