High-res multi-view results

This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

Accuracy [%]: The fraction of the reconstruction which is closer to the ground truth than the evaluation threshold distance (*). Larger is better.
Completeness [%]: The fraction of the ground truth which is closer to the reconstruction than the evaluation threshold distance (*). Larger is better.
F₁ score [%]: The harmonic mean of accuracy and completeness, used to rank methods based on both metrics. Larger is better.
Time [s]: The runtime of the method. Smaller is better.

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.

Method	all	high-res multi-view	indoor	outdoor	botani.	boulde.	bridge	door	exhibi.	lectur.	living.	lounge	observ.	old co.	statue	terrac.

MSLP-MVS++		99.89 1	99.85 2	99.99 12	100.00 1	99.96 24	100.00 1	99.95 19	99.11 7	100.00 1	100.00 1	99.60 18	100.00 1	100.00 1	100.00 1	100.00 1

NCCC		99.86 2	99.82 3	100.00 1	100.00 1	99.99 5	100.00 1	99.71 61	99.07 10	100.00 1	100.00 1	99.59 21	100.00 1	100.00 1	100.00 1	100.00 1

CHOSEN 280x420		99.85 3	99.87 1	99.80 101	99.99 49	99.97 21	99.97 240	99.98 16	98.96 32	100.00 1	100.00 1	99.96 5	99.42 253	100.00 1	100.00 1	100.00 1

MCST-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 5	100.00 1	99.73 56	99.19 5	100.00 1	100.00 1	99.31 65	100.00 1	100.00 1	100.00 1	100.00 1

CNVR-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 5	100.00 1	99.77 48	99.07 10	100.00 1	100.00 1	99.39 58	100.00 1	100.00 1	100.00 1	100.00 1

APDe-MVS		99.84 6	99.78 7	99.99 12	100.00 1	99.98 17	100.00 1	99.44 116	99.06 12	100.00 1	100.00 1	99.56 24	99.99 94	100.00 1	100.00 1	100.00 1
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
SED-MVS		99.83 7	99.77 9	100.00 1	100.00 1	99.99 5	100.00 1	99.42 138	99.03 20	100.00 1	100.00 1	99.50 38	100.00 1	100.00 1	100.00 1	100.00 1

DVP-MVS		99.83 7	99.78 7	100.00 1	100.00 1	99.99 5	100.00 1	99.42 138	99.04 15	100.00 1	100.00 1	99.53 30	100.00 1	100.00 1	100.00 1	100.00 1
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
TSAR-MVS + MP.		99.82 9	99.77 9	99.99 12	100.00 1	99.96 24	100.00 1	99.43 122	99.05 14	100.00 1	100.00 1	99.45 46	99.99 94	100.00 1	100.00 1	100.00 1
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
HPM-MVS++		99.82 9	99.76 12	99.99 12	99.99 49	99.98 17	100.00 1	99.83 39	98.88 44	99.96 119	100.00 1	99.21 78	100.00 1	100.00 1	100.00 1	99.99 107

DVP-MVS++		99.81 11	99.75 14	100.00 1	100.00 1	99.99 5	100.00 1	99.42 138	98.79 60	100.00 1	100.00 1	99.54 27	100.00 1	100.00 1	100.00 1	100.00 1

MSP-MVS		99.81 11	99.77 9	99.94 63	100.00 1	99.86 77	100.00 1	99.42 138	98.87 47	100.00 1	100.00 1	99.65 16	99.96 137	100.00 1	100.00 1	100.00 1
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
SD-MVS		99.81 11	99.75 14	99.99 12	99.99 49	99.96 24	100.00 1	99.42 138	99.01 26	100.00 1	100.00 1	99.33 60	100.00 1	100.00 1	100.00 1	100.00 1
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
DPE-MVS		99.79 14	99.73 17	99.99 12	99.99 49	99.98 17	100.00 1	99.42 138	98.91 41	100.00 1	100.00 1	99.22 77	100.00 1	100.00 1	100.00 1	100.00 1
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
XVS		99.79 14	99.73 17	99.98 23	100.00 1	99.94 40	100.00 1	99.75 52	98.67 67	100.00 1	100.00 1	99.16 82	100.00 1	100.00 1	100.00 1	100.00 1

SteuartSystems-ACMMP		99.78 16	99.71 20	99.98 23	99.76 148	99.95 32	100.00 1	99.42 138	98.69 65	100.00 1	100.00 1	99.52 33	99.99 94	100.00 1	100.00 1	100.00 1
Skip Steuart: Steuart Systems R&D Blog.
PAPM		99.78 16	99.76 12	99.85 85	99.01 281	99.95 32	100.00 1	99.75 52	99.37 3	99.99 103	100.00 1	99.76 12	99.60 213	100.00 1	100.00 1	100.00 1

DP-MVS Recon		99.76 18	99.69 22	99.98 23	100.00 1	99.95 32	100.00 1	99.52 72	97.99 110	99.99 103	100.00 1	99.72 13	100.00 1	99.96 85	100.00 1	100.00 1

PAPR		99.76 18	99.68 25	99.99 12	100.00 1	99.96 24	100.00 1	99.47 79	98.16 96	100.00 1	100.00 1	99.51 34	100.00 1	100.00 1	100.00 1	100.00 1

DeepC-MVS_fast	98.92 1	99.75 20	99.67 27	99.99 12	99.99 49	99.96 24	99.73 299	99.52 72	99.06 12	100.00 1	100.00 1	98.80 120	100.00 1	99.95 91	100.00 1	100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MG-MVS		99.75 20	99.68 25	99.97 31	100.00 1	99.91 51	99.98 234	99.47 79	99.09 9	100.00 1	100.00 1	98.59 130	100.00 1	99.95 91	100.00 1	100.00 1

HFP-MVS		99.74 22	99.67 27	99.96 42	100.00 1	99.89 65	100.00 1	99.76 49	97.95 118	100.00 1	100.00 1	99.31 65	100.00 1	99.99 61	100.00 1	100.00 1

ACMMPR		99.74 22	99.67 27	99.96 42	100.00 1	99.89 65	100.00 1	99.76 49	97.95 118	100.00 1	100.00 1	99.29 71	100.00 1	99.99 61	100.00 1	100.00 1

PAPM_NR		99.74 22	99.66 30	99.99 12	100.00 1	99.96 24	100.00 1	99.47 79	97.87 123	100.00 1	100.00 1	99.60 18	100.00 1	100.00 1	100.00 1	100.00 1

CDPH-MVS		99.73 25	99.64 33	99.99 12	100.00 1	99.97 21	100.00 1	99.42 138	98.02 108	100.00 1	100.00 1	99.32 63	99.99 94	100.00 1	100.00 1	100.00 1

region2R		99.72 26	99.64 33	99.97 31	100.00 1	99.90 58	100.00 1	99.74 55	97.86 124	100.00 1	100.00 1	99.19 80	100.00 1	99.99 61	100.00 1	100.00 1

API-MVS		99.72 26	99.70 21	99.79 103	99.97 89	99.37 143	99.96 245	99.94 22	98.48 75	100.00 1	100.00 1	98.92 109	100.00 1	100.00 1	100.00 1	100.00 1

CNLPA		99.72 26	99.65 31	99.91 68	99.97 89	99.72 95	100.00 1	99.47 79	98.43 78	99.88 159	100.00 1	99.14 85	100.00 1	99.97 83	100.00 1	100.00 1

ZNCC-MVS		99.71 29	99.62 41	99.97 31	99.99 49	99.90 58	100.00 1	99.79 45	97.97 114	99.97 114	100.00 1	98.97 100	100.00 1	99.94 93	100.00 1	100.00 1

train_agg		99.71 29	99.63 37	99.97 31	100.00 1	99.95 32	100.00 1	99.42 138	97.70 135	100.00 1	100.00 1	99.51 34	99.97 125	100.00 1	100.00 1	100.00 1

MVS_111021_HR		99.71 29	99.63 37	99.93 66	99.95 96	99.83 83	100.00 1	100.00 1	98.89 43	100.00 1	100.00 1	97.85 152	99.95 149	100.00 1	100.00 1	100.00 1

EI-MVSNet-Vis-set		99.70 32	99.64 33	99.87 78	100.00 1	99.64 105	99.98 234	99.44 116	98.35 86	99.99 103	100.00 1	99.04 95	99.96 137	99.98 73	100.00 1	100.00 1

MVS_111021_LR		99.70 32	99.65 31	99.88 77	99.96 94	99.70 100	100.00 1	99.97 17	98.96 32	100.00 1	100.00 1	97.93 148	99.95 149	99.99 61	100.00 1	100.00 1

PLC	98.56 2	99.70 32	99.74 16	99.58 141	100.00 1	98.79 191	100.00 1	99.54 71	98.58 72	99.96 119	100.00 1	99.59 21	100.00 1	100.00 1	100.00 1	99.94 133
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
SMA-MVS		99.69 35	99.59 44	99.98 23	99.99 49	99.93 43	100.00 1	99.43 122	97.50 162	100.00 1	100.00 1	99.43 51	100.00 1	100.00 1	100.00 1	100.00 1
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
MVS_0304		99.69 35	99.63 37	99.86 81	99.96 94	99.63 107	100.00 1	99.92 34	99.03 20	99.97 114	100.00 1	97.87 150	99.96 137	100.00 1	99.96 113	100.00 1

EI-MVSNet-UG-set		99.69 35	99.63 37	99.87 78	99.99 49	99.64 105	99.95 251	99.44 116	98.35 86	100.00 1	100.00 1	98.98 99	99.97 125	99.98 73	100.00 1	100.00 1

PGM-MVS		99.69 35	99.61 42	99.95 51	99.99 49	99.85 80	100.00 1	99.58 67	97.69 137	100.00 1	100.00 1	99.44 47	100.00 1	99.79 119	100.00 1	100.00 1

mPP-MVS		99.69 35	99.60 43	99.97 31	100.00 1	99.91 51	100.00 1	99.42 138	97.91 120	100.00 1	100.00 1	99.04 95	100.00 1	100.00 1	100.00 1	100.00 1

SR-MVS		99.68 40	99.58 46	99.98 23	100.00 1	99.95 32	100.00 1	99.64 64	97.59 151	100.00 1	100.00 1	98.99 98	99.99 94	100.00 1	100.00 1	100.00 1

MTAPA		99.68 40	99.59 44	99.97 31	99.99 49	99.91 51	100.00 1	99.42 138	98.32 88	99.94 144	100.00 1	98.65 126	100.00 1	99.96 85	100.00 1	100.00 1

APD-MVS		99.68 40	99.58 46	99.97 31	99.99 49	99.96 24	100.00 1	99.42 138	97.53 157	100.00 1	100.00 1	99.27 74	99.97 125	100.00 1	100.00 1	100.00 1
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ACMMP_NAP		99.67 43	99.57 49	99.97 31	99.98 85	99.92 48	100.00 1	99.42 138	97.83 125	100.00 1	100.00 1	98.89 112	100.00 1	99.98 73	100.00 1	100.00 1

CP-MVS		99.67 43	99.58 46	99.95 51	100.00 1	99.84 82	100.00 1	99.42 138	97.77 130	100.00 1	100.00 1	99.07 89	100.00 1	100.00 1	100.00 1	100.00 1

SF-MVS		99.66 45	99.57 49	99.95 51	99.99 49	99.85 80	100.00 1	99.42 138	97.67 138	100.00 1	100.00 1	99.05 92	99.99 94	100.00 1	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 46	99.55 56	99.97 31	99.99 49	99.91 51	100.00 1	99.48 78	97.54 155	100.00 1	100.00 1	98.97 100	99.99 94	99.98 73	100.00 1	100.00 1

ACMMP		99.65 46	99.57 49	99.89 73	99.99 49	99.66 103	99.75 293	99.73 56	98.16 96	99.75 183	100.00 1	98.90 111	100.00 1	99.96 85	99.88 128	100.00 1
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
GST-MVS		99.64 48	99.53 59	99.95 51	100.00 1	99.86 77	100.00 1	99.79 45	97.72 133	99.95 142	100.00 1	98.39 137	100.00 1	99.96 85	99.99 97	100.00 1

PS-MVSNAJ		99.64 48	99.57 49	99.85 85	99.78 145	99.81 85	99.95 251	99.42 138	98.38 80	100.00 1	100.00 1	98.75 122	100.00 1	99.88 103	99.99 97	99.74 227

F-COLMAP		99.64 48	99.64 33	99.67 125	99.99 49	99.07 171	100.00 1	99.44 116	98.30 89	99.90 154	100.00 1	99.18 81	99.99 94	99.91 98	100.00 1	99.94 133

fmvsm_l_conf0.5_n_a		99.63 51	99.55 56	99.86 81	99.83 120	99.58 111	100.00 1	99.36 212	98.98 30	100.00 1	100.00 1	97.85 152	99.99 94	100.00 1	99.94 118	100.00 1

fmvsm_l_conf0.5_n		99.63 51	99.56 54	99.86 81	99.81 127	99.59 110	100.00 1	99.36 212	98.98 30	100.00 1	100.00 1	97.92 149	99.99 94	100.00 1	99.95 116	100.00 1

MM		99.63 51	99.52 61	99.94 63	99.99 49	99.82 84	100.00 1	99.97 17	99.11 7	100.00 1	100.00 1	96.65 198	100.00 1	100.00 1	99.97 110	100.00 1

SR-MVS-dyc-post		99.63 51	99.52 61	99.97 31	99.99 49	99.91 51	100.00 1	99.42 138	97.62 144	100.00 1	100.00 1	98.65 126	99.99 94	99.99 61	100.00 1	100.00 1

DPM-MVS		99.63 51	99.51 63	100.00 1	99.90 108	100.00 1	100.00 1	99.43 122	99.00 27	100.00 1	100.00 1	99.58 23	100.00 1	97.64 266	100.00 1	100.00 1

EPNet		99.62 56	99.69 22	99.42 160	99.99 49	98.37 218	100.00 1	99.89 37	98.83 53	100.00 1	100.00 1	98.97 100	100.00 1	99.90 99	99.61 154	99.89 161
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DELS-MVS		99.62 56	99.56 54	99.82 91	99.92 104	99.45 133	100.00 1	99.78 47	98.92 39	99.73 185	100.00 1	97.70 159	100.00 1	99.93 95	100.00 1	100.00 1
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023
MP-MVS-pluss		99.61 58	99.50 64	99.97 31	99.98 85	99.92 48	100.00 1	99.42 138	97.53 157	99.77 180	100.00 1	98.77 121	100.00 1	99.99 61	100.00 1	99.99 107
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MP-MVS		99.61 58	99.49 66	99.98 23	99.99 49	99.94 40	100.00 1	99.42 138	97.82 126	99.99 103	100.00 1	98.20 140	100.00 1	99.99 61	100.00 1	100.00 1
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
TSAR-MVS + GP.		99.61 58	99.69 22	99.35 171	99.99 49	98.06 243	100.00 1	99.36 212	99.83 2	100.00 1	100.00 1	98.95 104	99.99 94	100.00 1	99.11 162	100.00 1

HPM-MVS_fast		99.60 61	99.49 66	99.91 68	99.99 49	99.78 88	100.00 1	99.42 138	97.09 192	100.00 1	100.00 1	98.95 104	99.96 137	99.98 73	100.00 1	100.00 1

HPM-MVS		99.59 62	99.50 64	99.89 73	100.00 1	99.70 100	100.00 1	99.42 138	97.46 166	100.00 1	100.00 1	98.60 129	99.96 137	99.99 61	100.00 1	100.00 1
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
mvsany_test1		99.57 63	99.48 69	99.85 85	99.86 115	99.54 116	100.00 1	99.36 212	98.94 37	100.00 1	100.00 1	97.97 146	100.00 1	99.88 103	99.28 159	100.00 1

test_fmvsmconf_n		99.56 64	99.46 70	99.86 81	99.68 159	99.58 111	100.00 1	99.31 238	98.92 39	99.88 159	100.00 1	97.35 176	99.99 94	99.98 73	99.99 97	100.00 1

test_fmvsm_n_1920		99.55 65	99.49 66	99.73 116	99.85 116	99.19 162	100.00 1	99.41 184	98.87 47	100.00 1	100.00 1	97.34 177	100.00 1	99.98 73	99.90 125	100.00 1

WTY-MVS		99.54 66	99.40 72	99.95 51	99.81 127	99.93 43	100.00 1	100.00 1	97.98 112	99.84 163	100.00 1	98.94 106	99.98 118	99.86 107	98.21 201	99.94 133

test_yl		99.51 67	99.37 77	99.95 51	99.82 121	99.90 58	100.00 1	99.47 79	97.48 164	100.00 1	100.00 1	99.80 6	100.00 1	99.98 73	97.75 229	99.94 133

DCV-MVSNet		99.51 67	99.37 77	99.95 51	99.82 121	99.90 58	100.00 1	99.47 79	97.48 164	100.00 1	100.00 1	99.80 6	100.00 1	99.98 73	97.75 229	99.94 133

xiu_mvs_v2_base		99.51 67	99.41 71	99.82 91	99.70 154	99.73 94	99.92 259	99.40 188	98.15 98	100.00 1	100.00 1	98.50 134	100.00 1	99.85 109	99.13 161	99.74 227

HY-MVS	96.53 9	99.50 70	99.35 82	99.96 42	99.81 127	99.93 43	99.64 311	100.00 1	97.97 114	99.84 163	99.85 242	98.94 106	99.99 94	99.86 107	98.23 200	99.95 128

PHI-MVS		99.50 70	99.39 73	99.82 91	100.00 1	99.45 133	100.00 1	99.94 22	96.38 249	100.00 1	100.00 1	98.18 141	100.00 1	100.00 1	100.00 1	100.00 1

CPTT-MVS		99.49 72	99.38 74	99.85 85	100.00 1	99.54 116	100.00 1	99.42 138	97.58 152	99.98 109	100.00 1	97.43 174	100.00 1	99.99 61	100.00 1	100.00 1

MAR-MVS		99.49 72	99.36 80	99.89 73	99.97 89	99.66 103	99.74 294	99.95 19	97.89 121	100.00 1	100.00 1	96.71 197	100.00 1	100.00 1	100.00 1	100.00 1
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
test2506		99.48 74	99.38 74	99.75 112	99.89 110	99.51 122	99.45 332	100.00 1	98.38 80	99.83 166	100.00 1	98.86 113	99.81 191	99.25 189	98.78 170	99.94 133

PVSNet_Blended		99.48 74	99.36 80	99.83 89	99.98 85	99.60 108	100.00 1	100.00 1	97.79 128	100.00 1	100.00 1	96.57 200	99.99 94	100.00 1	99.88 128	99.90 156

test_fmvsmvis_n_1920		99.46 76	99.37 77	99.73 116	98.88 298	99.18 164	100.00 1	99.26 266	98.85 49	99.79 177	100.00 1	97.70 159	100.00 1	99.98 73	99.86 132	100.00 1

sss		99.45 77	99.34 84	99.80 101	99.76 148	99.50 124	100.00 1	99.91 36	97.72 133	99.98 109	99.94 222	98.45 135	100.00 1	99.53 172	98.75 173	99.89 161

AdaColmap		99.44 78	99.26 89	99.95 51	100.00 1	99.86 77	99.70 304	99.99 13	98.53 73	99.90 154	100.00 1	95.34 218	100.00 1	99.92 96	100.00 1	100.00 1

thisisatest0515		99.42 79	99.31 85	99.74 113	99.59 194	99.55 114	100.00 1	99.46 94	96.65 231	99.92 149	100.00 1	99.44 47	99.85 182	99.09 202	99.63 153	99.81 202

CANet		99.40 80	99.24 92	99.89 73	99.99 49	99.76 90	100.00 1	99.73 56	98.40 79	99.78 179	100.00 1	95.28 219	99.96 137	100.00 1	99.99 97	99.96 122

114514_t		99.39 81	99.25 90	99.81 96	99.97 89	99.48 131	100.00 1	99.42 138	95.53 281	100.00 1	100.00 1	98.37 138	99.95 149	99.97 83	100.00 1	100.00 1

alignmvs		99.38 82	99.21 96	99.91 68	99.73 151	99.92 48	100.00 1	99.51 76	97.61 148	100.00 1	100.00 1	99.06 90	99.93 165	99.83 113	97.12 241	99.90 156

1314		99.38 82	99.19 100	99.96 42	98.88 298	99.89 65	99.24 353	99.93 30	98.88 44	98.79 251	100.00 1	97.02 183	100.00 1	100.00 1	100.00 1	100.00 1

thisisatest0530		99.37 84	99.27 86	99.69 122	99.59 194	99.41 138	100.00 1	99.46 94	96.46 242	99.90 154	100.00 1	99.44 47	99.85 182	98.97 205	99.58 155	99.80 216

xiu_mvs_v1_base_debu		99.35 85	99.21 96	99.79 103	99.67 164	99.71 96	99.78 284	99.36 212	98.13 100	100.00 1	100.00 1	97.00 187	100.00 1	99.83 113	99.07 163	99.66 236

xiu_mvs_v1_base		99.35 85	99.21 96	99.79 103	99.67 164	99.71 96	99.78 284	99.36 212	98.13 100	100.00 1	100.00 1	97.00 187	100.00 1	99.83 113	99.07 163	99.66 236

xiu_mvs_v1_base_debi		99.35 85	99.21 96	99.79 103	99.67 164	99.71 96	99.78 284	99.36 212	98.13 100	100.00 1	100.00 1	97.00 187	100.00 1	99.83 113	99.07 163	99.66 236

ETV-MVS		99.34 88	99.24 92	99.64 130	99.58 199	99.33 145	100.00 1	99.25 268	97.57 153	99.96 119	100.00 1	97.44 173	99.79 193	99.70 137	99.65 151	99.81 202

tttt0517		99.34 88	99.23 95	99.67 125	99.57 202	99.38 140	100.00 1	99.46 94	96.33 253	99.89 157	100.00 1	99.44 47	99.84 184	98.93 207	99.46 158	99.78 222

CS-MVS		99.33 90	99.27 86	99.50 149	99.99 49	99.00 181	100.00 1	99.13 316	97.26 183	99.96 119	100.00 1	97.79 156	99.64 211	99.64 154	99.67 149	99.87 181

PVSNet_Blended_VisFu		99.33 90	99.18 103	99.78 107	99.82 121	99.49 127	100.00 1	99.95 19	97.36 173	99.63 190	100.00 1	96.45 204	99.95 149	99.79 119	99.65 151	99.89 161

fmvsm_s_conf0.5_n_a		99.32 92	99.15 105	99.81 96	99.80 138	99.47 132	100.00 1	99.35 223	98.22 91	100.00 1	100.00 1	95.21 222	99.99 94	99.96 85	99.86 132	99.98 109

HyFIR lowres test		99.32 92	99.24 92	99.58 141	99.95 96	99.26 152	100.00 1	99.99 13	96.72 223	99.29 213	99.91 229	99.49 40	99.47 245	99.74 128	98.08 208	100.00 1

CS-MVS-test		99.31 94	99.27 86	99.43 158	99.99 49	98.77 192	100.00 1	99.19 293	97.24 184	99.96 119	100.00 1	97.56 166	99.70 208	99.68 145	99.81 140	99.82 193

LS3D		99.31 94	99.13 106	99.87 78	99.99 49	99.71 96	99.55 322	99.46 94	97.32 178	99.82 174	100.00 1	96.85 194	99.97 125	99.14 197	100.00 1	99.92 145

PVSNet	94.91 18	99.30 96	99.25 90	99.44 156	100.00 1	98.32 224	100.00 1	99.86 38	98.04 107	100.00 1	100.00 1	96.10 207	100.00 1	99.55 167	99.73 144	100.00 1

lupinMVS		99.29 97	99.16 104	99.69 122	99.45 238	99.49 127	100.00 1	99.15 307	97.45 167	99.97 114	100.00 1	96.76 195	99.76 200	99.67 148	100.00 1	99.81 202

CSCG		99.28 98	99.35 82	99.05 195	99.99 49	97.15 287	100.00 1	99.47 79	97.44 168	99.42 201	100.00 1	97.83 155	100.00 1	99.99 61	100.00 1	100.00 1

thres200		99.27 99	99.04 113	99.96 42	99.81 127	99.90 58	100.00 1	99.94 22	97.31 180	99.83 166	99.96 209	97.04 180	100.00 1	99.62 158	97.88 218	99.98 109

OMC-MVS		99.27 99	99.38 74	98.96 203	99.95 96	97.06 291	100.00 1	99.40 188	98.83 53	99.88 159	100.00 1	97.01 184	99.86 176	99.47 175	99.84 137	99.97 116

testing11		99.26 101	99.19 100	99.46 153	99.64 178	98.61 203	100.00 1	99.43 122	96.94 201	99.92 149	99.94 222	99.43 51	99.97 125	99.67 148	97.79 227	99.82 193

EIA-MVS		99.26 101	99.19 100	99.45 155	99.63 181	98.75 193	100.00 1	99.27 260	96.93 202	99.95 142	100.00 1	97.47 170	99.79 193	99.74 128	99.72 145	99.82 193

tfpn200view9		99.26 101	99.03 114	99.96 42	99.81 127	99.89 65	100.00 1	99.94 22	97.23 185	99.83 166	99.96 209	97.04 180	100.00 1	99.59 162	97.85 220	99.98 109

thres400		99.26 101	99.03 114	99.95 51	99.81 127	99.89 65	100.00 1	99.94 22	97.23 185	99.83 166	99.96 209	97.04 180	100.00 1	99.59 162	97.85 220	99.97 116

test_fmvsmconf0.1_n		99.25 105	99.05 112	99.82 91	98.92 294	99.55 114	100.00 1	99.23 277	98.91 41	99.75 183	99.97 195	94.79 229	99.94 161	99.94 93	99.99 97	99.97 116

thres100view900		99.25 105	99.01 116	99.95 51	99.81 127	99.87 74	100.00 1	99.94 22	97.13 190	99.83 166	99.96 209	97.01 184	100.00 1	99.59 162	97.85 220	99.98 109

EPMVS		99.25 105	99.13 106	99.60 135	99.60 190	99.20 161	99.60 317	100.00 1	96.93 202	99.92 149	99.36 314	99.05 92	99.71 207	98.77 217	98.94 167	99.90 156

thres600view7		99.24 108	99.00 118	99.95 51	99.81 127	99.87 74	100.00 1	99.94 22	97.13 190	99.83 166	99.96 209	97.01 184	100.00 1	99.54 170	97.77 228	99.97 116

MVS		99.22 109	98.96 123	99.98 23	99.00 285	99.95 32	99.24 353	99.94 22	98.14 99	98.88 241	100.00 1	95.63 216	100.00 1	99.85 109	100.00 1	100.00 1

fmvsm_s_conf0.5_n		99.21 110	99.01 116	99.83 89	99.84 117	99.53 118	100.00 1	99.38 203	98.29 90	100.00 1	100.00 1	93.62 243	99.99 94	99.99 61	99.93 121	99.98 109

EC-MVSNet		99.19 111	99.09 110	99.48 152	99.42 242	99.07 171	100.00 1	99.21 289	96.95 200	99.96 119	100.00 1	96.88 193	99.48 243	99.64 154	99.79 143	99.88 172

testing91		99.18 112	99.10 108	99.41 161	99.60 190	98.43 210	100.00 1	99.43 122	96.76 216	99.82 174	99.92 227	99.05 92	99.98 118	99.62 158	97.67 233	99.81 202

testing99		99.18 112	99.10 108	99.41 161	99.60 190	98.43 210	100.00 1	99.43 122	96.76 216	99.84 163	99.92 227	99.06 90	99.98 118	99.62 158	97.67 233	99.81 202

UWE-MVS		99.18 112	99.06 111	99.51 146	99.67 164	98.80 190	100.00 1	99.43 122	96.80 213	99.93 148	99.86 237	99.79 8	99.94 161	97.78 262	98.33 195	99.80 216

ETVMVS		99.16 115	98.98 121	99.69 122	99.67 164	99.56 113	100.00 1	99.45 102	96.36 250	99.98 109	99.95 217	98.65 126	99.64 211	99.11 201	97.63 236	99.88 172

FE-MVS		99.16 115	98.99 120	99.66 128	99.65 172	99.18 164	99.58 319	99.43 122	95.24 291	99.91 152	99.59 294	99.37 59	99.97 125	98.31 241	99.81 140	99.83 188

testing222		99.14 117	98.94 128	99.73 116	99.67 164	99.51 122	100.00 1	99.43 122	96.90 207	99.99 103	99.90 231	98.55 132	99.86 176	98.85 212	97.18 240	99.81 202

PMMVS		99.12 118	98.97 122	99.58 141	99.57 202	98.98 183	100.00 1	99.30 242	97.14 189	99.96 119	100.00 1	96.53 203	99.82 188	99.70 137	98.49 179	99.94 133

jason		99.11 119	98.96 123	99.59 137	99.17 265	99.31 148	100.00 1	99.13 316	97.38 172	99.83 166	100.00 1	95.54 217	99.72 206	99.57 166	99.97 110	99.74 227
jason: jason.
EPP-MVSNet		99.10 120	99.00 118	99.40 165	99.51 221	98.68 199	99.92 259	99.43 122	95.47 287	99.65 189	100.00 1	99.51 34	99.76 200	99.53 172	98.00 209	99.75 226

TESTMET0.1,1		99.08 121	98.96 123	99.44 156	99.63 181	99.38 140	100.00 1	99.45 102	95.53 281	99.48 197	100.00 1	99.71 14	99.02 272	96.84 291	99.99 97	99.91 147

IS-MVSNet		99.08 121	98.91 132	99.59 137	99.65 172	99.38 140	99.78 284	99.24 273	96.70 225	99.51 195	100.00 1	98.44 136	99.52 238	98.47 235	98.39 187	99.88 172

UA-Net		99.06 123	98.83 138	99.74 113	99.52 216	99.40 139	99.08 377	99.45 102	97.64 142	99.83 166	100.00 1	95.80 211	99.94 161	98.35 239	99.80 142	99.88 172

3Dnovator	95.63 14	99.06 123	98.76 146	99.96 42	98.86 302	99.90 58	99.98 234	99.93 30	98.95 35	98.49 271	100.00 1	92.91 255	100.00 1	99.71 134	100.00 1	100.00 1

patch_mono-2		99.04 125	99.79 6	96.81 322	99.92 104	90.47 370	100.00 1	99.41 184	98.95 35	100.00 1	100.00 1	99.78 9	100.00 1	100.00 1	100.00 1	99.95 128

VNet		99.04 125	98.75 148	99.90 71	99.81 127	99.75 91	99.50 328	99.47 79	98.36 84	100.00 1	99.99 182	94.66 231	100.00 1	99.90 99	97.09 242	99.96 122

canonicalmvs		99.03 127	98.73 150	99.94 63	99.75 150	99.95 32	100.00 1	99.30 242	97.64 142	100.00 1	100.00 1	95.22 221	99.97 125	99.76 126	96.90 247	99.91 147

test-LLR		99.03 127	98.91 132	99.40 165	99.40 249	99.28 150	100.00 1	99.45 102	96.70 225	99.42 201	99.12 323	99.31 65	99.01 273	96.82 292	99.99 97	99.91 147

PatchmatchNet		99.03 127	98.96 123	99.26 185	99.49 229	98.33 222	99.38 340	99.45 102	96.64 232	99.96 119	99.58 296	99.49 40	99.50 241	97.63 267	99.00 166	99.93 143
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
3Dnovator+	95.58 15	99.03 127	98.71 153	99.96 42	98.99 288	99.89 65	100.00 1	99.51 76	98.96 32	98.32 279	100.00 1	92.78 257	100.00 1	99.87 106	100.00 1	100.00 1

CANet_DTU		99.02 131	98.90 135	99.41 161	99.88 112	98.71 197	100.00 1	99.29 246	98.84 51	100.00 1	100.00 1	94.02 238	100.00 1	98.08 250	99.96 113	99.52 242

PatchMatch-RL		99.02 131	98.78 143	99.74 113	99.99 49	99.29 149	100.00 1	100.00 1	98.38 80	99.89 157	99.81 251	93.14 253	99.99 94	97.85 260	99.98 107	99.95 128

FA-MVS(test-final)		99.00 133	98.75 148	99.73 116	99.63 181	99.43 136	99.83 274	99.43 122	95.84 272	99.52 194	99.37 313	97.84 154	99.96 137	97.63 267	99.68 147	99.79 219

CHOSEN 1792x2688		99.00 133	98.91 132	99.25 186	99.90 108	97.79 263	100.00 1	99.99 13	98.79 60	98.28 282	100.00 1	93.63 242	99.95 149	99.66 152	99.95 116	100.00 1

DeepC-MVS	97.84 5	99.00 133	98.80 142	99.60 135	99.93 101	99.03 176	100.00 1	99.40 188	98.61 71	99.33 211	100.00 1	92.23 266	99.95 149	99.74 128	99.96 113	99.83 188
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
baseline2		98.99 136	98.93 130	99.18 190	99.26 262	99.15 168	100.00 1	99.46 94	96.71 224	96.79 338	100.00 1	99.42 54	99.25 264	98.75 219	99.94 118	99.15 248

QAPM		98.99 136	98.66 155	99.96 42	99.01 281	99.87 74	99.88 268	99.93 30	97.99 110	98.68 256	100.00 1	93.17 251	100.00 1	99.32 184	100.00 1	100.00 1

Vis-MVSNet (Re-imp)		98.99 136	98.89 136	99.29 180	99.64 178	98.89 187	99.98 234	99.31 238	96.74 220	99.48 197	100.00 1	98.11 143	99.10 268	98.39 237	98.34 192	99.89 161

tpmrst		98.98 139	98.93 130	99.14 192	99.61 188	97.74 264	99.52 326	99.36 212	96.05 263	99.98 109	99.64 282	99.04 95	99.86 176	98.94 206	98.19 203	99.82 193

test-mter		98.96 140	98.82 139	99.40 165	99.40 249	99.28 150	100.00 1	99.45 102	95.44 290	99.42 201	99.12 323	99.70 15	99.01 273	96.82 292	99.99 97	99.91 147

diffmvs		98.96 140	98.73 150	99.63 131	99.54 206	99.16 167	100.00 1	99.18 300	97.33 177	99.96 119	100.00 1	94.60 232	99.91 168	99.66 152	98.33 195	99.82 193
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		98.96 140	98.95 127	99.01 199	99.48 231	98.36 220	99.93 258	99.37 206	96.79 214	99.31 212	99.83 245	99.77 11	98.91 282	98.07 251	97.98 210	99.77 223
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MVSFormer		98.94 143	98.82 139	99.28 183	99.45 238	99.49 127	100.00 1	99.13 316	95.46 288	99.97 114	100.00 1	96.76 195	98.59 314	98.63 227	100.00 1	99.74 227

MVS_Test		98.93 144	98.65 156	99.77 110	99.62 186	99.50 124	99.99 210	99.19 293	95.52 283	99.96 119	99.86 237	96.54 202	99.98 118	98.65 224	98.48 180	99.82 193

baseline1		98.91 145	98.61 160	99.81 96	99.71 152	99.77 89	99.78 284	99.44 116	97.51 161	98.81 249	99.99 182	98.25 139	99.76 200	98.60 230	95.41 260	99.89 161

1112_ss		98.91 145	98.71 153	99.51 146	99.69 155	98.75 193	99.99 210	99.15 307	96.82 211	98.84 246	100.00 1	97.45 171	99.89 171	98.66 222	97.75 229	99.89 161

MSDG		98.90 147	98.63 158	99.70 121	99.92 104	99.25 154	100.00 1	99.37 206	95.71 275	99.40 207	100.00 1	96.58 199	99.95 149	96.80 294	99.94 118	99.91 147

dcpmvs_2		98.87 148	99.53 59	96.90 316	99.87 114	90.88 369	99.94 256	99.07 336	98.20 94	100.00 1	100.00 1	98.69 125	99.86 176	100.00 1	100.00 1	99.95 128

DP-MVS		98.86 149	98.54 166	99.81 96	99.97 89	99.45 133	99.52 326	99.40 188	94.35 315	98.36 275	100.00 1	96.13 206	99.97 125	99.12 200	100.00 1	100.00 1

CostFormer		98.84 150	98.77 144	99.04 197	99.41 244	97.58 269	99.67 309	99.35 223	94.66 304	99.96 119	99.36 314	99.28 73	99.74 203	99.41 178	97.81 224	99.81 202

Test_1112_low_res		98.83 151	98.60 162	99.51 146	99.69 155	98.75 193	99.99 210	99.14 312	96.81 212	98.84 246	99.06 327	97.45 171	99.89 171	98.66 222	97.75 229	99.89 161

BH-w/o		98.82 152	98.81 141	98.88 208	99.62 186	96.71 299	100.00 1	99.28 252	97.09 192	98.81 249	100.00 1	94.91 227	99.96 137	99.54 170	100.00 1	99.96 122

mvs_anonymous		98.80 153	98.60 162	99.38 169	99.57 202	99.24 156	100.00 1	99.21 289	95.87 267	98.92 237	99.82 248	96.39 205	99.03 271	99.13 199	98.50 178	99.88 172

fmvsm_s_conf0.1_n		98.77 154	98.42 173	99.82 91	99.47 234	99.52 121	100.00 1	99.27 260	97.53 157	100.00 1	100.00 1	89.73 298	99.96 137	99.84 112	99.93 121	99.97 116

TAMVS		98.76 155	98.73 150	98.86 209	99.44 240	97.69 265	99.57 320	99.34 229	96.57 236	99.12 223	99.81 251	98.83 117	99.16 266	97.97 257	97.91 216	99.73 231

OpenMVS	95.20 17	98.76 155	98.41 174	99.78 107	98.89 297	99.81 85	99.99 210	99.76 49	98.02 108	98.02 297	100.00 1	91.44 272	100.00 1	99.63 157	99.97 110	99.55 240

iter_conf05		98.73 157	98.77 144	98.60 221	99.65 172	99.22 159	100.00 1	99.22 280	96.68 229	98.98 235	99.97 195	99.99 3	98.84 290	99.29 187	95.11 279	97.75 272

iter_conf_final		98.72 158	98.76 146	98.59 223	99.64 178	99.17 166	100.00 1	99.22 280	96.63 234	99.02 232	99.97 195	99.98 4	98.84 290	99.22 194	95.18 273	97.76 261

dp		98.72 158	98.61 160	99.03 198	99.53 209	97.39 275	99.45 332	99.39 201	95.62 278	99.94 144	99.52 304	98.83 117	99.82 188	96.77 297	98.42 184	99.89 161

fmvsm_s_conf0.1_n_a		98.71 160	98.36 181	99.78 107	99.09 271	99.42 137	100.00 1	99.26 266	97.42 170	100.00 1	100.00 1	89.78 296	99.96 137	99.82 118	99.85 135	99.97 116

PVSNet_BlendedMVS		98.71 160	98.62 159	98.98 202	99.98 85	99.60 108	100.00 1	100.00 1	97.23 185	100.00 1	99.03 332	96.57 200	99.99 94	100.00 1	94.75 287	97.35 356

ADS-MVSNet		98.70 162	98.51 168	99.28 183	99.51 221	98.39 215	99.24 353	99.44 116	95.52 283	99.96 119	99.70 266	97.57 164	99.58 219	97.11 283	98.54 176	99.88 172

baseline		98.69 163	98.45 172	99.41 161	99.52 216	98.67 200	100.00 1	99.17 305	97.03 197	99.13 222	100.00 1	93.17 251	99.74 203	99.70 137	98.34 192	99.81 202

PCF-MVS	98.23 3	98.69 163	98.37 179	99.62 132	99.78 145	99.02 177	99.23 358	99.06 344	96.43 243	98.08 291	100.00 1	94.72 230	99.95 149	98.16 248	99.91 124	99.90 156
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
casdiffmvs		98.65 165	98.38 177	99.46 153	99.52 216	98.74 196	100.00 1	99.15 307	96.91 205	99.05 230	100.00 1	92.75 258	99.83 185	99.70 137	98.38 189	99.81 202
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
casdiffmvs_mvg		98.64 166	98.39 176	99.40 165	99.50 225	98.60 204	100.00 1	99.22 280	96.85 209	99.10 224	100.00 1	92.75 258	99.78 197	99.71 134	98.35 191	99.81 202
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		98.64 166	98.58 164	98.81 212	99.42 242	97.12 288	99.69 306	99.37 206	93.63 331	99.94 144	99.67 274	98.96 103	99.47 245	98.62 229	97.95 214	99.83 188

BH-untuned		98.64 166	98.65 156	98.60 221	99.59 194	96.17 305	100.00 1	99.28 252	96.67 230	98.41 274	100.00 1	94.52 233	99.83 185	99.41 178	100.00 1	99.81 202

test_cas_vis1_n_1920		98.63 169	98.25 185	99.77 110	99.69 155	99.32 146	100.00 1	99.31 238	98.84 51	99.96 119	100.00 1	87.42 326	99.99 94	99.14 197	99.86 132	100.00 1

test_fmvsmconf0.01_n		98.60 170	98.24 187	99.67 125	96.90 369	99.21 160	99.99 210	99.04 349	98.80 57	99.57 192	99.96 209	90.12 290	99.91 168	99.89 101	99.89 126	99.90 156

tpmvs		98.59 171	98.38 177	99.23 187	99.69 155	97.90 255	99.31 348	99.47 79	94.52 309	99.68 188	99.28 318	97.64 162	99.89 171	97.71 264	98.17 205	99.89 161

Effi-MVS+		98.58 172	98.24 187	99.61 133	99.60 190	99.26 152	97.85 393	99.10 326	96.22 258	99.97 114	99.89 232	93.75 240	99.77 198	99.43 176	98.34 192	99.81 202

MVSTER		98.58 172	98.52 167	98.77 214	99.65 172	99.68 102	100.00 1	99.29 246	95.63 277	98.65 257	99.80 254	99.78 9	98.88 288	98.59 231	95.31 264	97.73 301

CVMVSNet		98.56 174	98.47 171	98.82 210	99.11 268	97.67 266	99.74 294	99.47 79	97.57 153	99.06 229	100.00 1	95.72 213	98.97 278	98.21 247	97.33 239	99.83 188

AllTest		98.55 175	98.40 175	98.99 200	99.93 101	97.35 278	100.00 1	99.40 188	97.08 194	99.09 225	99.98 187	93.37 246	99.95 149	96.94 287	99.84 137	99.68 234

DeepPCF-MVS	98.03 4	98.54 176	99.72 19	94.98 345	99.99 49	84.94 384	100.00 1	99.42 138	99.98 1	100.00 1	100.00 1	98.11 143	100.00 1	100.00 1	100.00 1	100.00 1

EPNet_dtu		98.53 177	98.23 190	99.43 158	99.92 104	99.01 179	99.96 245	99.47 79	98.80 57	99.96 119	99.96 209	98.56 131	99.30 261	87.78 376	99.68 147	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
myMVS_eth3d		98.52 178	98.51 168	98.53 226	99.50 225	97.98 248	100.00 1	99.57 68	96.23 256	98.07 292	100.00 1	99.09 88	97.81 361	96.17 304	97.96 212	99.82 193

Vis-MVSNet		98.52 178	98.25 185	99.34 172	99.68 159	98.55 206	99.68 308	99.41 184	97.34 176	99.94 144	100.00 1	90.38 289	99.70 208	99.03 204	98.84 168	99.76 225
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Effi-MVS+-dtu		98.51 180	98.86 137	97.47 292	99.77 147	94.21 342	100.00 1	98.94 360	97.61 148	99.91 152	98.75 350	95.89 209	99.51 240	99.36 180	99.48 157	98.68 254

SDMVSNet		98.49 181	98.08 197	99.73 116	99.82 121	99.53 118	99.99 210	99.45 102	97.62 144	99.38 208	99.86 237	90.06 293	99.88 175	99.92 96	96.61 250	99.79 219

BH-RMVSNet		98.46 182	98.08 197	99.59 137	99.61 188	99.19 162	100.00 1	99.28 252	97.06 196	98.95 236	100.00 1	88.99 308	99.82 188	98.83 215	100.00 1	99.77 223

testing3		98.44 183	98.37 179	98.65 218	99.51 221	98.32 224	100.00 1	99.62 66	96.43 243	97.93 302	99.99 182	99.11 86	97.81 361	94.88 324	97.80 225	99.82 193

ECVR-MVS		98.43 184	98.14 193	99.32 177	99.89 110	98.21 232	99.46 330	100.00 1	98.38 80	99.47 200	100.00 1	87.91 319	99.80 192	99.35 181	98.78 170	99.94 133

cascas		98.43 184	98.07 199	99.50 149	99.65 172	99.02 177	100.00 1	99.22 280	94.21 318	99.72 186	99.98 187	92.03 269	99.93 165	99.68 145	98.12 206	99.54 241

test1111		98.42 186	98.12 194	99.29 180	99.88 112	98.15 235	99.46 330	100.00 1	98.36 84	99.42 201	100.00 1	87.91 319	99.79 193	99.31 185	98.78 170	99.94 133

ab-mvs		98.42 186	98.02 204	99.61 133	99.71 152	99.00 181	99.10 374	99.64 64	96.70 225	99.04 231	99.81 251	90.64 283	99.98 118	99.64 154	97.93 215	99.84 185

UGNet		98.41 188	98.11 195	99.31 179	99.54 206	98.55 206	99.18 361	100.00 1	98.64 70	99.79 177	99.04 330	87.61 324	100.00 1	99.30 186	99.89 126	99.40 245
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+		98.40 189	98.02 204	99.55 145	99.63 181	99.06 173	100.00 1	99.15 307	95.07 293	99.42 201	99.95 217	93.26 249	99.73 205	97.44 273	98.24 199	99.87 181

Fast-Effi-MVS+-dtu		98.38 190	98.56 165	97.82 282	99.58 199	94.44 339	100.00 1	99.16 306	96.75 218	99.51 195	99.63 286	95.03 225	99.60 213	97.71 264	99.67 149	99.42 244

test_fmvs1		98.37 191	98.04 202	99.34 172	99.84 117	98.07 241	100.00 1	99.00 355	98.85 49	100.00 1	100.00 1	85.11 346	99.96 137	99.69 144	99.88 128	100.00 1

miper_enhance_ethall		98.33 192	98.27 184	98.51 227	99.66 171	99.04 175	100.00 1	99.22 280	97.53 157	98.51 269	99.38 312	99.49 40	98.75 300	98.02 253	92.61 308	97.76 261

SCA		98.30 193	97.98 206	99.23 187	99.41 244	98.25 229	99.99 210	99.45 102	96.91 205	99.76 182	99.58 296	89.65 300	99.54 232	98.31 241	98.79 169	99.91 147

XVG-OURS		98.30 193	98.36 181	98.13 257	99.58 199	95.91 308	100.00 1	99.36 212	98.69 65	99.23 215	100.00 1	91.20 275	99.92 167	99.34 182	97.82 223	98.56 257

COLMAP_ROB	97.10 7	98.29 195	98.17 192	98.65 218	99.94 99	97.39 275	99.30 349	99.40 188	95.64 276	97.75 311	100.00 1	92.69 262	99.95 149	98.89 209	99.92 123	98.62 256
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ADS-MVSNet2		98.28 196	98.51 168	97.62 288	99.51 221	95.03 319	99.24 353	99.41 184	95.52 283	99.96 119	99.70 266	97.57 164	97.94 358	97.11 283	98.54 176	99.88 172

XVG-OURS-SEG-HR		98.27 197	98.31 183	98.14 254	99.59 194	95.92 307	100.00 1	99.36 212	98.48 75	99.21 216	100.00 1	89.27 305	99.94 161	99.76 126	99.17 160	98.56 257

tpm		98.24 198	98.22 191	98.32 239	99.13 267	95.79 310	99.53 325	99.12 322	95.20 292	99.96 119	99.36 314	97.58 163	99.28 263	97.41 275	96.67 248	99.88 172

cl22		98.23 199	98.11 195	98.58 225	99.82 121	99.01 179	100.00 1	99.28 252	96.92 204	98.33 278	99.21 320	98.09 145	98.97 278	98.72 220	92.61 308	97.76 261

TR-MVS		98.14 200	97.74 214	99.33 175	99.59 194	98.28 227	99.27 350	99.21 289	96.42 245	99.15 221	99.94 222	88.87 311	99.79 193	98.88 210	98.29 197	99.93 143

mvsmamba		98.13 201	98.06 200	98.32 239	98.22 329	98.50 209	100.00 1	99.22 280	96.41 246	98.91 239	99.96 209	95.69 214	98.73 302	99.19 196	94.95 286	97.73 301

test0.0.03 1		98.12 202	98.03 203	98.39 233	99.11 268	98.07 241	100.00 1	99.93 30	96.70 225	96.91 334	99.95 217	99.31 65	98.19 338	91.93 350	98.44 182	98.91 252

GeoE		98.06 203	97.65 219	99.29 180	99.47 234	98.41 212	100.00 1	99.19 293	94.85 298	98.88 241	100.00 1	91.21 274	99.59 215	97.02 285	98.19 203	99.88 172

tpm cat1		98.05 204	97.76 212	98.92 205	99.50 225	97.10 290	99.77 289	99.30 242	90.20 370	99.72 186	98.71 351	97.71 158	99.86 176	96.75 298	98.20 202	99.81 202

PS-MVSNAJss		98.03 205	98.06 200	97.94 276	97.63 350	97.33 281	99.89 266	99.23 277	96.27 255	98.03 295	99.59 294	98.75 122	98.78 295	98.52 233	94.61 291	97.70 317

CR-MVSNet		98.02 206	97.71 217	98.93 204	99.31 256	98.86 188	99.13 371	99.00 355	96.53 239	99.96 119	98.98 336	96.94 190	98.10 348	91.18 355	98.40 185	99.84 185

EI-MVSNet		97.98 207	97.93 207	98.16 252	99.11 268	97.84 260	99.74 294	99.29 246	94.39 314	98.65 257	100.00 1	97.21 178	98.88 288	97.62 269	95.31 264	97.75 272

FIs		97.95 208	97.73 216	98.62 220	98.53 314	99.24 156	100.00 1	99.43 122	96.74 220	97.87 306	99.82 248	95.27 220	98.89 285	98.78 216	93.07 303	97.74 295

Anonymous202405211		97.87 209	97.53 222	98.90 206	99.81 127	96.70 300	99.35 343	99.46 94	92.98 346	98.83 248	99.99 182	90.63 284	100.00 1	99.70 137	97.03 243	100.00 1

FC-MVSNet-test		97.84 210	97.63 220	98.45 230	98.30 324	99.05 174	100.00 1	99.43 122	96.63 234	97.61 317	99.82 248	95.19 223	98.57 317	98.64 225	93.05 304	97.73 301

Patchmatch-test		97.83 211	97.42 225	99.06 193	99.08 272	97.66 267	98.66 387	99.21 289	93.65 330	98.25 286	99.58 296	99.47 44	99.57 220	90.25 364	98.59 175	99.95 128

sd_testset		97.81 212	97.48 223	98.79 213	99.82 121	96.80 297	99.32 345	99.45 102	97.62 144	99.38 208	99.86 237	85.56 344	99.77 198	99.72 131	96.61 250	99.79 219

miper_ehance_all_eth		97.81 212	97.66 218	98.23 245	99.49 229	98.37 218	99.99 210	99.11 324	94.78 299	98.25 286	99.21 320	98.18 141	98.57 317	97.35 279	92.61 308	97.76 261

test_vis1_n_1920		97.77 214	97.24 237	99.34 172	99.79 142	98.04 245	100.00 1	99.25 268	98.88 44	100.00 1	100.00 1	77.52 377	100.00 1	99.88 103	99.85 135	100.00 1

RRT_MVS		97.77 214	97.76 212	97.78 284	97.89 342	97.06 291	100.00 1	99.29 246	95.74 274	98.00 300	99.97 195	95.94 208	98.55 320	98.87 211	94.18 294	97.72 308

HQP-MVS		97.73 216	97.85 209	97.39 294	99.07 273	94.82 323	100.00 1	99.40 188	99.04 15	99.17 217	99.97 195	88.61 314	99.57 220	99.79 119	95.58 254	97.77 259

GA-MVS		97.72 217	97.27 235	99.06 193	99.24 263	97.93 254	100.00 1	99.24 273	95.80 273	98.99 234	99.64 282	89.77 297	99.36 256	95.12 321	97.62 237	99.89 161

bld_raw_dy_0_64		97.71 218	97.56 221	98.15 253	97.83 345	98.16 233	99.95 251	99.12 322	95.95 266	98.73 254	99.97 195	93.19 250	98.63 308	98.64 225	94.69 289	97.66 328

HQP_MVS		97.71 218	97.82 211	97.37 295	99.00 285	94.80 326	100.00 1	99.40 188	99.00 27	99.08 227	99.97 195	88.58 316	99.55 229	99.79 119	95.57 258	97.76 261

nrg030		97.64 220	97.27 235	98.75 215	98.34 319	99.53 118	100.00 1	99.22 280	96.21 259	98.27 284	99.95 217	94.40 234	98.98 276	99.23 192	89.78 344	97.75 272

TAPA-MVS	96.40 10	97.64 220	97.37 229	98.45 230	99.94 99	95.70 311	100.00 1	99.40 188	97.65 140	99.53 193	100.00 1	99.31 65	99.66 210	80.48 391	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CLD-MVS		97.64 220	97.74 214	97.36 296	99.01 281	94.76 331	100.00 1	99.34 229	99.30 4	99.00 233	99.97 195	87.49 325	99.57 220	99.96 85	95.58 254	97.75 272
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
D2MVS		97.63 223	97.83 210	97.05 307	98.83 305	94.60 335	100.00 1	99.82 40	96.89 208	98.28 282	99.03 332	94.05 236	99.47 245	98.58 232	94.97 284	97.09 362

c3_l		97.58 224	97.42 225	98.06 264	99.48 231	98.16 233	99.96 245	99.10 326	94.54 308	98.13 290	99.20 322	97.87 150	98.25 337	97.28 280	91.20 332	97.75 272

IterMVS-LS		97.56 225	97.44 224	97.92 279	99.38 253	97.90 255	99.89 266	99.10 326	94.41 313	98.32 279	99.54 303	97.21 178	98.11 345	97.50 271	91.62 324	97.75 272
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test_djsdf		97.55 226	97.38 228	98.07 260	97.50 358	97.99 247	100.00 1	99.13 316	95.46 288	98.47 272	99.85 242	92.01 270	98.59 314	98.63 227	95.36 262	97.62 339

dmvs_re		97.54 227	97.88 208	96.54 327	99.55 205	90.35 371	99.86 270	99.46 94	97.00 198	99.41 206	100.00 1	90.78 282	99.30 261	99.60 161	95.24 269	99.96 122

cl____		97.54 227	97.32 231	98.18 249	99.47 234	98.14 237	100.00 1	99.10 326	94.16 321	97.60 318	99.63 286	97.52 167	98.65 307	96.47 299	91.97 320	97.76 261

IB-MVS	96.24 12	97.54 227	96.95 242	99.33 175	99.67 164	98.10 240	100.00 1	99.47 79	97.42 170	99.26 214	99.69 269	98.83 117	99.89 171	99.43 176	78.77 388	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		97.52 230	97.35 230	98.05 268	99.46 237	98.11 238	100.00 1	99.10 326	94.21 318	97.62 316	99.63 286	97.65 161	98.29 334	96.47 299	91.98 319	97.76 261

eth_miper_zixun_eth		97.47 231	97.28 233	98.06 264	99.41 244	97.94 253	99.62 315	99.08 332	94.46 312	98.19 289	99.56 300	96.91 192	98.50 323	96.78 295	91.49 327	97.74 295

test_fmvs1_n		97.43 232	96.86 245	99.15 191	99.68 159	97.48 272	99.99 210	98.98 358	98.82 55	100.00 1	100.00 1	74.85 382	99.96 137	99.67 148	99.70 146	100.00 1

LFMVS		97.42 233	96.62 254	99.81 96	99.80 138	99.50 124	99.16 367	99.56 70	94.48 311	100.00 1	100.00 1	79.35 372	100.00 1	99.89 101	97.37 238	99.94 133

miper_lstm_enhance		97.40 234	97.28 233	97.75 285	99.48 231	97.52 270	100.00 1	99.07 336	94.08 322	98.01 298	99.61 292	97.38 175	97.98 356	96.44 302	91.47 329	97.76 261

RPSCF		97.37 235	98.24 187	94.76 348	99.80 138	84.57 385	99.99 210	99.05 346	94.95 296	99.82 174	100.00 1	94.03 237	100.00 1	98.15 249	98.38 189	99.70 232

ACMM	97.17 6	97.37 235	97.40 227	97.29 300	99.01 281	94.64 334	100.00 1	99.25 268	98.07 106	98.44 273	99.98 187	87.38 327	99.55 229	99.25 189	95.19 272	97.69 321
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LPG-MVS_test		97.31 237	97.32 231	97.28 301	98.85 303	94.60 335	100.00 1	99.37 206	97.35 174	98.85 244	99.98 187	86.66 333	99.56 224	99.55 167	95.26 266	97.70 317

FMVSNet3		97.30 238	96.95 242	98.37 235	99.65 172	99.25 154	99.71 302	99.28 252	94.23 316	98.53 266	98.91 343	93.30 248	98.11 345	95.31 317	93.60 297	97.73 301

UniMVSNet (Re)		97.29 239	96.85 246	98.59 223	98.49 315	99.13 169	100.00 1	99.42 138	96.52 240	98.24 288	98.90 344	94.93 226	98.89 285	97.54 270	87.61 362	97.75 272

OPM-MVS		97.21 240	97.18 240	97.32 299	98.08 335	94.66 332	100.00 1	99.28 252	98.65 69	98.92 237	99.98 187	86.03 340	99.56 224	98.28 245	95.41 260	97.72 308
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMP	97.00 8	97.19 241	97.16 241	97.27 303	98.97 290	94.58 338	100.00 1	99.32 233	97.97 114	97.45 322	99.98 187	85.79 342	99.56 224	99.70 137	95.24 269	97.67 327
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
pmmvs4		97.17 242	96.80 247	98.27 242	97.68 349	98.64 202	100.00 1	99.18 300	94.22 317	98.55 264	99.71 263	93.67 241	98.47 326	95.66 311	92.57 311	97.71 316

anonymousdsp		97.16 243	96.88 244	98.00 272	97.08 368	98.06 243	99.81 278	99.15 307	94.58 306	97.84 307	99.62 290	90.49 286	98.60 312	97.98 254	95.32 263	97.33 357

UniMVSNet_NR-MVSNet		97.16 243	96.80 247	98.22 246	98.38 318	98.41 212	100.00 1	99.45 102	96.14 261	97.76 308	99.64 282	95.05 224	98.50 323	97.98 254	86.84 366	97.75 272

XXY-MVS		97.14 245	96.63 253	98.67 217	98.65 308	98.92 186	99.54 324	99.29 246	95.57 280	97.63 314	99.83 245	87.79 323	99.35 258	98.39 237	92.95 305	97.75 272

WR-MVS		97.09 246	96.64 252	98.46 229	98.43 316	99.09 170	99.97 240	99.33 231	95.62 278	97.76 308	99.67 274	91.17 276	98.56 319	98.49 234	89.28 350	97.74 295

JIA-IIPM		97.09 246	96.34 268	99.36 170	98.88 298	98.59 205	99.81 278	99.43 122	84.81 386	99.96 119	90.34 396	98.55 132	99.52 238	97.00 286	98.28 198	99.98 109

jajsoiax		97.07 248	96.79 249	97.89 280	97.28 366	97.12 288	99.95 251	99.19 293	96.55 237	97.31 325	99.69 269	87.35 329	98.91 282	98.70 221	95.12 278	97.66 328

MIMVSNet		97.06 249	96.73 250	98.05 268	99.38 253	96.64 302	98.47 389	99.35 223	93.41 336	99.48 197	98.53 358	89.66 299	97.70 367	94.16 333	98.11 207	99.80 216

X-MVStestdata		97.04 250	96.06 279	99.98 23	100.00 1	99.94 40	100.00 1	99.75 52	98.67 67	100.00 1	66.97 407	99.16 82	100.00 1	100.00 1	100.00 1	100.00 1

h-mvs33		97.03 251	96.53 257	98.51 227	99.79 142	95.90 309	99.45 332	99.45 102	98.21 92	100.00 1	99.78 257	97.49 168	99.99 94	99.72 131	74.92 390	99.65 239

VPA-MVSNet		97.03 251	96.43 263	98.82 210	98.64 309	99.32 146	99.38 340	99.47 79	96.73 222	98.91 239	98.94 341	87.00 331	99.40 254	99.23 192	89.59 345	97.76 261

WB-MVSnew		97.02 253	97.24 237	96.37 331	99.44 240	97.36 277	100.00 1	99.43 122	96.12 262	99.35 210	99.89 232	93.60 244	98.42 329	88.91 375	98.39 187	93.33 390

mvs_tets		97.00 254	96.69 251	97.94 276	97.41 365	97.27 283	99.60 317	99.18 300	96.51 241	97.35 324	99.69 269	86.53 335	98.91 282	98.84 213	95.09 280	97.65 333

gg-mvs-nofinetune		96.95 255	96.10 277	99.50 149	99.41 244	99.36 144	99.07 379	99.52 72	83.69 388	99.96 119	83.60 404	100.00 1	99.20 265	99.68 145	99.99 97	99.96 122

Anonymous20240529		96.93 256	96.22 273	99.05 195	99.79 142	97.30 282	99.16 367	99.47 79	88.51 376	98.69 255	100.00 1	83.50 357	100.00 1	99.83 113	97.02 244	99.83 188

DU-MVS		96.93 256	96.49 260	98.22 246	98.31 322	98.41 212	100.00 1	99.37 206	96.41 246	97.76 308	99.65 278	92.14 267	98.50 323	97.98 254	86.84 366	97.75 272

Patchmtry		96.81 258	96.37 266	98.14 254	99.31 256	98.55 206	98.91 382	99.00 355	90.45 366	97.92 303	98.98 336	96.94 190	98.12 343	94.27 330	91.53 326	97.75 272

hse-mvs2		96.79 259	96.38 265	98.04 270	99.68 159	95.54 313	99.81 278	99.42 138	98.21 92	100.00 1	99.80 254	97.49 168	99.46 249	99.72 131	73.27 393	99.12 249

ACMH	96.25 11	96.77 260	96.62 254	97.21 304	98.96 291	94.43 340	99.64 311	99.33 231	97.43 169	96.55 343	99.97 195	83.52 356	99.54 232	99.07 203	95.13 277	97.66 328
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IterMVS		96.76 261	96.46 262	97.63 286	99.41 244	96.89 294	99.99 210	99.13 316	94.74 302	97.59 319	99.66 276	89.63 302	98.28 335	95.71 309	92.31 314	97.72 308
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CP-MVSNet		96.73 262	96.25 271	98.18 249	98.21 330	98.67 200	99.77 289	99.32 233	95.06 294	97.20 328	99.65 278	90.10 291	98.19 338	98.06 252	88.90 353	97.66 328

WR-MVS_H		96.73 262	96.32 270	97.95 275	98.26 326	97.88 257	99.72 301	99.43 122	95.06 294	96.99 331	98.68 353	93.02 254	98.53 321	97.43 274	88.33 358	97.43 352

IterMVS-SCA-FT		96.72 264	96.42 264	97.62 288	99.40 249	96.83 296	99.99 210	99.14 312	94.65 305	97.55 320	99.72 261	89.65 300	98.31 333	95.62 313	92.05 317	97.73 301

v2v482		96.70 265	96.18 274	98.27 242	98.04 336	98.39 215	100.00 1	99.13 316	94.19 320	98.58 262	99.08 326	90.48 287	98.67 305	95.69 310	90.44 340	97.75 272

test_vis1_n		96.69 266	95.81 289	99.32 177	99.14 266	97.98 248	99.97 240	98.98 358	98.45 77	100.00 1	100.00 1	66.44 393	99.99 94	99.78 125	99.57 156	100.00 1

V42		96.65 267	96.16 276	98.11 259	98.17 333	98.23 230	99.99 210	99.09 331	93.97 323	98.74 253	99.05 329	91.09 277	98.82 293	95.46 315	89.90 342	97.27 358

EU-MVSNet		96.63 268	96.53 257	96.94 314	97.59 354	96.87 295	99.76 291	99.47 79	96.35 251	96.85 336	99.78 257	92.57 263	96.27 381	95.33 316	91.08 333	97.68 323

NR-MVSNet		96.63 268	96.04 280	98.38 234	98.31 322	98.98 183	99.22 360	99.35 223	95.87 267	94.43 366	99.65 278	92.73 260	98.40 330	96.78 295	88.05 359	97.75 272

XVG-ACMP-BASELINE		96.60 270	96.52 259	96.84 320	98.41 317	93.29 351	99.99 210	99.32 233	97.76 132	98.51 269	99.29 317	81.95 363	99.54 232	98.40 236	95.03 281	97.68 323

VDD-MVS		96.58 271	95.99 282	98.34 237	99.52 216	95.33 314	99.18 361	99.38 203	96.64 232	99.77 180	100.00 1	72.51 387	100.00 1	100.00 1	96.94 246	99.70 232

tt0805		96.52 272	96.23 272	97.40 293	99.30 259	93.55 347	99.32 345	99.45 102	96.75 218	97.88 305	99.99 182	79.99 370	99.59 215	97.39 277	95.98 253	99.06 251

LCM-MVSNet-Re		96.52 272	97.21 239	94.44 349	99.27 260	85.80 382	99.85 272	96.61 399	95.98 264	92.75 373	98.48 360	93.97 239	97.55 368	99.58 165	98.43 183	99.98 109

our_test_3		96.51 274	96.35 267	96.98 312	97.61 352	95.05 318	99.98 234	99.01 354	94.68 303	96.77 340	99.06 327	95.87 210	98.14 341	91.81 351	92.37 313	97.75 272

MVP-Stereo		96.51 274	96.48 261	96.60 326	95.65 380	94.25 341	98.84 384	98.16 376	95.85 271	95.23 357	99.04 330	92.54 264	99.13 267	92.98 343	99.98 107	96.43 374
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
v1144		96.51 274	95.97 284	98.13 257	97.98 339	98.04 245	99.99 210	99.08 332	93.51 335	98.62 260	98.98 336	90.98 281	98.62 309	93.79 337	90.79 336	97.74 295

ACMH+	96.20 13	96.49 277	96.33 269	97.00 310	99.06 277	93.80 345	99.81 278	99.31 238	97.32 178	95.89 354	99.97 195	82.62 361	99.54 232	98.34 240	94.63 290	97.65 333

TranMVSNet+NR-MVSNet		96.45 278	96.01 281	97.79 283	98.00 338	97.62 268	100.00 1	99.35 223	95.98 264	97.31 325	99.64 282	90.09 292	98.00 355	96.89 290	86.80 369	97.75 272

ET-MVSNet_ETH3D		96.41 279	95.48 309	99.20 189	99.81 127	99.75 91	100.00 1	99.02 352	97.30 182	78.33 396	100.00 1	97.73 157	97.94 358	99.70 137	87.41 363	99.92 145

VPNet		96.41 279	95.76 294	98.33 238	98.61 310	98.30 226	99.48 329	99.45 102	96.98 199	98.87 243	99.88 234	81.57 364	98.93 280	99.22 194	87.82 361	97.76 261

PVSNet_0	93.57 19	96.41 279	95.74 295	98.41 232	99.84 117	95.22 316	100.00 1	100.00 1	98.08 105	97.55 320	99.78 257	84.40 349	100.00 1	100.00 1	81.99 381	100.00 1

v144192		96.40 282	95.81 289	98.17 251	97.89 342	98.11 238	99.99 210	99.06 344	93.39 337	98.75 252	99.09 325	90.43 288	98.66 306	93.10 342	90.55 339	97.75 272

VDDNet		96.39 283	95.55 304	98.90 206	99.27 260	97.45 273	99.15 369	99.92 34	91.28 359	99.98 109	100.00 1	73.55 383	100.00 1	99.85 109	96.98 245	99.24 246

tfpnnormal		96.36 284	95.69 300	98.37 235	98.55 312	98.71 197	99.69 306	99.45 102	93.16 344	96.69 342	99.71 263	88.44 318	98.99 275	94.17 331	91.38 330	97.41 353

v8		96.35 285	95.73 296	98.21 248	98.11 334	98.23 230	99.94 256	99.07 336	92.66 352	98.29 281	99.00 335	91.46 271	98.77 298	94.17 331	88.83 355	97.62 339

PS-CasMVS		96.34 286	95.78 293	98.03 271	98.18 332	98.27 228	99.71 302	99.32 233	94.75 300	96.82 337	99.65 278	86.98 332	98.15 340	97.74 263	88.85 354	97.66 328

LTVRE_ROB	95.29 16	96.32 287	96.10 277	96.99 311	98.55 312	93.88 344	99.45 332	99.28 252	94.50 310	96.46 344	99.52 304	84.86 347	99.48 243	97.26 281	95.03 281	97.59 343
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		96.29 288	95.70 297	98.07 260	99.80 138	97.49 271	99.15 369	99.40 188	89.11 373	97.75 311	99.45 309	88.93 310	98.98 276	98.26 246	89.47 347	97.73 301

v148		96.29 288	95.84 288	97.63 286	97.74 347	96.53 303	100.00 1	99.07 336	93.52 334	98.01 298	99.42 311	91.22 273	98.60 312	96.37 303	87.22 365	97.75 272

AUN-MVS		96.26 290	95.67 301	98.06 264	99.68 159	95.60 312	99.82 277	99.42 138	96.78 215	99.88 159	99.80 254	94.84 228	99.47 245	97.48 272	73.29 392	99.12 249

FMVSNet2		96.22 291	95.60 303	98.06 264	99.53 209	98.33 222	99.45 332	99.27 260	93.71 326	98.03 295	98.84 346	84.23 351	98.10 348	93.97 335	93.40 300	97.73 301

LF4IMVS		96.19 292	96.18 274	96.23 334	98.26 326	92.09 361	100.00 1	97.89 386	97.82 126	97.94 301	99.87 235	82.71 360	99.38 255	97.41 275	93.71 296	97.20 359

v1192		96.18 293	95.49 307	98.26 244	98.01 337	98.15 235	99.99 210	99.08 332	93.36 338	98.54 265	98.97 339	89.47 303	98.89 285	91.15 356	90.82 335	97.75 272

testgi		96.18 293	95.93 285	96.93 315	98.98 289	94.20 343	100.00 1	99.07 336	97.16 188	96.06 351	99.86 237	84.08 354	97.79 364	90.38 363	97.80 225	98.81 253

Syy-MVS		96.17 295	96.57 256	95.00 343	99.50 225	87.37 380	100.00 1	99.57 68	96.23 256	98.07 292	100.00 1	92.41 265	97.81 361	85.34 381	97.96 212	99.82 193

ppachtmachnet_test		96.17 295	95.89 286	97.02 309	97.61 352	95.24 315	99.99 210	99.24 273	93.31 340	96.71 341	99.62 290	94.34 235	98.07 350	89.87 365	92.30 315	97.75 272

v1921920		96.16 297	95.50 305	98.14 254	97.88 344	97.96 251	99.99 210	99.07 336	93.33 339	98.60 261	99.24 319	89.37 304	98.71 303	91.28 354	90.74 337	97.75 272

Baseline_NR-MVSNet		96.16 297	95.70 297	97.56 291	98.28 325	96.79 298	100.00 1	97.86 387	91.93 356	97.63 314	99.47 308	92.14 267	98.35 332	97.13 282	86.83 368	97.54 346

v10		96.14 299	95.50 305	98.07 260	98.19 331	97.96 251	99.83 274	99.07 336	92.10 355	98.07 292	98.94 341	91.07 278	98.61 310	92.41 349	89.82 343	97.63 337

OurMVSNet-221017-0		96.14 299	95.98 283	96.62 325	97.49 360	93.44 349	99.92 259	98.16 376	95.86 269	97.65 313	99.95 217	85.71 343	98.78 295	94.93 323	94.18 294	97.64 336

GBi-Net		96.07 301	95.80 291	96.89 317	99.53 209	94.87 320	99.18 361	99.27 260	93.71 326	98.53 266	98.81 347	84.23 351	98.07 350	95.31 317	93.60 297	97.72 308

test1		96.07 301	95.80 291	96.89 317	99.53 209	94.87 320	99.18 361	99.27 260	93.71 326	98.53 266	98.81 347	84.23 351	98.07 350	95.31 317	93.60 297	97.72 308

v7n		96.06 303	95.42 313	97.99 274	97.58 355	97.35 278	99.86 270	99.11 324	92.81 351	97.91 304	99.49 306	90.99 280	98.92 281	92.51 346	88.49 357	97.70 317

PEN-MVS		96.01 304	95.48 309	97.58 290	97.74 347	97.26 284	99.90 263	99.29 246	94.55 307	96.79 338	99.55 301	87.38 327	97.84 360	96.92 289	87.24 364	97.65 333

v1240		95.96 305	95.25 314	98.07 260	97.91 341	97.87 259	99.96 245	99.07 336	93.24 342	98.64 259	98.96 340	88.98 309	98.61 310	89.58 369	90.92 334	97.75 272

pmmvs5		95.94 306	95.61 302	96.95 313	97.42 363	94.66 332	100.00 1	98.08 380	93.60 332	97.05 330	99.43 310	87.02 330	98.46 327	95.76 307	92.12 316	97.72 308

PatchT		95.90 307	94.95 321	98.75 215	99.03 279	98.39 215	99.08 377	99.32 233	85.52 384	99.96 119	94.99 388	97.94 147	98.05 354	80.20 392	98.47 181	99.81 202

USDC		95.90 307	95.70 297	96.50 328	98.60 311	92.56 359	100.00 1	98.30 374	97.77 130	96.92 332	99.94 222	81.25 367	99.45 250	93.54 339	94.96 285	97.49 349

pm-mvs1		95.76 309	95.01 319	98.00 272	98.23 328	97.45 273	99.24 353	99.04 349	93.13 345	95.93 353	99.72 261	86.28 336	98.84 290	95.62 313	87.92 360	97.72 308

SixPastTwentyTwo		95.71 310	95.49 307	96.38 330	97.42 363	93.01 352	99.84 273	98.23 375	94.75 300	95.98 352	99.97 195	85.35 345	98.43 328	94.71 325	93.17 302	97.69 321

MS-PatchMatch		95.66 311	95.87 287	95.05 341	97.80 346	89.25 374	98.88 383	99.30 242	96.35 251	96.86 335	99.01 334	81.35 366	99.43 251	93.30 341	99.98 107	96.46 373

DTE-MVSNet		95.52 312	94.99 320	97.08 306	97.49 360	96.45 304	100.00 1	99.25 268	93.82 325	96.17 349	99.57 299	87.81 322	97.18 369	94.57 326	86.26 371	97.62 339

TinyColmap		95.50 313	95.12 318	96.64 324	98.69 307	93.00 353	99.40 338	97.75 389	96.40 248	96.14 350	99.87 235	79.47 371	99.50 241	93.62 338	94.72 288	97.40 354

K. test v3		95.46 314	95.14 317	96.40 329	97.53 357	93.40 350	99.99 210	99.23 277	95.49 286	92.70 374	99.73 260	84.26 350	98.12 343	93.94 336	93.38 301	97.68 323

FMVSNet5		95.32 315	95.43 312	94.99 344	99.39 252	92.99 354	99.25 352	99.24 273	90.45 366	97.44 323	98.45 361	95.78 212	94.39 390	87.02 377	91.88 321	97.59 343

UniMVSNet_ETH3D		95.28 316	94.41 322	97.89 280	98.91 295	95.14 317	99.13 371	99.35 223	92.11 354	97.17 329	99.66 276	70.28 390	99.36 256	97.88 259	95.18 273	99.16 247

RPMNet		95.26 317	93.82 325	99.56 144	99.31 256	98.86 188	99.13 371	99.42 138	79.82 393	99.96 119	95.13 386	95.69 214	99.98 118	77.54 396	98.40 185	99.84 185

DSMNet-mixed		95.18 318	95.21 316	95.08 340	96.03 375	90.21 372	99.65 310	93.64 405	92.91 347	98.34 277	97.40 377	90.05 294	95.51 387	91.02 357	97.86 219	99.51 243

test_fmvs2		95.17 319	95.23 315	95.01 342	98.95 293	88.99 376	99.99 210	97.77 388	97.79 128	98.58 262	99.70 266	73.36 384	99.34 259	95.88 306	95.03 281	96.70 370

TransMVSNet (Re)		94.78 320	93.72 326	97.93 278	98.34 319	97.88 257	99.23 358	97.98 384	91.60 357	94.55 363	99.71 263	87.89 321	98.36 331	89.30 371	84.92 372	97.56 345

FMVSNet1		94.45 321	93.63 328	96.89 317	98.87 301	94.87 320	99.18 361	99.27 260	90.95 363	97.31 325	98.81 347	72.89 386	98.07 350	92.61 344	92.81 306	97.72 308

test_0402		94.35 322	93.70 327	96.32 332	97.92 340	93.60 346	99.61 316	98.85 367	88.19 379	94.68 362	99.48 307	80.01 369	98.58 316	89.39 370	95.15 276	96.77 368

UnsupCasMVSNet_eth		94.25 323	93.89 324	95.34 339	97.63 350	92.13 360	99.73 299	99.36 212	94.88 297	92.78 371	98.63 355	82.72 359	96.53 377	94.57 326	84.73 373	97.36 355

KD-MVS_2432*1600		94.15 324	93.08 333	97.35 297	99.53 209	97.83 261	99.63 313	99.19 293	92.88 348	96.29 346	97.68 374	98.84 115	96.70 373	89.73 366	63.92 397	97.53 347

miper_refine_blended		94.15 324	93.08 333	97.35 297	99.53 209	97.83 261	99.63 313	99.19 293	92.88 348	96.29 346	97.68 374	98.84 115	96.70 373	89.73 366	63.92 397	97.53 347

MVS-HIRNet		94.12 326	92.73 339	98.29 241	99.33 255	95.95 306	99.38 340	99.19 293	74.54 396	98.26 285	86.34 400	86.07 338	99.06 270	91.60 353	99.87 131	99.85 184

new_pmnet		94.11 327	93.47 330	96.04 336	96.60 372	92.82 355	99.97 240	98.91 363	90.21 369	95.26 356	98.05 372	85.89 341	98.14 341	84.28 383	92.01 318	97.16 360

pmmvs6		93.64 328	92.87 336	95.94 337	97.47 362	91.41 366	98.92 381	99.02 352	87.84 380	95.01 359	99.61 292	77.24 378	98.77 298	94.33 329	86.41 370	97.63 337

Patchmatch-RL test		93.49 329	93.63 328	93.05 360	91.78 391	83.41 386	98.21 391	96.95 396	91.58 358	91.05 376	97.64 376	99.40 57	95.83 385	94.11 334	81.95 382	99.91 147

Anonymous20231206		93.45 330	93.17 332	94.30 352	95.00 385	89.69 373	99.98 234	98.43 373	93.30 341	94.50 365	98.59 356	90.52 285	95.73 386	77.46 397	90.73 338	97.48 351

Anonymous20240521		93.29 331	92.76 338	94.90 347	95.64 381	91.27 367	99.97 240	98.82 368	87.04 381	94.71 361	98.19 367	83.86 355	96.80 372	84.04 384	92.56 312	96.64 371

dmvs_testset		93.27 332	95.48 309	86.65 372	98.74 306	68.42 401	99.92 259	98.91 363	96.19 260	93.28 370	100.00 1	91.06 279	91.67 397	89.64 368	91.54 325	99.86 183

test20.03		93.11 333	92.85 337	93.88 357	95.19 384	91.83 362	100.00 1	98.87 366	93.68 329	92.76 372	98.88 345	89.20 306	92.71 395	77.88 395	89.19 351	97.09 362

test_vis1_rt		93.10 334	92.93 335	93.58 358	99.63 181	85.07 383	99.99 210	93.71 404	97.49 163	90.96 377	97.10 378	60.40 395	99.95 149	99.24 191	97.90 217	95.72 380

APD_test1		93.07 335	94.14 323	89.85 366	99.18 264	72.49 394	99.76 291	98.90 365	92.86 350	96.35 345	99.94 222	75.56 380	99.91 168	86.73 378	97.98 210	97.15 361

EG-PatchMatch MVS		92.94 336	92.49 340	94.29 353	95.87 377	87.07 381	99.07 379	98.11 379	93.19 343	88.98 383	98.66 354	70.89 388	99.08 269	92.43 348	95.21 271	96.72 369

MDA-MVSNet_test_wron		92.61 337	91.09 345	97.19 305	96.71 371	97.26 284	100.00 1	99.14 312	88.61 375	67.90 402	98.32 366	89.03 307	96.57 376	90.47 362	89.59 345	97.74 295

YYNet1		92.44 338	90.92 346	97.03 308	96.20 373	97.06 291	99.99 210	99.14 312	88.21 378	67.93 401	98.43 363	88.63 313	96.28 380	90.64 358	89.08 352	97.74 295

MIMVSNet1		91.96 339	91.20 342	94.23 354	94.94 386	91.69 364	99.34 344	99.22 280	88.23 377	94.18 367	98.45 361	75.52 381	93.41 394	79.37 393	91.49 327	97.60 342

TDRefinement		91.93 340	90.48 348	96.27 333	81.60 404	92.65 358	99.10 374	97.61 392	93.96 324	93.77 368	99.85 242	80.03 368	99.53 237	97.82 261	70.59 394	96.63 372

OpenMVS_ROB	88.34 20	91.89 341	91.12 343	94.19 355	95.55 382	87.63 379	99.26 351	98.03 381	86.61 383	90.65 381	96.82 380	70.14 391	98.78 295	86.54 379	96.50 252	96.15 375

N_pmnet		91.88 342	93.37 331	87.40 371	97.24 367	66.33 404	99.90 263	91.05 407	89.77 372	95.65 355	98.58 357	90.05 294	98.11 345	85.39 380	92.72 307	97.75 272

pmmvs-eth3d		91.73 343	90.67 347	94.92 346	91.63 393	92.71 357	99.90 263	98.54 372	91.19 360	88.08 385	95.50 384	79.31 373	96.13 382	90.55 361	81.32 384	95.91 379

MDA-MVSNet-bldmvs		91.65 344	89.94 352	96.79 323	96.72 370	96.70 300	99.42 337	98.94 360	88.89 374	66.97 404	98.37 364	81.43 365	95.91 384	89.24 372	89.46 348	97.75 272

KD-MVS_self_test		91.16 345	90.09 350	94.35 351	94.44 387	91.27 367	99.74 294	99.08 332	90.82 364	94.53 364	94.91 389	86.11 337	94.78 389	82.67 386	68.52 395	96.99 364

CL-MVSNet_self_test		91.07 346	90.35 349	93.24 359	93.27 388	89.16 375	99.55 322	99.25 268	92.34 353	95.23 357	97.05 379	88.86 312	93.59 393	80.67 390	66.95 396	96.96 365

test_method		91.04 347	91.10 344	90.85 363	98.34 319	77.63 390	100.00 1	98.93 362	76.69 394	96.25 348	98.52 359	70.44 389	97.98 356	89.02 374	91.74 322	96.92 366

CMPMVS	66.12 22	90.65 348	92.04 341	86.46 373	96.18 374	66.87 403	98.03 392	99.38 203	83.38 389	85.49 391	99.55 301	77.59 376	98.80 294	94.44 328	94.31 293	93.72 388
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs3		90.62 349	89.36 355	94.40 350	90.53 398	91.49 365	100.00 1	96.73 397	84.21 387	93.65 369	96.65 381	82.56 362	94.83 388	82.28 387	77.62 389	96.89 367

new-patchmatchnet		90.30 350	89.46 354	92.84 361	90.77 396	88.55 378	99.83 274	98.80 369	90.07 371	87.86 386	95.00 387	78.77 374	94.30 391	84.86 382	79.15 386	95.68 382

UnsupCasMVSNet_bld		89.50 351	88.00 357	93.99 356	95.30 383	88.86 377	98.52 388	99.28 252	85.50 385	87.80 387	94.11 390	61.63 394	96.96 371	90.63 359	79.26 385	96.15 375

mvsany_test3		89.36 352	88.96 356	90.56 364	91.95 390	78.97 389	99.74 294	96.59 400	96.84 210	89.25 382	96.07 382	52.59 397	97.11 370	95.17 320	82.44 380	95.58 383

PM-MVS		88.39 353	87.41 358	91.31 362	91.73 392	82.02 388	99.79 283	96.62 398	91.06 362	90.71 380	95.73 383	48.60 399	95.96 383	90.56 360	81.91 383	95.97 378

WB-MVS		88.24 354	90.09 350	82.68 379	91.56 394	69.51 399	100.00 1	98.73 370	90.72 365	87.29 388	98.12 368	92.87 256	85.01 401	62.19 402	89.34 349	93.54 389

SSC-MVS		87.61 355	89.47 353	82.04 380	90.63 397	68.77 400	99.99 210	98.66 371	90.34 368	86.70 389	98.08 369	92.72 261	84.12 402	59.41 405	88.71 356	93.22 393

test_fmvs3		87.19 356	87.02 359	87.71 370	92.69 389	76.64 391	99.96 245	97.27 393	93.55 333	90.82 379	94.03 391	38.00 405	92.19 396	93.49 340	83.35 379	94.32 385

test_f		86.87 357	86.06 360	89.28 367	91.45 395	76.37 392	99.87 269	97.11 394	91.10 361	88.46 384	93.05 393	38.31 404	96.66 375	91.77 352	83.46 378	94.82 384

Gipuma		84.73 358	83.50 363	88.40 369	97.50 358	82.21 387	88.87 398	99.05 346	65.81 398	85.71 390	90.49 395	53.70 396	96.31 379	78.64 394	91.74 322	86.67 397
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
testf1		84.40 359	84.79 361	83.23 377	95.71 378	58.71 410	98.79 385	97.75 389	81.58 390	84.94 392	98.07 370	45.33 401	97.73 365	77.09 398	83.85 375	93.24 391

APD_test2		84.40 359	84.79 361	83.23 377	95.71 378	58.71 410	98.79 385	97.75 389	81.58 390	84.94 392	98.07 370	45.33 401	97.73 365	77.09 398	83.85 375	93.24 391

testmvs		80.17 361	81.95 364	74.80 384	58.54 411	59.58 409	100.00 1	87.14 410	76.09 395	99.61 191	100.00 1	67.06 392	74.19 407	98.84 213	50.30 401	90.64 396

test_vis3_rt		79.61 362	78.19 367	83.86 376	88.68 399	69.56 398	99.81 278	82.19 412	86.78 382	68.57 400	84.51 403	25.06 409	98.26 336	89.18 373	78.94 387	83.75 400

EGC-MVSNET		79.46 363	74.04 371	95.72 338	96.00 376	92.73 356	99.09 376	99.04 349	5.08 408	16.72 408	98.71 351	73.03 385	98.74 301	82.05 388	96.64 249	95.69 381

test123		79.44 364	79.23 366	80.05 382	80.03 405	71.72 395	100.00 1	77.93 413	62.52 399	94.81 360	99.69 269	78.21 375	74.53 406	92.57 345	27.33 406	93.90 386

PMMVS2		79.15 365	77.28 368	84.76 375	82.34 403	72.66 393	99.70 304	95.11 403	71.68 397	84.78 394	90.87 394	32.05 407	89.99 398	75.53 400	63.45 399	91.64 394

LCM-MVSNet		79.01 366	76.93 369	85.27 374	78.28 406	68.01 402	96.57 395	98.03 381	55.10 402	82.03 395	93.27 392	31.99 408	93.95 392	82.72 385	74.37 391	93.84 387

FPMVS		77.92 367	79.45 365	73.34 386	76.87 407	46.81 413	98.24 390	99.05 346	59.89 401	73.55 397	98.34 365	36.81 406	86.55 399	80.96 389	91.35 331	86.65 398

tmp_tt		75.80 368	74.26 370	80.43 381	52.91 413	53.67 412	87.42 400	97.98 384	61.80 400	67.04 403	100.00 1	76.43 379	96.40 378	96.47 299	28.26 405	91.23 395

E-PMN		70.72 369	70.06 372	72.69 387	83.92 402	65.48 406	99.95 251	92.72 406	49.88 404	72.30 398	86.26 401	47.17 400	77.43 404	53.83 406	44.49 402	75.17 404

EMVS		69.88 370	69.09 373	72.24 388	84.70 401	65.82 405	99.96 245	87.08 411	49.82 405	71.51 399	84.74 402	49.30 398	75.32 405	50.97 407	43.71 403	75.59 403

MVE	68.59 21	67.22 371	64.68 375	74.84 383	74.67 409	62.32 408	95.84 396	90.87 408	50.98 403	58.72 405	81.05 405	12.20 413	78.95 403	61.06 404	56.75 400	83.24 401
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ANet_high		66.05 372	63.44 376	73.88 385	61.14 410	63.45 407	95.68 397	87.18 409	79.93 392	47.35 406	80.68 406	22.35 410	72.33 408	61.24 403	35.42 404	85.88 399

PMVS	60.66 23	65.98 373	65.05 374	68.75 389	55.06 412	38.40 414	88.19 399	96.98 395	48.30 406	44.82 407	88.52 398	12.22 412	86.49 400	67.58 401	83.79 377	81.35 402
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
wuyk23d		28.28 374	29.73 378	23.92 390	75.89 408	32.61 415	66.50 401	12.88 414	16.09 407	14.59 409	16.59 408	12.35 411	32.36 409	39.36 408	13.36 407	6.79 405

cdsmvs_eth3d_5k		24.41 375	32.55 377	0.00 391	0.00 414	0.00 416	0.00 402	99.39 201	0.00 409	0.00 410	100.00 1	93.55 245	0.00 410	0.00 409	0.00 408	0.00 406

ab-mvs-re		8.33 376	11.11 379	0.00 391	0.00 414	0.00 416	0.00 402	0.00 415	0.00 409	0.00 410	100.00 1	0.00 414	0.00 410	0.00 409	0.00 408	0.00 406

pcd_1.5k_mvsjas		8.24 377	10.99 380	0.00 391	0.00 414	0.00 416	0.00 402	0.00 415	0.00 409	0.00 410	0.14 410	98.75 122	0.00 410	0.00 409	0.00 408	0.00 406

test_blank		0.07 378	0.09 381	0.00 391	0.00 414	0.00 416	0.00 402	0.00 415	0.00 409	0.00 410	0.79 409	0.00 414	0.00 410	0.00 409	0.00 408	0.00 406

uanet_test		0.01 379	0.02 382	0.00 391	0.00 414	0.00 416	0.00 402	0.00 415	0.00 409	0.00 410	0.14 410	0.00 414	0.00 410	0.00 409	0.00 408	0.00 406

DCPMVS		0.01 379	0.02 382	0.00 391	0.00 414	0.00 416	0.00 402	0.00 415	0.00 409	0.00 410	0.14 410	0.00 414	0.00 410	0.00 409	0.00 408	0.00 406

sosnet-low-res		0.01 379	0.02 382	0.00 391	0.00 414	0.00 416	0.00 402	0.00 415	0.00 409	0.00 410	0.14 410	0.00 414	0.00 410	0.00 409	0.00 408	0.00 406

sosnet		0.01 379	0.02 382	0.00 391	0.00 414	0.00 416	0.00 402	0.00 415	0.00 409	0.00 410	0.14 410	0.00 414	0.00 410	0.00 409	0.00 408	0.00 406

uncertanet		0.01 379	0.02 382	0.00 391	0.00 414	0.00 416	0.00 402	0.00 415	0.00 409	0.00 410	0.14 410	0.00 414	0.00 410	0.00 409	0.00 408	0.00 406

Regformer		0.01 379	0.02 382	0.00 391	0.00 414	0.00 416	0.00 402	0.00 415	0.00 409	0.00 410	0.14 410	0.00 414	0.00 410	0.00 409	0.00 408	0.00 406

uanet		0.01 379	0.02 382	0.00 391	0.00 414	0.00 416	0.00 402	0.00 415	0.00 409	0.00 410	0.14 410	0.00 414	0.00 410	0.00 409	0.00 408	0.00 406

WAC-MVS						97.98 248								95.74 308

FOURS1					100.00 1	99.97 21	100.00 1	99.42 138	98.52 74	100.00 1

MSC_two_6792asdad				100.00 1	100.00 1	100.00 1		99.42 138					100.00 1	100.00 1	100.00 1	100.00 1

PC_three_1452									98.80 57	100.00 1	100.00 1	99.54 27	100.00 1	100.00 1	100.00 1	100.00 1

No_MVS				100.00 1	100.00 1	100.00 1		99.42 138					100.00 1	100.00 1	100.00 1	100.00 1

test_one_0601					100.00 1	99.99 5		99.42 138	98.72 64	100.00 1	100.00 1	99.60 18

eth-test2					0.00 414

eth-test					0.00 414

ZD-MVS					100.00 1	99.98 17		99.80 43	97.31 180	100.00 1	100.00 1	99.32 63	99.99 94	100.00 1	100.00 1

RE-MVS-def			99.55 56		99.99 49	99.91 51	100.00 1	99.42 138	97.62 144	100.00 1	100.00 1	98.94 106		99.99 61	100.00 1	100.00 1

IU-MVS					100.00 1	99.99 5		99.42 138	99.12 6	100.00 1				100.00 1	100.00 1	100.00 1

OPU-MVS				100.00 1	100.00 1	100.00 1	100.00 1				100.00 1	99.54 27	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_TWO								99.42 138	99.03 20	100.00 1	100.00 1	99.56 24	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_ONE					100.00 1	99.99 5		99.42 138	99.03 20	100.00 1	100.00 1	99.50 38	100.00 1

9.14			99.57 49		99.99 49		100.00 1	99.42 138	97.54 155	100.00 1	100.00 1	99.15 84	99.99 94	100.00 1	100.00 1

save fliter					99.99 49	99.93 43	100.00 1	99.42 138	98.93 38

test_0728_THIRD									98.79 60	100.00 1	100.00 1	99.61 17	100.00 1	100.00 1	100.00 1	100.00 1

test_0728_SECOND				100.00 1	99.99 49	99.99 5	100.00 1	99.42 138					100.00 1	100.00 1	100.00 1	100.00 1

test0726					100.00 1	99.99 5	100.00 1	99.42 138	99.04 15	100.00 1	100.00 1	99.53 30

GSMVS																99.91 147

test_part2					100.00 1	99.99 5				100.00 1

sam_mvs1												99.29 71				99.91 147

sam_mvs												99.33 60

ambc				88.45 368	86.84 400	70.76 397	97.79 394	98.02 383		90.91 378	95.14 385	38.69 403	98.51 322	94.97 322	84.23 374	96.09 377

MTGPA								99.42 138

test_post1							99.32 345				88.24 399	99.33 60	99.59 215	98.31 241

test_post											89.05 397	99.49 40	99.59 215

patchmatchnet-post											97.79 373	99.41 56	99.54 232

GG-mvs-BLEND				99.59 137	99.54 206	99.49 127	99.17 366	99.52 72		99.96 119	99.68 273	100.00 1	99.33 260	99.71 134	99.99 97	99.96 122

MTMP							100.00 1	99.18 300

gm-plane-assit					99.52 216	97.26 284			95.86 269		100.00 1		99.43 251	98.76 218

test9_res														100.00 1	100.00 1	100.00 1

TEST9					100.00 1	99.95 32	100.00 1	99.42 138	97.65 140	100.00 1	100.00 1	99.53 30	99.97 125

test_8					100.00 1	99.91 51	100.00 1	99.42 138	97.70 135	100.00 1	100.00 1	99.51 34	99.98 118

agg_prior2														100.00 1	100.00 1	100.00 1

agg_prior					100.00 1	99.88 72		99.42 138		100.00 1			99.97 125

TestCases				98.99 200	99.93 101	97.35 278		99.40 188	97.08 194	99.09 225	99.98 187	93.37 246	99.95 149	96.94 287	99.84 137	99.68 234

test_prior4						99.93 43	100.00 1

test_prior2							100.00 1		98.82 55	100.00 1	100.00 1	99.47 44		100.00 1	100.00 1

test_prior				99.90 71	100.00 1	99.75 91		99.73 56					99.97 125			100.00 1

旧先验2							100.00 1		98.11 104	100.00 1			100.00 1	99.67 148

新几何2							100.00 1

新几何1				99.99 12	100.00 1	99.96 24		99.81 42	97.89 121	100.00 1	100.00 1	99.20 79	100.00 1	97.91 258	100.00 1	100.00 1

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

无先验							100.00 1	99.80 43	97.98 112				100.00 1	99.33 183		100.00 1

原ACMM2							100.00 1

原ACMM1				99.93 66	100.00 1	99.80 87		99.66 63	98.18 95	100.00 1	100.00 1	99.43 51	100.00 1	99.50 174	100.00 1	100.00 1

test222					99.99 49	99.90 58	100.00 1	99.69 62	97.66 139	100.00 1	100.00 1	99.30 70			100.00 1	100.00 1

testdata2													100.00 1	97.36 278

segment_acmp												99.55 26

testdata				99.66 128	99.99 49	98.97 185		99.73 56	97.96 117	100.00 1	100.00 1	99.42 54	100.00 1	99.28 188	100.00 1	100.00 1

testdata1							100.00 1		98.77 63

test12				99.95 51	99.99 49	99.89 65		99.42 138		100.00 1		99.24 76	99.97 125		100.00 1	100.00 1

plane_prior7					99.00 285	94.78 330

plane_prior6					99.06 277	94.80 326						88.58 316

plane_prior5								99.40 188					99.55 229	99.79 119	95.57 258	97.76 261

plane_prior4											99.97 195

plane_prior3						94.79 329			99.03 20	99.08 227

plane_prior2							100.00 1		99.00 27

plane_prior1					99.02 280

plane_prior						94.80 326	100.00 1		99.03 20						95.58 254

n2								0.00 415

nn								0.00 415

door-mid								96.32 401

lessismore_v0				96.05 335	97.55 356	91.80 363		99.22 280		91.87 375	99.91 229	83.50 357	98.68 304	92.48 347	90.42 341	97.68 323

LGP-MVS_train				97.28 301	98.85 303	94.60 335		99.37 206	97.35 174	98.85 244	99.98 187	86.66 333	99.56 224	99.55 167	95.26 266	97.70 317

test11								99.42 138

door								96.13 402

HQP5-MVS						94.82 323

HQP-NCC					99.07 273		100.00 1		99.04 15	99.17 217

ACMP_Plane					99.07 273		100.00 1		99.04 15	99.17 217

BP-MVS														99.79 119

HQP4-MVS										99.17 217			99.57 220			97.77 259

HQP3-MVS								99.40 188							95.58 254

HQP2-MVS												88.61 314

NP-MVS					99.07 273	94.81 325					99.97 195

MDTV_nov1_ep13_2view						99.24 156	99.56 321		96.31 254	99.96 119		98.86 113		98.92 208		99.89 161

MDTV_nov1_ep13			98.94 128		99.53 209	98.36 220	99.39 339	99.46 94	96.54 238	99.99 103	99.63 286	98.92 109	99.86 176	98.30 244	98.71 174

ACMMP++_ref															94.58 292

ACMMP++															95.17 275

Test By Simon												99.10 87

ITE_SJBPF				96.84 320	98.96 291	93.49 348		98.12 378	98.12 103	98.35 276	99.97 195	84.45 348	99.56 224	95.63 312	95.25 268	97.49 349

DeepMVS_CX				89.98 365	98.90 296	71.46 396		99.18 300	97.61 148	96.92 332	99.83 245	86.07 338	99.83 185	96.02 305	97.65 235	98.65 255

High-resolution multi-view benchmark