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		99.34 7	99.79 4	98.81 10	99.69 1	99.94 17	99.75 13	96.91 8	99.98 3	96.76 12	99.37 37	100.00 1	99.90 4	99.88 9	99.46 17	99.84 31	99.92 120

CNVR-MVS		99.39 2	99.75 12	98.98 2	99.69 1	99.95 12	99.76 7	96.91 8	99.98 3	97.59 6	99.64 19	100.00 1	99.93 1	99.94 2	98.75 48	99.97 10	99.97 82

PGM-MVS		98.47 31	99.73 16	97.00 35	99.68 3	99.94 17	99.76 7	91.74 44	99.84 50	91.17 51	100.00 1	99.69 52	99.81 11	99.38 27	99.30 25	99.82 41	99.95 108

AdaColmap		99.21 11	99.45 37	98.92 5	99.67 4	99.95 12	99.65 25	96.77 19	99.97 8	97.67 4	100.00 1	99.69 52	99.93 1	99.26 29	97.25 91	99.85 27	100.00 1

NCCC		99.24 9	99.75 12	98.65 12	99.63 5	99.96 7	99.76 7	96.91 8	99.97 8	95.86 20	99.67 11	100.00 1	99.75 14	99.85 12	98.80 44	99.98 8	99.97 82

DVP-MVS		99.38 4	99.57 33	99.15 1	99.62 6	99.94 17	99.72 20	96.99 2	99.98 3	98.85 1	98.21 69	100.00 1	99.88 6	99.88 9	98.96 35	99.85 27	100.00 1

ACMMP_NAP		98.68 26	99.58 30	97.62 28	99.62 6	99.92 36	99.72 20	96.78 18	99.71 66	90.13 64	99.66 15	99.99 29	99.64 24	99.78 14	98.14 62	99.82 41	99.89 129

HPM-MVS++		98.98 22	99.62 26	98.22 21	99.62 6	99.94 17	99.74 16	96.95 4	99.87 43	93.76 31	99.49 32	100.00 1	99.39 36	99.73 17	98.35 56	99.89 22	99.96 101

APDe-MVS		99.40 1	99.81 2	98.92 5	99.62 6	99.96 7	99.76 7	96.87 12	99.95 22	97.66 5	99.57 26	100.00 1	99.63 25	99.88 9	99.28 26	100.00 1	100.00 1

SR-MVS					99.61 10			96.80 15				100.00 1

MSP-MVS		99.38 4	99.78 5	98.91 8	99.61 10	99.96 7	99.85 2	96.94 6	99.96 16	97.38 10	99.60 23	100.00 1	99.70 17	99.96 1	98.96 35	100.00 1	100.00 1

APD-MVS		99.33 8	99.85 1	98.73 11	99.61 10	99.92 36	99.77 6	96.91 8	99.93 29	96.31 17	99.59 24	99.95 38	99.84 9	99.73 17	99.84 9	99.95 13	100.00 1
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
DPE-MVS		99.37 6	99.74 15	98.94 4	99.60 13	99.94 17	99.87 1	96.95 4	99.94 26	97.42 8	99.62 21	100.00 1	99.80 13	99.91 5	98.78 46	99.98 8	100.00 1

MSLP-MVS++		99.39 2	99.76 9	98.95 3	99.60 13	99.99 1	99.83 3	96.82 14	99.92 33	97.58 7	99.58 25	100.00 1	99.93 1	98.98 33	99.86 8	99.96 11	100.00 1

CSCG		98.22 33	98.37 65	98.04 23	99.60 13	99.82 55	99.45 31	93.59 40	99.16 101	96.46 16	98.22 68	95.86 100	99.41 35	96.33 124	99.22 28	99.75 86	99.94 113

MCST-MVS		99.08 18	99.72 18	98.33 19	99.59 16	99.97 3	99.78 5	96.96 3	99.95 22	93.72 32	99.67 11	100.00 1	99.90 4	99.91 5	98.55 52	100.00 1	100.00 1

zzz-MVS		99.12 16	99.52 36	98.65 12	99.58 17	99.93 30	99.74 16	96.72 22	99.44 85	96.47 15	99.62 21	100.00 1	99.63 25	99.74 16	97.97 67	99.77 70	99.94 113

HFP-MVS		99.19 12	99.77 8	98.51 16	99.55 18	99.94 17	99.76 7	96.84 13	99.88 40	95.27 24	99.67 11	100.00 1	99.85 8	99.56 22	99.36 21	99.79 59	99.97 82

X-MVS		98.62 27	99.75 12	97.29 29	99.50 19	99.94 17	99.71 22	96.55 28	99.85 47	88.58 80	99.65 16	99.98 31	99.67 21	99.60 21	99.26 27	99.77 70	99.97 82

DeepC-MVS_fast	98.03 2	99.05 20	99.78 5	98.21 22	99.47 20	99.97 3	99.75 13	96.80 15	99.97 8	93.58 35	98.68 56	99.94 39	99.69 18	99.93 4	99.95 3	99.96 11	99.98 71
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PLC	98.06 1	99.17 13	99.38 39	98.92 5	99.47 20	99.90 44	99.48 30	96.47 30	99.96 16	98.73 2	99.52 30	100.00 1	99.55 30	98.54 52	97.73 79	99.84 31	99.99 53
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
ACMMPR		99.12 16	99.76 9	98.36 18	99.45 22	99.94 17	99.75 13	96.70 24	99.93 29	94.65 28	99.65 16	99.96 36	99.84 9	99.51 25	99.35 22	99.79 59	99.96 101

CP-MVS		99.14 15	99.67 21	98.53 15	99.45 22	99.94 17	99.63 27	96.62 27	99.82 52	95.92 19	99.65 16	100.00 1	99.71 16	99.76 15	98.56 51	99.83 37	100.00 1

CPTT-MVS		99.08 18	99.53 35	98.57 14	99.44 24	99.93 30	99.60 28	95.92 35	99.77 60	97.01 11	99.67 11	100.00 1	99.72 15	99.56 22	97.76 76	99.70 107	99.98 71

SteuartSystems-ACMMP		98.95 23	99.80 3	97.95 25	99.43 25	99.96 7	99.76 7	96.45 31	99.82 52	93.63 33	99.64 19	100.00 1	98.56 73	99.90 8	99.31 24	99.84 31	100.00 1
Skip Steuart: Steuart Systems R&D Blog.
MP-MVS		98.82 25	99.63 24	97.88 27	99.41 26	99.91 43	99.74 16	96.76 20	99.88 40	91.89 43	99.50 31	99.94 39	99.65 23	99.71 20	98.49 54	99.82 41	99.97 82
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
OMC-MVS		98.59 29	99.07 41	98.03 24	99.41 26	99.90 44	99.26 36	94.33 39	99.94 26	96.03 18	96.68 85	99.72 51	99.42 33	98.86 36	98.84 41	99.72 104	99.58 163

3Dnovator	95.01 8	97.98 39	98.89 48	96.92 37	99.36 28	99.76 66	98.72 50	89.98 57	99.98 3	93.99 30	94.60 107	99.43 62	99.50 31	98.55 49	99.91 5	99.99 5	99.98 71

QAPM		97.90 41	98.89 48	96.74 38	99.35 29	99.80 62	98.84 46	90.20 56	99.94 26	92.85 36	94.17 110	99.78 47	99.42 33	98.71 38	99.87 7	99.79 59	99.98 71

CNLPA		99.24 9	99.58 30	98.85 9	99.34 30	99.95 12	99.32 33	96.65 25	99.96 16	98.44 3	98.97 48	100.00 1	99.57 28	98.66 40	99.56 15	99.76 77	99.97 82

MAR-MVS		97.03 52	98.00 76	95.89 48	99.32 31	99.74 69	96.76 90	84.89 102	99.97 8	94.86 26	98.29 62	90.58 122	99.67 21	98.02 82	99.50 16	99.82 41	99.92 120
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
OpenMVS	94.03 11	96.87 55	98.10 73	95.44 54	99.29 32	99.78 64	98.46 59	89.92 60	99.47 83	85.78 101	91.05 131	98.50 74	99.30 41	98.49 59	99.41 18	99.89 22	99.98 71

3Dnovator+	95.21 7	98.17 34	99.08 40	97.12 33	99.28 33	99.78 64	98.61 52	89.93 59	99.93 29	95.36 23	95.50 94	100.00 1	99.56 29	98.58 47	99.80 10	99.95 13	99.97 82

MVS_111021_HR		97.94 40	99.59 28	96.02 47	99.27 34	99.97 3	97.03 83	90.44 52	99.89 37	90.75 55	100.00 1	99.73 49	98.68 70	98.67 39	98.89 39	99.95 13	99.97 82

mPP-MVS					99.23 35							99.87 42

MVS_111021_LR		98.15 36	99.69 20	96.36 43	99.23 35	99.93 30	97.79 64	91.84 43	99.87 43	90.53 60	100.00 1	99.57 57	98.93 58	99.44 26	99.08 32	99.85 27	99.95 108

abl_6				97.06 34	99.17 37	99.82 55	98.68 51	90.86 50	100.00 1	94.53 29	97.40 80	100.00 1	99.17 49			99.93 16	99.99 53

TSAR-MVS + ACMM		98.30 32	99.64 23	96.74 38	99.08 38	99.94 17	99.67 24	96.73 21	99.97 8	86.30 98	98.30 61	99.99 29	98.78 66	99.73 17	99.57 14	99.88 25	99.98 71

train_agg		98.62 27	99.76 9	97.28 30	99.03 39	99.93 30	99.65 25	96.37 32	99.98 3	89.24 74	99.53 28	99.83 44	99.59 27	99.85 12	99.19 29	99.80 52	100.00 1

CDPH-MVS		97.88 42	99.59 28	95.89 48	98.90 40	99.95 12	99.40 32	92.86 42	99.86 46	85.33 103	98.62 58	99.45 61	99.06 54	99.29 28	99.94 4	99.81 48	100.00 1

ACMMP		98.16 35	99.01 43	97.18 31	98.86 41	99.92 36	98.77 49	95.73 36	99.31 97	91.15 52	100.00 1	99.81 46	98.82 65	98.11 76	95.91 125	99.77 70	99.97 82
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
PatchMatch-RL		96.84 57	98.03 75	95.47 51	98.84 42	99.81 60	95.61 107	89.20 66	99.65 70	91.28 49	99.39 34	93.46 112	98.18 81	98.05 78	96.28 114	99.69 113	99.55 165

tmp_tt				78.81 192	98.80 43	85.73 206	70.08 207	77.87 161	98.68 121	83.71 109	99.53 28	74.55 167	54.97 208	78.28 202	72.43 205	87.45 207

TAPA-MVS	96.62 5	97.60 44	98.46 63	96.60 41	98.73 44	99.90 44	99.30 34	94.96 38	99.46 84	87.57 86	96.05 92	98.53 73	99.26 44	98.04 80	97.33 90	99.77 70	99.88 134
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
MSDG		97.29 47	97.55 85	97.00 35	98.66 45	99.71 70	99.03 42	96.15 33	99.59 73	89.67 71	92.77 124	94.86 103	98.75 67	98.22 70	97.94 68	99.72 104	99.76 155

PHI-MVS		98.85 24	99.67 21	97.89 26	98.63 46	99.93 30	98.95 44	95.20 37	99.84 50	94.94 25	99.74 10	100.00 1	99.69 18	98.40 60	99.75 11	99.93 16	99.99 53

DeepPCF-MVS	97.16 4	97.58 45	99.72 18	95.07 59	98.45 47	99.96 7	93.83 135	95.93 34	100.00 1	90.79 54	98.38 60	99.85 43	95.28 126	99.94 2	99.97 1	96.15 200	99.97 82

EPNet		98.11 37	99.63 24	96.34 44	98.44 48	99.88 50	98.55 54	90.25 55	99.93 29	92.60 41	100.00 1	99.73 49	98.41 75	98.87 35	99.02 33	99.82 41	99.97 82
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet_dtu		95.10 91	98.81 52	90.78 107	98.38 49	98.47 124	96.54 92	89.36 64	99.78 59	65.65 174	99.31 38	98.24 81	94.79 131	98.28 66	99.35 22	99.93 16	98.27 184
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DPM-MVS		98.58 30	99.78 5	97.17 32	98.02 50	99.64 77	99.80 4	96.72 22	99.96 16	90.05 66	99.57 26	100.00 1	98.66 71	99.56 22	99.96 2	99.80 52	99.80 151

SD-MVS		99.16 14	99.73 16	98.49 17	97.93 51	99.95 12	99.74 16	96.94 6	99.96 16	96.60 14	99.47 33	100.00 1	99.88 6	99.15 31	99.59 13	99.84 31	100.00 1
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
TSAR-MVS + MP.		98.99 21	99.61 27	98.27 20	97.88 52	99.92 36	99.71 22	96.80 15	99.96 16	95.58 22	98.71 55	100.00 1	99.68 20	99.91 5	98.78 46	99.99 5	100.00 1
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
COLMAP_ROB	93.56 12	96.03 66	96.83 103	95.11 57	97.87 53	99.52 82	98.81 48	91.40 47	99.42 88	84.97 104	90.46 134	96.82 91	98.05 84	96.46 120	96.19 117	99.54 136	98.92 180
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
PCF-MVS	97.20 3	97.49 46	98.20 70	96.66 40	97.62 54	99.92 36	98.93 45	96.64 26	98.53 128	88.31 84	94.04 113	99.58 56	98.94 56	97.53 95	97.79 74	99.54 136	99.97 82
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
DeepC-MVS	96.33 6	97.05 49	97.59 84	96.42 42	97.37 55	99.92 36	99.10 40	96.54 29	99.34 96	86.64 95	91.93 128	93.15 114	99.11 52	99.11 32	99.68 12	99.73 100	99.97 82
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CANet		97.62 43	98.94 46	96.08 46	97.19 56	99.93 30	99.29 35	90.38 53	99.87 43	91.00 53	95.79 93	99.51 58	98.72 69	98.53 54	99.00 34	99.90 21	99.99 53

DELS-MVS		97.05 49	98.05 74	95.88 50	97.09 57	99.99 1	98.82 47	90.30 54	98.44 134	91.40 47	92.91 121	96.57 93	97.68 98	98.56 48	99.88 6	100.00 1	100.00 1
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
LS3D		96.44 61	97.31 91	95.41 55	97.06 58	99.87 51	99.51 29	97.48 1	99.57 74	79.00 121	95.39 96	89.19 128	99.81 11	98.55 49	98.84 41	99.62 125	99.78 152

CHOSEN 280x420		97.16 48	99.58 30	94.35 73	96.95 59	99.97 3	97.19 78	81.55 138	99.92 33	91.75 44	100.00 1	100.00 1	98.84 64	98.55 49	98.65 49	99.79 59	99.97 82

RPSCF		95.86 71	96.94 101	94.61 68	96.52 60	98.67 122	98.54 55	88.43 77	99.56 75	90.51 62	99.39 34	98.70 71	97.72 94	93.77 168	92.00 174	95.93 201	96.50 197

PVSNet_BlendedMVS		96.01 67	96.48 111	95.46 52	96.47 61	99.89 48	95.64 104	91.23 48	99.75 63	91.59 45	96.80 82	82.44 146	98.05 84	98.53 54	97.92 70	99.80 52	100.00 1

PVSNet_Blended		96.01 67	96.48 111	95.46 52	96.47 61	99.89 48	95.64 104	91.23 48	99.75 63	91.59 45	96.80 82	82.44 146	98.05 84	98.53 54	97.92 70	99.80 52	100.00 1

MVS_0304		97.04 51	98.72 54	95.08 58	96.32 63	99.90 44	99.15 38	89.61 63	99.89 37	87.22 92	95.47 95	98.22 82	98.22 80	98.63 44	98.90 38	99.93 16	100.00 1

TSAR-MVS + COLMAP		95.20 85	95.03 131	95.41 55	96.17 64	98.69 121	99.11 39	93.40 41	99.97 8	84.89 106	98.23 67	75.01 165	99.34 38	97.27 106	96.37 113	99.58 129	99.64 162

CHOSEN 1792x2688		93.69 108	94.89 134	92.28 98	96.17 64	99.84 52	95.69 103	83.17 123	98.54 127	82.04 114	77.58 187	91.15 118	96.90 104	98.36 64	98.82 43	99.73 100	99.98 71

HyFIR lowres test		93.13 118	94.48 138	91.56 103	96.12 66	99.68 72	93.52 137	79.98 146	97.24 149	81.73 117	72.66 195	95.74 101	98.29 78	98.27 67	97.79 74	99.70 107	100.00 1

OPM-MVS		93.50 112	93.00 149	94.07 76	95.82 67	98.26 131	98.49 58	91.62 45	94.69 170	81.93 115	92.82 123	76.18 163	96.82 106	96.12 129	94.57 139	99.74 90	98.39 183

MS-PatchMatch		93.46 116	95.91 122	90.61 110	95.48 68	99.31 98	95.62 106	77.23 165	99.42 88	81.88 116	88.92 142	96.06 99	93.80 144	96.45 122	93.11 162	99.65 117	98.10 188

CMPMVS	65.66 17	84.62 188	85.02 194	84.15 176	95.40 69	97.79 139	88.35 181	79.22 153	89.66 201	60.71 190	72.20 196	73.94 171	87.32 191	86.73 199	84.55 201	93.90 203	90.31 205
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PVSNet_Blended_VisFu		95.37 83	97.44 89	92.95 94	95.20 70	99.80 62	92.68 143	88.41 78	99.12 104	87.64 85	88.31 145	99.10 67	94.07 142	98.27 67	97.51 85	99.73 100	100.00 1

HQP-MVS		94.48 99	95.39 129	93.42 83	95.10 71	98.35 127	98.19 60	91.41 46	99.77 60	79.79 118	99.30 39	77.08 156	96.25 114	96.93 109	96.28 114	99.76 77	99.99 53

XVS					95.09 72	99.94 17	97.49 71			88.58 80		99.98 31				99.78 66

X-MVStestdata					95.09 72	99.94 17	97.49 71			88.58 80		99.98 31				99.78 66

LGP-MVS_train		93.60 109	95.05 130	91.90 102	94.90 74	98.29 130	97.93 62	88.06 80	99.14 103	74.83 137	99.26 41	76.50 159	96.07 117	96.31 125	95.90 127	99.59 127	99.97 82

ACMM	94.44 10	94.26 104	94.62 136	93.84 79	94.86 75	97.73 140	93.48 138	90.76 51	99.27 99	87.46 87	99.04 44	76.60 158	96.76 109	96.37 123	93.76 153	99.74 90	99.55 165
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CANet_DTU		94.90 94	98.98 45	90.13 115	94.74 76	99.81 60	98.53 56	82.23 131	99.97 8	66.76 171	100.00 1	98.50 74	98.74 68	97.52 96	97.19 97	99.76 77	99.88 134

TSAR-MVS + GP.		98.06 38	99.55 34	96.32 45	94.72 77	99.92 36	99.22 37	89.98 57	99.97 8	94.77 27	99.94 9	100.00 1	99.43 32	98.52 57	98.53 53	99.79 59	100.00 1

UGNet		96.05 65	98.55 57	93.13 89	94.64 78	99.65 76	94.70 123	87.78 81	99.40 91	89.69 70	98.25 65	99.25 66	92.12 158	96.50 116	97.08 100	99.84 31	99.72 157
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
IB-MVS	90.59 15	92.70 126	95.70 124	89.21 124	94.62 79	99.45 90	83.77 193	88.92 69	99.53 76	92.82 37	98.86 51	86.08 134	75.24 202	92.81 183	93.17 160	99.89 22	100.00 1
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
UA-Net		94.95 93	98.66 55	90.63 109	94.60 80	98.94 115	96.03 97	85.28 97	98.01 144	78.92 122	97.42 79	99.96 36	89.09 180	98.95 34	98.80 44	99.82 41	98.57 182

ACMP	94.49 9	94.19 105	94.74 135	93.56 82	94.25 81	98.32 129	96.02 98	89.35 65	98.90 117	87.28 90	99.14 43	76.41 161	94.94 129	96.07 132	94.35 148	99.49 147	99.99 53
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMH	92.34 14	91.59 139	93.02 148	89.92 117	93.97 82	97.98 137	90.10 168	84.70 104	98.46 131	76.80 130	93.38 119	71.94 177	94.39 137	95.34 143	94.04 150	99.54 136	100.00 1
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CLD-MVS		94.53 98	94.45 139	94.61 68	93.85 83	98.36 126	98.12 61	89.68 61	99.35 95	89.62 72	95.19 98	77.08 156	96.66 111	95.51 139	95.67 128	99.74 90	100.00 1
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
TDRefinement		87.79 166	88.76 182	86.66 150	93.54 84	98.02 135	95.76 101	85.18 100	96.57 154	67.90 164	80.51 173	66.51 197	78.37 199	93.20 179	89.73 192	99.22 185	96.75 195

Anonymous202405211			95.78 123		93.26 85	99.52 82	96.70 91	88.55 74	97.93 145		88.99 141	90.68 121	98.99 55	96.46 120	97.02 104	99.64 121	99.89 129

DCV-MVSNet		95.85 73	97.53 86	93.89 78	93.20 86	97.01 151	97.14 80	84.77 103	99.16 101	90.38 63	98.96 49	93.73 109	98.23 79	96.57 115	97.37 89	99.64 121	99.93 116

thres100view900		95.86 71	96.62 105	94.97 60	93.10 87	99.83 53	97.76 65	89.15 67	98.62 124	90.69 56	99.00 45	84.86 137	99.30 41	97.57 94	96.48 109	99.81 48	100.00 1

tfpn200view9		95.78 76	96.54 108	94.89 63	93.10 87	99.82 55	97.67 66	88.85 70	98.62 124	90.69 56	99.00 45	84.86 137	99.28 43	97.41 101	96.10 118	99.76 77	99.99 53

thres200		95.77 77	96.55 107	94.86 64	93.09 89	99.82 55	97.63 69	88.85 70	98.49 129	90.66 58	98.99 47	84.86 137	99.20 46	97.41 101	96.28 114	99.76 77	100.00 1

ACMH+	92.61 13	91.80 136	93.03 147	90.37 112	93.03 90	98.17 132	94.00 133	84.13 115	98.12 141	77.39 128	91.95 127	74.62 166	94.36 139	94.62 154	93.82 152	99.32 177	99.87 139

Anonymous20231211		94.96 92	94.99 132	94.91 61	93.01 91	99.44 93	96.85 88	88.49 76	98.78 119	92.61 40	83.94 159	90.25 124	98.94 56	95.87 135	96.77 107	99.58 129	99.89 129

thres400		95.72 79	96.48 111	94.84 65	93.00 92	99.83 53	97.55 70	88.93 68	98.49 129	90.61 59	98.86 51	84.63 141	99.20 46	97.45 97	96.10 118	99.77 70	99.99 53

canonicalmvs		95.80 75	97.02 96	94.37 71	92.96 93	99.47 87	97.49 71	84.58 105	99.44 85	92.05 42	98.54 59	86.65 132	99.37 37	96.18 127	98.93 37	99.77 70	99.92 120

thres600view7		95.64 80	96.38 114	94.79 67	92.96 93	99.82 55	97.48 75	88.85 70	98.38 135	90.52 61	98.84 53	84.61 142	99.15 50	97.41 101	95.60 130	99.76 77	99.99 53

baseline1		96.87 55	98.55 57	94.91 61	92.89 95	99.45 90	96.34 94	88.54 75	98.88 118	92.82 37	98.93 50	96.58 92	99.07 53	98.19 72	98.04 65	99.80 52	99.78 152

MVSTER		97.00 53	98.85 50	94.83 66	92.71 96	97.43 145	99.03 42	85.52 95	99.82 52	92.74 39	99.15 42	99.94 39	99.19 48	98.66 40	96.99 105	99.79 59	99.98 71

DWT-MVSNet_training		96.26 64	98.44 64	93.72 81	92.58 97	99.34 97	96.15 96	83.00 126	99.76 62	93.63 33	97.89 74	99.46 59	97.23 102	94.43 156	98.19 59	99.70 107	100.00 1

USDC		90.36 146	91.68 154	88.82 128	92.58 97	98.02 135	96.27 95	79.83 147	98.37 137	70.61 157	89.05 140	67.50 192	94.17 140	95.77 136	94.43 143	99.46 155	98.62 181

PMMVS		96.45 60	98.24 69	94.36 72	92.58 97	99.01 108	97.08 82	87.42 88	99.88 40	90.06 65	99.39 34	94.63 104	99.33 39	97.85 88	96.99 105	99.70 107	99.96 101

EPMVS		94.08 106	98.54 61	88.87 126	92.51 100	99.47 87	94.18 131	66.53 192	99.68 68	82.40 112	95.24 97	99.40 63	97.86 91	98.12 75	97.99 66	99.75 86	99.88 134

TinyColmap		89.94 148	90.88 160	88.84 127	92.43 101	97.91 138	95.59 108	80.10 145	98.12 141	71.33 154	84.56 155	67.46 193	94.15 141	95.57 138	94.27 149	99.43 163	98.26 185

IS_MVSNet		96.66 59	98.62 56	94.38 70	92.41 102	99.70 71	97.19 78	87.67 83	99.05 109	91.27 50	95.09 100	98.46 78	97.95 89	98.64 42	99.37 19	99.79 59	100.00 1

Vis-MVSNet (Re-imp)		95.60 81	98.52 62	92.19 99	92.37 103	99.56 81	96.37 93	87.41 89	98.95 112	84.77 108	94.88 105	98.48 77	92.44 155	98.63 44	99.37 19	99.76 77	99.77 154

FC-MVSNet-train		94.61 95	96.27 115	92.68 97	92.35 104	97.14 149	93.45 139	87.73 82	98.93 113	87.31 88	96.42 88	89.35 126	95.67 121	96.06 133	96.01 122	99.56 133	99.98 71

baseline		95.85 73	98.13 72	93.20 88	92.29 105	99.58 80	97.49 71	84.33 110	99.44 85	87.28 90	97.00 81	94.04 108	97.93 90	98.36 64	98.47 55	99.87 26	99.99 53

MVS_Test		95.74 78	98.18 71	92.90 95	92.16 106	99.49 86	97.36 76	84.30 111	99.79 57	84.94 105	96.65 86	93.63 111	98.85 62	98.61 46	99.10 31	99.81 48	100.00 1

tpmrst		92.52 130	97.45 88	86.77 149	92.15 107	99.36 96	92.53 146	65.95 195	99.53 76	72.50 142	92.22 126	99.83 44	97.81 93	95.18 147	96.05 121	99.69 113	100.00 1

CS-MVS		96.88 54	99.06 42	94.34 74	92.11 108	99.67 73	98.58 53	87.30 90	99.95 22	89.40 73	98.68 56	98.41 79	98.85 62	98.54 52	98.15 61	99.80 52	99.99 53

ADS-MVSNet		92.91 122	97.97 77	87.01 146	92.07 109	99.27 101	92.70 142	65.39 199	99.85 47	75.40 134	94.93 104	98.26 80	96.86 105	96.09 130	97.52 84	99.65 117	99.84 144

dps		94.29 103	97.33 90	90.75 108	92.02 110	99.21 102	94.31 129	66.97 191	99.50 79	95.61 21	96.22 91	98.64 72	96.08 116	93.71 170	94.03 151	99.52 140	99.98 71

SCA		93.53 110	98.90 47	87.27 143	92.01 111	99.30 99	93.43 140	65.72 196	99.80 55	75.20 136	97.66 77	99.74 48	97.44 99	98.21 71	97.62 82	99.84 31	100.00 1

diffmvs		94.60 96	95.63 126	93.41 84	91.98 112	99.30 99	96.86 87	87.62 84	99.30 98	86.07 99	94.12 112	81.63 150	98.16 82	97.43 98	97.60 83	99.76 77	100.00 1

EIA-MVS		96.34 62	98.55 57	93.76 80	91.93 113	99.66 74	97.14 80	88.33 79	99.51 78	85.98 100	98.82 54	96.08 98	99.33 39	98.38 62	97.40 88	99.81 48	100.00 1

PatchmatchNet		93.48 115	98.84 51	87.22 144	91.93 113	99.39 94	92.55 145	66.06 194	99.71 66	75.61 133	98.24 66	99.59 55	97.35 100	97.87 87	97.64 81	99.83 37	99.43 168
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
casdiffmvs		94.54 97	95.56 127	93.36 85	91.84 115	99.46 89	95.92 99	87.54 87	98.45 132	86.57 97	90.51 133	84.72 140	98.49 74	97.97 84	97.80 73	99.77 70	100.00 1

tpm cat1		93.29 117	96.53 109	89.50 121	91.84 115	99.18 104	94.70 123	67.70 188	98.38 135	86.67 93	89.16 139	99.38 64	96.66 111	94.33 157	95.30 132	99.43 163	100.00 1

ETV-MVS		96.76 58	99.01 43	94.14 75	91.83 117	99.66 74	97.20 77	88.68 73	99.95 22	88.61 79	98.18 70	98.73 70	98.66 71	98.51 58	98.07 64	99.85 27	100.00 1

EPP-MVSNet		96.29 63	98.34 66	93.90 77	91.77 118	99.38 95	95.45 112	87.25 91	99.38 92	91.36 48	94.86 106	98.49 76	97.83 92	98.01 83	98.23 58	99.75 86	99.99 53

thisisatest0530		95.89 69	98.32 67	93.06 92	91.76 119	99.75 67	94.94 118	87.60 85	99.91 35	86.66 94	98.28 63	99.98 31	97.72 94	97.10 107	93.24 158	99.65 117	99.95 108

DI_MVS_plusplus_trai		95.29 84	97.02 96	93.28 87	91.76 119	99.52 82	97.84 63	85.67 94	99.08 108	87.29 89	87.76 148	97.46 88	97.31 101	97.83 89	97.48 86	99.83 37	100.00 1

tttt0517		95.88 70	98.31 68	93.04 93	91.75 121	99.75 67	94.90 119	87.60 85	99.91 35	86.63 96	98.28 63	99.98 31	97.72 94	97.10 107	93.24 158	99.65 117	99.95 108

MDTV_nov1_ep13		94.32 101	98.77 53	89.14 125	91.70 122	99.52 82	95.21 114	72.09 185	99.80 55	78.91 123	96.32 89	99.62 54	97.71 97	98.39 61	97.71 80	99.22 185	100.00 1

test-LLR		93.71 107	97.23 92	89.60 119	91.69 123	99.10 105	94.68 125	83.60 117	99.36 93	71.94 148	93.82 115	96.51 94	95.96 118	97.42 99	94.37 145	99.74 90	99.99 53

test0.0.03 1		95.15 89	97.87 80	91.99 101	91.69 123	98.82 119	93.04 141	83.60 117	99.65 70	88.80 77	94.15 111	97.67 86	94.97 128	96.62 114	98.16 60	99.83 37	100.00 1

CostFormer		93.50 112	96.50 110	90.00 116	91.69 123	98.65 123	93.88 134	67.64 189	98.97 110	89.16 75	97.79 75	88.92 129	97.97 88	95.14 148	96.06 120	99.63 123	100.00 1

CVMVSNet		92.13 134	95.40 128	88.32 137	91.29 126	97.29 147	91.85 150	86.42 93	96.71 153	71.84 150	89.56 137	91.18 117	88.98 182	96.17 128	97.76 76	99.51 144	99.14 176

Vis-MVSNet		93.08 120	96.76 104	88.78 130	91.14 127	99.63 79	94.85 120	83.34 121	97.19 150	74.78 138	91.92 129	93.15 114	88.81 183	97.59 93	98.35 56	99.78 66	99.49 167
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
IterMVS-LS		93.50 112	96.22 116	90.33 114	90.93 128	95.50 184	94.83 121	80.54 142	98.92 114	79.11 120	90.64 132	93.70 110	96.79 107	96.93 109	97.85 72	99.78 66	99.99 53
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Effi-MVS+		93.06 121	95.94 121	89.70 118	90.82 129	99.45 90	95.71 102	78.94 156	98.72 120	74.71 139	97.92 73	80.73 151	98.35 76	97.72 90	97.05 103	99.70 107	100.00 1

RPMNet		92.64 128	97.88 79	86.53 151	90.79 130	98.95 113	95.13 115	64.44 203	99.09 106	72.36 144	93.58 118	99.01 68	96.74 110	98.05 78	96.45 111	99.71 106	100.00 1

testgi		92.47 131	95.68 125	88.73 131	90.68 131	98.35 127	91.67 153	79.50 151	98.96 111	77.12 129	95.17 99	85.84 135	93.95 143	95.75 137	96.47 110	99.45 158	99.21 174

CR-MVSNet		92.32 133	97.97 77	85.74 160	90.63 132	98.95 113	95.46 110	65.50 197	99.09 106	67.51 167	94.20 109	98.18 83	95.59 124	98.16 73	97.20 95	99.74 90	100.00 1

gg-mvs-nofinetune		86.69 182	91.30 158	81.30 188	90.42 133	99.64 77	98.50 57	61.68 207	79.23 207	40.35 209	66.58 201	97.14 89	96.92 103	98.64 42	97.94 68	99.91 20	99.97 82

IterMVS-SCA-FT		91.75 137	96.87 102	85.78 158	90.34 134	95.93 173	95.06 117	73.85 180	98.91 115	61.01 187	89.21 138	98.87 69	94.66 135	98.09 77	97.12 99	99.76 77	99.99 53

PatchT		91.06 141	97.66 82	83.36 182	90.32 135	98.96 112	82.30 197	64.72 202	98.45 132	67.51 167	93.28 120	97.60 87	95.59 124	98.16 73	97.20 95	99.70 107	100.00 1

baseline2		95.13 90	98.55 57	91.15 106	90.29 136	99.00 109	94.49 127	82.00 132	99.68 68	84.82 107	96.47 87	99.30 65	95.71 120	98.24 69	97.14 98	99.57 131	100.00 1

IterMVS		91.65 138	96.62 105	85.85 157	90.27 137	95.80 175	95.32 113	74.15 176	98.91 115	60.95 188	88.79 144	97.76 85	94.69 134	98.04 80	97.07 101	99.73 100	100.00 1
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
tpm		89.60 150	94.93 133	83.39 180	89.94 138	97.11 150	90.09 169	65.28 200	98.67 122	60.03 192	96.79 84	84.38 143	95.66 123	91.90 187	95.65 129	99.32 177	99.98 71

CDS-MVSNet		94.32 101	97.00 98	91.19 105	89.82 139	98.71 120	95.51 109	85.14 101	96.85 151	82.33 113	92.48 125	96.40 96	94.71 132	96.86 111	97.76 76	99.63 123	99.92 120
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
FMVSNet3		95.59 82	97.51 87	93.34 86	89.48 140	96.57 158	97.67 66	84.17 112	99.48 80	89.76 67	95.09 100	94.35 105	99.14 51	98.37 63	98.86 40	99.82 41	99.89 129

GBi-Net		95.19 87	96.99 99	93.09 90	89.11 141	96.47 160	96.90 84	84.17 112	99.48 80	89.76 67	95.09 100	94.35 105	98.87 59	96.50 116	97.21 92	99.74 90	99.81 148

test1		95.19 87	96.99 99	93.09 90	89.11 141	96.47 160	96.90 84	84.17 112	99.48 80	89.76 67	95.09 100	94.35 105	98.87 59	96.50 116	97.21 92	99.74 90	99.81 148

FMVSNet2		94.48 99	95.95 120	92.77 96	89.11 141	96.47 160	96.90 84	83.38 120	99.11 105	88.64 78	87.50 153	92.26 116	98.87 59	97.91 86	98.60 50	99.74 90	99.81 148

Fast-Effi-MVS+		92.11 135	94.33 140	89.52 120	89.06 144	99.00 109	95.13 115	76.72 168	98.59 126	78.21 126	89.99 135	77.35 155	98.34 77	97.97 84	97.44 87	99.67 115	99.96 101

Fast-Effi-MVS+-dtu		92.73 125	97.62 83	87.02 145	88.91 145	98.83 118	95.79 100	73.98 179	99.89 37	68.62 163	97.73 76	93.30 113	95.21 127	97.67 91	95.96 124	99.59 127	100.00 1

MVS-HIRNet		88.27 159	94.05 143	81.51 187	88.90 146	98.93 116	83.38 195	60.52 209	98.06 143	63.78 180	80.67 171	90.36 123	92.94 150	97.29 105	96.41 112	99.56 133	96.66 196

Effi-MVS+-dtu		93.13 118	97.13 94	88.47 134	88.86 147	99.19 103	96.79 89	79.08 155	99.64 72	70.01 158	97.51 78	89.38 125	96.53 113	97.60 92	96.55 108	99.57 131	100.00 1

TAMVS		92.43 132	94.21 142	90.35 113	88.68 148	98.85 117	94.15 132	81.53 139	95.58 160	83.61 110	87.05 154	86.45 133	94.71 132	96.27 126	95.91 125	99.42 166	99.38 170

UniMVSNet_ETH3D		88.05 162	87.01 191	89.27 123	88.53 149	97.49 143	90.35 165	83.48 119	94.57 171	77.87 127	70.08 199	61.75 204	96.22 115	90.17 195	95.21 134	99.16 189	99.82 147

GA-MVS		90.38 145	94.59 137	85.46 164	88.30 150	98.44 125	92.18 147	83.30 122	97.89 146	58.05 195	92.86 122	84.25 144	91.27 167	96.65 113	92.61 169	99.66 116	99.43 168

FC-MVSNet-test		92.78 124	96.19 118	88.80 129	88.00 151	97.54 142	93.60 136	82.36 130	98.16 139	79.71 119	91.55 130	95.41 102	89.65 175	96.09 130	95.23 133	99.49 147	99.31 171

FMVSNet1		92.55 129	93.66 144	91.26 104	87.91 152	96.12 166	94.75 122	81.69 137	97.67 147	85.63 102	80.56 172	87.88 131	98.15 83	96.50 116	97.21 92	99.41 168	99.71 158

tfpnnormal		89.09 154	89.71 168	88.38 135	87.37 153	96.78 154	91.46 154	85.20 99	90.33 198	72.35 145	83.45 160	69.30 188	94.45 136	95.29 144	92.86 165	99.44 162	99.93 116

TESTMET0.1,1		92.87 123	97.23 92	87.79 140	86.96 154	99.10 105	94.68 125	77.46 164	99.36 93	71.94 148	93.82 115	96.51 94	95.96 118	97.42 99	94.37 145	99.74 90	99.99 53

FMVSNet5		93.53 110	96.09 119	90.56 111	86.74 155	92.84 199	92.64 144	77.50 163	99.41 90	88.97 76	98.02 72	97.81 84	98.00 87	94.85 151	95.43 131	99.50 146	94.25 201

test-mter		92.67 127	97.13 94	87.47 142	86.72 156	99.07 107	94.28 130	76.90 166	99.21 100	71.53 152	93.63 117	96.32 97	95.67 121	97.32 104	94.36 147	99.74 90	99.99 53

TransMVSNet (Re)		88.33 158	89.55 173	86.91 148	86.65 157	95.56 181	90.48 161	84.44 109	92.02 197	71.07 156	80.13 174	72.48 175	89.41 177	95.05 150	94.44 142	99.39 170	97.14 193

LTVRE_ROB	88.65 16	87.87 164	91.11 159	84.10 177	86.64 158	97.47 144	94.40 128	78.41 159	96.13 157	52.02 202	87.95 146	65.92 198	93.59 147	95.29 144	95.09 136	99.52 140	99.95 108
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
EG-PatchMatch MVS		86.96 177	89.56 172	83.93 178	86.29 159	97.61 141	90.75 159	73.31 183	95.43 164	66.08 173	75.88 193	71.31 180	87.55 190	94.79 152	92.74 166	99.61 126	99.13 177

pm-mvs1		89.68 149	92.00 152	86.96 147	86.23 160	96.62 157	90.36 164	83.05 125	93.97 178	72.15 147	81.77 167	82.10 148	90.69 172	95.38 142	94.50 141	99.29 181	99.65 160

NR-MVSNet		89.52 151	90.71 161	88.14 139	86.19 161	96.20 164	92.07 148	84.58 105	95.54 161	75.27 135	87.52 151	67.96 191	91.24 168	94.33 157	93.45 156	99.49 147	99.97 82

our_test_3					85.89 162	96.09 167	82.15 198

pmmvs4		91.41 140	93.05 146	89.49 122	85.85 163	96.52 159	91.70 152	82.49 128	98.14 140	83.17 111	87.57 150	81.76 149	94.39 137	95.47 140	92.62 168	99.33 175	99.29 172

UniMVSNet (Re)		90.41 144	91.96 153	88.59 133	85.71 164	96.73 155	90.82 157	84.11 116	95.23 166	78.54 124	88.91 143	76.41 161	92.84 152	93.40 176	93.05 163	99.55 135	100.00 1

v8		87.54 168	89.33 177	85.45 165	85.41 165	95.50 184	90.32 166	78.94 156	94.35 176	66.93 170	81.90 166	70.99 182	91.62 163	91.49 189	91.22 185	99.48 151	99.87 139

SixPastTwentyTwo		88.35 157	91.51 156	84.66 170	85.39 166	96.96 152	86.57 185	79.62 150	96.57 154	63.73 181	87.86 147	75.18 164	93.43 148	94.03 161	90.37 191	99.24 184	99.58 163

MIMVSNet		91.01 142	96.22 116	84.93 168	85.24 167	98.09 134	90.40 163	64.96 201	97.55 148	72.65 140	96.23 90	90.81 120	96.79 107	96.69 112	97.06 102	99.52 140	97.09 194

thisisatest0515		90.28 147	94.32 141	85.57 163	85.23 168	97.23 148	85.44 189	83.09 124	96.80 152	72.41 143	89.82 136	90.87 119	87.93 188	95.27 146	90.39 190	99.33 175	99.88 134

V42		87.84 165	89.42 176	85.99 156	85.16 169	96.01 170	90.52 160	81.78 136	94.43 174	67.59 165	81.32 168	71.87 178	91.48 165	91.25 190	91.16 186	99.43 163	99.92 120

WR-MVS_H		88.47 156	90.55 163	86.04 153	85.13 170	96.07 168	89.86 175	79.80 148	94.37 175	72.32 146	83.12 162	74.44 169	89.60 176	93.52 173	92.40 170	99.51 144	99.96 101

N_pmnet		87.31 173	91.51 156	82.41 186	85.13 170	95.57 180	80.59 200	81.79 135	96.20 156	58.52 194	78.62 182	85.66 136	89.36 178	94.64 153	92.14 173	99.08 191	97.72 192

EU-MVSNet		87.20 175	90.47 164	83.38 181	85.11 172	93.85 197	86.10 187	79.76 149	93.30 189	65.39 176	84.41 156	78.43 153	85.04 195	92.20 186	93.03 164	98.86 193	98.05 189

UniMVSNet_NR-MVSNet		90.50 143	92.31 151	88.38 135	85.04 173	96.34 163	90.94 155	85.32 96	95.87 159	75.69 131	87.68 149	78.49 152	93.78 145	93.21 178	94.60 138	99.53 139	99.97 82

v10		87.40 171	89.62 170	84.80 169	84.93 174	95.07 190	90.44 162	75.63 172	94.51 172	66.52 172	78.87 180	73.47 173	91.86 161	93.69 171	91.87 177	99.45 158	99.86 142

pmmvs6		85.75 185	86.97 192	84.34 173	84.88 175	95.59 179	87.41 184	79.19 154	87.81 203	67.56 166	63.05 204	77.76 154	89.15 179	93.45 175	91.90 176	97.83 198	99.21 174

v1144		87.49 169	89.64 169	84.97 167	84.73 176	95.84 174	90.17 167	79.30 152	93.96 179	64.65 178	78.83 181	73.38 174	91.51 164	93.77 168	91.77 178	99.45 158	99.93 116

DU-MVS		89.49 152	90.60 162	88.19 138	84.71 177	96.20 164	90.94 155	84.58 105	95.54 161	75.69 131	87.52 151	68.74 190	93.78 145	91.10 191	95.13 135	99.47 153	99.97 82

Baseline_NR-MVSNet		89.13 153	89.53 174	88.66 132	84.71 177	94.43 192	91.79 151	84.49 108	95.54 161	78.28 125	78.52 184	72.46 176	93.29 149	91.10 191	94.82 137	99.42 166	99.86 142

v148		86.63 183	87.79 188	85.28 166	84.65 179	95.97 171	86.46 186	82.84 127	92.91 192	71.52 153	78.99 179	66.74 196	86.83 192	89.28 197	90.69 188	99.41 168	99.94 113

CP-MVSNet		88.09 161	89.57 171	86.36 152	84.63 180	95.46 186	89.48 177	80.53 143	93.42 185	71.26 155	81.25 169	69.90 186	92.78 153	93.30 177	93.69 154	99.47 153	99.96 101

v2v482		87.46 170	88.90 180	85.78 158	84.58 181	95.95 172	89.90 174	82.43 129	94.19 177	65.65 174	79.80 176	69.12 189	92.67 154	91.88 188	91.46 183	99.45 158	99.93 116

PS-CasMVS		87.24 174	88.52 185	85.73 161	84.58 181	95.35 188	89.03 180	80.17 144	93.11 191	68.86 162	77.71 186	66.89 194	92.30 156	93.13 180	93.50 155	99.46 155	99.96 101

v1192		86.93 178	89.01 178	84.50 171	84.46 183	95.51 183	89.93 173	78.65 158	93.75 180	62.29 183	77.19 188	70.88 183	92.28 157	93.84 165	91.96 175	99.38 172	99.90 126

WR-MVS		88.23 160	90.15 165	86.00 155	84.39 184	95.64 177	89.96 172	81.80 134	94.46 173	71.60 151	82.10 165	74.36 170	88.76 184	92.48 184	92.20 172	99.46 155	99.83 146

v144192		86.80 180	88.90 180	84.35 172	84.33 185	95.56 181	89.34 178	77.74 162	93.60 182	64.03 179	77.82 185	70.76 184	91.28 166	92.91 182	91.74 180	99.37 173	99.90 126

pmmvs5		87.33 172	90.01 166	84.20 175	84.31 186	96.04 169	87.63 183	76.59 169	93.17 190	65.35 177	84.30 158	71.68 179	91.91 160	95.41 141	91.37 184	99.39 170	98.13 186

v1921920		86.81 179	88.93 179	84.33 174	84.23 187	95.41 187	90.09 169	78.10 160	93.74 181	62.17 184	76.98 190	71.14 181	92.05 159	93.69 171	91.69 181	99.32 177	99.88 134

gm-plane-assit		84.93 187	91.61 155	77.14 196	84.14 188	91.29 202	66.18 210	69.70 186	85.22 206	47.95 206	78.58 183	89.24 127	94.90 130	98.82 37	98.12 63	99.99 5	100.00 1

TranMVSNet+NR-MVSNet		88.88 155	89.90 167	87.69 141	84.06 189	95.68 176	91.88 149	85.23 98	95.16 167	72.54 141	83.06 163	70.14 185	92.93 151	90.81 194	94.53 140	99.48 151	99.89 129

v1240		86.24 184	88.56 184	83.54 179	84.05 190	95.21 189	89.27 179	76.76 167	93.42 185	60.68 191	75.99 192	69.80 187	91.21 169	93.83 167	91.76 179	99.29 181	99.91 125

PEN-MVS		87.20 175	88.22 186	86.01 154	84.01 191	94.93 191	90.00 171	81.52 141	93.46 184	69.29 160	79.69 177	65.51 199	91.72 162	91.01 193	93.12 161	99.49 147	99.84 144

MDTV_nov1_ep13_2view		87.75 167	93.32 145	81.26 189	83.74 192	96.64 156	85.66 188	66.20 193	98.36 138	61.61 185	84.34 157	87.95 130	91.12 171	94.01 162	92.66 167	99.22 185	99.27 173

anonymousdsp		87.98 163	92.38 150	82.85 183	83.68 193	96.79 153	90.78 158	74.06 178	95.29 165	57.91 196	83.33 161	83.12 145	91.15 170	95.96 134	92.37 171	99.52 140	99.76 155

DTE-MVSNet		86.70 181	87.66 190	85.58 162	83.30 194	94.29 193	89.74 176	81.53 139	92.77 193	68.93 161	80.13 174	64.00 202	90.62 173	89.45 196	93.34 157	99.32 177	99.67 159

FPMVS		73.80 198	74.62 200	72.84 200	83.09 195	84.44 207	83.89 191	73.64 181	92.20 196	48.50 204	72.19 197	59.51 205	63.16 205	69.13 205	66.26 209	84.74 208	78.59 211

v7n		85.39 186	87.70 189	82.70 184	82.77 196	95.64 177	88.27 182	74.83 174	92.30 195	62.58 182	76.37 191	64.80 201	88.38 186	94.29 159	90.61 189	99.34 174	99.87 139

test20.03		83.86 191	88.73 183	78.16 194	82.60 197	93.00 198	81.61 199	74.68 175	92.36 194	57.50 197	83.01 164	74.48 168	73.30 203	92.40 185	91.14 187	99.29 181	94.75 200

Anonymous20231206		84.28 189	89.53 174	78.17 193	82.31 198	94.16 195	82.57 196	76.51 170	93.38 188	52.98 201	79.47 178	73.74 172	75.45 201	95.07 149	94.41 144	99.18 188	96.46 198

ET-MVSNet_ETH3D		95.20 85	97.82 81	92.15 100	80.77 199	98.13 133	97.65 68	86.93 92	99.72 65	88.56 83	99.29 40	97.01 90	99.24 45	94.58 155	95.98 123	99.75 86	99.99 53

new_pmnet		84.12 190	87.89 187	79.72 191	80.43 200	94.14 196	80.26 201	74.14 177	96.01 158	56.30 200	74.94 194	76.45 160	88.59 185	93.11 181	89.31 193	98.59 196	91.27 204

PM-MVS		82.79 193	84.51 195	80.77 190	77.22 201	92.13 200	83.61 194	73.31 183	93.50 183	61.06 186	77.15 189	46.52 210	90.55 174	94.14 160	89.05 196	98.85 194	99.12 178

pmmvs-eth3d		82.92 192	83.31 197	82.47 185	76.97 202	91.76 201	83.79 192	76.10 171	90.33 198	69.95 159	71.04 198	48.09 207	89.02 181	93.85 164	89.14 194	99.02 192	98.96 179

new-patchmatchnet		78.17 197	80.82 199	75.07 199	76.93 203	91.20 203	71.90 206	73.32 182	86.59 205	48.91 203	67.11 200	47.85 209	81.19 197	88.18 198	87.02 197	98.19 197	97.79 191

pmmvs3		80.91 194	85.62 193	75.42 198	75.01 204	89.09 205	75.31 204	68.70 187	86.99 204	46.74 208	81.18 170	62.91 203	87.95 187	93.84 165	89.06 195	98.80 195	96.23 199

Gipuma		71.02 199	72.60 203	69.19 201	71.31 205	75.11 210	66.36 209	61.65 208	94.93 168	47.29 207	38.74 209	38.52 211	75.52 200	86.09 200	85.92 200	93.01 204	88.87 207
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MDA-MVSNet-bldmvs		80.30 196	82.83 198	77.34 195	69.16 206	94.29 193	72.16 205	81.97 133	90.14 200	57.32 198	94.01 114	47.97 208	86.81 193	68.74 206	86.82 198	96.63 199	97.86 190

MIMVSNet1		80.64 195	83.97 196	76.76 197	68.91 207	91.15 204	78.32 203	75.47 173	89.58 202	56.64 199	65.10 202	65.17 200	82.14 196	93.51 174	91.64 182	99.10 190	91.66 203

PMVS	60.14 18	62.67 202	64.05 205	61.06 203	68.32 208	53.27 216	52.23 214	67.63 190	75.07 209	48.30 205	58.27 205	57.43 206	49.99 211	67.20 207	62.42 210	79.87 211	74.68 212
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
ambc			74.33 201		66.84 209	84.26 208	84.17 190		93.39 187	58.99 193	45.93 208	18.06 217	70.61 204	93.94 163	86.62 199	92.61 206	98.13 186

PMMVS2		65.18 201	68.25 204	61.59 202	61.37 210	79.72 209	59.18 213	61.80 206	64.72 210	37.33 210	53.82 206	35.59 212	54.46 210	73.94 204	80.52 202	95.40 202	89.43 206

EMVS		55.14 205	55.29 208	54.97 204	60.87 211	57.52 213	38.58 216	63.57 205	64.54 211	23.36 214	36.96 210	27.99 214	60.69 206	51.17 210	66.61 208	82.73 210	82.25 209

E-PMN		55.33 204	55.79 207	54.81 205	59.81 212	57.23 214	38.83 215	63.59 204	64.06 212	24.66 213	35.33 211	26.40 215	58.69 207	55.41 209	70.54 206	83.26 209	81.56 210

MVE	58.81 19	52.07 206	55.15 209	48.48 207	42.45 213	62.35 212	36.41 217	54.70 210	49.88 213	27.65 212	29.98 212	18.08 216	54.87 209	65.93 208	77.26 204	74.79 212	82.59 208
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
testmvs		61.76 203	72.90 202	48.76 206	21.21 214	68.61 211	66.11 211	37.38 211	94.83 169	33.06 211	64.31 203	29.72 213	86.08 194	74.44 203	78.71 203	48.74 213	99.65 160

test123		48.14 207	58.11 206	36.51 208	8.71 215	56.81 215	59.55 212	24.08 212	77.50 208	14.41 215	49.20 207	11.94 218	80.98 198	41.62 211	69.81 207	31.32 214	99.90 126

GG-mvs-BLEND		69.85 200	99.39 38	35.39 209	3.67 216	99.94 17	99.10 40	1.69 213	99.85 47	3.19 216	98.13 71	99.46 59	4.92 212	99.23 30	99.14 30	99.80 52	100.00 1

sosnet-low-res		0.00 208	0.00 210	0.00 210	0.00 217	0.00 217	0.00 218	0.00 214	0.00 214	0.00 217	0.00 213	0.00 219	0.00 213	0.00 212	0.00 211	0.00 215	0.00 213

sosnet		0.00 208	0.00 210	0.00 210	0.00 217	0.00 217	0.00 218	0.00 214	0.00 214	0.00 217	0.00 213	0.00 219	0.00 213	0.00 212	0.00 211	0.00 215	0.00 213

test_part1																	100.00 1

MTAPA										96.61 13		100.00 1

MTMP										97.42 8		100.00 1

Patchmatch-RL test							68.01 208

NP-MVS									99.79 57

Patchmtry						99.00 109	95.46 110	65.50 197		67.51 167

DeepMVS_CX						97.31 146	79.48 202	89.65 62	98.66 123	60.89 189	94.40 108	66.89 194	87.65 189	81.69 201		92.76 205	94.24 202

High-resolution multi-view benchmark