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.

MED-MVS		99.89 1	99.86 2	99.99 13	100.00 1	99.98 18	100.00 1	99.95 19	99.18 6	99.99 129	100.00 1	99.58 27	100.00 1	100.00 1	100.00 1	100.00 1

MSLP-MVS++		99.89 1	99.85 3	99.99 13	100.00 1	99.96 30	100.00 1	99.95 19	99.11 10	100.00 1	100.00 1	99.60 21	100.00 1	100.00 1	100.00 1	100.00 1

aaEdge-Enhanced		99.87 3	99.83 4	99.99 13	99.99 53	99.98 18	100.00 1	99.95 19	99.05 18	100.00 1	100.00 1	99.50 43	100.00 1	100.00 1	100.00 1	100.00 1

NCCC		99.86 4	99.82 5	100.00 1	100.00 1	99.99 6	100.00 1	99.71 66	99.07 14	100.00 1	100.00 1	99.59 24	100.00 1	100.00 1	100.00 1	100.00 1

TestfortrainingZip a		99.85 5	99.81 6	99.99 13	100.00 1	99.98 18	100.00 1	99.95 19	99.18 6	100.00 1	100.00 1	99.45 53	99.99 107	99.68 183	99.99 107	100.00 1

CHOSEN 280x420		99.85 5	99.87 1	99.80 123	99.99 53	99.97 27	99.97 310	99.98 16	98.96 39	100.00 1	100.00 1	99.96 4	99.42 338	100.00 1	100.00 1	100.00 1

MCST-MVS		99.85 5	99.80 7	100.00 1	100.00 1	99.99 6	100.00 1	99.73 61	99.19 5	100.00 1	100.00 1	99.31 76	100.00 1	100.00 1	100.00 1	100.00 1

CNVR-MVS		99.85 5	99.80 7	100.00 1	100.00 1	99.99 6	100.00 1	99.77 53	99.07 14	100.00 1	100.00 1	99.39 69	100.00 1	100.00 1	100.00 1	100.00 1

APDe-MVS		99.84 9	99.78 10	99.99 13	100.00 1	99.98 18	100.00 1	99.44 125	99.06 16	100.00 1	100.00 1	99.56 29	99.99 107	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 10	99.77 12	100.00 1	100.00 1	99.99 6	100.00 1	99.42 153	99.03 25	100.00 1	100.00 1	99.50 43	100.00 1	100.00 1	100.00 1	100.00 1

DVP-MVS		99.83 10	99.78 10	100.00 1	100.00 1	99.99 6	100.00 1	99.42 153	99.04 20	100.00 1	100.00 1	99.53 35	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 12	99.77 12	99.99 13	100.00 1	99.96 30	100.00 1	99.43 134	99.05 18	100.00 1	100.00 1	99.45 53	99.99 107	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 12	99.76 15	99.99 13	99.99 53	99.98 18	100.00 1	99.83 44	98.88 61	99.96 152	100.00 1	99.21 89	100.00 1	100.00 1	100.00 1	99.99 124

DVP-MVS++		99.81 14	99.75 17	100.00 1	100.00 1	99.99 6	100.00 1	99.42 153	98.79 80	100.00 1	100.00 1	99.54 32	100.00 1	100.00 1	100.00 1	100.00 1

MSP-MVS		99.81 14	99.77 12	99.94 74	100.00 1	99.86 90	100.00 1	99.42 153	98.87 64	100.00 1	100.00 1	99.65 19	99.96 170	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 14	99.75 17	99.99 13	99.99 53	99.96 30	100.00 1	99.42 153	99.01 31	100.00 1	100.00 1	99.33 71	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 17	99.73 20	99.99 13	99.99 53	99.98 18	100.00 1	99.42 153	98.91 55	100.00 1	100.00 1	99.22 88	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 17	99.73 20	99.98 28	100.00 1	99.94 47	100.00 1	99.75 57	98.67 88	100.00 1	100.00 1	99.16 94	100.00 1	100.00 1	100.00 1	100.00 1

SteuartSystems-ACMMP		99.78 19	99.71 23	99.98 28	99.76 170	99.95 38	100.00 1	99.42 153	98.69 86	100.00 1	100.00 1	99.52 38	99.99 107	100.00 1	100.00 1	100.00 1
Skip Steuart: Steuart Systems R&D Blog.
PAPM		99.78 19	99.76 15	99.85 104	99.01 367	99.95 38	100.00 1	99.75 57	99.37 3	99.99 129	100.00 1	99.76 12	99.60 293	100.00 1	100.00 1	100.00 1

reproduce_model		99.76 21	99.69 25	99.98 28	99.96 104	99.93 53	100.00 1	99.42 153	98.81 76	100.00 1	100.00 1	98.98 116	100.00 1	100.00 1	100.00 1	100.00 1

reproduce-ours		99.76 21	99.69 25	99.98 28	99.96 104	99.94 47	100.00 1	99.42 153	98.82 72	100.00 1	100.00 1	98.99 113	100.00 1	100.00 1	100.00 1	100.00 1

our_new_method		99.76 21	99.69 25	99.98 28	99.96 104	99.94 47	100.00 1	99.42 153	98.82 72	100.00 1	100.00 1	98.99 113	100.00 1	100.00 1	100.00 1	100.00 1

DP-MVS Recon		99.76 21	99.69 25	99.98 28	100.00 1	99.95 38	100.00 1	99.52 78	97.99 135	99.99 129	100.00 1	99.72 14	100.00 1	99.96 106	100.00 1	100.00 1

PAPR		99.76 21	99.68 31	99.99 13	100.00 1	99.96 30	100.00 1	99.47 85	98.16 121	100.00 1	100.00 1	99.51 39	100.00 1	100.00 1	100.00 1	100.00 1

DeepC-MVS_fast	98.92 1	99.75 26	99.67 33	99.99 13	99.99 53	99.96 30	99.73 396	99.52 78	99.06 16	100.00 1	100.00 1	98.80 138	100.00 1	99.95 112	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 26	99.68 31	99.97 40	100.00 1	99.91 64	99.98 300	99.47 85	99.09 13	100.00 1	100.00 1	98.59 148	100.00 1	99.95 112	100.00 1	100.00 1

HFP-MVS		99.74 28	99.67 33	99.96 52	100.00 1	99.89 78	100.00 1	99.76 54	97.95 143	100.00 1	100.00 1	99.31 76	100.00 1	99.99 77	100.00 1	100.00 1

ACMMPR		99.74 28	99.67 33	99.96 52	100.00 1	99.89 78	100.00 1	99.76 54	97.95 143	100.00 1	100.00 1	99.29 82	100.00 1	99.99 77	100.00 1	100.00 1

PAPM_NR		99.74 28	99.66 36	99.99 13	100.00 1	99.96 30	100.00 1	99.47 85	97.87 148	100.00 1	100.00 1	99.60 21	100.00 1	100.00 1	100.00 1	100.00 1

CDPH-MVS		99.73 31	99.64 40	99.99 13	100.00 1	99.97 27	100.00 1	99.42 153	98.02 133	100.00 1	100.00 1	99.32 74	99.99 107	100.00 1	100.00 1	100.00 1

MGCNet		99.72 32	99.65 37	99.93 78	99.99 53	99.79 103	100.00 1	99.91 40	99.17 8	100.00 1	100.00 1	97.84 176	100.00 1	100.00 1	99.95 128	100.00 1

region2R		99.72 32	99.64 40	99.97 40	100.00 1	99.90 71	100.00 1	99.74 60	97.86 149	100.00 1	100.00 1	99.19 91	100.00 1	99.99 77	100.00 1	100.00 1

API-MVS		99.72 32	99.70 24	99.79 128	99.97 98	99.37 173	99.96 318	99.94 27	98.48 98	100.00 1	100.00 1	98.92 127	100.00 1	100.00 1	100.00 1	100.00 1

CNLPA		99.72 32	99.65 37	99.91 83	99.97 98	99.72 116	100.00 1	99.47 85	98.43 101	99.88 208	100.00 1	99.14 97	100.00 1	99.97 104	100.00 1	100.00 1

ZNCC-MVS		99.71 36	99.62 47	99.97 40	99.99 53	99.90 71	100.00 1	99.79 50	97.97 139	99.97 145	100.00 1	98.97 118	100.00 1	99.94 114	100.00 1	100.00 1

train_agg		99.71 36	99.63 44	99.97 40	100.00 1	99.95 38	100.00 1	99.42 153	97.70 162	100.00 1	100.00 1	99.51 39	99.97 150	100.00 1	100.00 1	100.00 1

MVS_111021_HR		99.71 36	99.63 44	99.93 78	99.95 108	99.83 98	100.00 1	100.00 1	98.89 60	100.00 1	100.00 1	97.85 174	99.95 183	100.00 1	100.00 1	100.00 1

EI-MVSNet-Vis-set		99.70 39	99.64 40	99.87 97	100.00 1	99.64 128	99.98 300	99.44 125	98.35 111	99.99 129	100.00 1	99.04 110	99.96 170	99.98 92	100.00 1	100.00 1

MVS_111021_LR		99.70 39	99.65 37	99.88 95	99.96 104	99.70 121	100.00 1	99.97 17	98.96 39	100.00 1	100.00 1	97.93 168	99.95 183	99.99 77	100.00 1	100.00 1

PLC	98.56 2	99.70 39	99.74 19	99.58 173	100.00 1	98.79 235	100.00 1	99.54 77	98.58 93	99.96 152	100.00 1	99.59 24	100.00 1	100.00 1	100.00 1	99.94 154
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
SMA-MVS		99.69 42	99.59 50	99.98 28	99.99 53	99.93 53	100.00 1	99.43 134	97.50 193	100.00 1	100.00 1	99.43 60	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
EI-MVSNet-UG-set		99.69 42	99.63 44	99.87 97	99.99 53	99.64 128	99.95 327	99.44 125	98.35 111	100.00 1	100.00 1	98.98 116	99.97 150	99.98 92	100.00 1	100.00 1

PGM-MVS		99.69 42	99.61 48	99.95 61	99.99 53	99.85 94	100.00 1	99.58 73	97.69 164	100.00 1	100.00 1	99.44 56	100.00 1	99.79 144	100.00 1	100.00 1

mPP-MVS		99.69 42	99.60 49	99.97 40	100.00 1	99.91 64	100.00 1	99.42 153	97.91 145	100.00 1	100.00 1	99.04 110	100.00 1	100.00 1	100.00 1	100.00 1

SR-MVS		99.68 46	99.58 52	99.98 28	100.00 1	99.95 38	100.00 1	99.64 70	97.59 181	100.00 1	100.00 1	98.99 113	99.99 107	100.00 1	100.00 1	100.00 1

MTAPA		99.68 46	99.59 50	99.97 40	99.99 53	99.91 64	100.00 1	99.42 153	98.32 113	99.94 190	100.00 1	98.65 144	100.00 1	99.96 106	100.00 1	100.00 1

APD-MVS		99.68 46	99.58 52	99.97 40	99.99 53	99.96 30	100.00 1	99.42 153	97.53 188	100.00 1	100.00 1	99.27 85	99.97 150	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 49	99.57 55	99.97 40	99.98 94	99.92 60	100.00 1	99.42 153	97.83 150	100.00 1	100.00 1	98.89 130	100.00 1	99.98 92	100.00 1	100.00 1

CP-MVS		99.67 49	99.58 52	99.95 61	100.00 1	99.84 96	100.00 1	99.42 153	97.77 157	100.00 1	100.00 1	99.07 104	100.00 1	100.00 1	100.00 1	100.00 1

SF-MVS		99.66 51	99.57 55	99.95 61	99.99 53	99.85 94	100.00 1	99.42 153	97.67 165	100.00 1	100.00 1	99.05 107	99.99 107	100.00 1	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 52	99.55 62	99.97 40	99.99 53	99.91 64	100.00 1	99.48 84	97.54 185	100.00 1	100.00 1	98.97 118	99.99 107	99.98 92	100.00 1	100.00 1

ACMMP		99.65 52	99.57 55	99.89 90	99.99 53	99.66 126	99.75 390	99.73 61	98.16 121	99.75 238	100.00 1	98.90 129	100.00 1	99.96 106	99.88 153	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
lecture		99.64 54	99.53 65	99.98 28	99.99 53	99.93 53	100.00 1	99.47 85	98.53 94	100.00 1	100.00 1	97.88 172	100.00 1	99.98 92	99.92 141	100.00 1

GST-MVS		99.64 54	99.53 65	99.95 61	100.00 1	99.86 90	100.00 1	99.79 50	97.72 160	99.95 183	100.00 1	98.39 157	100.00 1	99.96 106	99.99 107	100.00 1

PS-MVSNAJ		99.64 54	99.57 55	99.85 104	99.78 167	99.81 100	99.95 327	99.42 153	98.38 105	100.00 1	100.00 1	98.75 140	100.00 1	99.88 124	99.99 107	99.74 300

F-COLMAP		99.64 54	99.64 40	99.67 154	99.99 53	99.07 205	100.00 1	99.44 125	98.30 114	99.90 202	100.00 1	99.18 92	99.99 107	99.91 119	100.00 1	99.94 154

fmvsm_l_conf0.5_n_a		99.63 58	99.55 62	99.86 100	99.83 135	99.58 136	100.00 1	99.36 235	98.98 35	100.00 1	100.00 1	97.85 174	99.99 107	100.00 1	99.94 134	100.00 1

fmvsm_l_conf0.5_n		99.63 58	99.56 60	99.86 100	99.81 144	99.59 134	100.00 1	99.36 235	98.98 35	100.00 1	100.00 1	97.92 169	99.99 107	100.00 1	99.95 128	100.00 1

MM		99.63 58	99.52 68	99.94 74	99.99 53	99.82 99	100.00 1	99.97 17	99.11 10	100.00 1	100.00 1	96.65 225	100.00 1	100.00 1	99.97 122	100.00 1

SR-MVS-dyc-post		99.63 58	99.52 68	99.97 40	99.99 53	99.91 64	100.00 1	99.42 153	97.62 173	100.00 1	100.00 1	98.65 144	99.99 107	99.99 77	100.00 1	100.00 1

DPM-MVS		99.63 58	99.51 70	100.00 1	99.90 120	100.00 1	100.00 1	99.43 134	99.00 32	100.00 1	100.00 1	99.58 27	100.00 1	97.64 346	100.00 1	100.00 1

EPNet		99.62 63	99.69 25	99.42 203	99.99 53	98.37 277	100.00 1	99.89 42	98.83 70	100.00 1	100.00 1	98.97 118	100.00 1	99.90 120	99.61 187	99.89 190
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DELS-MVS		99.62 63	99.56 60	99.82 112	99.92 116	99.45 162	100.00 1	99.78 52	98.92 52	99.73 244	100.00 1	97.70 182	100.00 1	99.93 116	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 65	99.50 71	99.97 40	99.98 94	99.92 60	100.00 1	99.42 153	97.53 188	99.77 235	100.00 1	98.77 139	100.00 1	99.99 77	100.00 1	99.99 124
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MP-MVS		99.61 65	99.49 73	99.98 28	99.99 53	99.94 47	100.00 1	99.42 153	97.82 152	99.99 129	100.00 1	98.20 160	100.00 1	99.99 77	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 65	99.69 25	99.35 221	99.99 53	98.06 314	100.00 1	99.36 235	99.83 2	100.00 1	100.00 1	98.95 122	99.99 107	100.00 1	99.11 200	100.00 1

HPM-MVS_fast		99.60 68	99.49 73	99.91 83	99.99 53	99.78 104	100.00 1	99.42 153	97.09 234	100.00 1	100.00 1	98.95 122	99.96 170	99.98 92	100.00 1	100.00 1

HPM-MVS		99.59 69	99.50 71	99.89 90	100.00 1	99.70 121	100.00 1	99.42 153	97.46 197	100.00 1	100.00 1	98.60 147	99.96 170	99.99 77	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 70	99.48 76	99.85 104	99.86 127	99.54 143	100.00 1	99.36 235	98.94 45	100.00 1	100.00 1	97.97 166	100.00 1	99.88 124	99.28 195	100.00 1

BP-MVS1		99.56 71	99.48 76	99.79 128	99.48 291	99.61 131	100.00 1	99.32 259	97.34 211	99.94 190	100.00 1	99.74 13	99.89 221	99.75 158	99.72 175	99.87 214

test_fmvsmconf_n		99.56 71	99.46 79	99.86 100	99.68 187	99.58 136	100.00 1	99.31 268	98.92 52	99.88 208	100.00 1	97.35 201	99.99 107	99.98 92	99.99 107	100.00 1

test_fmvsm_n_1920		99.55 73	99.49 73	99.73 143	99.85 129	99.19 195	100.00 1	99.41 202	98.87 64	100.00 1	100.00 1	97.34 202	100.00 1	99.98 92	99.90 149	100.00 1

WTY-MVS		99.54 74	99.40 81	99.95 61	99.81 144	99.93 53	100.00 1	100.00 1	97.98 137	99.84 212	100.00 1	98.94 124	99.98 141	99.86 128	98.21 270	99.94 154

test_yl		99.51 75	99.37 86	99.95 61	99.82 138	99.90 71	100.00 1	99.47 85	97.48 195	100.00 1	100.00 1	99.80 6	100.00 1	99.98 92	97.75 309	99.94 154

DCV-MVSNet		99.51 75	99.37 86	99.95 61	99.82 138	99.90 71	100.00 1	99.47 85	97.48 195	100.00 1	100.00 1	99.80 6	100.00 1	99.98 92	97.75 309	99.94 154

xiu_mvs_v2_base		99.51 75	99.41 80	99.82 112	99.70 179	99.73 114	99.92 343	99.40 206	98.15 123	100.00 1	100.00 1	98.50 152	100.00 1	99.85 131	99.13 199	99.74 300

HY-MVS	96.53 9	99.50 78	99.35 91	99.96 52	99.81 144	99.93 53	99.64 409	100.00 1	97.97 139	99.84 212	99.85 318	98.94 124	99.99 107	99.86 128	98.23 269	99.95 149

PHI-MVS		99.50 78	99.39 82	99.82 112	100.00 1	99.45 162	100.00 1	99.94 27	96.38 327	100.00 1	100.00 1	98.18 161	100.00 1	100.00 1	100.00 1	100.00 1

CPTT-MVS		99.49 80	99.38 83	99.85 104	100.00 1	99.54 143	100.00 1	99.42 153	97.58 182	99.98 139	100.00 1	97.43 199	100.00 1	99.99 77	100.00 1	100.00 1

MAR-MVS		99.49 80	99.36 89	99.89 90	99.97 98	99.66 126	99.74 391	99.95 19	97.89 146	100.00 1	100.00 1	96.71 224	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 82	99.38 83	99.75 139	99.89 122	99.51 150	99.45 433	100.00 1	98.38 105	99.83 215	100.00 1	98.86 131	99.81 254	99.25 261	98.78 209	99.94 154

PVSNet_Blended		99.48 82	99.36 89	99.83 110	99.98 94	99.60 132	100.00 1	100.00 1	97.79 155	100.00 1	100.00 1	96.57 227	99.99 107	100.00 1	99.88 153	99.90 182

NormalMVS		99.47 84	99.48 76	99.43 200	99.99 53	98.55 255	99.94 335	99.28 291	98.39 103	100.00 1	100.00 1	98.44 154	99.98 141	99.36 249	99.92 141	99.75 293

test_fmvsmvis_n_1920		99.46 85	99.37 86	99.73 143	98.88 386	99.18 197	100.00 1	99.26 312	98.85 66	99.79 232	100.00 1	97.70 182	100.00 1	99.98 92	99.86 159	100.00 1

testing3-2		99.45 86	99.31 94	99.86 100	99.70 179	99.73 114	100.00 1	99.47 85	97.46 197	99.97 145	99.97 264	99.48 50	100.00 1	99.78 150	97.99 288	99.85 219

sss		99.45 86	99.34 93	99.80 123	99.76 170	99.50 152	100.00 1	99.91 40	97.72 160	99.98 139	99.94 296	98.45 153	100.00 1	99.53 229	98.75 212	99.89 190

AdaColmap		99.44 88	99.26 102	99.95 61	100.00 1	99.86 90	99.70 402	99.99 13	98.53 94	99.90 202	100.00 1	95.34 248	100.00 1	99.92 117	100.00 1	100.00 1

BridgeMVS		99.43 89	99.28 96	99.85 104	99.68 187	99.68 124	99.97 310	99.28 291	97.03 241	99.96 152	99.97 264	97.90 170	99.93 200	99.77 152	100.00 1	99.94 154

thisisatest0515		99.42 90	99.31 94	99.74 140	99.59 231	99.55 140	100.00 1	99.46 103	96.65 296	99.92 197	100.00 1	99.44 56	99.85 241	99.09 275	99.63 186	99.81 246

myMVS_eth3d28		99.41 91	99.28 96	99.80 123	99.69 182	99.53 145	100.00 1	99.43 134	97.12 233	99.98 139	99.97 264	99.41 66	100.00 1	99.81 142	98.07 285	99.88 203

CANet		99.40 92	99.24 108	99.89 90	99.99 53	99.76 108	100.00 1	99.73 61	98.40 102	99.78 234	100.00 1	95.28 249	99.96 170	100.00 1	99.99 107	99.96 143

GDP-MVS		99.39 93	99.26 102	99.77 136	99.53 254	99.55 140	100.00 1	99.11 415	97.14 229	99.96 152	100.00 1	99.83 5	99.89 221	98.47 309	99.26 196	99.87 214

MVSMamba_PlusPlus		99.39 93	99.25 104	99.80 123	99.68 187	99.59 134	99.99 267	99.30 274	96.66 294	99.96 152	99.97 264	97.89 171	99.92 206	99.76 154	100.00 1	99.90 182

114514_t		99.39 93	99.25 104	99.81 117	99.97 98	99.48 160	100.00 1	99.42 153	95.53 364	100.00 1	100.00 1	98.37 158	99.95 183	99.97 104	100.00 1	100.00 1

fmvsm_l_conf0.5_n_3		99.38 96	99.20 117	99.92 82	99.80 157	99.78 104	100.00 1	99.35 246	98.94 45	100.00 1	100.00 1	94.77 267	99.99 107	99.99 77	99.92 141	100.00 1

alignmvs		99.38 96	99.21 113	99.91 83	99.73 175	99.92 60	100.00 1	99.51 82	97.61 177	100.00 1	100.00 1	99.06 105	99.93 200	99.83 135	97.12 321	99.90 182

1314		99.38 96	99.19 118	99.96 52	98.88 386	99.89 78	99.24 455	99.93 35	98.88 61	98.79 334	100.00 1	97.02 208	100.00 1	100.00 1	100.00 1	100.00 1

thisisatest0530		99.37 99	99.27 98	99.69 150	99.59 231	99.41 168	100.00 1	99.46 103	96.46 319	99.90 202	100.00 1	99.44 56	99.85 241	98.97 280	99.58 188	99.80 278

UBG		99.36 100	99.27 98	99.63 161	99.63 215	99.01 214	100.00 1	99.43 134	96.99 244	100.00 1	99.92 302	99.69 17	99.99 107	99.74 159	98.06 286	99.88 203

fmvsm_l_conf0.5_n_9		99.35 101	99.15 123	99.95 61	99.83 135	99.84 96	100.00 1	99.30 274	98.92 52	100.00 1	100.00 1	94.32 283	100.00 1	100.00 1	99.93 138	100.00 1

xiu_mvs_v1_base_debu		99.35 101	99.21 113	99.79 128	99.67 195	99.71 117	99.78 381	99.36 235	98.13 125	100.00 1	100.00 1	97.00 212	100.00 1	99.83 135	99.07 201	99.66 314

xiu_mvs_v1_base		99.35 101	99.21 113	99.79 128	99.67 195	99.71 117	99.78 381	99.36 235	98.13 125	100.00 1	100.00 1	97.00 212	100.00 1	99.83 135	99.07 201	99.66 314

xiu_mvs_v1_base_debi		99.35 101	99.21 113	99.79 128	99.67 195	99.71 117	99.78 381	99.36 235	98.13 125	100.00 1	100.00 1	97.00 212	100.00 1	99.83 135	99.07 201	99.66 314

fmvsm_s_conf0.5_n_8		99.34 105	99.14 125	99.91 83	99.83 135	99.74 112	100.00 1	99.38 225	98.94 45	100.00 1	100.00 1	94.25 285	99.99 107	100.00 1	99.91 147	100.00 1

ETV-MVS		99.34 105	99.24 108	99.64 160	99.58 236	99.33 176	100.00 1	99.25 316	97.57 183	99.96 152	100.00 1	97.44 198	99.79 259	99.70 173	99.65 183	99.81 246

tttt0517		99.34 105	99.23 111	99.67 154	99.57 240	99.38 170	100.00 1	99.46 103	96.33 333	99.89 205	100.00 1	99.44 56	99.84 245	98.93 282	99.46 192	99.78 289

CS-MVS		99.33 108	99.27 98	99.50 183	99.99 53	99.00 217	100.00 1	99.13 407	97.26 220	99.96 152	100.00 1	97.79 179	99.64 291	99.64 197	99.67 180	99.87 214

PVSNet_Blended_VisFu		99.33 108	99.18 121	99.78 133	99.82 138	99.49 156	100.00 1	99.95 19	97.36 207	99.63 258	100.00 1	96.45 231	99.95 183	99.79 144	99.65 183	99.89 190

fmvsm_s_conf0.5_n_a		99.32 110	99.15 123	99.81 117	99.80 157	99.47 161	100.00 1	99.35 246	98.22 116	100.00 1	100.00 1	95.21 254	99.99 107	99.96 106	99.86 159	99.98 127

HyFIR lowres test		99.32 110	99.24 108	99.58 173	99.95 108	99.26 185	100.00 1	99.99 13	96.72 283	99.29 290	99.91 305	99.49 46	99.47 328	99.74 159	98.08 284	100.00 1

SPE-MVS-test		99.31 112	99.27 98	99.43 200	99.99 53	98.77 236	100.00 1	99.19 365	97.24 221	99.96 152	100.00 1	97.56 190	99.70 288	99.68 183	99.81 169	99.82 230

LS3D		99.31 112	99.13 126	99.87 97	99.99 53	99.71 117	99.55 422	99.46 103	97.32 214	99.82 224	100.00 1	96.85 219	99.97 150	99.14 269	100.00 1	99.92 167

SymmetryMVS		99.30 114	99.25 104	99.45 194	99.79 162	98.55 255	99.94 335	99.47 85	98.39 103	100.00 1	100.00 1	98.44 154	99.98 141	99.36 249	97.83 302	99.83 224

fmvsm_s_conf0.5_n_6		99.30 114	99.12 128	99.84 109	99.24 346	99.56 138	100.00 1	99.31 268	98.90 59	100.00 1	100.00 1	94.75 269	99.97 150	99.98 92	99.88 153	100.00 1

PVSNet	94.91 18	99.30 114	99.25 104	99.44 197	100.00 1	98.32 287	100.00 1	99.86 43	98.04 132	100.00 1	100.00 1	96.10 235	100.00 1	99.55 222	99.73 174	100.00 1

UWE-MVS-28		99.29 117	99.23 111	99.48 188	99.73 175	98.86 229	100.00 1	99.43 134	96.97 247	99.99 129	99.83 321	99.43 60	99.77 267	99.35 253	98.31 253	99.80 278

lupinMVS		99.29 117	99.16 122	99.69 150	99.45 312	99.49 156	100.00 1	99.15 393	97.45 199	99.97 145	100.00 1	96.76 220	99.76 272	99.67 187	100.00 1	99.81 246

CSCG		99.28 119	99.35 91	99.05 265	99.99 53	97.15 361	100.00 1	99.47 85	97.44 201	99.42 276	100.00 1	97.83 178	100.00 1	99.99 77	100.00 1	100.00 1

thres200		99.27 120	99.04 135	99.96 52	99.81 144	99.90 71	100.00 1	99.94 27	97.31 216	99.83 215	99.96 282	97.04 205	100.00 1	99.62 206	97.88 297	99.98 127

OMC-MVS		99.27 120	99.38 83	98.96 274	99.95 108	97.06 365	100.00 1	99.40 206	98.83 70	99.88 208	100.00 1	97.01 209	99.86 234	99.47 238	99.84 164	99.97 137

testing11		99.26 122	99.19 118	99.46 190	99.64 213	98.61 251	100.00 1	99.43 134	96.94 250	99.92 197	99.94 296	99.43 60	99.97 150	99.67 187	97.79 307	99.82 230

EIA-MVS		99.26 122	99.19 118	99.45 194	99.63 215	98.75 237	100.00 1	99.27 306	96.93 251	99.95 183	100.00 1	97.47 195	99.79 259	99.74 159	99.72 175	99.82 230

tfpn200view9		99.26 122	99.03 136	99.96 52	99.81 144	99.89 78	100.00 1	99.94 27	97.23 223	99.83 215	99.96 282	97.04 205	100.00 1	99.59 213	97.85 299	99.98 127

thres400		99.26 122	99.03 136	99.95 61	99.81 144	99.89 78	100.00 1	99.94 27	97.23 223	99.83 215	99.96 282	97.04 205	100.00 1	99.59 213	97.85 299	99.97 137

test_fmvsmconf0.1_n		99.25 126	99.05 134	99.82 112	98.92 382	99.55 140	100.00 1	99.23 327	98.91 55	99.75 238	99.97 264	94.79 266	99.94 196	99.94 114	99.99 107	99.97 137

thres100view900		99.25 126	99.01 138	99.95 61	99.81 144	99.87 87	100.00 1	99.94 27	97.13 231	99.83 215	99.96 282	97.01 209	100.00 1	99.59 213	97.85 299	99.98 127

EPMVS		99.25 126	99.13 126	99.60 167	99.60 227	99.20 194	99.60 416	100.00 1	96.93 251	99.92 197	99.36 405	99.05 107	99.71 286	98.77 291	98.94 206	99.90 182

thres600view7		99.24 129	99.00 141	99.95 61	99.81 144	99.87 87	100.00 1	99.94 27	97.13 231	99.83 215	99.96 282	97.01 209	100.00 1	99.54 226	97.77 308	99.97 137

MVS		99.22 130	98.96 147	99.98 28	99.00 372	99.95 38	99.24 455	99.94 27	98.14 124	98.88 324	100.00 1	95.63 245	100.00 1	99.85 131	100.00 1	100.00 1

guyue		99.21 131	99.07 132	99.62 163	99.55 247	99.29 180	100.00 1	99.32 259	97.66 166	99.96 152	100.00 1	95.84 239	99.84 245	99.63 204	99.67 180	99.75 293

fmvsm_s_conf0.5_n		99.21 131	99.01 138	99.83 110	99.84 131	99.53 145	100.00 1	99.38 225	98.29 115	100.00 1	100.00 1	93.62 301	99.99 107	99.99 77	99.93 138	99.98 127

EC-MVSNet		99.19 133	99.09 131	99.48 188	99.42 318	99.07 205	100.00 1	99.21 351	96.95 249	99.96 152	100.00 1	96.88 218	99.48 326	99.64 197	99.79 173	99.88 203

testing91		99.18 134	99.10 129	99.41 204	99.60 227	98.43 267	100.00 1	99.43 134	96.76 271	99.82 224	99.92 302	99.05 107	99.98 141	99.62 206	97.67 313	99.81 246

testing99		99.18 134	99.10 129	99.41 204	99.60 227	98.43 267	100.00 1	99.43 134	96.76 271	99.84 212	99.92 302	99.06 105	99.98 141	99.62 206	97.67 313	99.81 246

UWE-MVS		99.18 134	99.06 133	99.51 180	99.67 195	98.80 234	100.00 1	99.43 134	96.80 265	99.93 195	99.86 313	99.79 8	99.94 196	97.78 342	98.33 249	99.80 278

ETVMVS		99.16 137	98.98 144	99.69 150	99.67 195	99.56 138	100.00 1	99.45 111	96.36 329	99.98 139	99.95 290	98.65 144	99.64 291	99.11 273	97.63 316	99.88 203

FE-MVS		99.16 137	98.99 143	99.66 157	99.65 207	99.18 197	99.58 418	99.43 134	95.24 376	99.91 200	99.59 377	99.37 70	99.97 150	98.31 316	99.81 169	99.83 224

testing222		99.14 139	98.94 152	99.73 143	99.67 195	99.51 150	100.00 1	99.43 134	96.90 256	99.99 129	99.90 307	98.55 150	99.86 234	98.85 286	97.18 320	99.81 246

PMMVS		99.12 140	98.97 146	99.58 173	99.57 240	98.98 219	100.00 1	99.30 274	97.14 229	99.96 152	100.00 1	96.53 230	99.82 250	99.70 173	98.49 222	99.94 154

jason		99.11 141	98.96 147	99.59 169	99.17 349	99.31 179	100.00 1	99.13 407	97.38 206	99.83 215	100.00 1	95.54 246	99.72 284	99.57 219	99.97 122	99.74 300
jason: jason.
EPP-MVSNet		99.10 142	99.00 141	99.40 209	99.51 275	98.68 245	99.92 343	99.43 134	95.47 370	99.65 257	100.00 1	99.51 39	99.76 272	99.53 229	98.00 287	99.75 293

fmvsm_s_conf0.5_n_10		99.08 143	98.78 170	99.97 40	99.84 131	99.92 60	100.00 1	99.28 291	98.93 49	100.00 1	100.00 1	91.07 351	99.99 107	100.00 1	99.95 128	100.00 1

TESTMET0.1,1		99.08 143	98.96 147	99.44 197	99.63 215	99.38 170	100.00 1	99.45 111	95.53 364	99.48 269	100.00 1	99.71 15	99.02 361	96.84 374	99.99 107	99.91 171

IS-MVSNet		99.08 143	98.91 157	99.59 169	99.65 207	99.38 170	99.78 381	99.24 322	96.70 289	99.51 266	100.00 1	98.44 154	99.52 319	98.47 309	98.39 231	99.88 203

LuminaMVS		99.07 146	98.92 156	99.50 183	98.87 389	99.12 202	99.92 343	99.22 332	97.45 199	99.82 224	99.98 251	96.29 233	99.85 241	99.71 169	99.05 204	99.52 324

UA-Net		99.06 147	98.83 164	99.74 140	99.52 268	99.40 169	99.08 482	99.45 111	97.64 170	99.83 215	100.00 1	95.80 240	99.94 196	98.35 314	99.80 172	99.88 203

3Dnovator	95.63 14	99.06 147	98.76 174	99.96 52	98.86 391	99.90 71	99.98 300	99.93 35	98.95 42	98.49 362	100.00 1	92.91 322	100.00 1	99.71 169	100.00 1	100.00 1

mvsmamba		99.05 149	98.98 144	99.27 252	99.57 240	98.10 310	100.00 1	99.28 291	95.92 349	99.96 152	99.97 264	96.73 223	99.89 221	99.72 165	99.65 183	99.81 246

fmvsm_s_conf0.5_n_9		99.04 150	98.78 170	99.81 117	99.86 127	99.44 165	100.00 1	99.32 259	98.94 45	100.00 1	100.00 1	91.00 354	99.99 107	100.00 1	99.94 134	100.00 1

patch_mono-2		99.04 150	99.79 9	96.81 415	99.92 116	90.47 472	100.00 1	99.41 202	98.95 42	100.00 1	100.00 1	99.78 9	100.00 1	100.00 1	100.00 1	99.95 149

VNet		99.04 150	98.75 175	99.90 87	99.81 144	99.75 109	99.50 428	99.47 85	98.36 109	100.00 1	99.99 243	94.66 272	100.00 1	99.90 120	97.09 322	99.96 143

AstraMVS		99.03 153	99.01 138	99.09 262	99.46 304	97.66 339	100.00 1	99.23 327	97.83 150	99.95 183	100.00 1	95.52 247	99.86 234	99.74 159	99.39 194	99.74 300

sasdasda		99.03 153	98.73 179	99.94 74	99.75 172	99.95 38	100.00 1	99.30 274	97.64 170	100.00 1	100.00 1	95.22 252	99.97 150	99.76 154	96.90 327	99.91 171

canonicalmvs		99.03 153	98.73 179	99.94 74	99.75 172	99.95 38	100.00 1	99.30 274	97.64 170	100.00 1	100.00 1	95.22 252	99.97 150	99.76 154	96.90 327	99.91 171

test-LLR		99.03 153	98.91 157	99.40 209	99.40 325	99.28 182	100.00 1	99.45 111	96.70 289	99.42 276	99.12 418	99.31 76	99.01 363	96.82 375	99.99 107	99.91 171

PatchmatchNet		99.03 153	98.96 147	99.26 253	99.49 288	98.33 285	99.38 441	99.45 111	96.64 297	99.96 152	99.58 379	99.49 46	99.50 324	97.63 347	99.00 205	99.93 165
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
3Dnovator+	95.58 15	99.03 153	98.71 185	99.96 52	98.99 375	99.89 78	100.00 1	99.51 82	98.96 39	98.32 375	100.00 1	92.78 324	100.00 1	99.87 127	100.00 1	100.00 1

CANet_DTU		99.02 159	98.90 160	99.41 204	99.88 124	98.71 242	100.00 1	99.29 283	98.84 68	100.00 1	100.00 1	94.02 291	100.00 1	98.08 325	99.96 126	99.52 324

PatchMatch-RL		99.02 159	98.78 170	99.74 140	99.99 53	99.29 180	100.00 1	100.00 1	98.38 105	99.89 205	99.81 328	93.14 317	99.99 107	97.85 336	99.98 118	99.95 149

MGCFI-Net		99.01 161	98.70 187	99.93 78	99.74 174	99.94 47	100.00 1	99.29 283	97.60 180	100.00 1	100.00 1	95.10 258	99.96 170	99.74 159	96.85 329	99.91 171

fmvsm_s_conf0.5_n_5		99.00 162	98.70 187	99.88 95	99.81 144	99.64 128	100.00 1	99.26 312	98.78 83	99.97 145	100.00 1	90.65 361	99.99 107	100.00 1	99.89 150	99.99 124

FA-MVS(test-final)		99.00 162	98.75 175	99.73 143	99.63 215	99.43 166	99.83 366	99.43 134	95.84 355	99.52 265	99.37 404	97.84 176	99.96 170	97.63 347	99.68 178	99.79 284

CHOSEN 1792x2688		99.00 162	98.91 157	99.25 254	99.90 120	97.79 335	100.00 1	99.99 13	98.79 80	98.28 378	100.00 1	93.63 300	99.95 183	99.66 194	99.95 128	100.00 1

DeepC-MVS	97.84 5	99.00 162	98.80 168	99.60 167	99.93 113	99.03 210	100.00 1	99.40 206	98.61 92	99.33 287	100.00 1	92.23 336	99.95 183	99.74 159	99.96 126	99.83 224
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
fmvsm_s_conf0.5_n_3		98.99 166	98.69 189	99.89 90	99.70 179	99.69 123	100.00 1	99.39 222	98.93 49	100.00 1	100.00 1	90.20 373	99.99 107	100.00 1	99.95 128	100.00 1

baseline2		98.99 166	98.93 154	99.18 258	99.26 345	99.15 200	100.00 1	99.46 103	96.71 288	96.79 436	100.00 1	99.42 64	99.25 349	98.75 293	99.94 134	99.15 335

QAPM		98.99 166	98.66 193	99.96 52	99.01 367	99.87 87	99.88 358	99.93 35	97.99 135	98.68 339	100.00 1	93.17 313	100.00 1	99.32 257	100.00 1	100.00 1

Vis-MVSNet (Re-imp)		98.99 166	98.89 161	99.29 246	99.64 213	98.89 228	99.98 300	99.31 268	96.74 277	99.48 269	100.00 1	98.11 163	99.10 356	98.39 312	98.34 246	99.89 190

fmvsm_s_conf0.5_n_7		98.98 170	98.85 163	99.37 217	99.67 195	98.34 284	100.00 1	99.31 268	98.97 37	100.00 1	100.00 1	91.70 342	99.97 150	99.99 77	99.97 122	99.80 278

fmvsm_s_conf0.5_n_4		98.98 170	98.74 177	99.68 153	99.81 144	99.50 152	100.00 1	99.26 312	98.91 55	100.00 1	100.00 1	90.87 358	99.97 150	99.99 77	99.81 169	99.57 320

tpmrst		98.98 170	98.93 154	99.14 261	99.61 224	97.74 336	99.52 426	99.36 235	96.05 346	99.98 139	99.64 365	99.04 110	99.86 234	98.94 281	98.19 273	99.82 230

test-mter		98.96 173	98.82 165	99.40 209	99.40 325	99.28 182	100.00 1	99.45 111	95.44 375	99.42 276	99.12 418	99.70 16	99.01 363	96.82 375	99.99 107	99.91 171

diffmvs		98.96 173	98.73 179	99.63 161	99.54 250	99.16 199	100.00 1	99.18 375	97.33 213	99.96 152	100.00 1	94.60 274	99.91 208	99.66 194	98.33 249	99.82 230
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		98.96 173	98.95 151	99.01 270	99.48 291	98.36 280	99.93 341	99.37 229	96.79 266	99.31 289	99.83 321	99.77 11	98.91 375	98.07 327	97.98 289	99.77 290
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
E3new		98.95 176	98.80 168	99.41 204	99.57 240	98.50 264	100.00 1	99.22 332	96.84 261	99.89 205	100.00 1	95.70 243	99.93 200	99.57 219	98.39 231	99.82 230

fmvsm_s_conf0.1_n_2		98.95 176	98.69 189	99.73 143	99.61 224	99.74 112	100.00 1	99.23 327	98.95 42	99.97 145	100.00 1	90.92 357	99.97 150	100.00 1	99.58 188	99.47 327

MVSFormer		98.94 178	98.82 165	99.28 249	99.45 312	99.49 156	100.00 1	99.13 407	95.46 371	99.97 145	100.00 1	96.76 220	98.59 410	98.63 301	100.00 1	99.74 300

MVS_Test		98.93 179	98.65 194	99.77 136	99.62 222	99.50 152	99.99 267	99.19 365	95.52 366	99.96 152	99.86 313	96.54 229	99.98 141	98.65 298	98.48 223	99.82 230

viewmamba		98.92 180	98.74 177	99.46 190	99.46 304	98.83 232	100.00 1	99.19 365	97.18 226	99.95 183	100.00 1	94.97 261	99.74 278	99.64 197	98.29 256	99.81 246

fmvsm_s_conf0.5_n_11		98.92 180	98.63 197	99.80 123	99.85 129	99.86 90	100.00 1	99.24 322	98.91 55	100.00 1	100.00 1	89.69 388	99.99 107	100.00 1	99.98 118	99.54 322

diffmvs_AUTHOR		98.92 180	98.73 179	99.49 187	99.48 291	98.81 233	99.94 335	99.14 400	97.24 221	99.96 152	100.00 1	94.85 264	99.87 231	99.67 187	98.31 253	99.79 284

baseline1		98.91 183	98.61 201	99.81 117	99.71 177	99.77 107	99.78 381	99.44 125	97.51 192	98.81 332	99.99 243	98.25 159	99.76 272	98.60 304	95.41 345	99.89 190

1112_ss		98.91 183	98.71 185	99.51 180	99.69 182	98.75 237	99.99 267	99.15 393	96.82 263	98.84 329	100.00 1	97.45 196	99.89 221	98.66 296	97.75 309	99.89 190

viewcassd2359sk11		98.90 185	98.73 179	99.40 209	99.57 240	98.47 265	99.99 267	99.22 332	96.79 266	99.82 224	100.00 1	95.24 251	99.91 208	99.54 226	98.38 235	99.82 230

fmvsm_s_conf0.5_n_2		98.90 185	98.57 209	99.90 87	99.79 162	99.78 104	100.00 1	99.25 316	98.97 37	100.00 1	100.00 1	89.22 397	99.99 107	100.00 1	99.88 153	99.92 167

MSDG		98.90 185	98.63 197	99.70 149	99.92 116	99.25 187	100.00 1	99.37 229	95.71 357	99.40 282	100.00 1	96.58 226	99.95 183	96.80 377	99.94 134	99.91 171

onestephybrid01		98.89 188	98.67 192	99.56 176	99.51 275	99.08 204	100.00 1	99.20 361	97.30 218	99.95 183	100.00 1	94.04 288	99.79 259	99.77 152	98.29 256	99.81 246

dcpmvs_2		98.87 189	99.53 65	96.90 403	99.87 126	90.88 468	99.94 335	99.07 429	98.20 119	100.00 1	100.00 1	98.69 143	99.86 234	100.00 1	100.00 1	99.95 149

viewmanbaseed2359cas		98.86 190	98.68 191	99.40 209	99.51 275	98.51 263	99.98 300	99.22 332	97.05 239	99.72 245	100.00 1	94.77 267	99.89 221	99.58 216	98.31 253	99.81 246

DP-MVS		98.86 190	98.54 214	99.81 117	99.97 98	99.45 162	99.52 426	99.40 206	94.35 403	98.36 370	100.00 1	96.13 234	99.97 150	99.12 272	100.00 1	100.00 1

hybridnocas07		98.85 192	98.63 197	99.53 179	99.52 268	98.95 224	100.00 1	99.19 365	97.15 228	99.93 195	100.00 1	93.83 297	99.82 250	99.67 187	98.38 235	99.82 230

CostFormer		98.84 193	98.77 173	99.04 267	99.41 320	97.58 342	99.67 407	99.35 246	94.66 392	99.96 152	99.36 405	99.28 84	99.74 278	99.41 247	97.81 304	99.81 246

Test_1112_low_res		98.83 194	98.60 204	99.51 180	99.69 182	98.75 237	99.99 267	99.14 400	96.81 264	98.84 329	99.06 422	97.45 196	99.89 221	98.66 296	97.75 309	99.89 190

BH-w/o		98.82 195	98.81 167	98.88 280	99.62 222	96.71 373	100.00 1	99.28 291	97.09 234	98.81 332	100.00 1	94.91 263	99.96 170	99.54 226	100.00 1	99.96 143

hybrid		98.81 196	98.60 204	99.45 194	99.52 268	98.74 240	100.00 1	99.19 365	97.04 240	99.95 183	100.00 1	93.89 296	99.78 265	99.64 197	98.19 273	99.81 246

mvs_anonymous		98.80 197	98.60 204	99.38 216	99.57 240	99.24 189	100.00 1	99.21 351	95.87 350	98.92 321	99.82 325	96.39 232	99.03 360	99.13 271	98.50 221	99.88 203

viewdifsd2359ckpt09		98.78 198	98.60 204	99.31 239	99.53 254	98.37 277	100.00 1	99.20 361	96.85 259	99.32 288	100.00 1	94.68 271	99.74 278	99.46 241	98.36 240	99.81 246

E2		98.77 199	98.57 209	99.37 217	99.53 254	98.38 276	99.98 300	99.22 332	96.77 270	99.75 238	100.00 1	94.03 289	99.91 208	99.53 229	98.35 242	99.82 230

E3		98.77 199	98.57 209	99.36 219	99.47 296	98.36 280	99.98 300	99.22 332	96.76 271	99.75 238	100.00 1	94.10 286	99.91 208	99.53 229	98.35 242	99.82 230

fmvsm_s_conf0.1_n		98.77 199	98.42 231	99.82 112	99.47 296	99.52 149	100.00 1	99.27 306	97.53 188	100.00 1	100.00 1	89.73 386	99.96 170	99.84 134	99.93 138	99.97 137

SSM_0404		98.76 202	98.56 212	99.35 221	99.53 254	98.65 249	99.80 375	99.15 393	96.53 310	99.47 272	100.00 1	94.38 280	99.76 272	99.64 197	98.59 217	99.64 318

TAMVS		98.76 202	98.73 179	98.86 281	99.44 314	97.69 337	99.57 419	99.34 253	96.57 306	99.12 302	99.81 328	98.83 135	99.16 354	97.97 333	97.91 295	99.73 309

OpenMVS	95.20 17	98.76 202	98.41 233	99.78 133	98.89 385	99.81 100	99.99 267	99.76 54	98.02 133	98.02 393	100.00 1	91.44 344	100.00 1	99.63 204	99.97 122	99.55 321

RRT-MVS		98.75 205	98.52 217	99.44 197	99.65 207	98.57 254	99.90 351	99.08 424	96.51 315	99.96 152	99.95 290	92.59 330	99.96 170	99.60 211	99.45 193	99.81 246

viewdifsd2359ckpt07		98.72 206	98.52 217	99.34 223	99.47 296	98.28 291	99.99 267	99.20 361	96.98 245	99.60 260	100.00 1	93.45 305	99.93 200	99.58 216	98.36 240	99.82 230

viewdifsd2359ckpt13		98.72 206	98.52 217	99.34 223	99.55 247	98.46 266	99.99 267	99.22 332	96.50 317	99.05 311	100.00 1	94.54 275	99.73 282	99.46 241	98.35 242	99.81 246

SSM_0407		98.72 206	98.52 217	99.33 231	99.53 254	98.52 260	99.88 358	99.15 393	96.53 310	98.95 317	100.00 1	94.38 280	99.72 284	99.64 197	98.62 214	99.75 293

dp		98.72 206	98.61 201	99.03 268	99.53 254	97.39 348	99.45 433	99.39 222	95.62 361	99.94 190	99.52 389	98.83 135	99.82 250	96.77 380	98.42 227	99.89 190

Casviewmamba		98.71 210	98.47 225	99.46 190	99.47 296	98.70 244	100.00 1	99.17 385	96.97 247	99.45 275	100.00 1	93.04 319	99.87 231	99.67 187	98.41 228	99.81 246

fmvsm_s_conf0.1_n_a		98.71 210	98.36 248	99.78 133	99.09 356	99.42 167	100.00 1	99.26 312	97.42 203	100.00 1	100.00 1	89.78 384	99.96 170	99.82 140	99.85 162	99.97 137

PVSNet_BlendedMVS		98.71 210	98.62 200	98.98 273	99.98 94	99.60 132	100.00 1	100.00 1	97.23 223	100.00 1	99.03 428	96.57 227	99.99 107	100.00 1	94.75 370	97.35 456

balanced_ft_v1		98.70 213	98.61 201	98.94 275	99.67 195	96.90 367	99.91 349	99.30 274	96.73 281	99.96 152	99.97 264	92.18 337	99.93 200	99.86 128	99.95 128	100.00 1

ADS-MVSNet		98.70 213	98.51 222	99.28 249	99.51 275	98.39 273	99.24 455	99.44 125	95.52 366	99.96 152	99.70 348	97.57 188	99.58 299	97.11 365	98.54 219	99.88 203

baseline		98.69 215	98.45 228	99.41 204	99.52 268	98.67 246	100.00 1	99.17 385	97.03 241	99.13 301	100.00 1	93.17 313	99.74 278	99.70 173	98.34 246	99.81 246

PCF-MVS	98.23 3	98.69 215	98.37 246	99.62 163	99.78 167	99.02 212	99.23 462	99.06 437	96.43 320	98.08 387	100.00 1	94.72 270	99.95 183	98.16 323	99.91 147	99.90 182
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
E4		98.68 217	98.46 227	99.33 231	99.51 275	98.27 293	99.96 318	99.21 351	96.66 294	99.68 249	100.00 1	93.38 306	99.91 208	99.49 235	98.27 262	99.81 246

casdiffmvs		98.65 218	98.38 244	99.46 190	99.52 268	98.74 240	100.00 1	99.15 393	96.91 254	99.05 311	100.00 1	92.75 325	99.83 247	99.70 173	98.38 235	99.81 246
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
hybridcas		98.64 219	98.41 233	99.33 231	99.54 250	98.41 269	100.00 1	99.18 375	96.78 268	99.68 249	100.00 1	92.58 331	99.75 277	99.57 219	98.38 235	99.82 230

E6new		98.64 219	98.41 233	99.30 243	99.46 304	98.19 302	99.79 376	99.21 351	96.62 302	99.68 249	100.00 1	93.24 311	99.91 208	99.47 238	98.26 264	99.81 246

E6		98.64 219	98.41 233	99.30 243	99.46 304	98.19 302	99.79 376	99.21 351	96.62 302	99.68 249	100.00 1	93.24 311	99.91 208	99.47 238	98.26 264	99.81 246

casdiffmvs_mvg		98.64 219	98.39 242	99.40 209	99.50 284	98.60 252	100.00 1	99.22 332	96.85 259	99.10 304	100.00 1	92.75 325	99.78 265	99.71 169	98.35 242	99.81 246
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		98.64 219	98.58 208	98.81 287	99.42 318	97.12 362	99.69 404	99.37 229	93.63 423	99.94 190	99.67 356	98.96 121	99.47 328	98.62 303	97.95 293	99.83 224

BH-untuned		98.64 219	98.65 194	98.60 298	99.59 231	96.17 383	100.00 1	99.28 291	96.67 293	98.41 367	100.00 1	94.52 276	99.83 247	99.41 247	100.00 1	99.81 246

E5new		98.63 225	98.41 233	99.31 239	99.51 275	98.21 299	99.79 376	99.21 351	96.62 302	99.67 255	100.00 1	93.15 315	99.91 208	99.46 241	98.26 264	99.81 246

E5		98.63 225	98.41 233	99.31 239	99.51 275	98.21 299	99.79 376	99.21 351	96.62 302	99.67 255	100.00 1	93.15 315	99.91 208	99.46 241	98.26 264	99.81 246

mamba_0408		98.63 225	98.40 239	99.34 223	99.53 254	98.52 260	99.24 455	99.16 388	96.43 320	98.95 317	99.98 251	94.47 277	99.76 272	99.21 267	98.62 214	99.75 293

test_cas_vis1_n_1920		98.63 225	98.25 256	99.77 136	99.69 182	99.32 177	100.00 1	99.31 268	98.84 68	99.96 152	100.00 1	87.42 420	99.99 107	99.14 269	99.86 159	100.00 1

KinetiMVS		98.61 229	98.26 255	99.65 159	99.46 304	99.24 189	99.96 318	99.44 125	97.54 185	99.99 129	99.99 243	90.83 359	99.95 183	97.18 363	99.92 141	99.75 293

reproduce_monomvs		98.61 229	98.54 214	98.82 284	99.97 98	99.28 182	100.00 1	99.33 256	98.51 97	97.87 401	99.24 412	99.98 3	99.45 334	99.02 278	92.93 389	97.74 387

test_fmvsmconf0.01_n		98.60 231	98.24 259	99.67 154	96.90 476	99.21 193	99.99 267	99.04 442	98.80 77	99.57 263	99.96 282	90.12 378	99.91 208	99.89 122	99.89 150	99.90 182

SSM_04072		98.59 232	98.40 239	99.15 259	99.53 254	98.52 260	99.24 455	99.16 388	96.43 320	98.95 317	99.98 251	94.47 277	99.19 353	99.21 267	98.62 214	99.75 293

tpmvs		98.59 232	98.38 244	99.23 255	99.69 182	97.90 326	99.31 449	99.47 85	94.52 397	99.68 249	99.28 409	97.64 185	99.89 221	97.71 344	98.17 276	99.89 190

Effi-MVS+		98.58 234	98.24 259	99.61 165	99.60 227	99.26 185	97.85 513	99.10 418	96.22 341	99.97 145	99.89 308	93.75 298	99.77 267	99.43 245	98.34 246	99.81 246

MVSTER		98.58 234	98.52 217	98.77 290	99.65 207	99.68 124	100.00 1	99.29 283	95.63 360	98.65 342	99.80 334	99.78 9	98.88 381	98.59 305	95.31 349	97.73 399

dtuplus		98.57 236	98.32 251	99.30 243	99.44 314	98.35 283	100.00 1	99.14 400	96.36 329	98.97 316	100.00 1	93.04 319	99.77 267	99.55 222	98.39 231	99.79 284

viewmacassd2359aftdt		98.57 236	98.31 252	99.33 231	99.49 288	98.31 289	99.89 355	99.21 351	96.87 258	99.10 304	100.00 1	92.48 334	99.88 229	99.50 233	98.28 259	99.81 246

viewmambaseed2359dif		98.57 236	98.34 250	99.28 249	99.46 304	98.23 296	100.00 1	99.16 388	96.26 337	99.11 303	100.00 1	93.12 318	99.79 259	99.61 209	98.33 249	99.80 278

CVMVSNet		98.56 239	98.47 225	98.82 284	99.11 353	97.67 338	99.74 391	99.47 85	97.57 183	99.06 310	100.00 1	95.72 242	98.97 369	98.21 322	97.33 319	99.83 224

kuosan		98.55 240	98.53 216	98.62 296	99.66 205	96.16 384	100.00 1	99.44 125	93.93 416	99.81 230	99.98 251	97.58 186	99.81 254	98.08 325	98.28 259	99.89 190

MonoMVSNet		98.55 240	98.64 196	98.26 326	98.21 427	95.76 391	99.94 335	99.16 388	96.23 338	99.47 272	99.24 412	96.75 222	99.22 350	99.61 209	99.17 197	99.81 246

AllTest		98.55 240	98.40 239	98.99 271	99.93 113	97.35 351	100.00 1	99.40 206	97.08 236	99.09 306	99.98 251	93.37 307	99.95 183	96.94 369	99.84 164	99.68 312

DeepPCF-MVS	98.03 4	98.54 243	99.72 22	94.98 448	99.99 53	84.94 492	100.00 1	99.42 153	99.98 1	100.00 1	100.00 1	98.11 163	100.00 1	100.00 1	100.00 1	100.00 1

EPNet_dtu		98.53 244	98.23 263	99.43 200	99.92 116	99.01 214	99.96 318	99.47 85	98.80 77	99.96 152	99.96 282	98.56 149	99.30 346	87.78 483	99.68 178	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
myMVS_eth3d		98.52 245	98.51 222	98.53 302	99.50 284	97.98 319	100.00 1	99.57 74	96.23 338	98.07 388	100.00 1	99.09 100	97.81 471	96.17 391	97.96 291	99.82 230

Vis-MVSNet		98.52 245	98.25 256	99.34 223	99.68 187	98.55 255	99.68 406	99.41 202	97.34 211	99.94 190	100.00 1	90.38 372	99.70 288	99.03 277	98.84 207	99.76 292
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Effi-MVS+-dtu		98.51 247	98.86 162	97.47 377	99.77 169	94.21 437	100.00 1	98.94 456	97.61 177	99.91 200	98.75 449	95.89 237	99.51 321	99.36 249	99.48 191	98.68 342

SDMVSNet		98.49 248	98.08 272	99.73 143	99.82 138	99.53 145	99.99 267	99.45 111	97.62 173	99.38 284	99.86 313	90.06 381	99.88 229	99.92 117	96.61 334	99.79 284

BH-RMVSNet		98.46 249	98.08 272	99.59 169	99.61 224	99.19 195	100.00 1	99.28 291	97.06 238	98.95 317	100.00 1	88.99 400	99.82 250	98.83 289	100.00 1	99.77 290

testing3		98.44 250	98.37 246	98.65 294	99.51 275	98.32 287	100.00 1	99.62 72	96.43 320	97.93 397	99.99 243	99.11 98	97.81 471	94.88 419	97.80 305	99.82 230

ECVR-MVS		98.43 251	98.14 266	99.32 237	99.89 122	98.21 299	99.46 431	100.00 1	98.38 105	99.47 272	100.00 1	87.91 413	99.80 258	99.35 253	98.78 209	99.94 154

cascas		98.43 251	98.07 274	99.50 183	99.65 207	99.02 212	100.00 1	99.22 332	94.21 407	99.72 245	99.98 251	92.03 340	99.93 200	99.68 183	98.12 282	99.54 322

test1111		98.42 253	98.12 267	99.29 246	99.88 124	98.15 305	99.46 431	100.00 1	98.36 109	99.42 276	100.00 1	87.91 413	99.79 259	99.31 258	98.78 209	99.94 154

ab-mvs		98.42 253	98.02 278	99.61 165	99.71 177	99.00 217	99.10 479	99.64 70	96.70 289	99.04 313	99.81 328	90.64 362	99.98 141	99.64 197	97.93 294	99.84 221

UGNet		98.41 255	98.11 268	99.31 239	99.54 250	98.55 255	99.18 465	100.00 1	98.64 91	99.79 232	99.04 425	87.61 418	100.00 1	99.30 259	99.89 150	99.40 330
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+		98.40 256	98.02 278	99.55 178	99.63 215	99.06 207	100.00 1	99.15 393	95.07 378	99.42 276	99.95 290	93.26 310	99.73 282	97.44 354	98.24 268	99.87 214

Fast-Effi-MVS+-dtu		98.38 257	98.56 212	97.82 367	99.58 236	94.44 430	100.00 1	99.16 388	96.75 274	99.51 266	99.63 369	95.03 260	99.60 293	97.71 344	99.67 180	99.42 329

IMVS_0403		98.37 258	98.39 242	98.29 321	99.38 329	95.36 396	99.97 310	99.18 375	96.72 283	99.68 249	100.00 1	94.61 273	99.77 267	97.84 337	98.15 278	99.74 300

test_fmvs1		98.37 258	98.04 276	99.34 223	99.84 131	98.07 312	100.00 1	99.00 449	98.85 66	100.00 1	100.00 1	85.11 441	99.96 170	99.69 182	99.88 153	100.00 1

IMVS_0407		98.36 260	98.42 231	98.19 333	99.38 329	95.36 396	99.73 396	99.18 375	96.72 283	99.58 261	100.00 1	95.17 256	99.47 328	97.84 337	98.15 278	99.74 300

miper_enhance_ethall		98.33 261	98.27 254	98.51 303	99.66 205	99.04 209	100.00 1	99.22 332	97.53 188	98.51 360	99.38 403	99.49 46	98.75 391	98.02 329	92.61 392	97.76 349

casdiffseed414692147		98.31 262	97.94 281	99.40 209	99.46 304	98.67 246	99.91 349	99.17 385	96.33 333	98.66 341	99.97 264	90.47 370	99.71 286	99.36 249	98.16 277	99.81 246

icg_test_0407_2		98.30 263	98.45 228	97.85 366	99.38 329	95.36 396	99.99 267	99.18 375	96.72 283	99.58 261	100.00 1	95.17 256	98.45 424	97.84 337	98.15 278	99.74 300

SCA		98.30 263	97.98 280	99.23 255	99.41 320	98.25 295	99.99 267	99.45 111	96.91 254	99.76 237	99.58 379	89.65 390	99.54 313	98.31 316	98.79 208	99.91 171

XVG-OURS		98.30 263	98.36 248	98.13 341	99.58 236	95.91 387	100.00 1	99.36 235	98.69 86	99.23 294	100.00 1	91.20 348	99.92 206	99.34 255	97.82 303	98.56 345

dongtai		98.29 266	98.25 256	98.42 311	99.58 236	95.86 389	100.00 1	99.44 125	93.46 429	99.69 248	99.97 264	97.53 191	99.51 321	96.28 390	98.27 262	99.89 190

COLMAP_ROB	97.10 7	98.29 266	98.17 265	98.65 294	99.94 111	97.39 348	99.30 450	99.40 206	95.64 359	97.75 407	100.00 1	92.69 329	99.95 183	98.89 284	99.92 141	98.62 344
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ADS-MVSNet2		98.28 268	98.51 222	97.62 373	99.51 275	95.03 405	99.24 455	99.41 202	95.52 366	99.96 152	99.70 348	97.57 188	97.94 468	97.11 365	98.54 219	99.88 203

PRO-TEST		98.27 269	98.24 259	98.37 315	99.67 195	95.43 395	100.00 1	98.99 453	96.55 307	99.95 183	99.98 251	89.26 396	99.87 231	99.81 142	99.92 141	99.81 246

XVG-OURS-SEG-HR		98.27 269	98.31 252	98.14 338	99.59 231	95.92 386	100.00 1	99.36 235	98.48 98	99.21 295	100.00 1	89.27 395	99.94 196	99.76 154	99.17 197	98.56 345

tpm		98.24 271	98.22 264	98.32 320	99.13 351	95.79 390	99.53 425	99.12 413	95.20 377	99.96 152	99.36 405	97.58 186	99.28 348	97.41 356	96.67 332	99.88 203

VortexMVS		98.23 272	98.11 268	98.59 299	99.56 246	99.37 173	99.95 327	99.03 445	96.47 318	98.69 337	99.55 385	95.91 236	98.66 396	99.01 279	94.80 369	97.73 399

cl22		98.23 272	98.11 268	98.58 301	99.82 138	99.01 214	100.00 1	99.28 291	96.92 253	98.33 374	99.21 415	98.09 165	98.97 369	98.72 294	92.61 392	97.76 349

WBMVS		98.19 274	98.10 271	98.47 305	99.63 215	99.03 210	100.00 1	99.32 259	95.46 371	98.39 369	99.40 402	99.69 17	98.61 405	98.64 299	92.39 397	97.76 349

TR-MVS		98.14 275	97.74 291	99.33 231	99.59 231	98.28 291	99.27 451	99.21 351	96.42 324	99.15 300	99.94 296	88.87 403	99.79 259	98.88 285	98.29 256	99.93 165

Elysia		98.12 276	97.72 294	99.34 223	99.30 339	98.96 222	99.95 327	99.28 291	96.64 297	99.75 238	99.99 243	88.71 405	99.81 254	95.99 393	99.84 164	99.26 331

StellarMVS		98.12 276	97.72 294	99.34 223	99.30 339	98.96 222	99.95 327	99.28 291	96.64 297	99.75 238	99.99 243	88.71 405	99.81 254	95.99 393	99.84 164	99.26 331

test0.0.03 1		98.12 276	98.03 277	98.39 313	99.11 353	98.07 312	100.00 1	99.93 35	96.70 289	96.91 432	99.95 290	99.31 76	98.19 445	91.93 451	98.44 225	98.91 339

GeoE		98.06 279	97.65 298	99.29 246	99.47 296	98.41 269	100.00 1	99.19 365	94.85 383	98.88 324	100.00 1	91.21 347	99.59 295	97.02 367	98.19 273	99.88 203

tpm cat1		98.05 280	97.76 290	98.92 277	99.50 284	97.10 364	99.77 386	99.30 274	90.20 465	99.72 245	98.71 450	97.71 181	99.86 234	96.75 381	98.20 272	99.81 246

PS-MVSNAJss		98.03 281	98.06 275	97.94 360	97.63 455	97.33 354	99.89 355	99.23 327	96.27 336	98.03 391	99.59 377	98.75 140	98.78 386	98.52 307	94.61 373	97.70 415

CR-MVSNet		98.02 282	97.71 296	98.93 276	99.31 336	98.86 229	99.13 475	99.00 449	96.53 310	99.96 152	98.98 432	96.94 215	98.10 457	91.18 457	98.40 229	99.84 221

viewdifsd2359ckpt11		97.98 283	97.89 283	98.26 326	99.47 296	94.98 407	99.99 267	99.22 332	96.74 277	99.24 292	100.00 1	90.14 375	99.90 219	99.49 235	96.73 330	99.90 182

viewmsd2359difaftdt		97.98 283	97.89 283	98.27 323	99.47 296	94.99 406	99.99 267	99.22 332	96.74 277	99.24 292	100.00 1	90.14 375	99.90 219	99.49 235	96.73 330	99.90 182

EI-MVSNet		97.98 283	97.93 282	98.16 337	99.11 353	97.84 332	99.74 391	99.29 283	94.39 402	98.65 342	100.00 1	97.21 203	98.88 381	97.62 350	95.31 349	97.75 360

FIs		97.95 286	97.73 293	98.62 296	98.53 406	99.24 189	100.00 1	99.43 134	96.74 277	97.87 401	99.82 325	95.27 250	98.89 378	98.78 290	93.07 386	97.74 387

SD_0403		97.92 287	98.43 230	96.39 424	99.68 187	89.74 478	99.92 343	99.34 253	96.75 274	99.39 283	99.93 301	93.54 304	99.51 321	99.11 273	98.21 270	99.92 167

IMVS_0404		97.87 288	97.89 283	97.81 368	99.38 329	95.36 396	99.84 364	99.18 375	96.72 283	98.41 367	100.00 1	91.43 345	98.32 432	97.84 337	98.15 278	99.74 300

Anonymous202405211		97.87 288	97.53 300	98.90 278	99.81 144	96.70 374	99.35 444	99.46 103	92.98 440	98.83 331	99.99 243	90.63 363	100.00 1	99.70 173	97.03 323	100.00 1

dtuonly		97.85 290	97.46 302	99.02 269	98.44 408	97.89 328	99.99 267	97.62 502	96.53 310	99.49 268	99.96 282	94.01 292	99.58 299	92.75 444	98.32 252	99.59 319

FC-MVSNet-test		97.84 291	97.63 299	98.45 307	98.30 418	99.05 208	100.00 1	99.43 134	96.63 301	97.61 413	99.82 325	95.19 255	98.57 414	98.64 299	93.05 387	97.73 399

Patchmatch-test		97.83 292	97.42 304	99.06 263	99.08 357	97.66 339	98.66 498	99.21 351	93.65 422	98.25 382	99.58 379	99.47 51	99.57 301	90.25 467	98.59 217	99.95 149

sd_testset		97.81 293	97.48 301	98.79 288	99.82 138	96.80 371	99.32 446	99.45 111	97.62 173	99.38 284	99.86 313	85.56 439	99.77 267	99.72 165	96.61 334	99.79 284

miper_ehance_all_eth		97.81 293	97.66 297	98.23 329	99.49 288	98.37 277	99.99 267	99.11 415	94.78 385	98.25 382	99.21 415	98.18 161	98.57 414	97.35 360	92.61 392	97.76 349

test_vis1_n_1920		97.77 295	97.24 316	99.34 223	99.79 162	98.04 316	100.00 1	99.25 316	98.88 61	100.00 1	100.00 1	77.52 474	100.00 1	99.88 124	99.85 162	100.00 1

HQP-MVS		97.73 296	97.85 287	97.39 379	99.07 358	94.82 411	100.00 1	99.40 206	99.04 20	99.17 296	99.97 264	88.61 408	99.57 301	99.79 144	95.58 339	97.77 347

GA-MVS		97.72 297	97.27 314	99.06 263	99.24 346	97.93 325	100.00 1	99.24 322	95.80 356	98.99 315	99.64 365	89.77 385	99.36 341	95.12 416	97.62 317	99.89 190

HQP_MVS		97.71 298	97.82 289	97.37 380	99.00 372	94.80 414	100.00 1	99.40 206	99.00 32	99.08 308	99.97 264	88.58 410	99.55 310	99.79 144	95.57 343	97.76 349

nrg030		97.64 299	97.27 314	98.75 291	98.34 412	99.53 145	100.00 1	99.22 332	96.21 342	98.27 380	99.95 290	94.40 279	98.98 367	99.23 264	89.78 435	97.75 360

TAPA-MVS	96.40 10	97.64 299	97.37 308	98.45 307	99.94 111	95.70 392	100.00 1	99.40 206	97.65 168	99.53 264	100.00 1	99.31 76	99.66 290	80.48 505	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CLD-MVS		97.64 299	97.74 291	97.36 381	99.01 367	94.76 419	100.00 1	99.34 253	99.30 4	99.00 314	99.97 264	87.49 419	99.57 301	99.96 106	95.58 339	97.75 360
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
D2MVS		97.63 302	97.83 288	97.05 394	98.83 394	94.60 424	100.00 1	99.82 45	96.89 257	98.28 378	99.03 428	94.05 287	99.47 328	98.58 306	94.97 367	97.09 462

0.3-1-1-0.015		97.60 303	97.19 319	98.83 283	99.13 351	96.55 379	100.00 1	99.40 206	94.19 409	99.83 215	99.81 328	99.18 92	99.97 150	99.70 173	83.50 484	99.98 127

0.4-1-1-0.2		97.60 303	97.18 320	98.86 281	99.05 364	96.62 377	100.00 1	99.40 206	94.24 404	99.82 224	99.81 328	99.09 100	99.97 150	99.70 173	83.50 484	99.98 127

c3_l		97.58 305	97.42 304	98.06 348	99.48 291	98.16 304	99.96 318	99.10 418	94.54 396	98.13 386	99.20 417	97.87 173	98.25 440	97.28 361	91.20 420	97.75 360

0.4-1-1-0.1		97.56 306	97.15 323	98.79 288	99.01 367	96.44 382	100.00 1	99.40 206	94.11 412	99.81 230	99.81 328	99.09 100	99.97 150	99.65 196	83.48 486	99.98 127

IterMVS-LS		97.56 306	97.44 303	97.92 363	99.38 329	97.90 326	99.89 355	99.10 418	94.41 401	98.32 375	99.54 388	97.21 203	98.11 453	97.50 352	91.62 412	97.75 360
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test_djsdf		97.55 308	97.38 307	98.07 344	97.50 463	97.99 318	100.00 1	99.13 407	95.46 371	98.47 363	99.85 318	92.01 341	98.59 410	98.63 301	95.36 347	97.62 438

dmvs_re		97.54 309	97.88 286	96.54 421	99.55 247	90.35 473	99.86 361	99.46 103	97.00 243	99.41 281	100.00 1	90.78 360	99.30 346	99.60 211	95.24 354	99.96 143

cl____		97.54 309	97.32 310	98.18 334	99.47 296	98.14 307	100.00 1	99.10 418	94.16 411	97.60 414	99.63 369	97.52 192	98.65 398	96.47 383	91.97 405	97.76 349

IB-MVS	96.24 12	97.54 309	96.95 326	99.33 231	99.67 195	98.10 310	100.00 1	99.47 85	97.42 203	99.26 291	99.69 351	98.83 135	99.89 221	99.43 245	78.77 505	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		97.52 312	97.35 309	98.05 352	99.46 304	98.11 308	100.00 1	99.10 418	94.21 407	97.62 412	99.63 369	97.65 184	98.29 437	96.47 383	91.98 404	97.76 349

eth_miper_zixun_eth		97.47 313	97.28 312	98.06 348	99.41 320	97.94 324	99.62 414	99.08 424	94.46 400	98.19 385	99.56 384	96.91 217	98.50 419	96.78 378	91.49 415	97.74 387

test_fmvs1_n		97.43 314	96.86 329	99.15 259	99.68 187	97.48 345	99.99 267	98.98 454	98.82 72	100.00 1	100.00 1	74.85 483	99.96 170	99.67 187	99.70 177	100.00 1

LFMVS		97.42 315	96.62 338	99.81 117	99.80 157	99.50 152	99.16 471	99.56 76	94.48 399	100.00 1	100.00 1	79.35 468	100.00 1	99.89 122	97.37 318	99.94 154

miper_lstm_enhance		97.40 316	97.28 312	97.75 370	99.48 291	97.52 343	100.00 1	99.07 429	94.08 413	98.01 394	99.61 375	97.38 200	97.98 466	96.44 386	91.47 417	97.76 349

RPSCF		97.37 317	98.24 259	94.76 451	99.80 157	84.57 493	99.99 267	99.05 439	94.95 381	99.82 224	100.00 1	94.03 289	100.00 1	98.15 324	98.38 235	99.70 310

ACMM	97.17 6	97.37 317	97.40 306	97.29 386	99.01 367	94.64 422	100.00 1	99.25 316	98.07 131	98.44 366	99.98 251	87.38 421	99.55 310	99.25 261	95.19 357	97.69 420
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
usedtu_dtu_shiyan1		97.34 319	96.97 324	98.43 309	97.82 445	98.91 226	100.00 1	99.29 283	94.70 389	98.46 364	98.89 441	93.95 294	98.64 400	95.86 397	93.75 377	97.74 387

FE-MVSNET3		97.34 319	96.97 324	98.43 309	97.82 445	98.91 226	100.00 1	99.29 283	94.70 389	98.46 364	98.89 441	93.95 294	98.64 400	95.88 395	93.75 377	97.74 387

LPG-MVS_test		97.31 321	97.32 310	97.28 387	98.85 392	94.60 424	100.00 1	99.37 229	97.35 208	98.85 327	99.98 251	86.66 427	99.56 305	99.55 222	95.26 351	97.70 415

FMVSNet3		97.30 322	96.95 326	98.37 315	99.65 207	99.25 187	99.71 400	99.28 291	94.23 405	98.53 356	98.91 439	93.30 309	98.11 453	95.31 412	93.60 380	97.73 399

UniMVSNet (Re)		97.29 323	96.85 330	98.59 299	98.49 407	99.13 201	100.00 1	99.42 153	96.52 314	98.24 384	98.90 440	94.93 262	98.89 378	97.54 351	87.61 456	97.75 360

OPM-MVS		97.21 324	97.18 320	97.32 384	98.08 434	94.66 420	100.00 1	99.28 291	98.65 90	98.92 321	99.98 251	86.03 435	99.56 305	98.28 320	95.41 345	97.72 406
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMP	97.00 8	97.19 325	97.16 322	97.27 389	98.97 378	94.58 427	100.00 1	99.32 259	97.97 139	97.45 419	99.98 251	85.79 437	99.56 305	99.70 173	95.24 354	97.67 426
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
pmmvs4		97.17 326	96.80 331	98.27 323	97.68 454	98.64 250	100.00 1	99.18 375	94.22 406	98.55 350	99.71 345	93.67 299	98.47 422	95.66 404	92.57 395	97.71 414

anonymousdsp		97.16 327	96.88 328	98.00 356	97.08 475	98.06 314	99.81 370	99.15 393	94.58 394	97.84 403	99.62 373	90.49 365	98.60 408	97.98 330	95.32 348	97.33 457

UniMVSNet_NR-MVSNet		97.16 327	96.80 331	98.22 330	98.38 411	98.41 269	100.00 1	99.45 111	96.14 344	97.76 404	99.64 365	95.05 259	98.50 419	97.98 330	86.84 465	97.75 360

XXY-MVS		97.14 329	96.63 337	98.67 293	98.65 399	98.92 225	99.54 424	99.29 283	95.57 363	97.63 410	99.83 321	87.79 417	99.35 343	98.39 312	92.95 388	97.75 360

WR-MVS		97.09 330	96.64 336	98.46 306	98.43 409	99.09 203	99.97 310	99.33 256	95.62 361	97.76 404	99.67 356	91.17 349	98.56 416	98.49 308	89.28 442	97.74 387

JIA-IIPM		97.09 330	96.34 352	99.36 219	98.88 386	98.59 253	99.81 370	99.43 134	84.81 493	99.96 152	90.34 522	98.55 150	99.52 319	97.00 368	98.28 259	99.98 127

jajsoiax		97.07 332	96.79 333	97.89 364	97.28 473	97.12 362	99.95 327	99.19 365	96.55 307	97.31 422	99.69 351	87.35 423	98.91 375	98.70 295	95.12 362	97.66 427

MIMVSNet		97.06 333	96.73 334	98.05 352	99.38 329	96.64 376	98.47 504	99.35 246	93.41 430	99.48 269	98.53 463	89.66 389	97.70 477	94.16 430	98.11 283	99.80 278

X-MVStestdata		97.04 334	96.06 363	99.98 28	100.00 1	99.94 47	100.00 1	99.75 57	98.67 88	100.00 1	66.97 551	99.16 94	100.00 1	100.00 1	100.00 1	100.00 1

h-mvs33		97.03 335	96.53 341	98.51 303	99.79 162	95.90 388	99.45 433	99.45 111	98.21 117	100.00 1	99.78 338	97.49 193	99.99 107	99.72 165	74.92 508	99.65 317

VPA-MVSNet		97.03 335	96.43 347	98.82 284	98.64 400	99.32 177	99.38 441	99.47 85	96.73 281	98.91 323	98.94 437	87.00 425	99.40 339	99.23 264	89.59 436	97.76 349

WB-MVSnew		97.02 337	97.24 316	96.37 426	99.44 314	97.36 350	100.00 1	99.43 134	96.12 345	99.35 286	99.89 308	93.60 302	98.42 426	88.91 481	98.39 231	93.33 513

mvs_tets		97.00 338	96.69 335	97.94 360	97.41 471	97.27 356	99.60 416	99.18 375	96.51 315	97.35 421	99.69 351	86.53 429	98.91 375	98.84 287	95.09 363	97.65 432

gg-mvs-nofinetune		96.95 339	96.10 361	99.50 183	99.41 320	99.36 175	99.07 484	99.52 78	83.69 496	99.96 152	83.60 536	100.00 1	99.20 352	99.68 183	99.99 107	99.96 143

Anonymous20240529		96.93 340	96.22 357	99.05 265	99.79 162	97.30 355	99.16 471	99.47 85	88.51 471	98.69 337	100.00 1	83.50 452	100.00 1	99.83 135	97.02 324	99.83 224

DU-MVS		96.93 340	96.49 344	98.22 330	98.31 416	98.41 269	100.00 1	99.37 229	96.41 325	97.76 404	99.65 361	92.14 338	98.50 419	97.98 330	86.84 465	97.75 360

Patchmtry		96.81 342	96.37 350	98.14 338	99.31 336	98.55 255	98.91 489	99.00 449	90.45 461	97.92 398	98.98 432	96.94 215	98.12 451	94.27 427	91.53 414	97.75 360

hse-mvs2		96.79 343	96.38 349	98.04 354	99.68 187	95.54 394	99.81 370	99.42 153	98.21 117	100.00 1	99.80 334	97.49 193	99.46 333	99.72 165	73.27 511	99.12 336

ACMH	96.25 11	96.77 344	96.62 338	97.21 390	98.96 379	94.43 431	99.64 409	99.33 256	97.43 202	96.55 441	99.97 264	83.52 451	99.54 313	99.07 276	95.13 361	97.66 427
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IterMVS		96.76 345	96.46 346	97.63 371	99.41 320	96.89 368	99.99 267	99.13 407	94.74 388	97.59 416	99.66 358	89.63 392	98.28 438	95.71 400	92.31 399	97.72 406
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CP-MVSNet		96.73 346	96.25 355	98.18 334	98.21 427	98.67 246	99.77 386	99.32 259	95.06 379	97.20 426	99.65 361	90.10 379	98.19 445	98.06 328	88.90 446	97.66 427

WR-MVS_H		96.73 346	96.32 354	97.95 359	98.26 422	97.88 329	99.72 399	99.43 134	95.06 379	96.99 429	98.68 452	93.02 321	98.53 417	97.43 355	88.33 451	97.43 452

IterMVS-SCA-FT		96.72 348	96.42 348	97.62 373	99.40 325	96.83 370	99.99 267	99.14 400	94.65 393	97.55 417	99.72 343	89.65 390	98.31 433	95.62 406	92.05 402	97.73 399

v2v482		96.70 349	96.18 358	98.27 323	98.04 435	98.39 273	100.00 1	99.13 407	94.19 409	98.58 348	99.08 421	90.48 366	98.67 395	95.69 401	90.44 429	97.75 360

test_vis1_n		96.69 350	95.81 374	99.32 237	99.14 350	97.98 319	99.97 310	98.98 454	98.45 100	100.00 1	100.00 1	66.44 500	99.99 107	99.78 150	99.57 190	100.00 1

V42		96.65 351	96.16 360	98.11 343	98.17 431	98.23 296	99.99 267	99.09 423	93.97 414	98.74 336	99.05 424	91.09 350	98.82 384	95.46 410	89.90 433	97.27 458

EU-MVSNet		96.63 352	96.53 341	96.94 401	97.59 459	96.87 369	99.76 388	99.47 85	96.35 331	96.85 434	99.78 338	92.57 332	96.27 492	95.33 411	91.08 421	97.68 422

NR-MVSNet		96.63 352	96.04 364	98.38 314	98.31 416	98.98 219	99.22 464	99.35 246	95.87 350	94.43 468	99.65 361	92.73 327	98.40 427	96.78 378	88.05 452	97.75 360

XVG-ACMP-BASELINE		96.60 354	96.52 343	96.84 407	98.41 410	93.29 447	99.99 267	99.32 259	97.76 159	98.51 360	99.29 408	81.95 459	99.54 313	98.40 311	95.03 364	97.68 422

VDD-MVS		96.58 355	95.99 366	98.34 318	99.52 268	95.33 400	99.18 465	99.38 225	96.64 297	99.77 235	100.00 1	72.51 489	100.00 1	100.00 1	96.94 326	99.70 310

tt0805		96.52 356	96.23 356	97.40 378	99.30 339	93.55 442	99.32 446	99.45 111	96.75 274	97.88 400	99.99 243	79.99 466	99.59 295	97.39 358	95.98 338	99.06 338

LCM-MVSNet-Re		96.52 356	97.21 318	94.44 453	99.27 343	85.80 489	99.85 363	96.61 516	95.98 347	92.75 478	98.48 465	93.97 293	97.55 479	99.58 216	98.43 226	99.98 127

our_test_3		96.51 358	96.35 351	96.98 399	97.61 457	95.05 404	99.98 300	99.01 448	94.68 391	96.77 438	99.06 422	95.87 238	98.14 449	91.81 452	92.37 398	97.75 360

MVP-Stereo		96.51 358	96.48 345	96.60 420	95.65 493	94.25 436	98.84 491	98.16 482	95.85 354	95.23 458	99.04 425	92.54 333	99.13 355	92.98 443	99.98 118	96.43 481
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
v1144		96.51 358	95.97 368	98.13 341	97.98 440	98.04 316	99.99 267	99.08 424	93.51 427	98.62 345	98.98 432	90.98 356	98.62 404	93.79 434	90.79 424	97.74 387

ACMH+	96.20 13	96.49 361	96.33 353	97.00 397	99.06 362	93.80 440	99.81 370	99.31 268	97.32 214	95.89 454	99.97 264	82.62 456	99.54 313	98.34 315	94.63 372	97.65 432

TranMVSNet+NR-MVSNet		96.45 362	96.01 365	97.79 369	98.00 439	97.62 341	100.00 1	99.35 246	95.98 347	97.31 422	99.64 365	90.09 380	98.00 464	96.89 373	86.80 468	97.75 360

ET-MVSNet_ETH3D		96.41 363	95.48 394	99.20 257	99.81 144	99.75 109	100.00 1	99.02 446	97.30 218	78.33 517	100.00 1	97.73 180	97.94 468	99.70 173	87.41 458	99.92 167

VPNet		96.41 363	95.76 379	98.33 319	98.61 401	98.30 290	99.48 429	99.45 111	96.98 245	98.87 326	99.88 310	81.57 460	98.93 373	99.22 266	87.82 455	97.76 349

PVSNet_0	93.57 19	96.41 363	95.74 380	98.41 312	99.84 131	95.22 402	100.00 1	100.00 1	98.08 130	97.55 417	99.78 338	84.40 444	100.00 1	100.00 1	81.99 491	100.00 1

v144192		96.40 366	95.81 374	98.17 336	97.89 443	98.11 308	99.99 267	99.06 437	93.39 431	98.75 335	99.09 420	90.43 371	98.66 396	93.10 442	90.55 427	97.75 360

VDDNet		96.39 367	95.55 389	98.90 278	99.27 343	97.45 346	99.15 473	99.92 39	91.28 453	99.98 139	100.00 1	73.55 485	100.00 1	99.85 131	96.98 325	99.24 333

tfpnnormal		96.36 368	95.69 385	98.37 315	98.55 404	98.71 242	99.69 404	99.45 111	93.16 438	96.69 440	99.71 345	88.44 412	98.99 366	94.17 428	91.38 418	97.41 453

v8		96.35 369	95.73 381	98.21 332	98.11 433	98.23 296	99.94 335	99.07 429	92.66 446	98.29 377	99.00 431	91.46 343	98.77 389	94.17 428	88.83 448	97.62 438

PS-CasMVS		96.34 370	95.78 378	98.03 355	98.18 430	98.27 293	99.71 400	99.32 259	94.75 386	96.82 435	99.65 361	86.98 426	98.15 447	97.74 343	88.85 447	97.66 427

LTVRE_ROB	95.29 16	96.32 371	96.10 361	96.99 398	98.55 404	93.88 439	99.45 433	99.28 291	94.50 398	96.46 442	99.52 389	84.86 442	99.48 326	97.26 362	95.03 364	97.59 442
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		96.29 372	95.70 382	98.07 344	99.80 157	97.49 344	99.15 473	99.40 206	89.11 468	97.75 407	99.45 398	88.93 402	98.98 367	98.26 321	89.47 439	97.73 399

v148		96.29 372	95.84 373	97.63 371	97.74 450	96.53 380	100.00 1	99.07 429	93.52 426	98.01 394	99.42 400	91.22 346	98.60 408	96.37 387	87.22 463	97.75 360

AUN-MVS		96.26 374	95.67 386	98.06 348	99.68 187	95.60 393	99.82 369	99.42 153	96.78 268	99.88 208	99.80 334	94.84 265	99.47 328	97.48 353	73.29 510	99.12 336

ttmdpeth		96.24 375	95.88 371	97.32 384	97.80 447	96.61 378	99.95 327	98.77 470	97.80 154	93.42 474	99.28 409	86.42 430	99.01 363	97.63 347	91.84 407	96.33 483

FMVSNet2		96.22 376	95.60 388	98.06 348	99.53 254	98.33 285	99.45 433	99.27 306	93.71 418	98.03 391	98.84 444	84.23 446	98.10 457	93.97 432	93.40 383	97.73 399

LF4IMVS		96.19 377	96.18 358	96.23 430	98.26 422	92.09 459	100.00 1	97.89 495	97.82 152	97.94 396	99.87 311	82.71 455	99.38 340	97.41 356	93.71 379	97.20 459

v1192		96.18 378	95.49 392	98.26 326	98.01 438	98.15 305	99.99 267	99.08 424	93.36 432	98.54 351	98.97 435	89.47 393	98.89 378	91.15 458	90.82 423	97.75 360

testgi		96.18 378	95.93 369	96.93 402	98.98 376	94.20 438	100.00 1	99.07 429	97.16 227	96.06 451	99.86 313	84.08 449	97.79 474	90.38 466	97.80 305	98.81 340

Syy-MVS		96.17 380	96.57 340	95.00 446	99.50 284	87.37 486	100.00 1	99.57 74	96.23 338	98.07 388	100.00 1	92.41 335	97.81 471	85.34 490	97.96 291	99.82 230

ppachtmachnet_test		96.17 380	95.89 370	97.02 396	97.61 457	95.24 401	99.99 267	99.24 322	93.31 434	96.71 439	99.62 373	94.34 282	98.07 459	89.87 470	92.30 400	97.75 360

v1921920		96.16 382	95.50 390	98.14 338	97.88 444	97.96 322	99.99 267	99.07 429	93.33 433	98.60 346	99.24 412	89.37 394	98.71 393	91.28 455	90.74 425	97.75 360

Baseline_NR-MVSNet		96.16 382	95.70 382	97.56 376	98.28 421	96.79 372	100.00 1	97.86 496	91.93 450	97.63 410	99.47 395	92.14 338	98.35 431	97.13 364	86.83 467	97.54 445

v10		96.14 384	95.50 390	98.07 344	98.19 429	97.96 322	99.83 366	99.07 429	92.10 449	98.07 388	98.94 437	91.07 351	98.61 405	92.41 450	89.82 434	97.63 436

OurMVSNet-221017-0		96.14 384	95.98 367	96.62 419	97.49 465	93.44 444	99.92 343	98.16 482	95.86 352	97.65 409	99.95 290	85.71 438	98.78 386	94.93 418	94.18 376	97.64 435

GBi-Net		96.07 386	95.80 376	96.89 404	99.53 254	94.87 408	99.18 465	99.27 306	93.71 418	98.53 356	98.81 446	84.23 446	98.07 459	95.31 412	93.60 380	97.72 406

test1		96.07 386	95.80 376	96.89 404	99.53 254	94.87 408	99.18 465	99.27 306	93.71 418	98.53 356	98.81 446	84.23 446	98.07 459	95.31 412	93.60 380	97.72 406

v7n		96.06 388	95.42 399	97.99 358	97.58 460	97.35 351	99.86 361	99.11 415	92.81 445	97.91 399	99.49 393	90.99 355	98.92 374	92.51 447	88.49 450	97.70 415

PEN-MVS		96.01 389	95.48 394	97.58 375	97.74 450	97.26 357	99.90 351	99.29 283	94.55 395	96.79 436	99.55 385	87.38 421	97.84 470	96.92 372	87.24 462	97.65 432

v1240		95.96 390	95.25 401	98.07 344	97.91 442	97.87 331	99.96 318	99.07 429	93.24 436	98.64 344	98.96 436	88.98 401	98.61 405	89.58 475	90.92 422	97.75 360

pmmvs5		95.94 391	95.61 387	96.95 400	97.42 469	94.66 420	100.00 1	98.08 487	93.60 424	97.05 428	99.43 399	87.02 424	98.46 423	95.76 398	92.12 401	97.72 406

PatchT		95.90 392	94.95 409	98.75 291	99.03 365	98.39 273	99.08 482	99.32 259	85.52 490	99.96 152	94.99 508	97.94 167	98.05 463	80.20 506	98.47 224	99.81 246

USDC		95.90 392	95.70 382	96.50 422	98.60 402	92.56 456	100.00 1	98.30 479	97.77 157	96.92 430	99.94 296	81.25 463	99.45 334	93.54 437	94.96 368	97.49 448

blend_shiyan4		95.76 394	95.40 400	96.82 413	95.50 496	94.40 432	100.00 1	99.22 332	87.12 481	98.67 340	98.59 455	99.09 100	98.31 433	96.31 388	84.14 479	97.75 360

pm-mvs1		95.76 394	95.01 406	98.00 356	98.23 426	97.45 346	99.24 455	99.04 442	93.13 439	95.93 453	99.72 343	86.28 431	98.84 383	95.62 406	87.92 453	97.72 406

SixPastTwentyTwo		95.71 396	95.49 392	96.38 425	97.42 469	93.01 448	99.84 364	98.23 480	94.75 386	95.98 452	99.97 264	85.35 440	98.43 425	94.71 420	93.17 385	97.69 420

MS-PatchMatch		95.66 397	95.87 372	95.05 444	97.80 447	89.25 480	98.88 490	99.30 274	96.35 331	96.86 433	99.01 430	81.35 462	99.43 336	93.30 439	99.98 118	96.46 480

DTE-MVSNet		95.52 398	94.99 407	97.08 393	97.49 465	96.45 381	100.00 1	99.25 316	93.82 417	96.17 447	99.57 383	87.81 416	97.18 480	94.57 423	86.26 471	97.62 438

TinyColmap		95.50 399	95.12 405	96.64 418	98.69 398	93.00 449	99.40 439	97.75 499	96.40 326	96.14 448	99.87 311	79.47 467	99.50 324	93.62 436	94.72 371	97.40 454

K. test v3		95.46 400	95.14 404	96.40 423	97.53 462	93.40 445	99.99 267	99.23 327	95.49 369	92.70 479	99.73 342	84.26 445	98.12 451	93.94 433	93.38 384	97.68 422

SSC-MVS3.2		95.32 401	94.97 408	96.37 426	98.29 420	92.75 452	100.00 1	99.30 274	95.46 371	98.36 370	99.42 400	78.92 470	98.63 402	93.28 441	91.72 410	97.72 406

FMVSNet5		95.32 401	95.43 397	94.99 447	99.39 328	92.99 450	99.25 454	99.24 322	90.45 461	97.44 420	98.45 467	95.78 241	94.39 504	87.02 485	91.88 406	97.59 442

UniMVSNet_ETH3D		95.28 403	94.41 410	97.89 364	98.91 383	95.14 403	99.13 475	99.35 246	92.11 448	97.17 427	99.66 358	70.28 494	99.36 341	97.88 335	95.18 358	99.16 334

RPMNet		95.26 404	93.82 415	99.56 176	99.31 336	98.86 229	99.13 475	99.42 153	79.82 505	99.96 152	95.13 505	95.69 244	99.98 141	77.54 514	98.40 229	99.84 221

DSMNet-mixed		95.18 405	95.21 403	95.08 443	96.03 486	90.21 475	99.65 408	93.64 526	92.91 441	98.34 373	97.40 486	90.05 382	95.51 500	91.02 459	97.86 298	99.51 326

test_fmvs2		95.17 406	95.23 402	95.01 445	98.95 381	88.99 482	99.99 267	97.77 498	97.79 155	98.58 348	99.70 348	73.36 486	99.34 344	95.88 395	95.03 364	96.70 474

dtuonlycased		95.07 407	95.43 397	93.98 461	98.26 422	85.63 490	99.98 300	98.92 459	94.83 384	94.13 471	99.47 395	82.60 457	97.61 478	94.66 421	96.01 337	98.70 341

TransMVSNet (Re)		94.78 408	93.72 416	97.93 362	98.34 412	97.88 329	99.23 462	97.98 492	91.60 451	94.55 465	99.71 345	87.89 415	98.36 430	89.30 477	84.92 474	97.56 444

mmtdpeth		94.58 409	94.18 411	95.81 436	98.82 396	91.09 467	99.99 267	98.61 475	96.38 327	100.00 1	97.23 487	76.52 478	99.85 241	99.82 140	80.22 499	96.48 479

ArgMatch-Sym		94.50 410	94.12 413	95.63 438	98.16 432	90.84 469	100.00 1	99.00 449	97.42 203	97.22 425	99.76 341	73.91 484	99.05 359	91.22 456	90.43 430	97.01 465

FMVSNet1		94.45 411	93.63 418	96.89 404	98.87 389	94.87 408	99.18 465	99.27 306	90.95 457	97.31 422	98.81 446	72.89 488	98.07 459	92.61 445	92.81 390	97.72 406

test_0402		94.35 412	93.70 417	96.32 428	97.92 441	93.60 441	99.61 415	98.85 466	88.19 475	94.68 463	99.48 394	80.01 465	98.58 413	89.39 476	95.15 360	96.77 470

MVStest1		94.27 413	93.30 422	97.19 391	98.83 394	97.18 360	99.93 341	98.79 469	86.80 486	84.88 507	99.04 425	94.32 283	98.25 440	90.55 463	86.57 469	96.12 489

UnsupCasMVSNet_eth		94.25 414	93.89 414	95.34 441	97.63 455	92.13 458	99.73 396	99.36 235	94.88 382	92.78 476	98.63 454	82.72 454	96.53 488	94.57 423	84.73 475	97.36 455

KD-MVS_2432*1600		94.15 415	93.08 425	97.35 382	99.53 254	97.83 333	99.63 411	99.19 365	92.88 442	96.29 444	97.68 483	98.84 133	96.70 484	89.73 471	63.92 530	97.53 446

miper_refine_blended		94.15 415	93.08 425	97.35 382	99.53 254	97.83 333	99.63 411	99.19 365	92.88 442	96.29 444	97.68 483	98.84 133	96.70 484	89.73 471	63.92 530	97.53 446

MVS-HIRNet		94.12 417	92.73 434	98.29 321	99.33 335	95.95 385	99.38 441	99.19 365	74.54 514	98.26 381	86.34 530	86.07 433	99.06 358	91.60 454	99.87 158	99.85 219

new_pmnet		94.11 418	93.47 420	96.04 434	96.60 481	92.82 451	99.97 310	98.91 460	90.21 464	95.26 457	98.05 481	85.89 436	98.14 449	84.28 494	92.01 403	97.16 460

mvs5depth		93.81 419	93.00 427	96.23 430	94.25 508	93.33 446	97.43 519	98.07 488	93.47 428	94.15 470	99.58 379	77.52 474	98.97 369	93.64 435	88.92 445	96.39 482

wanda-best-256-512		93.76 420	92.74 432	96.84 407	95.22 498	94.54 428	100.00 1	99.22 332	87.22 479	98.54 351	98.56 458	90.48 366	98.22 442	95.67 402	69.73 519	97.75 360

FE-blended-shiyan7		93.76 420	92.74 432	96.84 407	95.22 498	94.54 428	100.00 1	99.22 332	87.22 479	98.54 351	98.56 458	90.48 366	98.22 442	95.67 402	69.73 519	97.75 360

ArgMatch-SfM		93.74 422	93.14 424	95.54 440	98.57 403	90.54 471	99.97 310	98.86 465	97.35 208	97.60 414	99.66 358	71.88 491	99.02 361	90.18 468	84.16 478	97.07 464

gbinet_0.2-2-1-0.02		93.73 423	92.69 435	96.84 407	94.91 506	94.62 423	100.00 1	99.28 291	87.02 485	98.53 356	98.45 467	89.72 387	98.15 447	96.65 382	69.64 523	97.74 387

blended_shiyan8		93.73 423	92.69 435	96.84 407	95.17 502	94.40 432	100.00 1	99.20 361	87.05 482	98.60 346	98.54 462	90.15 374	98.39 428	95.54 409	69.93 518	97.74 387

blended_shiyan6		93.70 425	92.67 437	96.78 417	95.17 502	94.38 435	100.00 1	99.22 332	87.03 484	98.54 351	98.56 458	90.14 375	98.22 442	95.62 406	69.73 519	97.75 360

pmmvs6		93.64 426	92.87 429	95.94 435	97.47 467	91.41 464	98.92 488	99.02 446	87.84 477	95.01 460	99.61 375	77.24 476	98.77 389	94.33 426	86.41 470	97.63 436

Patchmatch-RL test		93.49 427	93.63 418	93.05 467	91.78 517	83.41 495	98.21 507	96.95 511	91.58 452	91.05 482	97.64 485	99.40 68	95.83 496	94.11 431	81.95 492	99.91 171

Anonymous20231206		93.45 428	93.17 423	94.30 456	95.00 504	89.69 479	99.98 300	98.43 477	93.30 435	94.50 467	98.59 455	90.52 364	95.73 498	77.46 515	90.73 426	97.48 451

Anonymous20240521		93.29 429	92.76 431	94.90 450	95.64 494	91.27 465	99.97 310	98.82 467	87.04 483	94.71 462	98.19 476	83.86 450	96.80 483	84.04 495	92.56 396	96.64 475

dmvs_testset		93.27 430	95.48 394	86.65 489	98.74 397	68.42 523	99.92 343	98.91 460	96.19 343	93.28 475	100.00 1	91.06 353	91.67 519	89.64 473	91.54 413	99.86 218

test20.03		93.11 431	92.85 430	93.88 462	95.19 501	91.83 460	100.00 1	98.87 463	93.68 421	92.76 477	98.88 443	89.20 398	92.71 514	77.88 513	89.19 443	97.09 462

test_vis1_rt		93.10 432	92.93 428	93.58 464	99.63 215	85.07 491	99.99 267	93.71 525	97.49 194	90.96 483	97.10 488	60.40 505	99.95 183	99.24 263	97.90 296	95.72 495

APD_test1		93.07 433	94.14 412	89.85 479	99.18 348	72.49 513	99.76 388	98.90 462	92.86 444	96.35 443	99.94 296	75.56 481	99.91 208	86.73 486	97.98 289	97.15 461

EG-PatchMatch MVS		92.94 434	92.49 438	94.29 457	95.87 489	87.07 487	99.07 484	98.11 485	93.19 437	88.98 491	98.66 453	70.89 492	99.08 357	92.43 449	95.21 356	96.72 472

usedtu_blend_shiyan5		92.75 435	91.39 441	96.82 413	95.22 498	94.40 432	99.05 486	98.64 474	75.98 513	98.54 351	98.56 458	90.48 366	98.31 433	96.31 388	69.73 519	97.75 360

MDA-MVSNet_test_wron		92.61 436	91.09 447	97.19 391	96.71 478	97.26 357	100.00 1	99.14 400	88.61 470	67.90 533	98.32 474	89.03 399	96.57 487	90.47 465	89.59 436	97.74 387

sc_t1		92.52 437	91.34 442	96.09 432	97.80 447	89.86 477	98.61 500	99.12 413	77.73 506	96.09 449	99.79 337	68.64 496	98.94 372	96.94 369	87.31 460	99.46 328

YYNet1		92.44 438	90.92 448	97.03 395	96.20 482	97.06 365	99.99 267	99.14 400	88.21 474	67.93 532	98.43 470	88.63 407	96.28 491	90.64 460	89.08 444	97.74 387

tt0320		92.36 439	91.28 443	95.58 439	98.30 418	90.65 470	98.69 497	99.14 400	76.73 507	96.07 450	99.50 392	72.28 490	98.39 428	93.29 440	87.56 457	97.70 415

MIMVSNet1		91.96 440	91.20 444	94.23 458	94.94 505	91.69 462	99.34 445	99.22 332	88.23 472	94.18 469	98.45 467	75.52 482	93.41 512	79.37 507	91.49 415	97.60 441

TDRefinement		91.93 441	90.48 451	96.27 429	81.60 547	92.65 455	99.10 479	97.61 503	93.96 415	93.77 472	99.85 318	80.03 464	99.53 318	97.82 341	70.59 517	96.63 476

MASt3R-SfM		91.92 442	92.47 439	90.28 477	96.64 480	75.61 509	99.63 411	98.31 478	95.70 358	95.42 456	98.84 444	67.34 498	99.22 350	89.92 469	90.47 428	96.01 491

OpenMVS_ROB	88.34 20	91.89 443	91.12 445	94.19 459	95.55 495	87.63 485	99.26 453	98.03 489	86.61 488	90.65 487	96.82 490	70.14 495	98.78 386	86.54 487	96.50 336	96.15 487

N_pmnet		91.88 444	93.37 421	87.40 487	97.24 474	66.33 530	99.90 351	91.05 530	89.77 467	95.65 455	98.58 457	90.05 382	98.11 453	85.39 489	92.72 391	97.75 360

pmmvs-eth3d		91.73 445	90.67 449	94.92 449	91.63 519	92.71 454	99.90 351	98.54 476	91.19 454	88.08 495	95.50 500	79.31 469	96.13 493	90.55 463	81.32 497	95.91 493

tt0320-xc		91.69 446	90.50 450	95.26 442	98.04 435	90.12 476	98.60 501	98.70 472	76.63 509	94.66 464	99.52 389	68.57 497	97.99 465	94.61 422	85.18 473	97.66 427

MDA-MVSNet-bldmvs		91.65 447	89.94 456	96.79 416	96.72 477	96.70 374	99.42 438	98.94 456	88.89 469	66.97 535	98.37 472	81.43 461	95.91 495	89.24 478	89.46 440	97.75 360

KD-MVS_self_test		91.16 448	90.09 453	94.35 455	94.44 507	91.27 465	99.74 391	99.08 424	90.82 458	94.53 466	94.91 509	86.11 432	94.78 503	82.67 498	68.52 524	96.99 466

FE-MVSNET2		91.15 449	90.00 455	94.58 452	90.74 523	92.52 457	99.56 420	98.87 463	90.82 458	88.96 492	95.40 503	76.26 480	95.56 499	87.84 482	81.59 495	95.66 498

CL-MVSNet_self_test		91.07 450	90.35 452	93.24 465	93.27 510	89.16 481	99.55 422	99.25 316	92.34 447	95.23 458	97.05 489	88.86 404	93.59 510	80.67 504	66.95 529	96.96 467

test_method		91.04 451	91.10 446	90.85 475	98.34 412	77.63 505	100.00 1	98.93 458	76.69 508	96.25 446	98.52 464	70.44 493	97.98 466	89.02 480	91.74 408	96.92 468

CMPMVS	66.12 22	90.65 452	92.04 440	86.46 490	96.18 483	66.87 528	98.03 511	99.38 225	83.38 497	85.49 504	99.55 385	77.59 473	98.80 385	94.44 425	94.31 375	93.72 511
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs3		90.62 453	89.36 460	94.40 454	90.53 526	91.49 463	100.00 1	96.73 514	84.21 495	93.65 473	96.65 493	82.56 458	94.83 501	82.28 499	77.62 506	96.89 469

DenseAffine		90.43 454	89.28 461	93.87 463	97.71 453	86.21 488	99.13 475	98.10 486	87.86 476	90.15 488	98.43 470	60.76 504	98.65 398	84.48 493	86.90 464	96.74 471

RoMa-SfM		90.39 455	89.63 457	92.66 470	97.47 467	83.18 497	98.81 492	98.21 481	85.44 492	89.21 490	99.46 397	63.72 501	98.30 436	87.11 484	87.25 461	96.51 478

new-patchmatchnet		90.30 456	89.46 459	92.84 469	90.77 522	88.55 484	99.83 366	98.80 468	90.07 466	87.86 496	95.00 507	78.77 471	94.30 505	84.86 492	79.15 502	95.68 497

FE-MVSNET		89.50 457	88.33 463	93.00 468	88.89 530	90.24 474	99.96 318	96.86 512	88.23 472	88.46 493	95.47 501	77.03 477	93.37 513	78.54 510	81.56 496	95.39 501

UnsupCasMVSNet_bld		89.50 457	88.00 464	93.99 460	95.30 497	88.86 483	98.52 503	99.28 291	85.50 491	87.80 497	94.11 511	61.63 502	96.96 482	90.63 461	79.26 501	96.15 487

mvsany_test3		89.36 459	88.96 462	90.56 476	91.95 516	78.97 503	99.74 391	96.59 517	96.84 261	89.25 489	96.07 497	52.59 521	97.11 481	95.17 415	82.44 490	95.58 500

DKM		88.67 460	87.74 465	91.44 473	97.38 472	82.60 498	98.95 487	97.94 494	87.54 478	87.00 499	98.48 465	55.08 515	95.81 497	86.05 488	81.29 498	95.91 493

LoFTR		88.61 461	87.13 467	93.06 466	96.18 483	83.87 494	99.48 429	97.21 507	86.37 489	82.32 513	96.66 492	58.07 510	98.59 410	81.76 501	86.15 472	96.72 472

PM-MVS		88.39 462	87.41 466	91.31 474	91.73 518	82.02 501	99.79 376	96.62 515	91.06 456	90.71 486	95.73 499	48.60 524	95.96 494	90.56 462	81.91 493	95.97 492

WB-MVS		88.24 463	90.09 453	82.68 505	91.56 520	69.51 518	100.00 1	98.73 471	90.72 460	87.29 498	98.12 477	92.87 323	85.01 533	62.19 530	89.34 441	93.54 512

SSC-MVS		87.61 464	89.47 458	82.04 506	90.63 524	68.77 522	99.99 267	98.66 473	90.34 463	86.70 500	98.08 478	92.72 328	84.12 534	59.41 533	88.71 449	93.22 516

RoMa-HiRes		87.37 465	86.72 469	89.32 481	95.81 490	78.25 504	98.63 499	97.01 509	82.18 499	86.32 501	99.25 411	56.48 513	94.79 502	83.17 496	81.62 494	94.91 504

test_fmvs3		87.19 466	87.02 468	87.71 486	92.69 512	76.64 506	99.96 318	97.27 506	93.55 425	90.82 485	94.03 512	38.00 533	92.19 516	93.49 438	83.35 488	94.32 508

DKM-HiRes		87.00 467	86.38 470	88.84 483	96.71 478	79.05 502	98.73 496	97.57 505	84.56 494	84.00 509	98.23 475	52.90 520	92.48 515	84.95 491	79.77 500	95.00 502

test_f		86.87 468	86.06 471	89.28 482	91.45 521	76.37 507	99.87 360	97.11 508	91.10 455	88.46 493	93.05 514	38.31 532	96.66 486	91.77 453	83.46 487	94.82 505

MatchFormer		86.71 469	84.75 475	92.57 471	96.14 485	82.52 499	99.27 451	97.86 496	80.17 503	78.74 516	96.16 496	54.81 516	98.63 402	75.87 518	83.75 483	96.56 477

usedtu_dtu_shiyan2		85.34 470	83.22 477	91.71 472	88.10 534	83.34 496	98.75 495	97.59 504	76.21 511	91.11 481	96.80 491	58.14 509	94.30 505	75.00 520	67.24 528	97.49 448

SP-DiffGlue		85.17 471	85.16 472	85.22 492	93.54 509	69.16 520	97.83 514	95.33 520	60.61 522	86.04 502	92.86 515	61.04 503	90.90 523	89.62 474	89.57 438	95.59 499

Gipuma		84.73 472	83.50 476	88.40 485	97.50 463	82.21 500	88.87 536	99.05 439	65.81 517	85.71 503	90.49 519	53.70 518	96.31 490	78.64 509	91.74 408	86.67 524
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
testf1		84.40 473	84.79 473	83.23 503	95.71 491	58.71 539	98.79 493	97.75 499	81.58 500	84.94 505	98.07 479	45.33 527	97.73 475	77.09 516	83.85 480	93.24 514

APD_test2		84.40 473	84.79 473	83.23 503	95.71 491	58.71 539	98.79 493	97.75 499	81.58 500	84.94 505	98.07 479	45.33 527	97.73 475	77.09 516	83.85 480	93.24 514

ELoFTR		83.63 475	81.67 482	89.53 480	92.30 514	75.98 508	98.27 505	96.74 513	83.38 497	74.05 523	95.78 498	43.66 529	98.11 453	78.01 511	72.80 513	94.48 507

SP-NN		83.33 476	82.73 478	85.13 494	98.98 376	65.96 531	97.92 512	95.13 522	56.43 527	83.71 510	90.52 518	58.27 507	91.69 518	71.99 521	91.66 411	97.74 387

SP-LightGlue		82.73 477	81.92 480	85.19 493	97.73 452	68.40 524	98.05 510	94.51 524	56.95 526	82.72 511	90.14 524	58.20 508	90.97 522	71.57 522	87.38 459	96.20 486

SP-SuperGlue		82.71 478	81.92 480	85.07 495	98.02 437	67.96 526	98.10 509	95.26 521	57.79 524	82.47 512	90.37 521	57.02 511	91.04 521	70.34 524	87.92 453	96.23 485

ALIKED-NN		82.28 479	81.49 483	84.63 497	99.44 314	67.26 527	97.36 520	90.47 532	62.09 520	81.26 515	95.45 502	59.17 506	93.89 508	63.93 529	84.26 476	92.75 517

SP-MNN		81.80 480	81.08 484	83.94 500	98.26 422	64.81 534	98.20 508	93.56 527	55.15 528	77.43 518	90.43 520	56.33 514	90.69 524	70.11 525	90.27 432	96.32 484

PMatch-SfM		81.57 481	79.80 485	86.88 488	92.36 513	73.86 511	97.50 518	92.66 529	80.39 502	73.10 525	96.35 494	33.54 539	91.86 517	81.28 502	71.01 516	94.92 503

ALIKED-LG		80.86 482	79.70 486	84.33 498	98.33 415	69.33 519	97.59 517	90.14 535	65.38 518	76.03 520	94.87 510	54.78 517	93.65 509	57.59 535	82.61 489	90.01 522

testmvs		80.17 483	81.95 479	74.80 512	58.54 556	59.58 538	100.00 1	87.14 537	76.09 512	99.61 259	100.00 1	67.06 499	74.19 546	98.84 287	50.30 534	90.64 521

test_vis3_rt		79.61 484	78.19 489	83.86 501	88.68 533	69.56 517	99.81 370	82.19 541	86.78 487	68.57 531	84.51 534	25.06 549	98.26 439	89.18 479	78.94 503	83.75 530

ALIKED-MNN		79.54 485	78.11 490	83.80 502	99.29 342	66.55 529	97.70 516	90.37 534	57.60 525	74.96 522	92.30 516	53.12 519	93.57 511	58.80 534	78.89 504	91.27 519

EGC-MVSNET		79.46 486	74.04 496	95.72 437	96.00 487	92.73 453	99.09 481	99.04 442	5.08 552	16.72 553	98.71 450	73.03 487	98.74 392	82.05 500	96.64 333	95.69 496

test123		79.44 487	79.23 488	80.05 510	80.03 549	71.72 514	100.00 1	77.93 546	62.52 519	94.81 461	99.69 351	78.21 472	74.53 545	92.57 446	27.33 546	93.90 509

PMatch-Up-SfM		79.27 488	77.62 491	84.22 499	90.58 525	69.08 521	96.98 521	90.47 532	76.44 510	71.47 528	96.27 495	30.15 544	88.77 526	78.74 508	67.46 525	94.81 506

PMMVS2		79.15 489	77.28 492	84.76 496	82.34 544	72.66 512	99.70 402	95.11 523	71.68 516	84.78 508	90.87 517	32.05 542	89.99 525	75.53 519	63.45 532	91.64 518

LCM-MVSNet		79.01 490	76.93 493	85.27 491	78.28 550	68.01 525	96.57 523	98.03 489	55.10 529	82.03 514	93.27 513	31.99 543	93.95 507	82.72 497	74.37 509	93.84 510

FPMVS		77.92 491	79.45 487	73.34 516	76.87 551	46.81 544	98.24 506	99.05 439	59.89 523	73.55 524	98.34 473	36.81 534	86.55 527	80.96 503	91.35 419	86.65 525

PDCNetPlus		75.87 492	73.92 497	81.72 507	89.55 529	74.48 510	98.59 502	62.34 551	72.19 515	76.04 519	95.03 506	47.66 525	86.31 529	77.97 512	45.88 536	84.35 528

tmp_tt		75.80 493	74.26 495	80.43 508	52.91 558	53.67 541	87.42 540	97.98 492	61.80 521	67.04 534	100.00 1	76.43 479	96.40 489	96.47 383	28.26 545	91.23 520

XFeat-NN		75.54 494	76.00 494	74.19 514	93.25 511	52.63 543	95.93 525	81.98 542	46.32 535	75.32 521	90.27 523	56.80 512	85.05 532	71.26 523	72.85 512	84.87 527

XFeat-MNN		73.39 495	73.10 498	74.25 513	89.63 528	53.35 542	96.25 524	84.01 539	43.66 536	69.74 529	89.91 525	52.56 522	85.32 530	64.72 528	67.44 526	84.08 529

E-PMN		70.72 496	70.06 499	72.69 517	83.92 542	65.48 533	99.95 327	92.72 528	49.88 532	72.30 526	86.26 531	47.17 526	77.43 542	53.83 536	44.49 537	75.17 534

GLUNet-SfM		70.22 497	66.87 502	80.24 509	84.13 541	61.64 537	96.72 522	82.62 540	51.83 530	60.24 539	88.02 529	36.12 535	91.44 520	67.32 527	34.86 543	87.65 523

EMVS		69.88 498	69.09 500	72.24 518	84.70 540	65.82 532	99.96 318	87.08 538	49.82 533	71.51 527	84.74 533	49.30 523	75.32 544	50.97 537	43.71 538	75.59 533

SIFT-NN		67.52 499	68.28 501	65.25 520	96.00 487	45.92 545	93.38 528	80.01 543	43.05 537	69.06 530	85.13 532	39.13 530	85.13 531	32.15 539	76.58 507	64.70 536

MVE	68.59 21	67.22 500	64.68 506	74.84 511	74.67 554	62.32 536	95.84 526	90.87 531	50.98 531	58.72 540	81.05 545	12.20 557	78.95 539	61.06 532	56.75 533	83.24 531
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ANet_high		66.05 501	63.44 507	73.88 515	61.14 555	63.45 535	95.68 527	87.18 536	79.93 504	47.35 542	80.68 547	22.35 552	72.33 548	61.24 531	35.42 541	85.88 526

PMVS	60.66 23	65.98 502	65.05 504	68.75 519	55.06 557	38.40 556	88.19 539	96.98 510	48.30 534	44.82 545	88.52 527	12.22 556	86.49 528	67.58 526	83.79 482	81.35 532
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
SIFT-MNN		64.77 503	65.11 503	63.77 521	92.18 515	44.02 547	91.93 530	78.84 544	41.80 539	61.69 537	84.03 535	33.92 538	81.69 536	29.20 544	72.39 514	65.59 535

SIFT-NN-NCMNet		64.49 504	64.92 505	63.20 522	88.84 531	44.41 546	92.37 529	78.67 545	41.90 538	62.62 536	83.27 537	34.31 536	81.88 535	30.88 540	71.40 515	63.31 538

SIFT-NN-CMatch		60.63 505	60.17 508	62.02 523	86.89 536	43.32 549	90.70 533	71.03 547	41.60 541	61.16 538	83.16 538	33.45 540	78.31 540	30.28 541	43.26 539	64.44 537

SIFT-NCM-Cal		59.75 506	59.15 509	61.53 524	90.12 527	43.18 550	91.26 531	70.04 549	40.34 543	38.39 548	81.51 544	27.19 545	79.90 537	26.25 549	67.30 527	61.50 540

SIFT-NN-UMatch		59.27 507	58.65 510	61.13 525	83.27 543	43.66 548	91.00 532	70.69 548	41.78 540	44.38 546	82.21 542	34.17 537	79.10 538	30.07 542	50.25 535	60.64 541

SIFT-NN-PointCN		57.34 508	56.95 511	58.53 528	82.11 545	41.35 554	90.36 534	61.72 552	40.01 544	54.78 541	80.99 546	32.74 541	72.39 547	29.64 543	40.16 540	61.83 539

SIFT-ConvMatch		56.83 509	55.72 512	60.16 526	88.80 532	43.02 551	88.55 537	64.15 550	40.75 542	45.84 543	83.12 539	27.00 546	77.01 543	28.36 545	34.89 542	60.45 542

SIFT-UMatch		55.48 510	53.92 513	60.16 526	85.84 539	42.45 552	89.09 535	61.68 553	39.97 545	41.34 547	82.92 540	26.90 547	77.66 541	27.36 546	30.17 544	60.37 543

SIFT-CM-Cal		53.99 511	52.89 514	57.28 529	87.31 535	41.77 553	86.71 542	54.86 555	39.82 547	45.09 544	82.10 543	25.89 548	71.72 549	27.27 547	26.97 547	58.36 544

SIFT-UM-Cal		51.73 512	50.25 515	56.15 530	85.87 538	41.10 555	88.21 538	50.44 556	39.83 546	33.54 550	82.23 541	23.59 550	71.25 550	27.05 548	21.52 549	56.10 546

SIFT-PointCN		49.44 513	48.89 516	51.12 531	81.24 548	34.25 557	87.16 541	56.78 554	36.95 548	33.84 549	76.32 549	20.17 553	61.65 552	21.99 551	25.53 548	57.46 545

SIFT-PCN-Cal		47.97 514	47.56 517	49.20 532	81.85 546	33.99 558	86.00 543	49.11 557	36.44 549	32.13 551	77.60 548	22.63 551	62.04 551	23.11 550	19.17 550	51.55 547

SIFT-NCMNet		41.74 515	41.17 518	43.45 533	76.48 552	31.10 560	80.74 544	30.14 558	35.07 550	28.33 552	71.87 550	16.32 554	52.56 553	19.72 552	11.82 552	46.67 548

wuyk23d		28.28 516	29.73 520	23.92 534	75.89 553	32.61 559	66.50 545	12.88 559	16.09 551	14.59 554	16.59 552	12.35 555	32.36 554	39.36 538	13.36 551	6.79 549

cdsmvs_eth3d_5k		24.41 517	32.55 519	0.00 535	0.00 559	0.00 561	0.00 546	99.39 222	0.00 553	0.00 555	100.00 1	93.55 303	0.00 555	0.00 553	0.00 553	0.00 550

ab-mvs-re		8.33 518	11.11 521	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	100.00 1	0.00 558	0.00 555	0.00 553	0.00 553	0.00 550

pcd_1.5k_mvsjas		8.24 519	10.99 522	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	0.14 554	98.75 140	0.00 555	0.00 553	0.00 553	0.00 550

test_blank		0.07 520	0.09 523	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	0.79 553	0.00 558	0.00 555	0.00 553	0.00 553	0.00 550

mmdepth		0.01 521	0.02 524	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	0.14 554	0.00 558	0.00 555	0.00 553	0.00 553	0.00 550

monomultidepth		0.01 521	0.02 524	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	0.14 554	0.00 558	0.00 555	0.00 553	0.00 553	0.00 550

uanet_test		0.01 521	0.02 524	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	0.14 554	0.00 558	0.00 555	0.00 553	0.00 553	0.00 550

DCPMVS		0.01 521	0.02 524	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	0.14 554	0.00 558	0.00 555	0.00 553	0.00 553	0.00 550

sosnet-low-res		0.01 521	0.02 524	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	0.14 554	0.00 558	0.00 555	0.00 553	0.00 553	0.00 550

sosnet		0.01 521	0.02 524	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	0.14 554	0.00 558	0.00 555	0.00 553	0.00 553	0.00 550

uncertanet		0.01 521	0.02 524	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	0.14 554	0.00 558	0.00 555	0.00 553	0.00 553	0.00 550

Regformer		0.01 521	0.02 524	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	0.14 554	0.00 558	0.00 555	0.00 553	0.00 553	0.00 550

uanet		0.01 521	0.02 524	0.00 535	0.00 559	0.00 561	0.00 546	0.00 560	0.00 553	0.00 555	0.14 554	0.00 558	0.00 555	0.00 553	0.00 553	0.00 550

test-260524					100.00 1	99.98 18		99.69 67		100.00 1		99.45 53	100.00 1	100.00 1	100.00 1

aaatest				99.99 13	100.00 1	99.98 18	100.00 1	99.95 19	99.10 12	99.99 129	100.00 1		100.00 1	100.00 1	100.00 1	100.00 1

TestfortrainingZip				100.00 1	99.99 53	100.00 1	100.00 1	99.95 19	99.03 25	100.00 1	100.00 1	99.59 24	100.00 1		100.00 1	100.00 1

WAC-MVS						97.98 319								95.74 399

FOURS1					100.00 1	99.97 27	100.00 1	99.42 153	98.52 96	100.00 1

MSC_two_6792asdad				100.00 1	100.00 1	100.00 1		99.42 153					100.00 1	100.00 1	100.00 1	100.00 1

PC_three_1452									98.80 77	100.00 1	100.00 1	99.54 32	100.00 1	100.00 1	100.00 1	100.00 1

No_MVS				100.00 1	100.00 1	100.00 1		99.42 153					100.00 1	100.00 1	100.00 1	100.00 1

test_one_0601					100.00 1	99.99 6		99.42 153	98.72 85	100.00 1	100.00 1	99.60 21

eth-test2					0.00 559

eth-test					0.00 559

ZD-MVS					100.00 1	99.98 18		99.80 48	97.31 216	100.00 1	100.00 1	99.32 74	99.99 107	100.00 1	100.00 1

RE-MVS-def			99.55 62		99.99 53	99.91 64	100.00 1	99.42 153	97.62 173	100.00 1	100.00 1	98.94 124		99.99 77	100.00 1	100.00 1

IU-MVS					100.00 1	99.99 6		99.42 153	99.12 9	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 32	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_TWO								99.42 153	99.03 25	100.00 1	100.00 1	99.56 29	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_ONE					100.00 1	99.99 6		99.42 153	99.03 25	100.00 1	100.00 1	99.50 43	100.00 1

9.14			99.57 55		99.99 53		100.00 1	99.42 153	97.54 185	100.00 1	100.00 1	99.15 96	99.99 107	100.00 1	100.00 1

save fliter					99.99 53	99.93 53	100.00 1	99.42 153	98.93 49

test_0728_THIRD									98.79 80	100.00 1	100.00 1	99.61 20	100.00 1	100.00 1	100.00 1	100.00 1

test_0728_SECOND				100.00 1	99.99 53	99.99 6	100.00 1	99.42 153					100.00 1	100.00 1	100.00 1	100.00 1

test0726					100.00 1	99.99 6	100.00 1	99.42 153	99.04 20	100.00 1	100.00 1	99.53 35

GSMVS																99.91 171

test_part2					100.00 1	99.99 6				100.00 1

sam_mvs1												99.29 82				99.91 171

sam_mvs												99.33 71

ambc				88.45 484	86.84 537	70.76 516	97.79 515	98.02 491		90.91 484	95.14 504	38.69 531	98.51 418	94.97 417	84.23 477	96.09 490

MTGPA								99.42 153

test_post1							99.32 446				88.24 528	99.33 71	99.59 295	98.31 316

test_post											89.05 526	99.49 46	99.59 295

patchmatchnet-post											97.79 482	99.41 66	99.54 313

GG-mvs-BLEND				99.59 169	99.54 250	99.49 156	99.17 470	99.52 78		99.96 152	99.68 355	100.00 1	99.33 345	99.71 169	99.99 107	99.96 143

MTMP							100.00 1	99.18 375

gm-plane-assit					99.52 268	97.26 357			95.86 352		100.00 1		99.43 336	98.76 292

test9_res														100.00 1	100.00 1	100.00 1

TEST9					100.00 1	99.95 38	100.00 1	99.42 153	97.65 168	100.00 1	100.00 1	99.53 35	99.97 150

test_8					100.00 1	99.91 64	100.00 1	99.42 153	97.70 162	100.00 1	100.00 1	99.51 39	99.98 141

agg_prior2														100.00 1	100.00 1	100.00 1

agg_prior					100.00 1	99.88 85		99.42 153		100.00 1			99.97 150

TestCases				98.99 271	99.93 113	97.35 351		99.40 206	97.08 236	99.09 306	99.98 251	93.37 307	99.95 183	96.94 369	99.84 164	99.68 312

test_prior4						99.93 53	100.00 1

test_prior2							100.00 1		98.82 72	100.00 1	100.00 1	99.47 51		100.00 1	100.00 1

test_prior				99.90 87	100.00 1	99.75 109		99.73 61					99.97 150			100.00 1

旧先验2							100.00 1		98.11 129	100.00 1			100.00 1	99.67 187

新几何2							100.00 1

新几何1				99.99 13	100.00 1	99.96 30		99.81 47	97.89 146	100.00 1	100.00 1	99.20 90	100.00 1	97.91 334	100.00 1	100.00 1

旧先验1					99.99 53	99.88 85		99.82 45			100.00 1	99.27 85			100.00 1	100.00 1

无先验							100.00 1	99.80 48	97.98 137				100.00 1	99.33 256		100.00 1

原ACMM2							100.00 1

原ACMM1				99.93 78	100.00 1	99.80 102		99.66 69	98.18 120	100.00 1	100.00 1	99.43 60	100.00 1	99.50 233	100.00 1	100.00 1

test222					99.99 53	99.90 71	100.00 1	99.69 67	97.66 166	100.00 1	100.00 1	99.30 81			100.00 1	100.00 1

testdata2													100.00 1	97.36 359

segment_acmp												99.55 31

testdata				99.66 157	99.99 53	98.97 221		99.73 61	97.96 142	100.00 1	100.00 1	99.42 64	100.00 1	99.28 260	100.00 1	100.00 1

testdata1							100.00 1		98.77 84

test12				99.95 61	99.99 53	99.89 78		99.42 153		100.00 1		99.24 87	99.97 150		100.00 1	100.00 1

plane_prior7					99.00 372	94.78 418

plane_prior6					99.06 362	94.80 414						88.58 410

plane_prior5								99.40 206					99.55 310	99.79 144	95.57 343	97.76 349

plane_prior4											99.97 264

plane_prior3						94.79 417			99.03 25	99.08 308

plane_prior2							100.00 1		99.00 32

plane_prior1					99.02 366

plane_prior						94.80 414	100.00 1		99.03 25						95.58 339

n2								0.00 560

nn								0.00 560

door-mid								96.32 518

lessismore_v0				96.05 433	97.55 461	91.80 461		99.22 332		91.87 480	99.91 305	83.50 452	98.68 394	92.48 448	90.42 431	97.68 422

LGP-MVS_train				97.28 387	98.85 392	94.60 424		99.37 229	97.35 208	98.85 327	99.98 251	86.66 427	99.56 305	99.55 222	95.26 351	97.70 415

test11								99.42 153

door								96.13 519

HQP5-MVS						94.82 411

HQP-NCC					99.07 358		100.00 1		99.04 20	99.17 296

ACMP_Plane					99.07 358		100.00 1		99.04 20	99.17 296

BP-MVS														99.79 144

HQP4-MVS										99.17 296			99.57 301			97.77 347

HQP3-MVS								99.40 206							95.58 339

HQP2-MVS												88.61 408

NP-MVS					99.07 358	94.81 413					99.97 264

MDTV_nov1_ep13_2view						99.24 189	99.56 420		96.31 335	99.96 152		98.86 131		98.92 283		99.89 190

MDTV_nov1_ep13			98.94 152		99.53 254	98.36 280	99.39 440	99.46 103	96.54 309	99.99 129	99.63 369	98.92 127	99.86 234	98.30 319	98.71 213

ACMMP++_ref															94.58 374

ACMMP++															95.17 359

Test By Simon												99.10 99

ITE_SJBPF				96.84 407	98.96 379	93.49 443		98.12 484	98.12 128	98.35 372	99.97 264	84.45 443	99.56 305	95.63 405	95.25 353	97.49 448

DeepMVS_CX				89.98 478	98.90 384	71.46 515		99.18 375	97.61 177	96.92 430	99.83 321	86.07 433	99.83 247	96.02 392	97.65 315	98.65 343

High-resolution multi-view benchmark