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	botani.	boulde.	bridge	door	exhibi.	lectur.	living.	lounge	observ.	old co.	statue	terrac.

MSLP-MVS++		99.89 1	99.85 2	99.99 12	100.00 1	99.96 24	100.00 1	99.95 19	99.11 7	100.00 1	100.00 1	99.60 16	100.00 1	100.00 1	100.00 1	100.00 1

NCCC		99.86 2	99.82 3	100.00 1	100.00 1	99.99 5	100.00 1	99.71 61	99.07 10	100.00 1	100.00 1	99.59 19	100.00 1	100.00 1	100.00 1	100.00 1

CHOSEN 280x420		99.85 3	99.87 1	99.80 104	99.99 49	99.97 21	99.97 243	99.98 16	98.96 32	100.00 1	100.00 1	99.96 3	99.42 262	100.00 1	100.00 1	100.00 1

MCST-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 5	100.00 1	99.73 56	99.19 5	100.00 1	100.00 1	99.31 63	100.00 1	100.00 1	100.00 1	100.00 1

CNVR-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 5	100.00 1	99.77 48	99.07 10	100.00 1	100.00 1	99.39 56	100.00 1	100.00 1	100.00 1	100.00 1

APDe-MVS		99.84 6	99.78 7	99.99 12	100.00 1	99.98 17	100.00 1	99.44 116	99.06 12	100.00 1	100.00 1	99.56 22	99.99 94	100.00 1	100.00 1	100.00 1
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
SED-MVS		99.83 7	99.77 9	100.00 1	100.00 1	99.99 5	100.00 1	99.42 140	99.03 20	100.00 1	100.00 1	99.50 36	100.00 1	100.00 1	100.00 1	100.00 1

DVP-MVS		99.83 7	99.78 7	100.00 1	100.00 1	99.99 5	100.00 1	99.42 140	99.04 15	100.00 1	100.00 1	99.53 28	100.00 1	100.00 1	100.00 1	100.00 1
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
TSAR-MVS + MP.		99.82 9	99.77 9	99.99 12	100.00 1	99.96 24	100.00 1	99.43 124	99.05 14	100.00 1	100.00 1	99.45 44	99.99 94	100.00 1	100.00 1	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
HPM-MVS++		99.82 9	99.76 12	99.99 12	99.99 49	99.98 17	100.00 1	99.83 39	98.88 44	99.96 121	100.00 1	99.21 76	100.00 1	100.00 1	100.00 1	99.99 107

DVP-MVS++		99.81 11	99.75 14	100.00 1	100.00 1	99.99 5	100.00 1	99.42 140	98.79 60	100.00 1	100.00 1	99.54 25	100.00 1	100.00 1	100.00 1	100.00 1

MSP-MVS		99.81 11	99.77 9	99.94 63	100.00 1	99.86 79	100.00 1	99.42 140	98.87 47	100.00 1	100.00 1	99.65 14	99.96 138	100.00 1	100.00 1	100.00 1
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
SD-MVS		99.81 11	99.75 14	99.99 12	99.99 49	99.96 24	100.00 1	99.42 140	99.01 26	100.00 1	100.00 1	99.33 58	100.00 1	100.00 1	100.00 1	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
DPE-MVS		99.79 14	99.73 17	99.99 12	99.99 49	99.98 17	100.00 1	99.42 140	98.91 41	100.00 1	100.00 1	99.22 75	100.00 1	100.00 1	100.00 1	100.00 1
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
XVS		99.79 14	99.73 17	99.98 23	100.00 1	99.94 41	100.00 1	99.75 52	98.67 67	100.00 1	100.00 1	99.16 80	100.00 1	100.00 1	100.00 1	100.00 1

SteuartSystems-ACMMP		99.78 16	99.71 20	99.98 23	99.76 148	99.95 32	100.00 1	99.42 140	98.69 65	100.00 1	100.00 1	99.52 31	99.99 94	100.00 1	100.00 1	100.00 1
Skip Steuart: Steuart Systems R&D Blog.
PAPM		99.78 16	99.76 12	99.85 87	99.01 288	99.95 32	100.00 1	99.75 52	99.37 3	99.99 105	100.00 1	99.76 10	99.60 221	100.00 1	100.00 1	100.00 1

DP-MVS Recon		99.76 18	99.69 22	99.98 23	100.00 1	99.95 32	100.00 1	99.52 72	97.99 110	99.99 105	100.00 1	99.72 11	100.00 1	99.96 85	100.00 1	100.00 1

PAPR		99.76 18	99.68 25	99.99 12	100.00 1	99.96 24	100.00 1	99.47 79	98.16 96	100.00 1	100.00 1	99.51 32	100.00 1	100.00 1	100.00 1	100.00 1

DeepC-MVS_fast	98.92 1	99.75 20	99.67 27	99.99 12	99.99 49	99.96 24	99.73 301	99.52 72	99.06 12	100.00 1	100.00 1	98.80 118	100.00 1	99.95 91	100.00 1	100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MG-MVS		99.75 20	99.68 25	99.97 31	100.00 1	99.91 53	99.98 237	99.47 79	99.09 9	100.00 1	100.00 1	98.59 128	100.00 1	99.95 91	100.00 1	100.00 1

HFP-MVS		99.74 22	99.67 27	99.96 42	100.00 1	99.89 67	100.00 1	99.76 49	97.95 118	100.00 1	100.00 1	99.31 63	100.00 1	99.99 61	100.00 1	100.00 1

ACMMPR		99.74 22	99.67 27	99.96 42	100.00 1	99.89 67	100.00 1	99.76 49	97.95 118	100.00 1	100.00 1	99.29 69	100.00 1	99.99 61	100.00 1	100.00 1

PAPM_NR		99.74 22	99.66 30	99.99 12	100.00 1	99.96 24	100.00 1	99.47 79	97.87 123	100.00 1	100.00 1	99.60 16	100.00 1	100.00 1	100.00 1	100.00 1

CDPH-MVS		99.73 25	99.64 33	99.99 12	100.00 1	99.97 21	100.00 1	99.42 140	98.02 108	100.00 1	100.00 1	99.32 61	99.99 94	100.00 1	100.00 1	100.00 1

region2R		99.72 26	99.64 33	99.97 31	100.00 1	99.90 60	100.00 1	99.74 55	97.86 124	100.00 1	100.00 1	99.19 78	100.00 1	99.99 61	100.00 1	100.00 1

API-MVS		99.72 26	99.70 21	99.79 106	99.97 89	99.37 147	99.96 248	99.94 22	98.48 75	100.00 1	100.00 1	98.92 107	100.00 1	100.00 1	100.00 1	100.00 1

CNLPA		99.72 26	99.65 31	99.91 70	99.97 89	99.72 97	100.00 1	99.47 79	98.43 78	99.88 165	100.00 1	99.14 83	100.00 1	99.97 83	100.00 1	100.00 1

ZNCC-MVS		99.71 29	99.62 41	99.97 31	99.99 49	99.90 60	100.00 1	99.79 45	97.97 114	99.97 116	100.00 1	98.97 98	100.00 1	99.94 93	100.00 1	100.00 1

train_agg		99.71 29	99.63 37	99.97 31	100.00 1	99.95 32	100.00 1	99.42 140	97.70 136	100.00 1	100.00 1	99.51 32	99.97 125	100.00 1	100.00 1	100.00 1

MVS_111021_HR		99.71 29	99.63 37	99.93 67	99.95 96	99.83 85	100.00 1	100.00 1	98.89 43	100.00 1	100.00 1	97.85 151	99.95 151	100.00 1	100.00 1	100.00 1

EI-MVSNet-Vis-set		99.70 32	99.64 33	99.87 80	100.00 1	99.64 107	99.98 237	99.44 116	98.35 86	99.99 105	100.00 1	99.04 93	99.96 138	99.98 73	100.00 1	100.00 1

MVS_111021_LR		99.70 32	99.65 31	99.88 79	99.96 94	99.70 102	100.00 1	99.97 17	98.96 32	100.00 1	100.00 1	97.93 146	99.95 151	99.99 61	100.00 1	100.00 1

PLC	98.56 2	99.70 32	99.74 16	99.58 146	100.00 1	98.79 195	100.00 1	99.54 71	98.58 72	99.96 121	100.00 1	99.59 19	100.00 1	100.00 1	100.00 1	99.94 133
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
SMA-MVS		99.69 35	99.59 44	99.98 23	99.99 49	99.93 45	100.00 1	99.43 124	97.50 165	100.00 1	100.00 1	99.43 49	100.00 1	100.00 1	100.00 1	100.00 1
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
MVS_0304		99.69 35	99.63 37	99.86 83	99.96 94	99.63 109	100.00 1	99.92 34	99.03 20	99.97 116	100.00 1	97.87 149	99.96 138	100.00 1	99.96 118	100.00 1

EI-MVSNet-UG-set		99.69 35	99.63 37	99.87 80	99.99 49	99.64 107	99.95 254	99.44 116	98.35 86	100.00 1	100.00 1	98.98 97	99.97 125	99.98 73	100.00 1	100.00 1

PGM-MVS		99.69 35	99.61 42	99.95 51	99.99 49	99.85 82	100.00 1	99.58 67	97.69 138	100.00 1	100.00 1	99.44 45	100.00 1	99.79 119	100.00 1	100.00 1

mPP-MVS		99.69 35	99.60 43	99.97 31	100.00 1	99.91 53	100.00 1	99.42 140	97.91 120	100.00 1	100.00 1	99.04 93	100.00 1	100.00 1	100.00 1	100.00 1

SR-MVS		99.68 40	99.58 46	99.98 23	100.00 1	99.95 32	100.00 1	99.64 64	97.59 154	100.00 1	100.00 1	98.99 96	99.99 94	100.00 1	100.00 1	100.00 1

MTAPA		99.68 40	99.59 44	99.97 31	99.99 49	99.91 53	100.00 1	99.42 140	98.32 88	99.94 149	100.00 1	98.65 124	100.00 1	99.96 85	100.00 1	100.00 1

APD-MVS		99.68 40	99.58 46	99.97 31	99.99 49	99.96 24	100.00 1	99.42 140	97.53 160	100.00 1	100.00 1	99.27 72	99.97 125	100.00 1	100.00 1	100.00 1
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ACMMP_NAP		99.67 43	99.57 49	99.97 31	99.98 85	99.92 50	100.00 1	99.42 140	97.83 125	100.00 1	100.00 1	98.89 110	100.00 1	99.98 73	100.00 1	100.00 1

CP-MVS		99.67 43	99.58 46	99.95 51	100.00 1	99.84 84	100.00 1	99.42 140	97.77 130	100.00 1	100.00 1	99.07 87	100.00 1	100.00 1	100.00 1	100.00 1

SF-MVS		99.66 45	99.57 49	99.95 51	99.99 49	99.85 82	100.00 1	99.42 140	97.67 139	100.00 1	100.00 1	99.05 90	99.99 94	100.00 1	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 46	99.55 56	99.97 31	99.99 49	99.91 53	100.00 1	99.48 78	97.54 158	100.00 1	100.00 1	98.97 98	99.99 94	99.98 73	100.00 1	100.00 1

ACMMP		99.65 46	99.57 49	99.89 75	99.99 49	99.66 105	99.75 295	99.73 56	98.16 96	99.75 190	100.00 1	98.90 109	100.00 1	99.96 85	99.88 133	100.00 1
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
GST-MVS		99.64 48	99.53 59	99.95 51	100.00 1	99.86 79	100.00 1	99.79 45	97.72 134	99.95 147	100.00 1	98.39 135	100.00 1	99.96 85	99.99 102	100.00 1

PS-MVSNAJ		99.64 48	99.57 49	99.85 87	99.78 145	99.81 87	99.95 254	99.42 140	98.38 80	100.00 1	100.00 1	98.75 120	100.00 1	99.88 103	99.99 102	99.74 235

F-COLMAP		99.64 48	99.64 33	99.67 130	99.99 49	99.07 174	100.00 1	99.44 116	98.30 89	99.90 160	100.00 1	99.18 79	99.99 94	99.91 98	100.00 1	99.94 133

fmvsm_l_conf0.5_n_a		99.63 51	99.55 56	99.86 83	99.83 120	99.58 115	100.00 1	99.36 214	98.98 30	100.00 1	100.00 1	97.85 151	99.99 94	100.00 1	99.94 123	100.00 1

fmvsm_l_conf0.5_n		99.63 51	99.56 54	99.86 83	99.81 127	99.59 113	100.00 1	99.36 214	98.98 30	100.00 1	100.00 1	97.92 147	99.99 94	100.00 1	99.95 121	100.00 1

MM		99.63 51	99.52 61	99.94 63	99.99 49	99.82 86	100.00 1	99.97 17	99.11 7	100.00 1	100.00 1	96.65 203	100.00 1	100.00 1	99.97 115	100.00 1

SR-MVS-dyc-post		99.63 51	99.52 61	99.97 31	99.99 49	99.91 53	100.00 1	99.42 140	97.62 146	100.00 1	100.00 1	98.65 124	99.99 94	99.99 61	100.00 1	100.00 1

DPM-MVS		99.63 51	99.51 63	100.00 1	99.90 108	100.00 1	100.00 1	99.43 124	99.00 27	100.00 1	100.00 1	99.58 21	100.00 1	97.64 270	100.00 1	100.00 1

EPNet		99.62 56	99.69 22	99.42 166	99.99 49	98.37 222	100.00 1	99.89 37	98.83 53	100.00 1	100.00 1	98.97 98	100.00 1	99.90 99	99.61 159	99.89 165
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DELS-MVS		99.62 56	99.56 54	99.82 93	99.92 104	99.45 137	100.00 1	99.78 47	98.92 39	99.73 192	100.00 1	97.70 160	100.00 1	99.93 95	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
MP-MVS-pluss		99.61 58	99.50 64	99.97 31	99.98 85	99.92 50	100.00 1	99.42 140	97.53 160	99.77 187	100.00 1	98.77 119	100.00 1	99.99 61	100.00 1	99.99 107
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MP-MVS		99.61 58	99.49 66	99.98 23	99.99 49	99.94 41	100.00 1	99.42 140	97.82 126	99.99 105	100.00 1	98.20 138	100.00 1	99.99 61	100.00 1	100.00 1
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
TSAR-MVS + GP.		99.61 58	99.69 22	99.35 177	99.99 49	98.06 246	100.00 1	99.36 214	99.83 2	100.00 1	100.00 1	98.95 102	99.99 94	100.00 1	99.11 167	100.00 1

HPM-MVS_fast		99.60 61	99.49 66	99.91 70	99.99 49	99.78 90	100.00 1	99.42 140	97.09 195	100.00 1	100.00 1	98.95 102	99.96 138	99.98 73	100.00 1	100.00 1

HPM-MVS		99.59 62	99.50 64	99.89 75	100.00 1	99.70 102	100.00 1	99.42 140	97.46 169	100.00 1	100.00 1	98.60 127	99.96 138	99.99 61	100.00 1	100.00 1
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
mvsany_test1		99.57 63	99.48 69	99.85 87	99.86 115	99.54 120	100.00 1	99.36 214	98.94 37	100.00 1	100.00 1	97.97 144	100.00 1	99.88 103	99.28 164	100.00 1

test_fmvsmconf_n		99.56 64	99.46 70	99.86 83	99.68 161	99.58 115	100.00 1	99.31 240	98.92 39	99.88 165	100.00 1	97.35 179	99.99 94	99.98 73	99.99 102	100.00 1

test_fmvsm_n_1920		99.55 65	99.49 66	99.73 120	99.85 116	99.19 166	100.00 1	99.41 186	98.87 47	100.00 1	100.00 1	97.34 180	100.00 1	99.98 73	99.90 130	100.00 1

WTY-MVS		99.54 66	99.40 72	99.95 51	99.81 127	99.93 45	100.00 1	100.00 1	97.98 112	99.84 169	100.00 1	98.94 104	99.98 118	99.86 107	98.21 208	99.94 133

test_yl		99.51 67	99.37 77	99.95 51	99.82 121	99.90 60	100.00 1	99.47 79	97.48 167	100.00 1	100.00 1	99.80 4	100.00 1	99.98 73	97.75 236	99.94 133

DCV-MVSNet		99.51 67	99.37 77	99.95 51	99.82 121	99.90 60	100.00 1	99.47 79	97.48 167	100.00 1	100.00 1	99.80 4	100.00 1	99.98 73	97.75 236	99.94 133

xiu_mvs_v2_base		99.51 67	99.41 71	99.82 93	99.70 156	99.73 96	99.92 261	99.40 190	98.15 98	100.00 1	100.00 1	98.50 132	100.00 1	99.85 109	99.13 166	99.74 235

HY-MVS	96.53 9	99.50 70	99.35 82	99.96 42	99.81 127	99.93 45	99.64 313	100.00 1	97.97 114	99.84 169	99.85 247	98.94 104	99.99 94	99.86 107	98.23 207	99.95 128

PHI-MVS		99.50 70	99.39 73	99.82 93	100.00 1	99.45 137	100.00 1	99.94 22	96.38 253	100.00 1	100.00 1	98.18 139	100.00 1	100.00 1	100.00 1	100.00 1

CPTT-MVS		99.49 72	99.38 74	99.85 87	100.00 1	99.54 120	100.00 1	99.42 140	97.58 155	99.98 111	100.00 1	97.43 177	100.00 1	99.99 61	100.00 1	100.00 1

MAR-MVS		99.49 72	99.36 80	99.89 75	99.97 89	99.66 105	99.74 296	99.95 19	97.89 121	100.00 1	100.00 1	96.71 202	100.00 1	100.00 1	100.00 1	100.00 1
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
test2506		99.48 74	99.38 74	99.75 116	99.89 110	99.51 126	99.45 334	100.00 1	98.38 80	99.83 172	100.00 1	98.86 111	99.81 198	99.25 195	98.78 175	99.94 133

PVSNet_Blended		99.48 74	99.36 80	99.83 91	99.98 85	99.60 111	100.00 1	100.00 1	97.79 128	100.00 1	100.00 1	96.57 205	99.99 94	100.00 1	99.88 133	99.90 159

test_fmvsmvis_n_1920		99.46 76	99.37 77	99.73 120	98.88 305	99.18 168	100.00 1	99.26 273	98.85 49	99.79 184	100.00 1	97.70 160	100.00 1	99.98 73	99.86 137	100.00 1

sss		99.45 77	99.34 84	99.80 104	99.76 148	99.50 128	100.00 1	99.91 36	97.72 134	99.98 111	99.94 227	98.45 133	100.00 1	99.53 179	98.75 178	99.89 165

AdaColmap		99.44 78	99.26 90	99.95 51	100.00 1	99.86 79	99.70 306	99.99 13	98.53 73	99.90 160	100.00 1	95.34 222	100.00 1	99.92 96	100.00 1	100.00 1

thisisatest0515		99.42 79	99.31 85	99.74 117	99.59 200	99.55 118	100.00 1	99.46 94	96.65 234	99.92 155	100.00 1	99.44 45	99.85 189	99.09 207	99.63 158	99.81 210

MVSMamba_pp		99.41 80	99.28 86	99.79 106	99.66 175	99.59 113	100.00 1	99.30 244	97.75 133	99.96 121	99.98 189	97.13 184	99.89 174	99.75 131	100.00 1	99.90 159

CANet		99.40 81	99.24 93	99.89 75	99.99 49	99.76 92	100.00 1	99.73 56	98.40 79	99.78 186	100.00 1	95.28 223	99.96 138	100.00 1	99.99 102	99.96 122

114514_t		99.39 82	99.25 91	99.81 99	99.97 89	99.48 135	100.00 1	99.42 140	95.53 283	100.00 1	100.00 1	98.37 136	99.95 151	99.97 83	100.00 1	100.00 1

alignmvs		99.38 83	99.21 97	99.91 70	99.73 153	99.92 50	100.00 1	99.51 76	97.61 150	100.00 1	100.00 1	99.06 88	99.93 167	99.83 113	97.12 248	99.90 159

1314		99.38 83	99.19 101	99.96 42	98.88 305	99.89 67	99.24 355	99.93 30	98.88 44	98.79 258	100.00 1	97.02 188	100.00 1	100.00 1	100.00 1	100.00 1

thisisatest0530		99.37 85	99.27 87	99.69 126	99.59 200	99.41 142	100.00 1	99.46 94	96.46 245	99.90 160	100.00 1	99.44 45	99.85 189	98.97 210	99.58 160	99.80 224

xiu_mvs_v1_base_debu		99.35 86	99.21 97	99.79 106	99.67 168	99.71 98	99.78 286	99.36 214	98.13 100	100.00 1	100.00 1	97.00 192	100.00 1	99.83 113	99.07 168	99.66 244

xiu_mvs_v1_base		99.35 86	99.21 97	99.79 106	99.67 168	99.71 98	99.78 286	99.36 214	98.13 100	100.00 1	100.00 1	97.00 192	100.00 1	99.83 113	99.07 168	99.66 244

xiu_mvs_v1_base_debi		99.35 86	99.21 97	99.79 106	99.67 168	99.71 98	99.78 286	99.36 214	98.13 100	100.00 1	100.00 1	97.00 192	100.00 1	99.83 113	99.07 168	99.66 244

ETV-MVS		99.34 89	99.24 93	99.64 135	99.58 205	99.33 149	100.00 1	99.25 276	97.57 156	99.96 121	100.00 1	97.44 176	99.79 201	99.70 144	99.65 156	99.81 210

tttt0517		99.34 89	99.23 96	99.67 130	99.57 209	99.38 144	100.00 1	99.46 94	96.33 257	99.89 163	100.00 1	99.44 45	99.84 191	98.93 212	99.46 163	99.78 230

CS-MVS		99.33 91	99.27 87	99.50 154	99.99 49	99.00 185	100.00 1	99.13 322	97.26 186	99.96 121	100.00 1	97.79 155	99.64 219	99.64 161	99.67 154	99.87 188

PVSNet_Blended_VisFu		99.33 91	99.18 104	99.78 111	99.82 121	99.49 131	100.00 1	99.95 19	97.36 176	99.63 198	100.00 1	96.45 209	99.95 151	99.79 119	99.65 156	99.89 165

fmvsm_s_conf0.5_n_a		99.32 93	99.15 106	99.81 99	99.80 138	99.47 136	100.00 1	99.35 225	98.22 91	100.00 1	100.00 1	95.21 227	99.99 94	99.96 85	99.86 137	99.98 109

iter_conf05		99.32 93	99.15 106	99.82 93	99.68 161	99.61 110	99.16 369	99.27 265	96.66 233	99.96 121	99.97 199	97.89 148	99.92 169	99.76 127	100.00 1	99.94 133

HyFIR lowres test		99.32 93	99.24 93	99.58 146	99.95 96	99.26 157	100.00 1	99.99 13	96.72 226	99.29 221	99.91 234	99.49 38	99.47 254	99.74 132	98.08 215	100.00 1

CS-MVS-test		99.31 96	99.27 87	99.43 164	99.99 49	98.77 196	100.00 1	99.19 299	97.24 187	99.96 121	100.00 1	97.56 168	99.70 216	99.68 152	99.81 145	99.82 201

LS3D		99.31 96	99.13 109	99.87 80	99.99 49	99.71 98	99.55 324	99.46 94	97.32 181	99.82 180	100.00 1	96.85 199	99.97 125	99.14 202	100.00 1	99.92 146

PVSNet	94.91 18	99.30 98	99.25 91	99.44 162	100.00 1	98.32 228	100.00 1	99.86 38	98.04 107	100.00 1	100.00 1	96.10 212	100.00 1	99.55 174	99.73 149	100.00 1

iter_conf05_11		99.29 99	99.15 106	99.69 126	99.65 178	99.28 154	99.99 212	99.26 273	96.49 244	99.96 121	99.97 199	97.34 180	99.89 174	99.71 140	100.00 1	99.89 165

lupinMVS		99.29 99	99.16 105	99.69 126	99.45 245	99.49 131	100.00 1	99.15 313	97.45 170	99.97 116	100.00 1	96.76 200	99.76 208	99.67 155	100.00 1	99.81 210

CSCG		99.28 101	99.35 82	99.05 201	99.99 49	97.15 290	100.00 1	99.47 79	97.44 171	99.42 209	100.00 1	97.83 154	100.00 1	99.99 61	100.00 1	100.00 1

thres200		99.27 102	99.04 117	99.96 42	99.81 127	99.90 60	100.00 1	99.94 22	97.31 183	99.83 172	99.96 214	97.04 185	100.00 1	99.62 165	97.88 225	99.98 109

OMC-MVS		99.27 102	99.38 74	98.96 209	99.95 96	97.06 294	100.00 1	99.40 190	98.83 53	99.88 165	100.00 1	97.01 189	99.86 183	99.47 182	99.84 142	99.97 116

testing11		99.26 104	99.19 101	99.46 158	99.64 184	98.61 207	100.00 1	99.43 124	96.94 204	99.92 155	99.94 227	99.43 49	99.97 125	99.67 155	97.79 234	99.82 201

EIA-MVS		99.26 104	99.19 101	99.45 160	99.63 186	98.75 197	100.00 1	99.27 265	96.93 205	99.95 147	100.00 1	97.47 173	99.79 201	99.74 132	99.72 150	99.82 201

tfpn200view9		99.26 104	99.03 118	99.96 42	99.81 127	99.89 67	100.00 1	99.94 22	97.23 188	99.83 172	99.96 214	97.04 185	100.00 1	99.59 169	97.85 227	99.98 109

thres400		99.26 104	99.03 118	99.95 51	99.81 127	99.89 67	100.00 1	99.94 22	97.23 188	99.83 172	99.96 214	97.04 185	100.00 1	99.59 169	97.85 227	99.97 116

test_fmvsmconf0.1_n		99.25 108	99.05 116	99.82 93	98.92 301	99.55 118	100.00 1	99.23 285	98.91 41	99.75 190	99.97 199	94.79 235	99.94 163	99.94 93	99.99 102	99.97 116

thres100view900		99.25 108	99.01 120	99.95 51	99.81 127	99.87 76	100.00 1	99.94 22	97.13 193	99.83 172	99.96 214	97.01 189	100.00 1	99.59 169	97.85 227	99.98 109

EPMVS		99.25 108	99.13 109	99.60 140	99.60 196	99.20 165	99.60 319	100.00 1	96.93 205	99.92 155	99.36 319	99.05 90	99.71 215	98.77 221	98.94 172	99.90 159

thres600view7		99.24 111	99.00 122	99.95 51	99.81 127	99.87 76	100.00 1	99.94 22	97.13 193	99.83 172	99.96 214	97.01 189	100.00 1	99.54 177	97.77 235	99.97 116

MVS		99.22 112	98.96 127	99.98 23	99.00 292	99.95 32	99.24 355	99.94 22	98.14 99	98.88 248	100.00 1	95.63 220	100.00 1	99.85 109	100.00 1	100.00 1

fmvsm_s_conf0.5_n		99.21 113	99.01 120	99.83 91	99.84 117	99.53 122	100.00 1	99.38 205	98.29 90	100.00 1	100.00 1	93.62 249	99.99 94	99.99 61	99.93 126	99.98 109

EC-MVSNet		99.19 114	99.09 114	99.48 157	99.42 249	99.07 174	100.00 1	99.21 295	96.95 203	99.96 121	100.00 1	96.88 198	99.48 252	99.64 161	99.79 148	99.88 179

testing91		99.18 115	99.10 112	99.41 167	99.60 196	98.43 214	100.00 1	99.43 124	96.76 219	99.82 180	99.92 232	99.05 90	99.98 118	99.62 165	97.67 240	99.81 210

testing99		99.18 115	99.10 112	99.41 167	99.60 196	98.43 214	100.00 1	99.43 124	96.76 219	99.84 169	99.92 232	99.06 88	99.98 118	99.62 165	97.67 240	99.81 210

UWE-MVS		99.18 115	99.06 115	99.51 151	99.67 168	98.80 194	100.00 1	99.43 124	96.80 216	99.93 154	99.86 242	99.79 6	99.94 163	97.78 266	98.33 200	99.80 224

ETVMVS		99.16 118	98.98 125	99.69 126	99.67 168	99.56 117	100.00 1	99.45 102	96.36 254	99.98 111	99.95 222	98.65 124	99.64 219	99.11 206	97.63 243	99.88 179

FE-MVS		99.16 118	98.99 124	99.66 133	99.65 178	99.18 168	99.58 321	99.43 124	95.24 293	99.91 158	99.59 299	99.37 57	99.97 125	98.31 244	99.81 145	99.83 196

testing222		99.14 120	98.94 132	99.73 120	99.67 168	99.51 126	100.00 1	99.43 124	96.90 210	99.99 105	99.90 236	98.55 130	99.86 183	98.85 216	97.18 247	99.81 210

PMMVS		99.12 121	98.97 126	99.58 146	99.57 209	98.98 187	100.00 1	99.30 244	97.14 192	99.96 121	100.00 1	96.53 208	99.82 195	99.70 144	98.49 184	99.94 133

jason		99.11 122	98.96 127	99.59 142	99.17 272	99.31 152	100.00 1	99.13 322	97.38 175	99.83 172	100.00 1	95.54 221	99.72 214	99.57 173	99.97 115	99.74 235
jason: jason.
EPP-MVSNet		99.10 123	99.00 122	99.40 171	99.51 228	98.68 203	99.92 261	99.43 124	95.47 289	99.65 197	100.00 1	99.51 32	99.76 208	99.53 179	98.00 216	99.75 234

TESTMET0.1,1		99.08 124	98.96 127	99.44 162	99.63 186	99.38 144	100.00 1	99.45 102	95.53 283	99.48 205	100.00 1	99.71 12	99.02 281	96.84 295	99.99 102	99.91 148

IS-MVSNet		99.08 124	98.91 136	99.59 142	99.65 178	99.38 144	99.78 286	99.24 281	96.70 228	99.51 203	100.00 1	98.44 134	99.52 246	98.47 238	98.39 192	99.88 179

UA-Net		99.06 126	98.83 142	99.74 117	99.52 223	99.40 143	99.08 381	99.45 102	97.64 143	99.83 172	100.00 1	95.80 215	99.94 163	98.35 242	99.80 147	99.88 179

3Dnovator	95.63 14	99.06 126	98.76 149	99.96 42	98.86 309	99.90 60	99.98 237	99.93 30	98.95 35	98.49 277	100.00 1	92.91 260	100.00 1	99.71 140	100.00 1	100.00 1

patch_mono-2		99.04 128	99.79 6	96.81 327	99.92 104	90.47 375	100.00 1	99.41 186	98.95 35	100.00 1	100.00 1	99.78 7	100.00 1	100.00 1	100.00 1	99.95 128

VNet		99.04 128	98.75 150	99.90 73	99.81 127	99.75 93	99.50 330	99.47 79	98.36 84	100.00 1	99.99 184	94.66 237	100.00 1	99.90 99	97.09 249	99.96 122

sasdasda		99.03 130	98.73 152	99.94 63	99.75 150	99.95 32	100.00 1	99.30 244	97.64 143	100.00 1	100.00 1	95.22 225	99.97 125	99.76 127	96.90 254	99.91 148

canonicalmvs		99.03 130	98.73 152	99.94 63	99.75 150	99.95 32	100.00 1	99.30 244	97.64 143	100.00 1	100.00 1	95.22 225	99.97 125	99.76 127	96.90 254	99.91 148

test-LLR		99.03 130	98.91 136	99.40 171	99.40 256	99.28 154	100.00 1	99.45 102	96.70 228	99.42 209	99.12 328	99.31 63	99.01 282	96.82 296	99.99 102	99.91 148

PatchmatchNet		99.03 130	98.96 127	99.26 191	99.49 236	98.33 226	99.38 342	99.45 102	96.64 235	99.96 121	99.58 301	99.49 38	99.50 250	97.63 271	99.00 171	99.93 144
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
3Dnovator+	95.58 15	99.03 130	98.71 156	99.96 42	98.99 295	99.89 67	100.00 1	99.51 76	98.96 32	98.32 285	100.00 1	92.78 262	100.00 1	99.87 106	100.00 1	100.00 1

CANet_DTU		99.02 135	98.90 139	99.41 167	99.88 112	98.71 201	100.00 1	99.29 250	98.84 51	100.00 1	100.00 1	94.02 244	100.00 1	98.08 253	99.96 118	99.52 250

PatchMatch-RL		99.02 135	98.78 147	99.74 117	99.99 49	99.29 153	100.00 1	100.00 1	98.38 80	99.89 163	99.81 256	93.14 258	99.99 94	97.85 264	99.98 112	99.95 128

MGCFI-Net		99.01 137	98.70 158	99.93 67	99.74 152	99.94 41	100.00 1	99.29 250	97.60 153	100.00 1	100.00 1	95.10 229	99.96 138	99.74 132	96.85 256	99.91 148

FA-MVS(test-final)		99.00 138	98.75 150	99.73 120	99.63 186	99.43 140	99.83 276	99.43 124	95.84 275	99.52 202	99.37 318	97.84 153	99.96 138	97.63 271	99.68 152	99.79 227

CHOSEN 1792x2688		99.00 138	98.91 136	99.25 192	99.90 108	97.79 266	100.00 1	99.99 13	98.79 60	98.28 288	100.00 1	93.63 248	99.95 151	99.66 159	99.95 121	100.00 1

DeepC-MVS	97.84 5	99.00 138	98.80 146	99.60 140	99.93 101	99.03 180	100.00 1	99.40 190	98.61 71	99.33 219	100.00 1	92.23 271	99.95 151	99.74 132	99.96 118	99.83 196
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
baseline2		98.99 141	98.93 134	99.18 196	99.26 269	99.15 171	100.00 1	99.46 94	96.71 227	96.79 343	100.00 1	99.42 52	99.25 273	98.75 223	99.94 123	99.15 257

QAPM		98.99 141	98.66 159	99.96 42	99.01 288	99.87 76	99.88 270	99.93 30	97.99 110	98.68 262	100.00 1	93.17 256	100.00 1	99.32 191	100.00 1	100.00 1

Vis-MVSNet (Re-imp)		98.99 141	98.89 140	99.29 186	99.64 184	98.89 191	99.98 237	99.31 240	96.74 223	99.48 205	100.00 1	98.11 141	99.10 277	98.39 240	98.34 197	99.89 165

tpmrst		98.98 144	98.93 134	99.14 198	99.61 194	97.74 267	99.52 328	99.36 214	96.05 267	99.98 111	99.64 287	99.04 93	99.86 183	98.94 211	98.19 210	99.82 201

test-mter		98.96 145	98.82 143	99.40 171	99.40 256	99.28 154	100.00 1	99.45 102	95.44 292	99.42 209	99.12 328	99.70 13	99.01 282	96.82 296	99.99 102	99.91 148

diffmvs		98.96 145	98.73 152	99.63 136	99.54 213	99.16 170	100.00 1	99.18 306	97.33 180	99.96 121	100.00 1	94.60 238	99.91 171	99.66 159	98.33 200	99.82 201
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
CDS-MVSNet		98.96 145	98.95 131	99.01 205	99.48 238	98.36 224	99.93 260	99.37 208	96.79 217	99.31 220	99.83 250	99.77 9	98.91 291	98.07 255	97.98 217	99.77 231
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
mamv4		98.95 148	99.11 111	98.46 234	99.68 161	95.67 316	99.14 374	99.27 265	96.43 246	99.94 149	99.97 199	97.79 155	99.88 180	99.77 126	100.00 1	99.84 192

MVSFormer		98.94 149	98.82 143	99.28 189	99.45 245	99.49 131	100.00 1	99.13 322	95.46 290	99.97 116	100.00 1	96.76 200	98.59 320	98.63 230	100.00 1	99.74 235

MVS_Test		98.93 150	98.65 160	99.77 114	99.62 192	99.50 128	99.99 212	99.19 299	95.52 285	99.96 121	99.86 242	96.54 207	99.98 118	98.65 228	98.48 185	99.82 201

baseline1		98.91 151	98.61 164	99.81 99	99.71 154	99.77 91	99.78 286	99.44 116	97.51 164	98.81 256	99.99 184	98.25 137	99.76 208	98.60 233	95.41 269	99.89 165

1112_ss		98.91 151	98.71 156	99.51 151	99.69 157	98.75 197	99.99 212	99.15 313	96.82 214	98.84 253	100.00 1	97.45 174	99.89 174	98.66 226	97.75 236	99.89 165

MSDG		98.90 153	98.63 162	99.70 125	99.92 104	99.25 159	100.00 1	99.37 208	95.71 277	99.40 215	100.00 1	96.58 204	99.95 151	96.80 298	99.94 123	99.91 148

dcpmvs_2		98.87 154	99.53 59	96.90 321	99.87 114	90.88 374	99.94 258	99.07 341	98.20 94	100.00 1	100.00 1	98.69 123	99.86 183	100.00 1	100.00 1	99.95 128

DP-MVS		98.86 155	98.54 171	99.81 99	99.97 89	99.45 137	99.52 328	99.40 190	94.35 317	98.36 281	100.00 1	96.13 211	99.97 125	99.12 205	100.00 1	100.00 1

CostFormer		98.84 156	98.77 148	99.04 203	99.41 251	97.58 272	99.67 311	99.35 225	94.66 306	99.96 121	99.36 319	99.28 71	99.74 211	99.41 185	97.81 231	99.81 210

Test_1112_low_res		98.83 157	98.60 166	99.51 151	99.69 157	98.75 197	99.99 212	99.14 318	96.81 215	98.84 253	99.06 332	97.45 174	99.89 174	98.66 226	97.75 236	99.89 165

BH-w/o		98.82 158	98.81 145	98.88 214	99.62 192	96.71 301	100.00 1	99.28 256	97.09 195	98.81 256	100.00 1	94.91 233	99.96 138	99.54 177	100.00 1	99.96 122

mvs_anonymous		98.80 159	98.60 166	99.38 175	99.57 209	99.24 161	100.00 1	99.21 295	95.87 270	98.92 244	99.82 253	96.39 210	99.03 280	99.13 204	98.50 183	99.88 179

fmvsm_s_conf0.1_n		98.77 160	98.42 179	99.82 93	99.47 241	99.52 125	100.00 1	99.27 265	97.53 160	100.00 1	100.00 1	89.73 303	99.96 138	99.84 112	99.93 126	99.97 116

bld_raw_dy_0_64		98.77 160	98.55 170	99.45 160	99.63 186	99.05 177	98.97 385	99.28 256	92.38 357	99.25 223	99.97 199	97.72 158	99.87 182	99.73 136	100.00 1	99.45 252

TAMVS		98.76 162	98.73 152	98.86 215	99.44 247	97.69 268	99.57 322	99.34 231	96.57 238	99.12 232	99.81 256	98.83 115	99.16 275	97.97 261	97.91 223	99.73 239

OpenMVS	95.20 17	98.76 162	98.41 180	99.78 111	98.89 304	99.81 87	99.99 212	99.76 49	98.02 108	98.02 303	100.00 1	91.44 277	100.00 1	99.63 164	99.97 115	99.55 248

dp		98.72 164	98.61 164	99.03 204	99.53 216	97.39 278	99.45 334	99.39 203	95.62 280	99.94 149	99.52 309	98.83 115	99.82 195	96.77 301	98.42 189	99.89 165

fmvsm_s_conf0.1_n_a		98.71 165	98.36 187	99.78 111	99.09 278	99.42 141	100.00 1	99.26 273	97.42 173	100.00 1	100.00 1	89.78 301	99.96 138	99.82 118	99.85 140	99.97 116

PVSNet_BlendedMVS		98.71 165	98.62 163	98.98 208	99.98 85	99.60 111	100.00 1	100.00 1	97.23 188	100.00 1	99.03 337	96.57 205	99.99 94	100.00 1	94.75 294	97.35 361

ADS-MVSNet		98.70 167	98.51 174	99.28 189	99.51 228	98.39 219	99.24 355	99.44 116	95.52 285	99.96 121	99.70 271	97.57 166	99.58 227	97.11 287	98.54 181	99.88 179

baseline		98.69 168	98.45 178	99.41 167	99.52 223	98.67 204	100.00 1	99.17 311	97.03 200	99.13 231	100.00 1	93.17 256	99.74 211	99.70 144	98.34 197	99.81 210

PCF-MVS	98.23 3	98.69 168	98.37 185	99.62 137	99.78 145	99.02 181	99.23 360	99.06 349	96.43 246	98.08 297	100.00 1	94.72 236	99.95 151	98.16 251	99.91 129	99.90 159
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
casdiffmvs		98.65 170	98.38 183	99.46 158	99.52 223	98.74 200	100.00 1	99.15 313	96.91 208	99.05 239	100.00 1	92.75 263	99.83 192	99.70 144	98.38 194	99.81 210
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
casdiffmvs_mvg		98.64 171	98.39 182	99.40 171	99.50 232	98.60 208	100.00 1	99.22 288	96.85 212	99.10 233	100.00 1	92.75 263	99.78 205	99.71 140	98.35 196	99.81 210
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
tpm2		98.64 171	98.58 168	98.81 218	99.42 249	97.12 291	99.69 308	99.37 208	93.63 334	99.94 149	99.67 279	98.96 101	99.47 254	98.62 232	97.95 221	99.83 196

BH-untuned		98.64 171	98.65 160	98.60 228	99.59 200	96.17 307	100.00 1	99.28 256	96.67 232	98.41 280	100.00 1	94.52 239	99.83 192	99.41 185	100.00 1	99.81 210

test_cas_vis1_n_1920		98.63 174	98.25 191	99.77 114	99.69 157	99.32 150	100.00 1	99.31 240	98.84 51	99.96 121	100.00 1	87.42 331	99.99 94	99.14 202	99.86 137	100.00 1

test_fmvsmconf0.01_n		98.60 175	98.24 194	99.67 130	96.90 374	99.21 164	99.99 212	99.04 354	98.80 57	99.57 200	99.96 214	90.12 295	99.91 171	99.89 101	99.89 131	99.90 159

tpmvs		98.59 176	98.38 183	99.23 193	99.69 157	97.90 258	99.31 350	99.47 79	94.52 311	99.68 196	99.28 323	97.64 163	99.89 174	97.71 268	98.17 212	99.89 165

Effi-MVS+		98.58 177	98.24 194	99.61 138	99.60 196	99.26 157	97.85 398	99.10 331	96.22 262	99.97 116	99.89 237	93.75 246	99.77 206	99.43 183	98.34 197	99.81 210

MVSTER		98.58 177	98.52 173	98.77 220	99.65 178	99.68 104	100.00 1	99.29 250	95.63 279	98.65 263	99.80 259	99.78 7	98.88 297	98.59 234	95.31 273	97.73 308

CVMVSNet		98.56 179	98.47 177	98.82 216	99.11 275	97.67 269	99.74 296	99.47 79	97.57 156	99.06 238	100.00 1	95.72 217	98.97 287	98.21 250	97.33 246	99.83 196

kuosan		98.55 180	98.53 172	98.62 226	99.66 175	96.16 308	100.00 1	99.44 116	93.93 327	99.81 183	99.98 189	97.58 164	99.81 198	98.08 253	98.28 203	99.89 165

AllTest		98.55 180	98.40 181	98.99 206	99.93 101	97.35 281	100.00 1	99.40 190	97.08 197	99.09 234	99.98 189	93.37 252	99.95 151	96.94 291	99.84 142	99.68 242

DeepPCF-MVS	98.03 4	98.54 182	99.72 19	94.98 350	99.99 49	84.94 389	100.00 1	99.42 140	99.98 1	100.00 1	100.00 1	98.11 141	100.00 1	100.00 1	100.00 1	100.00 1

EPNet_dtu		98.53 183	98.23 197	99.43 164	99.92 104	99.01 183	99.96 248	99.47 79	98.80 57	99.96 121	99.96 214	98.56 129	99.30 270	87.78 381	99.68 152	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
myMVS_eth3d		98.52 184	98.51 174	98.53 231	99.50 232	97.98 251	100.00 1	99.57 68	96.23 260	98.07 298	100.00 1	99.09 86	97.81 366	96.17 309	97.96 219	99.82 201

Vis-MVSNet		98.52 184	98.25 191	99.34 178	99.68 161	98.55 210	99.68 310	99.41 186	97.34 179	99.94 149	100.00 1	90.38 294	99.70 216	99.03 209	98.84 173	99.76 233
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Effi-MVS+-dtu		98.51 186	98.86 141	97.47 297	99.77 147	94.21 347	100.00 1	98.94 365	97.61 150	99.91 158	98.75 355	95.89 213	99.51 248	99.36 187	99.48 162	98.68 263

SDMVSNet		98.49 187	98.08 204	99.73 120	99.82 121	99.53 122	99.99 212	99.45 102	97.62 146	99.38 216	99.86 242	90.06 298	99.88 180	99.92 96	96.61 259	99.79 227

BH-RMVSNet		98.46 188	98.08 204	99.59 142	99.61 194	99.19 166	100.00 1	99.28 256	97.06 199	98.95 243	100.00 1	88.99 313	99.82 195	98.83 219	100.00 1	99.77 231

testing3		98.44 189	98.37 185	98.65 224	99.51 228	98.32 228	100.00 1	99.62 66	96.43 246	97.93 307	99.99 184	99.11 84	97.81 366	94.88 329	97.80 232	99.82 201

ECVR-MVS		98.43 190	98.14 200	99.32 183	99.89 110	98.21 236	99.46 332	100.00 1	98.38 80	99.47 208	100.00 1	87.91 324	99.80 200	99.35 188	98.78 175	99.94 133

cascas		98.43 190	98.07 206	99.50 154	99.65 178	99.02 181	100.00 1	99.22 288	94.21 320	99.72 193	99.98 189	92.03 274	99.93 167	99.68 152	98.12 213	99.54 249

test1111		98.42 192	98.12 201	99.29 186	99.88 112	98.15 238	99.46 332	100.00 1	98.36 84	99.42 209	100.00 1	87.91 324	99.79 201	99.31 192	98.78 175	99.94 133

ab-mvs		98.42 192	98.02 211	99.61 138	99.71 154	99.00 185	99.10 378	99.64 64	96.70 228	99.04 240	99.81 256	90.64 288	99.98 118	99.64 161	97.93 222	99.84 192

UGNet		98.41 194	98.11 202	99.31 185	99.54 213	98.55 210	99.18 363	100.00 1	98.64 70	99.79 184	99.04 335	87.61 329	100.00 1	99.30 193	99.89 131	99.40 254
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
Fast-Effi-MVS+		98.40 195	98.02 211	99.55 150	99.63 186	99.06 176	100.00 1	99.15 313	95.07 295	99.42 209	99.95 222	93.26 255	99.73 213	97.44 277	98.24 206	99.87 188

Fast-Effi-MVS+-dtu		98.38 196	98.56 169	97.82 288	99.58 205	94.44 344	100.00 1	99.16 312	96.75 221	99.51 203	99.63 291	95.03 231	99.60 221	97.71 268	99.67 154	99.42 253

test_fmvs1		98.37 197	98.04 209	99.34 178	99.84 117	98.07 244	100.00 1	99.00 360	98.85 49	100.00 1	100.00 1	85.11 351	99.96 138	99.69 151	99.88 133	100.00 1

miper_enhance_ethall		98.33 198	98.27 190	98.51 232	99.66 175	99.04 179	100.00 1	99.22 288	97.53 160	98.51 275	99.38 317	99.49 38	98.75 307	98.02 257	92.61 313	97.76 270

SCA		98.30 199	97.98 213	99.23 193	99.41 251	98.25 233	99.99 212	99.45 102	96.91 208	99.76 189	99.58 301	89.65 305	99.54 240	98.31 244	98.79 174	99.91 148

XVG-OURS		98.30 199	98.36 187	98.13 263	99.58 205	95.91 311	100.00 1	99.36 214	98.69 65	99.23 224	100.00 1	91.20 280	99.92 169	99.34 189	97.82 230	98.56 266

dongtai		98.29 201	98.25 191	98.42 238	99.58 205	95.86 313	100.00 1	99.44 116	93.46 339	99.69 195	99.97 199	97.53 169	99.51 248	96.28 308	98.27 205	99.89 165

COLMAP_ROB	97.10 7	98.29 201	98.17 199	98.65 224	99.94 99	97.39 278	99.30 351	99.40 190	95.64 278	97.75 316	100.00 1	92.69 267	99.95 151	98.89 214	99.92 128	98.62 265
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ADS-MVSNet2		98.28 203	98.51 174	97.62 293	99.51 228	95.03 324	99.24 355	99.41 186	95.52 285	99.96 121	99.70 271	97.57 166	97.94 363	97.11 287	98.54 181	99.88 179

XVG-OURS-SEG-HR		98.27 204	98.31 189	98.14 260	99.59 200	95.92 310	100.00 1	99.36 214	98.48 75	99.21 225	100.00 1	89.27 310	99.94 163	99.76 127	99.17 165	98.56 266

tpm		98.24 205	98.22 198	98.32 246	99.13 274	95.79 314	99.53 327	99.12 328	95.20 294	99.96 121	99.36 319	97.58 164	99.28 272	97.41 279	96.67 257	99.88 179

cl22		98.23 206	98.11 202	98.58 230	99.82 121	99.01 183	100.00 1	99.28 256	96.92 207	98.33 284	99.21 325	98.09 143	98.97 287	98.72 224	92.61 313	97.76 270

TR-MVS		98.14 207	97.74 220	99.33 181	99.59 200	98.28 231	99.27 352	99.21 295	96.42 249	99.15 230	99.94 227	88.87 316	99.79 201	98.88 215	98.29 202	99.93 144

mvsmamba		98.13 208	98.06 207	98.32 246	98.22 336	98.50 213	100.00 1	99.22 288	96.41 250	98.91 246	99.96 214	95.69 218	98.73 309	99.19 201	94.95 293	97.73 308

test0.0.03 1		98.12 209	98.03 210	98.39 240	99.11 275	98.07 244	100.00 1	99.93 30	96.70 228	96.91 339	99.95 222	99.31 63	98.19 343	91.93 355	98.44 187	98.91 261

GeoE		98.06 210	97.65 225	99.29 186	99.47 241	98.41 216	100.00 1	99.19 299	94.85 300	98.88 248	100.00 1	91.21 279	99.59 223	97.02 289	98.19 210	99.88 179

tpm cat1		98.05 211	97.76 219	98.92 211	99.50 232	97.10 293	99.77 291	99.30 244	90.20 375	99.72 193	98.71 356	97.71 159	99.86 183	96.75 302	98.20 209	99.81 210

PS-MVSNAJss		98.03 212	98.06 207	97.94 282	97.63 355	97.33 284	99.89 268	99.23 285	96.27 259	98.03 301	99.59 299	98.75 120	98.78 302	98.52 236	94.61 297	97.70 323

CR-MVSNet		98.02 213	97.71 223	98.93 210	99.31 263	98.86 192	99.13 375	99.00 360	96.53 241	99.96 121	98.98 341	96.94 195	98.10 353	91.18 360	98.40 190	99.84 192

EI-MVSNet		97.98 214	97.93 214	98.16 259	99.11 275	97.84 263	99.74 296	99.29 250	94.39 316	98.65 263	100.00 1	97.21 182	98.88 297	97.62 273	95.31 273	97.75 280

FIs		97.95 215	97.73 222	98.62 226	98.53 321	99.24 161	100.00 1	99.43 124	96.74 223	97.87 311	99.82 253	95.27 224	98.89 294	98.78 220	93.07 308	97.74 302

Anonymous202405211		97.87 216	97.53 227	98.90 212	99.81 127	96.70 302	99.35 345	99.46 94	92.98 350	98.83 255	99.99 184	90.63 289	100.00 1	99.70 144	97.03 250	100.00 1

FC-MVSNet-test		97.84 217	97.63 226	98.45 236	98.30 331	99.05 177	100.00 1	99.43 124	96.63 237	97.61 322	99.82 253	95.19 228	98.57 323	98.64 229	93.05 309	97.73 308

Patchmatch-test		97.83 218	97.42 230	99.06 199	99.08 279	97.66 270	98.66 392	99.21 295	93.65 333	98.25 292	99.58 301	99.47 42	99.57 228	90.25 369	98.59 180	99.95 128

sd_testset		97.81 219	97.48 228	98.79 219	99.82 121	96.80 299	99.32 347	99.45 102	97.62 146	99.38 216	99.86 242	85.56 349	99.77 206	99.72 137	96.61 259	99.79 227

miper_ehance_all_eth		97.81 219	97.66 224	98.23 252	99.49 236	98.37 222	99.99 212	99.11 329	94.78 301	98.25 292	99.21 325	98.18 139	98.57 323	97.35 283	92.61 313	97.76 270

test_vis1_n_1920		97.77 221	97.24 242	99.34 178	99.79 142	98.04 248	100.00 1	99.25 276	98.88 44	100.00 1	100.00 1	77.52 382	100.00 1	99.88 103	99.85 140	100.00 1

HQP-MVS		97.73 222	97.85 216	97.39 299	99.07 280	94.82 328	100.00 1	99.40 190	99.04 15	99.17 226	99.97 199	88.61 319	99.57 228	99.79 119	95.58 263	97.77 268

GA-MVS		97.72 223	97.27 240	99.06 199	99.24 270	97.93 257	100.00 1	99.24 281	95.80 276	98.99 242	99.64 287	89.77 302	99.36 265	95.12 326	97.62 244	99.89 165

HQP_MVS		97.71 224	97.82 218	97.37 300	99.00 292	94.80 331	100.00 1	99.40 190	99.00 27	99.08 236	99.97 199	88.58 321	99.55 237	99.79 119	95.57 267	97.76 270

nrg030		97.64 225	97.27 240	98.75 221	98.34 326	99.53 122	100.00 1	99.22 288	96.21 263	98.27 290	99.95 222	94.40 240	98.98 285	99.23 198	89.78 349	97.75 280

TAPA-MVS	96.40 10	97.64 225	97.37 234	98.45 236	99.94 99	95.70 315	100.00 1	99.40 190	97.65 141	99.53 201	100.00 1	99.31 63	99.66 218	80.48 396	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CLD-MVS		97.64 225	97.74 220	97.36 301	99.01 288	94.76 336	100.00 1	99.34 231	99.30 4	99.00 241	99.97 199	87.49 330	99.57 228	99.96 85	95.58 263	97.75 280
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
D2MVS		97.63 228	97.83 217	97.05 312	98.83 312	94.60 340	100.00 1	99.82 40	96.89 211	98.28 288	99.03 337	94.05 242	99.47 254	98.58 235	94.97 291	97.09 367

c3_l		97.58 229	97.42 230	98.06 270	99.48 238	98.16 237	99.96 248	99.10 331	94.54 310	98.13 296	99.20 327	97.87 149	98.25 342	97.28 284	91.20 337	97.75 280

IterMVS-LS		97.56 230	97.44 229	97.92 285	99.38 260	97.90 258	99.89 268	99.10 331	94.41 315	98.32 285	99.54 308	97.21 182	98.11 350	97.50 275	91.62 329	97.75 280
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test_djsdf		97.55 231	97.38 233	98.07 266	97.50 363	97.99 250	100.00 1	99.13 322	95.46 290	98.47 278	99.85 247	92.01 275	98.59 320	98.63 230	95.36 271	97.62 344

dmvs_re		97.54 232	97.88 215	96.54 332	99.55 212	90.35 376	99.86 272	99.46 94	97.00 201	99.41 214	100.00 1	90.78 287	99.30 270	99.60 168	95.24 278	99.96 122

cl____		97.54 232	97.32 236	98.18 256	99.47 241	98.14 240	100.00 1	99.10 331	94.16 323	97.60 323	99.63 291	97.52 170	98.65 314	96.47 303	91.97 325	97.76 270

IB-MVS	96.24 12	97.54 232	96.95 247	99.33 181	99.67 168	98.10 243	100.00 1	99.47 79	97.42 173	99.26 222	99.69 274	98.83 115	99.89 174	99.43 183	78.77 393	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
DIV-MVS_self_test		97.52 235	97.35 235	98.05 274	99.46 244	98.11 241	100.00 1	99.10 331	94.21 320	97.62 321	99.63 291	97.65 162	98.29 339	96.47 303	91.98 324	97.76 270

eth_miper_zixun_eth		97.47 236	97.28 238	98.06 270	99.41 251	97.94 256	99.62 317	99.08 337	94.46 314	98.19 295	99.56 305	96.91 197	98.50 328	96.78 299	91.49 332	97.74 302

test_fmvs1_n		97.43 237	96.86 250	99.15 197	99.68 161	97.48 275	99.99 212	98.98 363	98.82 55	100.00 1	100.00 1	74.85 387	99.96 138	99.67 155	99.70 151	100.00 1

LFMVS		97.42 238	96.62 259	99.81 99	99.80 138	99.50 128	99.16 369	99.56 70	94.48 313	100.00 1	100.00 1	79.35 377	100.00 1	99.89 101	97.37 245	99.94 133

miper_lstm_enhance		97.40 239	97.28 238	97.75 290	99.48 238	97.52 273	100.00 1	99.07 341	94.08 324	98.01 304	99.61 297	97.38 178	97.98 361	96.44 306	91.47 334	97.76 270

RPSCF		97.37 240	98.24 194	94.76 353	99.80 138	84.57 390	99.99 212	99.05 351	94.95 298	99.82 180	100.00 1	94.03 243	100.00 1	98.15 252	98.38 194	99.70 240

ACMM	97.17 6	97.37 240	97.40 232	97.29 305	99.01 288	94.64 339	100.00 1	99.25 276	98.07 106	98.44 279	99.98 189	87.38 332	99.55 237	99.25 195	95.19 281	97.69 327
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LPG-MVS_test		97.31 242	97.32 236	97.28 306	98.85 310	94.60 340	100.00 1	99.37 208	97.35 177	98.85 251	99.98 189	86.66 338	99.56 232	99.55 174	95.26 275	97.70 323

FMVSNet3		97.30 243	96.95 247	98.37 242	99.65 178	99.25 159	99.71 304	99.28 256	94.23 318	98.53 272	98.91 348	93.30 254	98.11 350	95.31 322	93.60 302	97.73 308

UniMVSNet (Re)		97.29 244	96.85 251	98.59 229	98.49 322	99.13 172	100.00 1	99.42 140	96.52 242	98.24 294	98.90 349	94.93 232	98.89 294	97.54 274	87.61 367	97.75 280

OPM-MVS		97.21 245	97.18 245	97.32 304	98.08 342	94.66 337	100.00 1	99.28 256	98.65 69	98.92 244	99.98 189	86.03 345	99.56 232	98.28 248	95.41 269	97.72 315
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMP	97.00 8	97.19 246	97.16 246	97.27 308	98.97 297	94.58 343	100.00 1	99.32 235	97.97 114	97.45 327	99.98 189	85.79 347	99.56 232	99.70 144	95.24 278	97.67 333
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
pmmvs4		97.17 247	96.80 252	98.27 249	97.68 354	98.64 206	100.00 1	99.18 306	94.22 319	98.55 270	99.71 268	93.67 247	98.47 331	95.66 316	92.57 316	97.71 322

anonymousdsp		97.16 248	96.88 249	98.00 278	97.08 373	98.06 246	99.81 280	99.15 313	94.58 308	97.84 312	99.62 295	90.49 291	98.60 318	97.98 258	95.32 272	97.33 362

UniMVSNet_NR-MVSNet		97.16 248	96.80 252	98.22 253	98.38 325	98.41 216	100.00 1	99.45 102	96.14 265	97.76 313	99.64 287	95.05 230	98.50 328	97.98 258	86.84 371	97.75 280

XXY-MVS		97.14 250	96.63 258	98.67 223	98.65 315	98.92 190	99.54 326	99.29 250	95.57 282	97.63 319	99.83 250	87.79 328	99.35 267	98.39 240	92.95 310	97.75 280

WR-MVS		97.09 251	96.64 257	98.46 234	98.43 323	99.09 173	99.97 243	99.33 233	95.62 280	97.76 313	99.67 279	91.17 281	98.56 325	98.49 237	89.28 355	97.74 302

JIA-IIPM		97.09 251	96.34 273	99.36 176	98.88 305	98.59 209	99.81 280	99.43 124	84.81 391	99.96 121	90.34 401	98.55 130	99.52 246	97.00 290	98.28 203	99.98 109

jajsoiax		97.07 253	96.79 254	97.89 286	97.28 371	97.12 291	99.95 254	99.19 299	96.55 239	97.31 330	99.69 274	87.35 334	98.91 291	98.70 225	95.12 286	97.66 334

MIMVSNet		97.06 254	96.73 255	98.05 274	99.38 260	96.64 304	98.47 394	99.35 225	93.41 340	99.48 205	98.53 363	89.66 304	97.70 372	94.16 338	98.11 214	99.80 224

X-MVStestdata		97.04 255	96.06 284	99.98 23	100.00 1	99.94 41	100.00 1	99.75 52	98.67 67	100.00 1	66.97 412	99.16 80	100.00 1	100.00 1	100.00 1	100.00 1

h-mvs33		97.03 256	96.53 262	98.51 232	99.79 142	95.90 312	99.45 334	99.45 102	98.21 92	100.00 1	99.78 262	97.49 171	99.99 94	99.72 137	74.92 395	99.65 247

VPA-MVSNet		97.03 256	96.43 268	98.82 216	98.64 316	99.32 150	99.38 342	99.47 79	96.73 225	98.91 246	98.94 346	87.00 336	99.40 263	99.23 198	89.59 350	97.76 270

WB-MVSnew		97.02 258	97.24 242	96.37 336	99.44 247	97.36 280	100.00 1	99.43 124	96.12 266	99.35 218	99.89 237	93.60 250	98.42 334	88.91 380	98.39 192	93.33 395

mvs_tets		97.00 259	96.69 256	97.94 282	97.41 370	97.27 286	99.60 319	99.18 306	96.51 243	97.35 329	99.69 274	86.53 340	98.91 291	98.84 217	95.09 287	97.65 338

gg-mvs-nofinetune		96.95 260	96.10 282	99.50 154	99.41 251	99.36 148	99.07 383	99.52 72	83.69 393	99.96 121	83.60 409	100.00 1	99.20 274	99.68 152	99.99 102	99.96 122

Anonymous20240529		96.93 261	96.22 278	99.05 201	99.79 142	97.30 285	99.16 369	99.47 79	88.51 381	98.69 261	100.00 1	83.50 362	100.00 1	99.83 113	97.02 251	99.83 196

DU-MVS		96.93 261	96.49 265	98.22 253	98.31 329	98.41 216	100.00 1	99.37 208	96.41 250	97.76 313	99.65 283	92.14 272	98.50 328	97.98 258	86.84 371	97.75 280

Patchmtry		96.81 263	96.37 271	98.14 260	99.31 263	98.55 210	98.91 387	99.00 360	90.45 371	97.92 308	98.98 341	96.94 195	98.12 348	94.27 335	91.53 331	97.75 280

hse-mvs2		96.79 264	96.38 270	98.04 276	99.68 161	95.54 318	99.81 280	99.42 140	98.21 92	100.00 1	99.80 259	97.49 171	99.46 258	99.72 137	73.27 398	99.12 258

ACMH	96.25 11	96.77 265	96.62 259	97.21 309	98.96 298	94.43 345	99.64 313	99.33 233	97.43 172	96.55 348	99.97 199	83.52 361	99.54 240	99.07 208	95.13 285	97.66 334
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IterMVS		96.76 266	96.46 267	97.63 291	99.41 251	96.89 296	99.99 212	99.13 322	94.74 304	97.59 324	99.66 281	89.63 307	98.28 340	95.71 314	92.31 319	97.72 315
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CP-MVSNet		96.73 267	96.25 276	98.18 256	98.21 337	98.67 204	99.77 291	99.32 235	95.06 296	97.20 333	99.65 283	90.10 296	98.19 343	98.06 256	88.90 358	97.66 334

WR-MVS_H		96.73 267	96.32 275	97.95 281	98.26 333	97.88 260	99.72 303	99.43 124	95.06 296	96.99 336	98.68 358	93.02 259	98.53 326	97.43 278	88.33 363	97.43 357

IterMVS-SCA-FT		96.72 269	96.42 269	97.62 293	99.40 256	96.83 298	99.99 212	99.14 318	94.65 307	97.55 325	99.72 266	89.65 305	98.31 338	95.62 318	92.05 322	97.73 308

v2v482		96.70 270	96.18 279	98.27 249	98.04 343	98.39 219	100.00 1	99.13 322	94.19 322	98.58 268	99.08 331	90.48 292	98.67 312	95.69 315	90.44 345	97.75 280

test_vis1_n		96.69 271	95.81 294	99.32 183	99.14 273	97.98 251	99.97 243	98.98 363	98.45 77	100.00 1	100.00 1	66.44 398	99.99 94	99.78 125	99.57 161	100.00 1

V42		96.65 272	96.16 281	98.11 265	98.17 340	98.23 234	99.99 212	99.09 336	93.97 325	98.74 260	99.05 334	91.09 282	98.82 300	95.46 320	89.90 347	97.27 363

EU-MVSNet		96.63 273	96.53 262	96.94 319	97.59 359	96.87 297	99.76 293	99.47 79	96.35 255	96.85 341	99.78 262	92.57 268	96.27 386	95.33 321	91.08 338	97.68 329

NR-MVSNet		96.63 273	96.04 285	98.38 241	98.31 329	98.98 187	99.22 362	99.35 225	95.87 270	94.43 371	99.65 283	92.73 265	98.40 335	96.78 299	88.05 364	97.75 280

XVG-ACMP-BASELINE		96.60 275	96.52 264	96.84 325	98.41 324	93.29 356	99.99 212	99.32 235	97.76 132	98.51 275	99.29 322	81.95 368	99.54 240	98.40 239	95.03 288	97.68 329

VDD-MVS		96.58 276	95.99 287	98.34 244	99.52 223	95.33 319	99.18 363	99.38 205	96.64 235	99.77 187	100.00 1	72.51 392	100.00 1	100.00 1	96.94 253	99.70 240

tt0805		96.52 277	96.23 277	97.40 298	99.30 266	93.55 352	99.32 347	99.45 102	96.75 221	97.88 310	99.99 184	79.99 375	99.59 223	97.39 281	95.98 262	99.06 260

LCM-MVSNet-Re		96.52 277	97.21 244	94.44 354	99.27 267	85.80 387	99.85 274	96.61 404	95.98 268	92.75 378	98.48 365	93.97 245	97.55 373	99.58 172	98.43 188	99.98 109

our_test_3		96.51 279	96.35 272	96.98 317	97.61 357	95.05 323	99.98 237	99.01 359	94.68 305	96.77 345	99.06 332	95.87 214	98.14 346	91.81 356	92.37 318	97.75 280

MVP-Stereo		96.51 279	96.48 266	96.60 331	95.65 385	94.25 346	98.84 389	98.16 381	95.85 274	95.23 362	99.04 335	92.54 269	99.13 276	92.98 348	99.98 112	96.43 379
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
v1144		96.51 279	95.97 289	98.13 263	97.98 346	98.04 248	99.99 212	99.08 337	93.51 338	98.62 266	98.98 341	90.98 286	98.62 315	93.79 342	90.79 341	97.74 302

ACMH+	96.20 13	96.49 282	96.33 274	97.00 315	99.06 284	93.80 350	99.81 280	99.31 240	97.32 181	95.89 359	99.97 199	82.62 366	99.54 240	98.34 243	94.63 296	97.65 338

TranMVSNet+NR-MVSNet		96.45 283	96.01 286	97.79 289	98.00 345	97.62 271	100.00 1	99.35 225	95.98 268	97.31 330	99.64 287	90.09 297	98.00 360	96.89 294	86.80 374	97.75 280

ET-MVSNet_ETH3D		96.41 284	95.48 314	99.20 195	99.81 127	99.75 93	100.00 1	99.02 357	97.30 185	78.33 401	100.00 1	97.73 157	97.94 363	99.70 144	87.41 368	99.92 146

VPNet		96.41 284	95.76 299	98.33 245	98.61 317	98.30 230	99.48 331	99.45 102	96.98 202	98.87 250	99.88 239	81.57 369	98.93 289	99.22 200	87.82 366	97.76 270

PVSNet_0	93.57 19	96.41 284	95.74 300	98.41 239	99.84 117	95.22 321	100.00 1	100.00 1	98.08 105	97.55 325	99.78 262	84.40 354	100.00 1	100.00 1	81.99 386	100.00 1

v144192		96.40 287	95.81 294	98.17 258	97.89 349	98.11 241	99.99 212	99.06 349	93.39 341	98.75 259	99.09 330	90.43 293	98.66 313	93.10 347	90.55 344	97.75 280

VDDNet		96.39 288	95.55 309	98.90 212	99.27 267	97.45 276	99.15 372	99.92 34	91.28 364	99.98 111	100.00 1	73.55 388	100.00 1	99.85 109	96.98 252	99.24 255

tfpnnormal		96.36 289	95.69 305	98.37 242	98.55 319	98.71 201	99.69 308	99.45 102	93.16 348	96.69 347	99.71 268	88.44 323	98.99 284	94.17 336	91.38 335	97.41 358

v8		96.35 290	95.73 301	98.21 255	98.11 341	98.23 234	99.94 258	99.07 341	92.66 356	98.29 287	99.00 340	91.46 276	98.77 305	94.17 336	88.83 360	97.62 344

PS-CasMVS		96.34 291	95.78 298	98.03 277	98.18 339	98.27 232	99.71 304	99.32 235	94.75 302	96.82 342	99.65 283	86.98 337	98.15 345	97.74 267	88.85 359	97.66 334

LTVRE_ROB	95.29 16	96.32 292	96.10 282	96.99 316	98.55 319	93.88 349	99.45 334	99.28 256	94.50 312	96.46 349	99.52 309	84.86 352	99.48 252	97.26 285	95.03 288	97.59 348
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
Anonymous20231211		96.29 293	95.70 302	98.07 266	99.80 138	97.49 274	99.15 372	99.40 190	89.11 378	97.75 316	99.45 314	88.93 315	98.98 285	98.26 249	89.47 352	97.73 308

v148		96.29 293	95.84 293	97.63 291	97.74 352	96.53 305	100.00 1	99.07 341	93.52 337	98.01 304	99.42 316	91.22 278	98.60 318	96.37 307	87.22 370	97.75 280

AUN-MVS		96.26 295	95.67 306	98.06 270	99.68 161	95.60 317	99.82 279	99.42 140	96.78 218	99.88 165	99.80 259	94.84 234	99.47 254	97.48 276	73.29 397	99.12 258

FMVSNet2		96.22 296	95.60 308	98.06 270	99.53 216	98.33 226	99.45 334	99.27 265	93.71 329	98.03 301	98.84 351	84.23 356	98.10 353	93.97 340	93.40 305	97.73 308

LF4IMVS		96.19 297	96.18 279	96.23 339	98.26 333	92.09 366	100.00 1	97.89 391	97.82 126	97.94 306	99.87 240	82.71 365	99.38 264	97.41 279	93.71 301	97.20 364

v1192		96.18 298	95.49 312	98.26 251	98.01 344	98.15 238	99.99 212	99.08 337	93.36 342	98.54 271	98.97 344	89.47 308	98.89 294	91.15 361	90.82 340	97.75 280

testgi		96.18 298	95.93 290	96.93 320	98.98 296	94.20 348	100.00 1	99.07 341	97.16 191	96.06 356	99.86 242	84.08 359	97.79 369	90.38 368	97.80 232	98.81 262

Syy-MVS		96.17 300	96.57 261	95.00 348	99.50 232	87.37 385	100.00 1	99.57 68	96.23 260	98.07 298	100.00 1	92.41 270	97.81 366	85.34 386	97.96 219	99.82 201

ppachtmachnet_test		96.17 300	95.89 291	97.02 314	97.61 357	95.24 320	99.99 212	99.24 281	93.31 344	96.71 346	99.62 295	94.34 241	98.07 355	89.87 370	92.30 320	97.75 280

v1921920		96.16 302	95.50 310	98.14 260	97.88 350	97.96 254	99.99 212	99.07 341	93.33 343	98.60 267	99.24 324	89.37 309	98.71 310	91.28 359	90.74 342	97.75 280

Baseline_NR-MVSNet		96.16 302	95.70 302	97.56 296	98.28 332	96.79 300	100.00 1	97.86 392	91.93 361	97.63 319	99.47 313	92.14 272	98.35 337	97.13 286	86.83 373	97.54 351

v10		96.14 304	95.50 310	98.07 266	98.19 338	97.96 254	99.83 276	99.07 341	92.10 360	98.07 298	98.94 346	91.07 283	98.61 316	92.41 354	89.82 348	97.63 342

OurMVSNet-221017-0		96.14 304	95.98 288	96.62 330	97.49 365	93.44 354	99.92 261	98.16 381	95.86 272	97.65 318	99.95 222	85.71 348	98.78 302	94.93 328	94.18 300	97.64 341

GBi-Net		96.07 306	95.80 296	96.89 322	99.53 216	94.87 325	99.18 363	99.27 265	93.71 329	98.53 272	98.81 352	84.23 356	98.07 355	95.31 322	93.60 302	97.72 315

test1		96.07 306	95.80 296	96.89 322	99.53 216	94.87 325	99.18 363	99.27 265	93.71 329	98.53 272	98.81 352	84.23 356	98.07 355	95.31 322	93.60 302	97.72 315

v7n		96.06 308	95.42 318	97.99 280	97.58 360	97.35 281	99.86 272	99.11 329	92.81 355	97.91 309	99.49 311	90.99 285	98.92 290	92.51 351	88.49 362	97.70 323

PEN-MVS		96.01 309	95.48 314	97.58 295	97.74 352	97.26 287	99.90 265	99.29 250	94.55 309	96.79 343	99.55 306	87.38 332	97.84 365	96.92 293	87.24 369	97.65 338

v1240		95.96 310	95.25 319	98.07 266	97.91 348	97.87 262	99.96 248	99.07 341	93.24 346	98.64 265	98.96 345	88.98 314	98.61 316	89.58 374	90.92 339	97.75 280

pmmvs5		95.94 311	95.61 307	96.95 318	97.42 368	94.66 337	100.00 1	98.08 385	93.60 335	97.05 335	99.43 315	87.02 335	98.46 332	95.76 312	92.12 321	97.72 315

PatchT		95.90 312	94.95 326	98.75 221	99.03 286	98.39 219	99.08 381	99.32 235	85.52 389	99.96 121	94.99 393	97.94 145	98.05 359	80.20 397	98.47 186	99.81 210

USDC		95.90 312	95.70 302	96.50 333	98.60 318	92.56 364	100.00 1	98.30 379	97.77 130	96.92 337	99.94 227	81.25 372	99.45 259	93.54 344	94.96 292	97.49 354

pm-mvs1		95.76 314	95.01 324	98.00 278	98.23 335	97.45 276	99.24 355	99.04 354	93.13 349	95.93 358	99.72 266	86.28 341	98.84 299	95.62 318	87.92 365	97.72 315

SixPastTwentyTwo		95.71 315	95.49 312	96.38 335	97.42 368	93.01 357	99.84 275	98.23 380	94.75 302	95.98 357	99.97 199	85.35 350	98.43 333	94.71 330	93.17 307	97.69 327

MS-PatchMatch		95.66 316	95.87 292	95.05 346	97.80 351	89.25 379	98.88 388	99.30 244	96.35 255	96.86 340	99.01 339	81.35 371	99.43 260	93.30 346	99.98 112	96.46 378

DTE-MVSNet		95.52 317	94.99 325	97.08 311	97.49 365	96.45 306	100.00 1	99.25 276	93.82 328	96.17 354	99.57 304	87.81 327	97.18 374	94.57 331	86.26 376	97.62 344

TinyColmap		95.50 318	95.12 323	96.64 329	98.69 314	93.00 358	99.40 340	97.75 394	96.40 252	96.14 355	99.87 240	79.47 376	99.50 250	93.62 343	94.72 295	97.40 359

K. test v3		95.46 319	95.14 322	96.40 334	97.53 362	93.40 355	99.99 212	99.23 285	95.49 288	92.70 379	99.73 265	84.26 355	98.12 348	93.94 341	93.38 306	97.68 329

FMVSNet5		95.32 320	95.43 317	94.99 349	99.39 259	92.99 359	99.25 354	99.24 281	90.45 371	97.44 328	98.45 366	95.78 216	94.39 395	87.02 382	91.88 326	97.59 348

UniMVSNet_ETH3D		95.28 321	94.41 327	97.89 286	98.91 302	95.14 322	99.13 375	99.35 225	92.11 359	97.17 334	99.66 281	70.28 395	99.36 265	97.88 263	95.18 282	99.16 256

RPMNet		95.26 322	93.82 330	99.56 149	99.31 263	98.86 192	99.13 375	99.42 140	79.82 398	99.96 121	95.13 391	95.69 218	99.98 118	77.54 401	98.40 190	99.84 192

DSMNet-mixed		95.18 323	95.21 321	95.08 345	96.03 380	90.21 377	99.65 312	93.64 410	92.91 351	98.34 283	97.40 382	90.05 299	95.51 392	91.02 362	97.86 226	99.51 251

test_fmvs2		95.17 324	95.23 320	95.01 347	98.95 300	88.99 381	99.99 212	97.77 393	97.79 128	98.58 268	99.70 271	73.36 389	99.34 268	95.88 311	95.03 288	96.70 375

TransMVSNet (Re)		94.78 325	93.72 331	97.93 284	98.34 326	97.88 260	99.23 360	97.98 389	91.60 362	94.55 368	99.71 268	87.89 326	98.36 336	89.30 376	84.92 377	97.56 350

FMVSNet1		94.45 326	93.63 333	96.89 322	98.87 308	94.87 325	99.18 363	99.27 265	90.95 368	97.31 330	98.81 352	72.89 391	98.07 355	92.61 349	92.81 311	97.72 315

test_0402		94.35 327	93.70 332	96.32 337	97.92 347	93.60 351	99.61 318	98.85 372	88.19 384	94.68 367	99.48 312	80.01 374	98.58 322	89.39 375	95.15 284	96.77 373

UnsupCasMVSNet_eth		94.25 328	93.89 329	95.34 344	97.63 355	92.13 365	99.73 301	99.36 214	94.88 299	92.78 376	98.63 360	82.72 364	96.53 382	94.57 331	84.73 378	97.36 360

KD-MVS_2432*1600		94.15 329	93.08 338	97.35 302	99.53 216	97.83 264	99.63 315	99.19 299	92.88 352	96.29 351	97.68 379	98.84 113	96.70 378	89.73 371	63.92 402	97.53 352

miper_refine_blended		94.15 329	93.08 338	97.35 302	99.53 216	97.83 264	99.63 315	99.19 299	92.88 352	96.29 351	97.68 379	98.84 113	96.70 378	89.73 371	63.92 402	97.53 352

MVS-HIRNet		94.12 331	92.73 344	98.29 248	99.33 262	95.95 309	99.38 342	99.19 299	74.54 401	98.26 291	86.34 405	86.07 343	99.06 279	91.60 358	99.87 136	99.85 191

new_pmnet		94.11 332	93.47 335	96.04 341	96.60 377	92.82 360	99.97 243	98.91 368	90.21 374	95.26 361	98.05 377	85.89 346	98.14 346	84.28 388	92.01 323	97.16 365

pmmvs6		93.64 333	92.87 341	95.94 342	97.47 367	91.41 371	98.92 386	99.02 357	87.84 385	95.01 364	99.61 297	77.24 383	98.77 305	94.33 334	86.41 375	97.63 342

Patchmatch-RL test		93.49 334	93.63 333	93.05 365	91.78 396	83.41 391	98.21 396	96.95 401	91.58 363	91.05 381	97.64 381	99.40 55	95.83 390	94.11 339	81.95 387	99.91 148

Anonymous20231206		93.45 335	93.17 337	94.30 357	95.00 390	89.69 378	99.98 237	98.43 378	93.30 345	94.50 370	98.59 361	90.52 290	95.73 391	77.46 402	90.73 343	97.48 356

Anonymous20240521		93.29 336	92.76 343	94.90 352	95.64 386	91.27 372	99.97 243	98.82 373	87.04 386	94.71 366	98.19 372	83.86 360	96.80 377	84.04 389	92.56 317	96.64 376

dmvs_testset		93.27 337	95.48 314	86.65 377	98.74 313	68.42 406	99.92 261	98.91 368	96.19 264	93.28 375	100.00 1	91.06 284	91.67 402	89.64 373	91.54 330	99.86 190

test20.03		93.11 338	92.85 342	93.88 362	95.19 389	91.83 367	100.00 1	98.87 371	93.68 332	92.76 377	98.88 350	89.20 311	92.71 400	77.88 400	89.19 356	97.09 367

test_vis1_rt		93.10 339	92.93 340	93.58 363	99.63 186	85.07 388	99.99 212	93.71 409	97.49 166	90.96 382	97.10 383	60.40 400	99.95 151	99.24 197	97.90 224	95.72 385

APD_test1		93.07 340	94.14 328	89.85 371	99.18 271	72.49 399	99.76 293	98.90 370	92.86 354	96.35 350	99.94 227	75.56 385	99.91 171	86.73 383	97.98 217	97.15 366

EG-PatchMatch MVS		92.94 341	92.49 345	94.29 358	95.87 382	87.07 386	99.07 383	98.11 384	93.19 347	88.98 388	98.66 359	70.89 393	99.08 278	92.43 353	95.21 280	96.72 374

MDA-MVSNet_test_wron		92.61 342	91.09 350	97.19 310	96.71 376	97.26 287	100.00 1	99.14 318	88.61 380	67.90 407	98.32 371	89.03 312	96.57 381	90.47 367	89.59 350	97.74 302

YYNet1		92.44 343	90.92 351	97.03 313	96.20 378	97.06 294	99.99 212	99.14 318	88.21 383	67.93 406	98.43 368	88.63 318	96.28 385	90.64 363	89.08 357	97.74 302

MIMVSNet1		91.96 344	91.20 347	94.23 359	94.94 391	91.69 369	99.34 346	99.22 288	88.23 382	94.18 372	98.45 366	75.52 386	93.41 399	79.37 398	91.49 332	97.60 347

TDRefinement		91.93 345	90.48 353	96.27 338	81.60 409	92.65 363	99.10 378	97.61 397	93.96 326	93.77 373	99.85 247	80.03 373	99.53 245	97.82 265	70.59 399	96.63 377

OpenMVS_ROB	88.34 20	91.89 346	91.12 348	94.19 360	95.55 387	87.63 384	99.26 353	98.03 386	86.61 388	90.65 386	96.82 385	70.14 396	98.78 302	86.54 384	96.50 261	96.15 380

N_pmnet		91.88 347	93.37 336	87.40 376	97.24 372	66.33 409	99.90 265	91.05 412	89.77 377	95.65 360	98.58 362	90.05 299	98.11 350	85.39 385	92.72 312	97.75 280

pmmvs-eth3d		91.73 348	90.67 352	94.92 351	91.63 398	92.71 362	99.90 265	98.54 377	91.19 365	88.08 390	95.50 389	79.31 378	96.13 387	90.55 366	81.32 389	95.91 384

MDA-MVSNet-bldmvs		91.65 349	89.94 357	96.79 328	96.72 375	96.70 302	99.42 339	98.94 365	88.89 379	66.97 409	98.37 369	81.43 370	95.91 389	89.24 377	89.46 353	97.75 280

KD-MVS_self_test		91.16 350	90.09 355	94.35 356	94.44 392	91.27 372	99.74 296	99.08 337	90.82 369	94.53 369	94.91 394	86.11 342	94.78 394	82.67 391	68.52 400	96.99 369

CL-MVSNet_self_test		91.07 351	90.35 354	93.24 364	93.27 393	89.16 380	99.55 324	99.25 276	92.34 358	95.23 362	97.05 384	88.86 317	93.59 398	80.67 395	66.95 401	96.96 370

test_method		91.04 352	91.10 349	90.85 368	98.34 326	77.63 395	100.00 1	98.93 367	76.69 399	96.25 353	98.52 364	70.44 394	97.98 361	89.02 379	91.74 327	96.92 371

CMPMVS	66.12 22	90.65 353	92.04 346	86.46 378	96.18 379	66.87 408	98.03 397	99.38 205	83.38 394	85.49 396	99.55 306	77.59 381	98.80 301	94.44 333	94.31 299	93.72 393
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs3		90.62 354	89.36 360	94.40 355	90.53 403	91.49 370	100.00 1	96.73 402	84.21 392	93.65 374	96.65 386	82.56 367	94.83 393	82.28 392	77.62 394	96.89 372

new-patchmatchnet		90.30 355	89.46 359	92.84 366	90.77 401	88.55 383	99.83 276	98.80 374	90.07 376	87.86 391	95.00 392	78.77 379	94.30 396	84.86 387	79.15 391	95.68 387

UnsupCasMVSNet_bld		89.50 356	88.00 362	93.99 361	95.30 388	88.86 382	98.52 393	99.28 256	85.50 390	87.80 392	94.11 395	61.63 399	96.96 376	90.63 364	79.26 390	96.15 380

mvsany_test3		89.36 357	88.96 361	90.56 369	91.95 395	78.97 394	99.74 296	96.59 405	96.84 213	89.25 387	96.07 387	52.59 402	97.11 375	95.17 325	82.44 385	95.58 388

PM-MVS		88.39 358	87.41 363	91.31 367	91.73 397	82.02 393	99.79 285	96.62 403	91.06 367	90.71 385	95.73 388	48.60 404	95.96 388	90.56 365	81.91 388	95.97 383

WB-MVS		88.24 359	90.09 355	82.68 384	91.56 399	69.51 404	100.00 1	98.73 375	90.72 370	87.29 393	98.12 373	92.87 261	85.01 406	62.19 407	89.34 354	93.54 394

SSC-MVS		87.61 360	89.47 358	82.04 385	90.63 402	68.77 405	99.99 212	98.66 376	90.34 373	86.70 394	98.08 374	92.72 266	84.12 407	59.41 410	88.71 361	93.22 398

test_fmvs3		87.19 361	87.02 364	87.71 375	92.69 394	76.64 396	99.96 248	97.27 398	93.55 336	90.82 384	94.03 396	38.00 410	92.19 401	93.49 345	83.35 384	94.32 390

test_f		86.87 362	86.06 365	89.28 372	91.45 400	76.37 397	99.87 271	97.11 399	91.10 366	88.46 389	93.05 398	38.31 409	96.66 380	91.77 357	83.46 383	94.82 389

Gipuma		84.73 363	83.50 368	88.40 374	97.50 363	82.21 392	88.87 403	99.05 351	65.81 403	85.71 395	90.49 400	53.70 401	96.31 384	78.64 399	91.74 327	86.67 402
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
testf1		84.40 364	84.79 366	83.23 382	95.71 383	58.71 415	98.79 390	97.75 394	81.58 395	84.94 397	98.07 375	45.33 406	97.73 370	77.09 403	83.85 380	93.24 396

APD_test2		84.40 364	84.79 366	83.23 382	95.71 383	58.71 415	98.79 390	97.75 394	81.58 395	84.94 397	98.07 375	45.33 406	97.73 370	77.09 403	83.85 380	93.24 396

testmvs		80.17 366	81.95 369	74.80 389	58.54 416	59.58 414	100.00 1	87.14 415	76.09 400	99.61 199	100.00 1	67.06 397	74.19 412	98.84 217	50.30 406	90.64 401

test_vis3_rt		79.61 367	78.19 372	83.86 381	88.68 404	69.56 403	99.81 280	82.19 417	86.78 387	68.57 405	84.51 408	25.06 414	98.26 341	89.18 378	78.94 392	83.75 405

EGC-MVSNET		79.46 368	74.04 376	95.72 343	96.00 381	92.73 361	99.09 380	99.04 354	5.08 413	16.72 413	98.71 356	73.03 390	98.74 308	82.05 393	96.64 258	95.69 386

test123		79.44 369	79.23 371	80.05 387	80.03 410	71.72 400	100.00 1	77.93 418	62.52 404	94.81 365	99.69 274	78.21 380	74.53 411	92.57 350	27.33 411	93.90 391

PMMVS2		79.15 370	77.28 373	84.76 380	82.34 408	72.66 398	99.70 306	95.11 408	71.68 402	84.78 399	90.87 399	32.05 412	89.99 403	75.53 405	63.45 404	91.64 399

LCM-MVSNet		79.01 371	76.93 374	85.27 379	78.28 411	68.01 407	96.57 400	98.03 386	55.10 407	82.03 400	93.27 397	31.99 413	93.95 397	82.72 390	74.37 396	93.84 392

FPMVS		77.92 372	79.45 370	73.34 391	76.87 412	46.81 418	98.24 395	99.05 351	59.89 406	73.55 402	98.34 370	36.81 411	86.55 404	80.96 394	91.35 336	86.65 403

tmp_tt		75.80 373	74.26 375	80.43 386	52.91 418	53.67 417	87.42 405	97.98 389	61.80 405	67.04 408	100.00 1	76.43 384	96.40 383	96.47 303	28.26 410	91.23 400

E-PMN		70.72 374	70.06 377	72.69 392	83.92 407	65.48 411	99.95 254	92.72 411	49.88 409	72.30 403	86.26 406	47.17 405	77.43 409	53.83 411	44.49 407	75.17 409

EMVS		69.88 375	69.09 378	72.24 393	84.70 406	65.82 410	99.96 248	87.08 416	49.82 410	71.51 404	84.74 407	49.30 403	75.32 410	50.97 412	43.71 408	75.59 408

MVE	68.59 21	67.22 376	64.68 380	74.84 388	74.67 414	62.32 413	95.84 401	90.87 413	50.98 408	58.72 410	81.05 410	12.20 418	78.95 408	61.06 409	56.75 405	83.24 406
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ANet_high		66.05 377	63.44 381	73.88 390	61.14 415	63.45 412	95.68 402	87.18 414	79.93 397	47.35 411	80.68 411	22.35 415	72.33 413	61.24 408	35.42 409	85.88 404

PMVS	60.66 23	65.98 378	65.05 379	68.75 394	55.06 417	38.40 419	88.19 404	96.98 400	48.30 411	44.82 412	88.52 403	12.22 417	86.49 405	67.58 406	83.79 382	81.35 407
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
wuyk23d		28.28 379	29.73 383	23.92 395	75.89 413	32.61 420	66.50 406	12.88 419	16.09 412	14.59 414	16.59 413	12.35 416	32.36 414	39.36 413	13.36 412	6.79 410

cdsmvs_eth3d_5k		24.41 380	32.55 382	0.00 396	0.00 419	0.00 421	0.00 407	99.39 203	0.00 414	0.00 415	100.00 1	93.55 251	0.00 415	0.00 414	0.00 413	0.00 411

ab-mvs-re		8.33 381	11.11 384	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	100.00 1	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

pcd_1.5k_mvsjas		8.24 382	10.99 385	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.14 415	98.75 120	0.00 415	0.00 414	0.00 413	0.00 411

test_blank		0.07 383	0.09 386	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.79 414	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

uanet_test		0.01 384	0.02 387	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.14 415	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

DCPMVS		0.01 384	0.02 387	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.14 415	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

sosnet-low-res		0.01 384	0.02 387	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.14 415	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

sosnet		0.01 384	0.02 387	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.14 415	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

uncertanet		0.01 384	0.02 387	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.14 415	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

Regformer		0.01 384	0.02 387	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.14 415	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

uanet		0.01 384	0.02 387	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.14 415	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

WAC-MVS						97.98 251								95.74 313

FOURS1					100.00 1	99.97 21	100.00 1	99.42 140	98.52 74	100.00 1

MSC_two_6792asdad				100.00 1	100.00 1	100.00 1		99.42 140					100.00 1	100.00 1	100.00 1	100.00 1

PC_three_1452									98.80 57	100.00 1	100.00 1	99.54 25	100.00 1	100.00 1	100.00 1	100.00 1

No_MVS				100.00 1	100.00 1	100.00 1		99.42 140					100.00 1	100.00 1	100.00 1	100.00 1

test_one_0601					100.00 1	99.99 5		99.42 140	98.72 64	100.00 1	100.00 1	99.60 16

eth-test2					0.00 419

eth-test					0.00 419

ZD-MVS					100.00 1	99.98 17		99.80 43	97.31 183	100.00 1	100.00 1	99.32 61	99.99 94	100.00 1	100.00 1

RE-MVS-def			99.55 56		99.99 49	99.91 53	100.00 1	99.42 140	97.62 146	100.00 1	100.00 1	98.94 104		99.99 61	100.00 1	100.00 1

IU-MVS					100.00 1	99.99 5		99.42 140	99.12 6	100.00 1				100.00 1	100.00 1	100.00 1

OPU-MVS				100.00 1	100.00 1	100.00 1	100.00 1				100.00 1	99.54 25	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_TWO								99.42 140	99.03 20	100.00 1	100.00 1	99.56 22	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_ONE					100.00 1	99.99 5		99.42 140	99.03 20	100.00 1	100.00 1	99.50 36	100.00 1

9.14			99.57 49		99.99 49		100.00 1	99.42 140	97.54 158	100.00 1	100.00 1	99.15 82	99.99 94	100.00 1	100.00 1

save fliter					99.99 49	99.93 45	100.00 1	99.42 140	98.93 38

test_0728_THIRD									98.79 60	100.00 1	100.00 1	99.61 15	100.00 1	100.00 1	100.00 1	100.00 1

test_0728_SECOND				100.00 1	99.99 49	99.99 5	100.00 1	99.42 140					100.00 1	100.00 1	100.00 1	100.00 1

test0726					100.00 1	99.99 5	100.00 1	99.42 140	99.04 15	100.00 1	100.00 1	99.53 28

GSMVS																99.91 148

test_part2					100.00 1	99.99 5				100.00 1

sam_mvs1												99.29 69				99.91 148

sam_mvs												99.33 58

ambc				88.45 373	86.84 405	70.76 402	97.79 399	98.02 388		90.91 383	95.14 390	38.69 408	98.51 327	94.97 327	84.23 379	96.09 382

MTGPA								99.42 140

test_post1							99.32 347				88.24 404	99.33 58	99.59 223	98.31 244

test_post											89.05 402	99.49 38	99.59 223

patchmatchnet-post											97.79 378	99.41 54	99.54 240

GG-mvs-BLEND				99.59 142	99.54 213	99.49 131	99.17 368	99.52 72		99.96 121	99.68 278	100.00 1	99.33 269	99.71 140	99.99 102	99.96 122

MTMP							100.00 1	99.18 306

gm-plane-assit					99.52 223	97.26 287			95.86 272		100.00 1		99.43 260	98.76 222

test9_res														100.00 1	100.00 1	100.00 1

TEST9					100.00 1	99.95 32	100.00 1	99.42 140	97.65 141	100.00 1	100.00 1	99.53 28	99.97 125

test_8					100.00 1	99.91 53	100.00 1	99.42 140	97.70 136	100.00 1	100.00 1	99.51 32	99.98 118

agg_prior2														100.00 1	100.00 1	100.00 1

agg_prior					100.00 1	99.88 74		99.42 140		100.00 1			99.97 125

TestCases				98.99 206	99.93 101	97.35 281		99.40 190	97.08 197	99.09 234	99.98 189	93.37 252	99.95 151	96.94 291	99.84 142	99.68 242

test_prior4						99.93 45	100.00 1

test_prior2							100.00 1		98.82 55	100.00 1	100.00 1	99.47 42		100.00 1	100.00 1

test_prior				99.90 73	100.00 1	99.75 93		99.73 56					99.97 125			100.00 1

旧先验2							100.00 1		98.11 104	100.00 1			100.00 1	99.67 155

新几何2							100.00 1

新几何1				99.99 12	100.00 1	99.96 24		99.81 42	97.89 121	100.00 1	100.00 1	99.20 77	100.00 1	97.91 262	100.00 1	100.00 1

旧先验1					99.99 49	99.88 74		99.82 40			100.00 1	99.27 72			100.00 1	100.00 1

无先验							100.00 1	99.80 43	97.98 112				100.00 1	99.33 190		100.00 1

原ACMM2							100.00 1

原ACMM1				99.93 67	100.00 1	99.80 89		99.66 63	98.18 95	100.00 1	100.00 1	99.43 49	100.00 1	99.50 181	100.00 1	100.00 1

test222					99.99 49	99.90 60	100.00 1	99.69 62	97.66 140	100.00 1	100.00 1	99.30 68			100.00 1	100.00 1

testdata2													100.00 1	97.36 282

segment_acmp												99.55 24

testdata				99.66 133	99.99 49	98.97 189		99.73 56	97.96 117	100.00 1	100.00 1	99.42 52	100.00 1	99.28 194	100.00 1	100.00 1

testdata1							100.00 1		98.77 63

test12				99.95 51	99.99 49	99.89 67		99.42 140		100.00 1		99.24 74	99.97 125		100.00 1	100.00 1

plane_prior7					99.00 292	94.78 335

plane_prior6					99.06 284	94.80 331						88.58 321

plane_prior5								99.40 190					99.55 237	99.79 119	95.57 267	97.76 270

plane_prior4											99.97 199

plane_prior3						94.79 334			99.03 20	99.08 236

plane_prior2							100.00 1		99.00 27

plane_prior1					99.02 287

plane_prior						94.80 331	100.00 1		99.03 20						95.58 263

n2								0.00 420

nn								0.00 420

door-mid								96.32 406

lessismore_v0				96.05 340	97.55 361	91.80 368		99.22 288		91.87 380	99.91 234	83.50 362	98.68 311	92.48 352	90.42 346	97.68 329

LGP-MVS_train				97.28 306	98.85 310	94.60 340		99.37 208	97.35 177	98.85 251	99.98 189	86.66 338	99.56 232	99.55 174	95.26 275	97.70 323

test11								99.42 140

door								96.13 407

HQP5-MVS						94.82 328

HQP-NCC					99.07 280		100.00 1		99.04 15	99.17 226

ACMP_Plane					99.07 280		100.00 1		99.04 15	99.17 226

BP-MVS														99.79 119

HQP4-MVS										99.17 226			99.57 228			97.77 268

HQP3-MVS								99.40 190							95.58 263

HQP2-MVS												88.61 319

NP-MVS					99.07 280	94.81 330					99.97 199

MDTV_nov1_ep13_2view						99.24 161	99.56 323		96.31 258	99.96 121		98.86 111		98.92 213		99.89 165

MDTV_nov1_ep13			98.94 132		99.53 216	98.36 224	99.39 341	99.46 94	96.54 240	99.99 105	99.63 291	98.92 107	99.86 183	98.30 247	98.71 179

ACMMP++_ref															94.58 298

ACMMP++															95.17 283

Test By Simon												99.10 85

ITE_SJBPF				96.84 325	98.96 298	93.49 353		98.12 383	98.12 103	98.35 282	99.97 199	84.45 353	99.56 232	95.63 317	95.25 277	97.49 354

DeepMVS_CX				89.98 370	98.90 303	71.46 401		99.18 306	97.61 150	96.92 337	99.83 250	86.07 343	99.83 192	96.02 310	97.65 242	98.65 264

High-resolution multi-view benchmark