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 18	99.11 7	100.00 1	100.00 1	99.60 17	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 60	99.07 9	100.00 1	100.00 1	99.59 20	100.00 1	100.00 1	100.00 1	100.00 1

CHOSEN 280x420		99.85 3	99.87 1	99.80 93	99.99 49	99.97 21	99.97 218	99.98 16	98.96 29	100.00 1	100.00 1	99.96 5	99.42 237	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 55	99.19 5	100.00 1	100.00 1	99.31 63	100.00 1	100.00 1	100.00 1	100.00 1

CNVR-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 5	100.00 1	99.77 47	99.07 9	100.00 1	100.00 1	99.39 56	100.00 1	100.00 1	100.00 1	100.00 1

APDe-MVS		99.84 6	99.78 7	99.99 12	100.00 1	99.98 17	100.00 1	99.44 111	99.06 11	100.00 1	100.00 1	99.56 23	99.99 93	100.00 1	100.00 1	100.00 1

SED-MVS		99.83 7	99.77 9	100.00 1	100.00 1	99.99 5	100.00 1	99.42 127	99.03 19	100.00 1	100.00 1	99.50 37	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	99.42 127	99.04 14	100.00 1	100.00 1	99.53 29	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	99.43 117	99.05 13	100.00 1	100.00 1	99.45 45	99.99 93	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 38	98.88 39	99.96 110	100.00 1	99.21 76	100.00 1	100.00 1	100.00 1	99.99 103

DVP-MVS++		99.81 11	99.75 14	100.00 1	100.00 1	99.99 5	100.00 1	99.42 127	98.79 54	100.00 1	100.00 1	99.54 26	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	99.42 127	98.87 42	100.00 1	100.00 1	99.65 15	99.96 128	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	99.42 127	99.01 25	100.00 1	100.00 1	99.33 58	100.00 1	100.00 1	100.00 1	100.00 1
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
DPE-MVS		99.79 14	99.73 17	99.99 12	99.99 49	99.98 17	100.00 1	99.42 127	98.91 37	100.00 1	100.00 1	99.22 75	100.00 1	100.00 1	100.00 1	100.00 1
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
XVS		99.79 14	99.73 17	99.98 23	100.00 1	99.94 40	100.00 1	99.75 51	98.67 61	100.00 1	100.00 1	99.16 80	100.00 1	100.00 1	100.00 1	100.00 1

SteuartSystems-ACMMP		99.78 16	99.71 20	99.98 23	99.76 143	99.95 32	100.00 1	99.42 127	98.69 59	100.00 1	100.00 1	99.52 32	99.99 93	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 81	99.01 263	99.95 32	100.00 1	99.75 51	99.37 3	99.99 96	100.00 1	99.76 11	99.60 197	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 68	97.99 102	99.99 96	100.00 1	99.72 12	100.00 1	99.96 80	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 75	98.16 88	100.00 1	100.00 1	99.51 33	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	99.73 277	99.52 68	99.06 11	100.00 1	100.00 1	98.80 114	100.00 1	99.95 85	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	99.98 212	99.47 75	99.09 8	100.00 1	100.00 1	98.59 123	100.00 1	99.95 85	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 48	97.95 110	100.00 1	100.00 1	99.31 63	100.00 1	99.99 58	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 48	97.95 110	100.00 1	100.00 1	99.29 69	100.00 1	99.99 58	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 75	97.87 115	100.00 1	100.00 1	99.60 17	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	99.42 127	98.02 100	100.00 1	100.00 1	99.32 61	99.99 93	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 54	97.86 116	100.00 1	100.00 1	99.19 78	100.00 1	99.99 58	100.00 1	100.00 1

API-MVS		99.72 26	99.70 21	99.79 95	99.97 88	99.37 132	99.96 223	99.94 21	98.48 69	100.00 1	100.00 1	98.92 103	100.00 1	100.00 1	100.00 1	100.00 1

CNLPA		99.72 26	99.65 31	99.91 67	99.97 88	99.72 94	100.00 1	99.47 75	98.43 72	99.88 148	100.00 1	99.14 83	100.00 1	99.97 78	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 44	97.97 106	99.97 105	100.00 1	98.97 94	100.00 1	99.94 87	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	99.42 127	97.70 127	100.00 1	100.00 1	99.51 33	99.97 117	100.00 1	100.00 1	100.00 1

MVS_111021_HR		99.71 29	99.63 37	99.93 65	99.95 95	99.83 83	100.00 1	100.00 1	98.89 38	100.00 1	100.00 1	97.85 143	99.95 138	100.00 1	100.00 1	100.00 1

EI-MVSNet-Vis-set		99.70 32	99.64 33	99.87 77	100.00 1	99.64 104	99.98 212	99.44 111	98.35 80	99.99 96	100.00 1	99.04 89	99.96 128	99.98 69	100.00 1	100.00 1

MVS_111021_LR		99.70 32	99.65 31	99.88 76	99.96 93	99.70 99	100.00 1	99.97 17	98.96 29	100.00 1	100.00 1	97.93 140	99.95 138	99.99 58	100.00 1	100.00 1

PLC	98.56 2	99.70 32	99.74 16	99.58 129	100.00 1	98.79 178	100.00 1	99.54 67	98.58 66	99.96 110	100.00 1	99.59 20	100.00 1	100.00 1	100.00 1	99.94 124
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	99.43 117	97.50 153	100.00 1	100.00 1	99.43 50	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 80	99.96 93	99.63 106	100.00 1	99.92 33	99.03 19	99.97 105	100.00 1	97.87 141	99.96 128	100.00 1	99.96 110	100.00 1

EI-MVSNet-UG-set		99.69 35	99.63 37	99.87 77	99.99 49	99.64 104	99.95 229	99.44 111	98.35 80	100.00 1	100.00 1	98.98 93	99.97 117	99.98 69	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 65	97.69 129	100.00 1	100.00 1	99.44 46	100.00 1	99.79 109	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	99.42 127	97.91 112	100.00 1	100.00 1	99.04 89	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 63	97.59 143	100.00 1	100.00 1	98.99 92	99.99 93	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	99.42 127	98.32 82	99.94 135	100.00 1	98.65 120	100.00 1	99.96 80	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	99.42 127	97.53 149	100.00 1	100.00 1	99.27 72	99.97 117	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 84	99.92 48	100.00 1	99.42 127	97.83 117	100.00 1	100.00 1	98.89 106	100.00 1	99.98 69	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	99.42 127	97.77 122	100.00 1	100.00 1	99.07 85	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	99.42 127	97.67 130	100.00 1	100.00 1	99.05 87	99.99 93	100.00 1	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 46	99.55 55	99.97 31	99.99 49	99.91 51	100.00 1	99.48 74	97.54 147	100.00 1	100.00 1	98.97 94	99.99 93	99.98 69	100.00 1	100.00 1

ACMMP		99.65 46	99.57 49	99.89 72	99.99 49	99.66 102	99.75 271	99.73 55	98.16 88	99.75 169	100.00 1	98.90 105	100.00 1	99.96 80	99.88 120	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 57	99.95 51	100.00 1	99.86 77	100.00 1	99.79 44	97.72 125	99.95 133	100.00 1	98.39 129	100.00 1	99.96 80	99.99 97	100.00 1

PS-MVSNAJ		99.64 48	99.57 49	99.85 81	99.78 140	99.81 84	99.95 229	99.42 127	98.38 74	100.00 1	100.00 1	98.75 116	100.00 1	99.88 95	99.99 97	99.74 208

F-COLMAP		99.64 48	99.64 33	99.67 114	99.99 49	99.07 159	100.00 1	99.44 111	98.30 83	99.90 143	100.00 1	99.18 79	99.99 93	99.91 91	100.00 1	99.94 124

SR-MVS-dyc-post		99.63 51	99.52 59	99.97 31	99.99 49	99.91 51	100.00 1	99.42 127	97.62 136	100.00 1	100.00 1	98.65 120	99.99 93	99.99 58	100.00 1	100.00 1

DPM-MVS		99.63 51	99.51 60	100.00 1	99.90 107	100.00 1	100.00 1	99.43 117	99.00 26	100.00 1	100.00 1	99.58 22	100.00 1	97.64 250	100.00 1	100.00 1

EPNet		99.62 53	99.69 22	99.42 146	99.99 49	98.37 202	100.00 1	99.89 36	98.83 48	100.00 1	100.00 1	98.97 94	100.00 1	99.90 92	99.61 144	99.89 151
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DELS-MVS		99.62 53	99.56 54	99.82 86	99.92 103	99.45 123	100.00 1	99.78 46	98.92 36	99.73 170	100.00 1	97.70 149	100.00 1	99.93 88	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 55	99.50 61	99.97 31	99.98 84	99.92 48	100.00 1	99.42 127	97.53 149	99.77 166	100.00 1	98.77 115	100.00 1	99.99 58	100.00 1	99.99 103
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MP-MVS		99.61 55	99.49 63	99.98 23	99.99 49	99.94 40	100.00 1	99.42 127	97.82 118	99.99 96	100.00 1	98.20 132	100.00 1	99.99 58	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 55	99.69 22	99.35 155	99.99 49	98.06 226	100.00 1	99.36 200	99.83 2	100.00 1	100.00 1	98.95 98	99.99 93	100.00 1	99.11 152	100.00 1

HPM-MVS_fast		99.60 58	99.49 63	99.91 67	99.99 49	99.78 87	100.00 1	99.42 127	97.09 182	100.00 1	100.00 1	98.95 98	99.96 128	99.98 69	100.00 1	100.00 1

HPM-MVS		99.59 59	99.50 61	99.89 72	100.00 1	99.70 99	100.00 1	99.42 127	97.46 157	100.00 1	100.00 1	98.60 122	99.96 128	99.99 58	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 60	99.48 66	99.85 81	99.86 114	99.54 110	100.00 1	99.36 200	98.94 34	100.00 1	100.00 1	97.97 138	100.00 1	99.88 95	99.28 149	100.00 1

test_fmvsm_n_1920		99.55 61	99.49 63	99.73 107	99.85 115	99.19 150	100.00 1	99.41 173	98.87 42	100.00 1	100.00 1	97.34 166	100.00 1	99.98 69	99.90 118	100.00 1

WTY-MVS		99.54 62	99.40 68	99.95 51	99.81 124	99.93 43	100.00 1	100.00 1	97.98 104	99.84 151	100.00 1	98.94 100	99.98 112	99.86 99	98.21 189	99.94 124

test_yl		99.51 63	99.37 73	99.95 51	99.82 118	99.90 58	100.00 1	99.47 75	97.48 155	100.00 1	100.00 1	99.80 6	100.00 1	99.98 69	97.75 213	99.94 124

DCV-MVSNet		99.51 63	99.37 73	99.95 51	99.82 118	99.90 58	100.00 1	99.47 75	97.48 155	100.00 1	100.00 1	99.80 6	100.00 1	99.98 69	97.75 213	99.94 124

xiu_mvs_v2_base		99.51 63	99.41 67	99.82 86	99.70 149	99.73 93	99.92 237	99.40 177	98.15 90	100.00 1	100.00 1	98.50 126	100.00 1	99.85 101	99.13 151	99.74 208

HY-MVS	96.53 9	99.50 66	99.35 78	99.96 42	99.81 124	99.93 43	99.64 289	100.00 1	97.97 106	99.84 151	99.85 222	98.94 100	99.99 93	99.86 99	98.23 188	99.95 119

PHI-MVS		99.50 66	99.39 69	99.82 86	100.00 1	99.45 123	100.00 1	99.94 21	96.38 233	100.00 1	100.00 1	98.18 133	100.00 1	100.00 1	100.00 1	100.00 1

CPTT-MVS		99.49 68	99.38 70	99.85 81	100.00 1	99.54 110	100.00 1	99.42 127	97.58 144	99.98 101	100.00 1	97.43 164	100.00 1	99.99 58	100.00 1	100.00 1

MAR-MVS		99.49 68	99.36 76	99.89 72	99.97 88	99.66 102	99.74 272	99.95 18	97.89 113	100.00 1	100.00 1	96.71 186	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 70	99.38 70	99.75 103	99.89 109	99.51 114	99.45 310	100.00 1	98.38 74	99.83 153	100.00 1	98.86 107	99.81 176	99.25 176	98.78 160	99.94 124

PVSNet_Blended		99.48 70	99.36 76	99.83 85	99.98 84	99.60 107	100.00 1	100.00 1	97.79 120	100.00 1	100.00 1	96.57 188	99.99 93	100.00 1	99.88 120	99.90 147

test_fmvsmvis_n_1920		99.46 72	99.37 73	99.73 107	98.88 279	99.18 152	100.00 1	99.26 249	98.85 44	99.79 163	100.00 1	97.70 149	100.00 1	99.98 69	99.86 124	100.00 1

sss		99.45 73	99.34 80	99.80 93	99.76 143	99.50 115	100.00 1	99.91 35	97.72 125	99.98 101	99.94 208	98.45 127	100.00 1	99.53 159	98.75 163	99.89 151

AdaColmap		99.44 74	99.26 85	99.95 51	100.00 1	99.86 77	99.70 282	99.99 13	98.53 67	99.90 143	100.00 1	95.34 206	100.00 1	99.92 89	100.00 1	100.00 1

thisisatest0515		99.42 75	99.31 81	99.74 104	99.59 182	99.55 109	100.00 1	99.46 90	96.65 216	99.92 139	100.00 1	99.44 46	99.85 167	99.09 188	99.63 143	99.81 187

CANet		99.40 76	99.24 88	99.89 72	99.99 49	99.76 89	100.00 1	99.73 55	98.40 73	99.78 165	100.00 1	95.28 207	99.96 128	100.00 1	99.99 97	99.96 113

114514_t		99.39 77	99.25 86	99.81 89	99.97 88	99.48 122	100.00 1	99.42 127	95.53 261	100.00 1	100.00 1	98.37 130	99.95 138	99.97 78	100.00 1	100.00 1

alignmvs		99.38 78	99.21 92	99.91 67	99.73 146	99.92 48	100.00 1	99.51 72	97.61 140	100.00 1	100.00 1	99.06 86	99.93 152	99.83 104	97.12 221	99.90 147

1314		99.38 78	99.19 96	99.96 42	98.88 279	99.89 65	99.24 331	99.93 29	98.88 39	98.79 234	100.00 1	97.02 172	100.00 1	100.00 1	100.00 1	100.00 1

thisisatest0530		99.37 80	99.27 82	99.69 112	99.59 182	99.41 127	100.00 1	99.46 90	96.46 227	99.90 143	100.00 1	99.44 46	99.85 167	98.97 191	99.58 145	99.80 198

xiu_mvs_v1_base_debu		99.35 81	99.21 92	99.79 95	99.67 158	99.71 95	99.78 262	99.36 200	98.13 92	100.00 1	100.00 1	97.00 176	100.00 1	99.83 104	99.07 153	99.66 217

xiu_mvs_v1_base		99.35 81	99.21 92	99.79 95	99.67 158	99.71 95	99.78 262	99.36 200	98.13 92	100.00 1	100.00 1	97.00 176	100.00 1	99.83 104	99.07 153	99.66 217

xiu_mvs_v1_base_debi		99.35 81	99.21 92	99.79 95	99.67 158	99.71 95	99.78 262	99.36 200	98.13 92	100.00 1	100.00 1	97.00 176	100.00 1	99.83 104	99.07 153	99.66 217

ETV-MVS		99.34 84	99.24 88	99.64 118	99.58 187	99.33 134	100.00 1	99.25 250	97.57 145	99.96 110	100.00 1	97.44 163	99.79 178	99.70 127	99.65 141	99.81 187

tttt0517		99.34 84	99.23 91	99.67 114	99.57 190	99.38 129	100.00 1	99.46 90	96.33 236	99.89 146	100.00 1	99.44 46	99.84 169	98.93 193	99.46 148	99.78 203

CS-MVS		99.33 86	99.27 82	99.50 136	99.99 49	99.00 169	100.00 1	99.13 297	97.26 173	99.96 110	100.00 1	97.79 146	99.64 196	99.64 143	99.67 139	99.87 170

PVSNet_Blended_VisFu		99.33 86	99.18 98	99.78 99	99.82 118	99.49 118	100.00 1	99.95 18	97.36 163	99.63 175	100.00 1	96.45 192	99.95 138	99.79 109	99.65 141	99.89 151

HyFIR lowres test		99.32 88	99.24 88	99.58 129	99.95 95	99.26 141	100.00 1	99.99 13	96.72 208	99.29 196	99.91 212	99.49 39	99.47 229	99.74 118	98.08 196	100.00 1

CS-MVS-test		99.31 89	99.27 82	99.43 144	99.99 49	98.77 179	100.00 1	99.19 274	97.24 174	99.96 110	100.00 1	97.56 156	99.70 193	99.68 135	99.81 130	99.82 182

LS3D		99.31 89	99.13 100	99.87 77	99.99 49	99.71 95	99.55 300	99.46 90	97.32 168	99.82 161	100.00 1	96.85 183	99.97 117	99.14 184	100.00 1	99.92 136

PVSNet	94.91 18	99.30 91	99.25 86	99.44 142	100.00 1	98.32 208	100.00 1	99.86 37	98.04 99	100.00 1	100.00 1	96.10 195	100.00 1	99.55 154	99.73 134	100.00 1

lupinMVS		99.29 92	99.16 99	99.69 112	99.45 222	99.49 118	100.00 1	99.15 288	97.45 158	99.97 105	100.00 1	96.76 184	99.76 185	99.67 138	100.00 1	99.81 187

CSCG		99.28 93	99.35 78	99.05 179	99.99 49	97.15 267	100.00 1	99.47 75	97.44 159	99.42 185	100.00 1	97.83 145	100.00 1	99.99 58	100.00 1	100.00 1

thres200		99.27 94	99.04 103	99.96 42	99.81 124	99.90 58	100.00 1	99.94 21	97.31 170	99.83 153	99.96 197	97.04 169	100.00 1	99.62 147	97.88 204	99.98 105

OMC-MVS		99.27 94	99.38 70	98.96 187	99.95 95	97.06 271	100.00 1	99.40 177	98.83 48	99.88 148	100.00 1	97.01 173	99.86 162	99.47 162	99.84 127	99.97 110

EIA-MVS		99.26 96	99.19 96	99.45 141	99.63 171	98.75 180	100.00 1	99.27 244	96.93 191	99.95 133	100.00 1	97.47 160	99.79 178	99.74 118	99.72 135	99.82 182

tfpn200view9		99.26 96	99.03 104	99.96 42	99.81 124	99.89 65	100.00 1	99.94 21	97.23 175	99.83 153	99.96 197	97.04 169	100.00 1	99.59 149	97.85 206	99.98 105

thres400		99.26 96	99.03 104	99.95 51	99.81 124	99.89 65	100.00 1	99.94 21	97.23 175	99.83 153	99.96 197	97.04 169	100.00 1	99.59 149	97.85 206	99.97 110

thres100view900		99.25 99	99.01 106	99.95 51	99.81 124	99.87 74	100.00 1	99.94 21	97.13 180	99.83 153	99.96 197	97.01 173	100.00 1	99.59 149	97.85 206	99.98 105

EPMVS		99.25 99	99.13 100	99.60 123	99.60 180	99.20 149	99.60 295	100.00 1	96.93 191	99.92 139	99.36 294	99.05 87	99.71 192	98.77 202	98.94 157	99.90 147

thres600view7		99.24 101	99.00 107	99.95 51	99.81 124	99.87 74	100.00 1	99.94 21	97.13 180	99.83 153	99.96 197	97.01 173	100.00 1	99.54 157	97.77 212	99.97 110

MVS		99.22 102	98.96 111	99.98 23	99.00 267	99.95 32	99.24 331	99.94 21	98.14 91	98.88 224	100.00 1	95.63 204	100.00 1	99.85 101	100.00 1	100.00 1

EC-MVSNet		99.19 103	99.09 102	99.48 139	99.42 225	99.07 159	100.00 1	99.21 270	96.95 190	99.96 110	100.00 1	96.88 182	99.48 227	99.64 143	99.79 133	99.88 162

FE-MVS		99.16 104	98.99 109	99.66 116	99.65 163	99.18 152	99.58 297	99.43 117	95.24 271	99.91 141	99.59 274	99.37 57	99.97 117	98.31 226	99.81 130	99.83 177

PMMVS		99.12 105	98.97 110	99.58 129	99.57 190	98.98 171	100.00 1	99.30 226	97.14 179	99.96 110	100.00 1	96.53 191	99.82 173	99.70 127	98.49 169	99.94 124

jason		99.11 106	98.96 111	99.59 125	99.17 248	99.31 137	100.00 1	99.13 297	97.38 162	99.83 153	100.00 1	95.54 205	99.72 191	99.57 153	99.97 108	99.74 208
jason: jason.
EPP-MVSNet		99.10 107	99.00 107	99.40 149	99.51 209	98.68 186	99.92 237	99.43 117	95.47 267	99.65 174	100.00 1	99.51 33	99.76 185	99.53 159	98.00 197	99.75 207

TESTMET0.1,1		99.08 108	98.96 111	99.44 142	99.63 171	99.38 129	100.00 1	99.45 98	95.53 261	99.48 181	100.00 1	99.71 13	99.02 256	96.84 275	99.99 97	99.91 138

IS-MVSNet		99.08 108	98.91 119	99.59 125	99.65 163	99.38 129	99.78 262	99.24 255	96.70 210	99.51 179	100.00 1	98.44 128	99.52 222	98.47 220	98.39 177	99.88 162

UA-Net		99.06 110	98.83 125	99.74 104	99.52 204	99.40 128	99.08 355	99.45 98	97.64 134	99.83 153	100.00 1	95.80 199	99.94 150	98.35 224	99.80 132	99.88 162

3Dnovator	95.63 14	99.06 110	98.76 133	99.96 42	98.86 283	99.90 58	99.98 212	99.93 29	98.95 32	98.49 254	100.00 1	92.91 239	100.00 1	99.71 124	100.00 1	100.00 1

patch_mono-2		99.04 112	99.79 6	96.81 304	99.92 103	90.47 350	100.00 1	99.41 173	98.95 32	100.00 1	100.00 1	99.78 8	100.00 1	100.00 1	100.00 1	99.95 119

VNet		99.04 112	98.75 135	99.90 70	99.81 124	99.75 90	99.50 306	99.47 75	98.36 78	100.00 1	99.99 172	94.66 217	100.00 1	99.90 92	97.09 222	99.96 113

canonicalmvs		99.03 114	98.73 137	99.94 63	99.75 145	99.95 32	100.00 1	99.30 226	97.64 134	100.00 1	100.00 1	95.22 209	99.97 117	99.76 116	96.90 227	99.91 138

test-LLR		99.03 114	98.91 119	99.40 149	99.40 232	99.28 139	100.00 1	99.45 98	96.70 210	99.42 185	99.12 303	99.31 63	99.01 257	96.82 276	99.99 97	99.91 138

PatchmatchNet		99.03 114	98.96 111	99.26 169	99.49 214	98.33 206	99.38 318	99.45 98	96.64 217	99.96 110	99.58 276	99.49 39	99.50 225	97.63 251	99.00 156	99.93 134
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
3Dnovator+	95.58 15	99.03 114	98.71 140	99.96 42	98.99 270	99.89 65	100.00 1	99.51 72	98.96 29	98.32 262	100.00 1	92.78 240	100.00 1	99.87 98	100.00 1	100.00 1

CANet_DTU		99.02 118	98.90 122	99.41 147	99.88 111	98.71 184	100.00 1	99.29 230	98.84 46	100.00 1	100.00 1	94.02 224	100.00 1	98.08 235	99.96 110	99.52 223

PatchMatch-RL		99.02 118	98.78 130	99.74 104	99.99 49	99.29 138	100.00 1	100.00 1	98.38 74	99.89 146	99.81 231	93.14 237	99.99 93	97.85 245	99.98 105	99.95 119

FA-MVS(test-final)		99.00 120	98.75 135	99.73 107	99.63 171	99.43 126	99.83 252	99.43 117	95.84 252	99.52 178	99.37 293	97.84 144	99.96 128	97.63 251	99.68 137	99.79 200

CHOSEN 1792x2688		99.00 120	98.91 119	99.25 170	99.90 107	97.79 244	100.00 1	99.99 13	98.79 54	98.28 265	100.00 1	93.63 228	99.95 138	99.66 141	99.95 113	100.00 1

DeepC-MVS	97.84 5	99.00 120	98.80 129	99.60 123	99.93 100	99.03 164	100.00 1	99.40 177	98.61 65	99.33 194	100.00 1	92.23 247	99.95 138	99.74 118	99.96 110	99.83 177
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
baseline2		98.99 123	98.93 117	99.18 174	99.26 245	99.15 156	100.00 1	99.46 90	96.71 209	96.79 318	100.00 1	99.42 52	99.25 248	98.75 204	99.94 114	99.15 229

QAPM		98.99 123	98.66 142	99.96 42	99.01 263	99.87 74	99.88 246	99.93 29	97.99 102	98.68 239	100.00 1	93.17 235	100.00 1	99.32 171	100.00 1	100.00 1

Vis-MVSNet (Re-imp)		98.99 123	98.89 123	99.29 164	99.64 169	98.89 175	99.98 212	99.31 223	96.74 205	99.48 181	100.00 1	98.11 135	99.10 252	98.39 222	98.34 181	99.89 151

tpmrst		98.98 126	98.93 117	99.14 176	99.61 178	97.74 245	99.52 304	99.36 200	96.05 243	99.98 101	99.64 262	99.04 89	99.86 162	98.94 192	98.19 191	99.82 182

test-mter		98.96 127	98.82 126	99.40 149	99.40 232	99.28 139	100.00 1	99.45 98	95.44 270	99.42 185	99.12 303	99.70 14	99.01 257	96.82 276	99.99 97	99.91 138

diffmvs		98.96 127	98.73 137	99.63 119	99.54 194	99.16 155	100.00 1	99.18 281	97.33 167	99.96 110	100.00 1	94.60 218	99.91 155	99.66 141	98.33 184	99.82 182
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		98.96 127	98.95 115	99.01 183	99.48 216	98.36 204	99.93 236	99.37 194	96.79 201	99.31 195	99.83 225	99.77 10	98.91 266	98.07 236	97.98 198	99.77 204
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MVSFormer		98.94 130	98.82 126	99.28 167	99.45 222	99.49 118	100.00 1	99.13 297	95.46 268	99.97 105	100.00 1	96.76 184	98.59 298	98.63 212	100.00 1	99.74 208

MVS_Test		98.93 131	98.65 143	99.77 101	99.62 176	99.50 115	99.99 190	99.19 274	95.52 263	99.96 110	99.86 218	96.54 190	99.98 112	98.65 209	98.48 170	99.82 182

baseline1		98.91 132	98.61 147	99.81 89	99.71 147	99.77 88	99.78 262	99.44 111	97.51 152	98.81 232	99.99 172	98.25 131	99.76 185	98.60 215	95.41 240	99.89 151

1112_ss		98.91 132	98.71 140	99.51 134	99.69 150	98.75 180	99.99 190	99.15 288	96.82 199	98.84 229	100.00 1	97.45 161	99.89 157	98.66 207	97.75 213	99.89 151

MSDG		98.90 134	98.63 145	99.70 111	99.92 103	99.25 143	100.00 1	99.37 194	95.71 255	99.40 191	100.00 1	96.58 187	99.95 138	96.80 278	99.94 114	99.91 138

dcpmvs_2		98.87 135	99.53 57	96.90 298	99.87 113	90.88 349	99.94 234	99.07 317	98.20 86	100.00 1	100.00 1	98.69 119	99.86 162	100.00 1	100.00 1	99.95 119

DP-MVS		98.86 136	98.54 153	99.81 89	99.97 88	99.45 123	99.52 304	99.40 177	94.35 295	98.36 258	100.00 1	96.13 194	99.97 117	99.12 187	100.00 1	100.00 1

CostFormer		98.84 137	98.77 131	99.04 181	99.41 227	97.58 250	99.67 287	99.35 209	94.66 284	99.96 110	99.36 294	99.28 71	99.74 188	99.41 165	97.81 210	99.81 187

Test_1112_low_res		98.83 138	98.60 149	99.51 134	99.69 150	98.75 180	99.99 190	99.14 293	96.81 200	98.84 229	99.06 307	97.45 161	99.89 157	98.66 207	97.75 213	99.89 151

BH-w/o		98.82 139	98.81 128	98.88 192	99.62 176	96.71 279	100.00 1	99.28 236	97.09 182	98.81 232	100.00 1	94.91 214	99.96 128	99.54 157	100.00 1	99.96 113

mvs_anonymous		98.80 140	98.60 149	99.38 153	99.57 190	99.24 145	100.00 1	99.21 270	95.87 247	98.92 220	99.82 228	96.39 193	99.03 255	99.13 186	98.50 168	99.88 162

TAMVS		98.76 141	98.73 137	98.86 193	99.44 224	97.69 246	99.57 298	99.34 214	96.57 221	99.12 206	99.81 231	98.83 111	99.16 250	97.97 242	97.91 202	99.73 212

OpenMVS	95.20 17	98.76 141	98.41 159	99.78 99	98.89 278	99.81 84	99.99 190	99.76 48	98.02 100	98.02 278	100.00 1	91.44 253	100.00 1	99.63 146	99.97 108	99.55 221

iter_conf05		98.73 143	98.77 131	98.60 204	99.65 163	99.22 148	100.00 1	99.22 261	96.68 214	98.98 218	99.97 184	99.99 3	98.84 274	99.29 174	95.11 259	97.75 253

iter_conf_final		98.72 144	98.76 133	98.59 206	99.64 169	99.17 154	100.00 1	99.22 261	96.63 219	99.02 215	99.97 184	99.98 4	98.84 274	99.22 181	95.18 253	97.76 242

dp		98.72 144	98.61 147	99.03 182	99.53 197	97.39 256	99.45 310	99.39 190	95.62 258	99.94 135	99.52 284	98.83 111	99.82 173	96.77 281	98.42 174	99.89 151

PVSNet_BlendedMVS		98.71 146	98.62 146	98.98 186	99.98 84	99.60 107	100.00 1	100.00 1	97.23 175	100.00 1	99.03 312	96.57 188	99.99 93	100.00 1	94.75 267	97.35 337

ADS-MVSNet		98.70 147	98.51 155	99.28 167	99.51 209	98.39 199	99.24 331	99.44 111	95.52 263	99.96 110	99.70 246	97.57 154	99.58 203	97.11 267	98.54 166	99.88 162

baseline		98.69 148	98.45 158	99.41 147	99.52 204	98.67 187	100.00 1	99.17 286	97.03 187	99.13 205	100.00 1	93.17 235	99.74 188	99.70 127	98.34 181	99.81 187

PCF-MVS	98.23 3	98.69 148	98.37 164	99.62 120	99.78 140	99.02 165	99.23 336	99.06 325	96.43 228	98.08 274	100.00 1	94.72 216	99.95 138	98.16 233	99.91 117	99.90 147
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
casdiffmvs		98.65 150	98.38 162	99.46 140	99.52 204	98.74 183	100.00 1	99.15 288	96.91 194	99.05 213	100.00 1	92.75 241	99.83 170	99.70 127	98.38 178	99.81 187
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		98.64 151	98.39 161	99.40 149	99.50 212	98.60 190	100.00 1	99.22 261	96.85 197	99.10 207	100.00 1	92.75 241	99.78 182	99.71 124	98.35 180	99.81 187
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		98.64 151	98.58 151	98.81 196	99.42 225	97.12 268	99.69 284	99.37 194	93.63 311	99.94 135	99.67 254	98.96 97	99.47 229	98.62 214	97.95 200	99.83 177

BH-untuned		98.64 151	98.65 143	98.60 204	99.59 182	96.17 285	100.00 1	99.28 236	96.67 215	98.41 257	100.00 1	94.52 219	99.83 170	99.41 165	100.00 1	99.81 187

test_cas_vis1_n_1920		98.63 154	98.25 168	99.77 101	99.69 150	99.32 135	100.00 1	99.31 223	98.84 46	99.96 110	100.00 1	87.42 304	99.99 93	99.14 184	99.86 124	100.00 1

tpmvs		98.59 155	98.38 162	99.23 171	99.69 150	97.90 236	99.31 326	99.47 75	94.52 289	99.68 173	99.28 298	97.64 152	99.89 157	97.71 248	98.17 193	99.89 151

Effi-MVS+		98.58 156	98.24 170	99.61 121	99.60 180	99.26 141	97.85 371	99.10 307	96.22 239	99.97 105	99.89 214	93.75 226	99.77 183	99.43 163	98.34 181	99.81 187

MVSTER		98.58 156	98.52 154	98.77 198	99.65 163	99.68 101	100.00 1	99.29 230	95.63 257	98.65 240	99.80 234	99.78 8	98.88 272	98.59 216	95.31 244	97.73 282

CVMVSNet		98.56 158	98.47 157	98.82 194	99.11 251	97.67 247	99.74 272	99.47 75	97.57 145	99.06 212	100.00 1	95.72 201	98.97 262	98.21 232	97.33 220	99.83 177

AllTest		98.55 159	98.40 160	98.99 184	99.93 100	97.35 258	100.00 1	99.40 177	97.08 184	99.09 208	99.98 176	93.37 230	99.95 138	96.94 271	99.84 127	99.68 215

DeepPCF-MVS	98.03 4	98.54 160	99.72 19	94.98 325	99.99 49	84.94 363	100.00 1	99.42 127	99.98 1	100.00 1	100.00 1	98.11 135	100.00 1	100.00 1	100.00 1	100.00 1

EPNet_dtu		98.53 161	98.23 172	99.43 144	99.92 103	99.01 167	99.96 223	99.47 75	98.80 52	99.96 110	99.96 197	98.56 124	99.30 245	87.78 356	99.68 137	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Vis-MVSNet		98.52 162	98.25 168	99.34 156	99.68 154	98.55 192	99.68 286	99.41 173	97.34 166	99.94 135	100.00 1	90.38 270	99.70 193	99.03 190	98.84 158	99.76 206
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Effi-MVS+-dtu		98.51 163	98.86 124	97.47 274	99.77 142	94.21 322	100.00 1	98.94 340	97.61 140	99.91 141	98.75 330	95.89 197	99.51 224	99.36 167	99.48 147	98.68 235

SDMVSNet		98.49 164	98.08 179	99.73 107	99.82 118	99.53 112	99.99 190	99.45 98	97.62 136	99.38 192	99.86 218	90.06 273	99.88 161	99.92 89	96.61 230	99.79 200

BH-RMVSNet		98.46 165	98.08 179	99.59 125	99.61 178	99.19 150	100.00 1	99.28 236	97.06 186	98.95 219	100.00 1	88.99 286	99.82 173	98.83 200	100.00 1	99.77 204

ECVR-MVS		98.43 166	98.14 175	99.32 161	99.89 109	98.21 215	99.46 308	100.00 1	98.38 74	99.47 184	100.00 1	87.91 297	99.80 177	99.35 168	98.78 160	99.94 124

cascas		98.43 166	98.07 181	99.50 136	99.65 163	99.02 165	100.00 1	99.22 261	94.21 298	99.72 171	99.98 176	92.03 250	99.93 152	99.68 135	98.12 194	99.54 222

test1111		98.42 168	98.12 176	99.29 164	99.88 111	98.15 218	99.46 308	100.00 1	98.36 78	99.42 185	100.00 1	87.91 297	99.79 178	99.31 172	98.78 160	99.94 124

ab-mvs		98.42 168	98.02 186	99.61 121	99.71 147	99.00 169	99.10 352	99.64 63	96.70 210	99.04 214	99.81 231	90.64 264	99.98 112	99.64 143	97.93 201	99.84 174

UGNet		98.41 170	98.11 177	99.31 163	99.54 194	98.55 192	99.18 339	100.00 1	98.64 64	99.79 163	99.04 310	87.61 302	100.00 1	99.30 173	99.89 119	99.40 226
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+		98.40 171	98.02 186	99.55 133	99.63 171	99.06 161	100.00 1	99.15 288	95.07 273	99.42 185	99.95 204	93.26 233	99.73 190	97.44 257	98.24 187	99.87 170

Fast-Effi-MVS+-dtu		98.38 172	98.56 152	97.82 264	99.58 187	94.44 319	100.00 1	99.16 287	96.75 203	99.51 179	99.63 266	95.03 212	99.60 197	97.71 248	99.67 139	99.42 225

test_fmvs1		98.37 173	98.04 184	99.34 156	99.84 116	98.07 224	100.00 1	99.00 335	98.85 44	100.00 1	100.00 1	85.11 324	99.96 128	99.69 134	99.88 120	100.00 1

miper_enhance_ethall		98.33 174	98.27 167	98.51 209	99.66 162	99.04 163	100.00 1	99.22 261	97.53 149	98.51 252	99.38 292	99.49 39	98.75 284	98.02 238	92.61 288	97.76 242

SCA		98.30 175	97.98 188	99.23 171	99.41 227	98.25 212	99.99 190	99.45 98	96.91 194	99.76 168	99.58 276	89.65 278	99.54 216	98.31 226	98.79 159	99.91 138

XVG-OURS		98.30 175	98.36 165	98.13 239	99.58 187	95.91 288	100.00 1	99.36 200	98.69 59	99.23 198	100.00 1	91.20 256	99.92 154	99.34 169	97.82 209	98.56 238

COLMAP_ROB	97.10 7	98.29 177	98.17 174	98.65 202	99.94 98	97.39 256	99.30 327	99.40 177	95.64 256	97.75 291	100.00 1	92.69 244	99.95 138	98.89 195	99.92 116	98.62 237
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ADS-MVSNet2		98.28 178	98.51 155	97.62 270	99.51 209	95.03 299	99.24 331	99.41 173	95.52 263	99.96 110	99.70 246	97.57 154	97.94 341	97.11 267	98.54 166	99.88 162

XVG-OURS-SEG-HR		98.27 179	98.31 166	98.14 236	99.59 182	95.92 287	100.00 1	99.36 200	98.48 69	99.21 199	100.00 1	89.27 283	99.94 150	99.76 116	99.17 150	98.56 238

tpm		98.24 180	98.22 173	98.32 221	99.13 250	95.79 290	99.53 303	99.12 303	95.20 272	99.96 110	99.36 294	97.58 153	99.28 247	97.41 259	96.67 228	99.88 162

cl22		98.23 181	98.11 177	98.58 208	99.82 118	99.01 167	100.00 1	99.28 236	96.92 193	98.33 261	99.21 300	98.09 137	98.97 262	98.72 205	92.61 288	97.76 242

TR-MVS		98.14 182	97.74 196	99.33 159	99.59 182	98.28 210	99.27 328	99.21 270	96.42 229	99.15 204	99.94 208	88.87 289	99.79 178	98.88 196	98.29 185	99.93 134

mvsmamba		98.13 183	98.06 182	98.32 221	98.22 310	98.50 195	100.00 1	99.22 261	96.41 230	98.91 222	99.96 197	95.69 202	98.73 286	99.19 183	94.95 266	97.73 282

test0.0.03 1		98.12 184	98.03 185	98.39 215	99.11 251	98.07 224	100.00 1	99.93 29	96.70 210	96.91 314	99.95 204	99.31 63	98.19 321	91.93 331	98.44 172	98.91 233

GeoE		98.06 185	97.65 201	99.29 164	99.47 219	98.41 196	100.00 1	99.19 274	94.85 278	98.88 224	100.00 1	91.21 255	99.59 199	97.02 269	98.19 191	99.88 162

tpm cat1		98.05 186	97.76 194	98.92 189	99.50 212	97.10 270	99.77 267	99.30 226	90.20 348	99.72 171	98.71 331	97.71 148	99.86 162	96.75 282	98.20 190	99.81 187

PS-MVSNAJss		98.03 187	98.06 182	97.94 258	97.63 331	97.33 261	99.89 244	99.23 259	96.27 238	98.03 276	99.59 274	98.75 116	98.78 279	98.52 218	94.61 271	97.70 298

CR-MVSNet		98.02 188	97.71 199	98.93 188	99.31 239	98.86 176	99.13 349	99.00 335	96.53 224	99.96 110	98.98 316	96.94 179	98.10 331	91.18 336	98.40 175	99.84 174

EI-MVSNet		97.98 189	97.93 189	98.16 234	99.11 251	97.84 241	99.74 272	99.29 230	94.39 294	98.65 240	100.00 1	97.21 167	98.88 272	97.62 253	95.31 244	97.75 253

FIs		97.95 190	97.73 198	98.62 203	98.53 295	99.24 145	100.00 1	99.43 117	96.74 205	97.87 286	99.82 228	95.27 208	98.89 269	98.78 201	93.07 283	97.74 276

Anonymous202405211		97.87 191	97.53 204	98.90 190	99.81 124	96.70 280	99.35 321	99.46 90	92.98 326	98.83 231	99.99 172	90.63 265	100.00 1	99.70 127	97.03 223	100.00 1

FC-MVSNet-test		97.84 192	97.63 202	98.45 212	98.30 305	99.05 162	100.00 1	99.43 117	96.63 219	97.61 297	99.82 228	95.19 210	98.57 301	98.64 210	93.05 284	97.73 282

Patchmatch-test		97.83 193	97.42 207	99.06 177	99.08 254	97.66 248	98.66 365	99.21 270	93.65 310	98.25 269	99.58 276	99.47 43	99.57 204	90.25 345	98.59 165	99.95 119

sd_testset		97.81 194	97.48 205	98.79 197	99.82 118	96.80 277	99.32 323	99.45 98	97.62 136	99.38 192	99.86 218	85.56 322	99.77 183	99.72 121	96.61 230	99.79 200

miper_ehance_all_eth		97.81 194	97.66 200	98.23 227	99.49 214	98.37 202	99.99 190	99.11 305	94.78 279	98.25 269	99.21 300	98.18 133	98.57 301	97.35 263	92.61 288	97.76 242

test_vis1_n_1920		97.77 196	97.24 219	99.34 156	99.79 137	98.04 228	100.00 1	99.25 250	98.88 39	100.00 1	100.00 1	77.52 355	100.00 1	99.88 95	99.85 126	100.00 1

RRT_MVS		97.77 196	97.76 194	97.78 266	97.89 323	97.06 271	100.00 1	99.29 230	95.74 254	98.00 281	99.97 184	95.94 196	98.55 304	98.87 197	94.18 274	97.72 289

HQP-MVS		97.73 198	97.85 191	97.39 276	99.07 255	94.82 303	100.00 1	99.40 177	99.04 14	99.17 200	99.97 184	88.61 292	99.57 204	99.79 109	95.58 234	97.77 240

GA-MVS		97.72 199	97.27 217	99.06 177	99.24 246	97.93 235	100.00 1	99.24 255	95.80 253	98.99 217	99.64 262	89.77 276	99.36 240	95.12 303	97.62 218	99.89 151

bld_raw_dy_0_64		97.71 200	97.56 203	98.15 235	97.83 326	98.16 216	99.95 229	99.12 303	95.95 246	98.73 237	99.97 184	93.19 234	98.63 292	98.64 210	94.69 269	97.66 309

HQP_MVS		97.71 200	97.82 193	97.37 277	99.00 267	94.80 306	100.00 1	99.40 177	99.00 26	99.08 210	99.97 184	88.58 294	99.55 213	99.79 109	95.57 238	97.76 242

nrg030		97.64 202	97.27 217	98.75 199	98.34 300	99.53 112	100.00 1	99.22 261	96.21 240	98.27 267	99.95 204	94.40 220	98.98 260	99.23 179	89.78 324	97.75 253

TAPA-MVS	96.40 10	97.64 202	97.37 211	98.45 212	99.94 98	95.70 291	100.00 1	99.40 177	97.65 132	99.53 177	100.00 1	99.31 63	99.66 195	80.48 370	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CLD-MVS		97.64 202	97.74 196	97.36 278	99.01 263	94.76 311	100.00 1	99.34 214	99.30 4	99.00 216	99.97 184	87.49 303	99.57 204	99.96 80	95.58 234	97.75 253
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
D2MVS		97.63 205	97.83 192	97.05 289	98.83 286	94.60 315	100.00 1	99.82 39	96.89 196	98.28 265	99.03 312	94.05 222	99.47 229	98.58 217	94.97 264	97.09 343

c3_l		97.58 206	97.42 207	98.06 246	99.48 216	98.16 216	99.96 223	99.10 307	94.54 288	98.13 273	99.20 302	97.87 141	98.25 320	97.28 264	91.20 312	97.75 253

IterMVS-LS		97.56 207	97.44 206	97.92 261	99.38 236	97.90 236	99.89 244	99.10 307	94.41 293	98.32 262	99.54 283	97.21 167	98.11 328	97.50 255	91.62 304	97.75 253
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test_djsdf		97.55 208	97.38 210	98.07 242	97.50 339	97.99 230	100.00 1	99.13 297	95.46 268	98.47 255	99.85 222	92.01 251	98.59 298	98.63 212	95.36 242	97.62 320

dmvs_re		97.54 209	97.88 190	96.54 309	99.55 193	90.35 351	99.86 248	99.46 90	97.00 188	99.41 190	100.00 1	90.78 263	99.30 245	99.60 148	95.24 249	99.96 113

cl____		97.54 209	97.32 213	98.18 231	99.47 219	98.14 220	100.00 1	99.10 307	94.16 301	97.60 298	99.63 266	97.52 157	98.65 291	96.47 283	91.97 300	97.76 242

IB-MVS	96.24 12	97.54 209	96.95 223	99.33 159	99.67 158	98.10 223	100.00 1	99.47 75	97.42 161	99.26 197	99.69 249	98.83 111	99.89 157	99.43 163	78.77 366	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		97.52 212	97.35 212	98.05 250	99.46 221	98.11 221	100.00 1	99.10 307	94.21 298	97.62 296	99.63 266	97.65 151	98.29 317	96.47 283	91.98 299	97.76 242

eth_miper_zixun_eth		97.47 213	97.28 215	98.06 246	99.41 227	97.94 234	99.62 293	99.08 313	94.46 292	98.19 272	99.56 280	96.91 181	98.50 307	96.78 279	91.49 307	97.74 276

test_fmvs1_n		97.43 214	96.86 226	99.15 175	99.68 154	97.48 253	99.99 190	98.98 338	98.82 50	100.00 1	100.00 1	74.85 360	99.96 128	99.67 138	99.70 136	100.00 1

LFMVS		97.42 215	96.62 235	99.81 89	99.80 134	99.50 115	99.16 345	99.56 66	94.48 291	100.00 1	100.00 1	79.35 350	100.00 1	99.89 94	97.37 219	99.94 124

miper_lstm_enhance		97.40 216	97.28 215	97.75 267	99.48 216	97.52 251	100.00 1	99.07 317	94.08 302	98.01 279	99.61 272	97.38 165	97.98 339	96.44 286	91.47 309	97.76 242

RPSCF		97.37 217	98.24 170	94.76 328	99.80 134	84.57 364	99.99 190	99.05 327	94.95 276	99.82 161	100.00 1	94.03 223	100.00 1	98.15 234	98.38 178	99.70 213

ACMM	97.17 6	97.37 217	97.40 209	97.29 282	99.01 263	94.64 314	100.00 1	99.25 250	98.07 98	98.44 256	99.98 176	87.38 305	99.55 213	99.25 176	95.19 252	97.69 302
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LPG-MVS_test		97.31 219	97.32 213	97.28 283	98.85 284	94.60 315	100.00 1	99.37 194	97.35 164	98.85 227	99.98 176	86.66 311	99.56 208	99.55 154	95.26 246	97.70 298

FMVSNet3		97.30 220	96.95 223	98.37 217	99.65 163	99.25 143	99.71 280	99.28 236	94.23 296	98.53 249	98.91 323	93.30 232	98.11 328	95.31 299	93.60 277	97.73 282

UniMVSNet (Re)		97.29 221	96.85 227	98.59 206	98.49 296	99.13 157	100.00 1	99.42 127	96.52 225	98.24 271	98.90 324	94.93 213	98.89 269	97.54 254	87.61 340	97.75 253

OPM-MVS		97.21 222	97.18 221	97.32 281	98.08 316	94.66 312	100.00 1	99.28 236	98.65 63	98.92 220	99.98 176	86.03 318	99.56 208	98.28 230	95.41 240	97.72 289
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMP	97.00 8	97.19 223	97.16 222	97.27 285	98.97 272	94.58 318	100.00 1	99.32 218	97.97 106	97.45 302	99.98 176	85.79 320	99.56 208	99.70 127	95.24 249	97.67 308
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
pmmvs4		97.17 224	96.80 228	98.27 224	97.68 330	98.64 189	100.00 1	99.18 281	94.22 297	98.55 247	99.71 243	93.67 227	98.47 310	95.66 293	92.57 291	97.71 297

anonymousdsp		97.16 225	96.88 225	98.00 254	97.08 349	98.06 226	99.81 256	99.15 288	94.58 286	97.84 287	99.62 270	90.49 267	98.60 296	97.98 239	95.32 243	97.33 338

UniMVSNet_NR-MVSNet		97.16 225	96.80 228	98.22 228	98.38 299	98.41 196	100.00 1	99.45 98	96.14 242	97.76 288	99.64 262	95.05 211	98.50 307	97.98 239	86.84 344	97.75 253

XXY-MVS		97.14 227	96.63 234	98.67 201	98.65 289	98.92 174	99.54 302	99.29 230	95.57 260	97.63 294	99.83 225	87.79 301	99.35 242	98.39 222	92.95 285	97.75 253

WR-MVS		97.09 228	96.64 233	98.46 211	98.43 297	99.09 158	99.97 218	99.33 216	95.62 258	97.76 288	99.67 254	91.17 257	98.56 303	98.49 219	89.28 329	97.74 276

JIA-IIPM		97.09 228	96.34 248	99.36 154	98.88 279	98.59 191	99.81 256	99.43 117	84.81 364	99.96 110	90.34 374	98.55 125	99.52 222	97.00 270	98.28 186	99.98 105

jajsoiax		97.07 230	96.79 230	97.89 262	97.28 347	97.12 268	99.95 229	99.19 274	96.55 222	97.31 305	99.69 249	87.35 307	98.91 266	98.70 206	95.12 258	97.66 309

MIMVSNet		97.06 231	96.73 231	98.05 250	99.38 236	96.64 282	98.47 367	99.35 209	93.41 316	99.48 181	98.53 338	89.66 277	97.70 347	94.16 314	98.11 195	99.80 198

X-MVStestdata		97.04 232	96.06 259	99.98 23	100.00 1	99.94 40	100.00 1	99.75 51	98.67 61	100.00 1	66.97 385	99.16 80	100.00 1	100.00 1	100.00 1	100.00 1

h-mvs33		97.03 233	96.53 237	98.51 209	99.79 137	95.90 289	99.45 310	99.45 98	98.21 84	100.00 1	99.78 237	97.49 158	99.99 93	99.72 121	74.92 368	99.65 220

VPA-MVSNet		97.03 233	96.43 243	98.82 194	98.64 290	99.32 135	99.38 318	99.47 75	96.73 207	98.91 222	98.94 321	87.00 309	99.40 238	99.23 179	89.59 325	97.76 242

mvs_tets		97.00 235	96.69 232	97.94 258	97.41 346	97.27 263	99.60 295	99.18 281	96.51 226	97.35 304	99.69 249	86.53 313	98.91 266	98.84 198	95.09 260	97.65 314

gg-mvs-nofinetune		96.95 236	96.10 257	99.50 136	99.41 227	99.36 133	99.07 357	99.52 68	83.69 366	99.96 110	83.60 382	100.00 1	99.20 249	99.68 135	99.99 97	99.96 113

Anonymous20240529		96.93 237	96.22 253	99.05 179	99.79 137	97.30 262	99.16 345	99.47 75	88.51 354	98.69 238	100.00 1	83.50 335	100.00 1	99.83 104	97.02 224	99.83 177

DU-MVS		96.93 237	96.49 240	98.22 228	98.31 303	98.41 196	100.00 1	99.37 194	96.41 230	97.76 288	99.65 258	92.14 248	98.50 307	97.98 239	86.84 344	97.75 253

Patchmtry		96.81 239	96.37 246	98.14 236	99.31 239	98.55 192	98.91 360	99.00 335	90.45 345	97.92 283	98.98 316	96.94 179	98.12 326	94.27 311	91.53 306	97.75 253

hse-mvs2		96.79 240	96.38 245	98.04 252	99.68 154	95.54 293	99.81 256	99.42 127	98.21 84	100.00 1	99.80 234	97.49 158	99.46 233	99.72 121	73.27 371	99.12 230

ACMH	96.25 11	96.77 241	96.62 235	97.21 286	98.96 273	94.43 320	99.64 289	99.33 216	97.43 160	96.55 323	99.97 184	83.52 334	99.54 216	99.07 189	95.13 257	97.66 309
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IterMVS		96.76 242	96.46 242	97.63 268	99.41 227	96.89 274	99.99 190	99.13 297	94.74 282	97.59 299	99.66 256	89.63 280	98.28 318	95.71 291	92.31 294	97.72 289
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CP-MVSNet		96.73 243	96.25 251	98.18 231	98.21 311	98.67 187	99.77 267	99.32 218	95.06 274	97.20 308	99.65 258	90.10 271	98.19 321	98.06 237	88.90 332	97.66 309

WR-MVS_H		96.73 243	96.32 250	97.95 257	98.26 307	97.88 238	99.72 279	99.43 117	95.06 274	96.99 311	98.68 333	93.02 238	98.53 305	97.43 258	88.33 336	97.43 333

IterMVS-SCA-FT		96.72 245	96.42 244	97.62 270	99.40 232	96.83 276	99.99 190	99.14 293	94.65 285	97.55 300	99.72 241	89.65 278	98.31 316	95.62 295	92.05 297	97.73 282

v2v482		96.70 246	96.18 254	98.27 224	98.04 317	98.39 199	100.00 1	99.13 297	94.19 300	98.58 245	99.08 306	90.48 268	98.67 289	95.69 292	90.44 320	97.75 253

test_vis1_n		96.69 247	95.81 269	99.32 161	99.14 249	97.98 231	99.97 218	98.98 338	98.45 71	100.00 1	100.00 1	66.44 371	99.99 93	99.78 115	99.57 146	100.00 1

V42		96.65 248	96.16 256	98.11 241	98.17 314	98.23 213	99.99 190	99.09 312	93.97 303	98.74 236	99.05 309	91.09 258	98.82 277	95.46 297	89.90 322	97.27 339

EU-MVSNet		96.63 249	96.53 237	96.94 296	97.59 335	96.87 275	99.76 269	99.47 75	96.35 234	96.85 316	99.78 237	92.57 245	96.27 361	95.33 298	91.08 313	97.68 304

NR-MVSNet		96.63 249	96.04 260	98.38 216	98.31 303	98.98 171	99.22 338	99.35 209	95.87 247	94.43 346	99.65 258	92.73 243	98.40 313	96.78 279	88.05 337	97.75 253

XVG-ACMP-BASELINE		96.60 251	96.52 239	96.84 302	98.41 298	93.29 331	99.99 190	99.32 218	97.76 124	98.51 252	99.29 297	81.95 341	99.54 216	98.40 221	95.03 261	97.68 304

VDD-MVS		96.58 252	95.99 262	98.34 219	99.52 204	95.33 294	99.18 339	99.38 192	96.64 217	99.77 166	100.00 1	72.51 365	100.00 1	100.00 1	96.94 226	99.70 213

tt0805		96.52 253	96.23 252	97.40 275	99.30 242	93.55 327	99.32 323	99.45 98	96.75 203	97.88 285	99.99 172	79.99 348	99.59 199	97.39 261	95.98 233	99.06 232

LCM-MVSNet-Re		96.52 253	97.21 220	94.44 329	99.27 243	85.80 361	99.85 250	96.61 377	95.98 244	92.75 353	98.48 340	93.97 225	97.55 348	99.58 152	98.43 173	99.98 105

our_test_3		96.51 255	96.35 247	96.98 294	97.61 333	95.05 298	99.98 212	99.01 334	94.68 283	96.77 320	99.06 307	95.87 198	98.14 324	91.81 332	92.37 293	97.75 253

MVP-Stereo		96.51 255	96.48 241	96.60 308	95.65 360	94.25 321	98.84 362	98.16 354	95.85 251	95.23 337	99.04 310	92.54 246	99.13 251	92.98 324	99.98 105	96.43 355
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
v1144		96.51 255	95.97 264	98.13 239	97.98 320	98.04 228	99.99 190	99.08 313	93.51 315	98.62 243	98.98 316	90.98 262	98.62 293	93.79 318	90.79 316	97.74 276

ACMH+	96.20 13	96.49 258	96.33 249	97.00 292	99.06 259	93.80 325	99.81 256	99.31 223	97.32 168	95.89 334	99.97 184	82.62 339	99.54 216	98.34 225	94.63 270	97.65 314

TranMVSNet+NR-MVSNet		96.45 259	96.01 261	97.79 265	98.00 319	97.62 249	100.00 1	99.35 209	95.98 244	97.31 305	99.64 262	90.09 272	98.00 338	96.89 274	86.80 347	97.75 253

ET-MVSNet_ETH3D		96.41 260	95.48 289	99.20 173	99.81 124	99.75 90	100.00 1	99.02 332	97.30 172	78.33 374	100.00 1	97.73 147	97.94 341	99.70 127	87.41 341	99.92 136

VPNet		96.41 260	95.76 274	98.33 220	98.61 291	98.30 209	99.48 307	99.45 98	96.98 189	98.87 226	99.88 215	81.57 342	98.93 264	99.22 181	87.82 339	97.76 242

PVSNet_0	93.57 19	96.41 260	95.74 275	98.41 214	99.84 116	95.22 296	100.00 1	100.00 1	98.08 97	97.55 300	99.78 237	84.40 327	100.00 1	100.00 1	81.99 359	100.00 1

v144192		96.40 263	95.81 269	98.17 233	97.89 323	98.11 221	99.99 190	99.06 325	93.39 317	98.75 235	99.09 305	90.43 269	98.66 290	93.10 323	90.55 319	97.75 253

VDDNet		96.39 264	95.55 284	98.90 190	99.27 243	97.45 254	99.15 347	99.92 33	91.28 339	99.98 101	100.00 1	73.55 361	100.00 1	99.85 101	96.98 225	99.24 227

tfpnnormal		96.36 265	95.69 280	98.37 217	98.55 293	98.71 184	99.69 284	99.45 98	93.16 324	96.69 322	99.71 243	88.44 296	98.99 259	94.17 312	91.38 310	97.41 334

v8		96.35 266	95.73 276	98.21 230	98.11 315	98.23 213	99.94 234	99.07 317	92.66 332	98.29 264	99.00 315	91.46 252	98.77 282	94.17 312	88.83 334	97.62 320

PS-CasMVS		96.34 267	95.78 273	98.03 253	98.18 313	98.27 211	99.71 280	99.32 218	94.75 280	96.82 317	99.65 258	86.98 310	98.15 323	97.74 247	88.85 333	97.66 309

LTVRE_ROB	95.29 16	96.32 268	96.10 257	96.99 293	98.55 293	93.88 324	99.45 310	99.28 236	94.50 290	96.46 324	99.52 284	84.86 325	99.48 227	97.26 265	95.03 261	97.59 324
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		96.29 269	95.70 277	98.07 242	99.80 134	97.49 252	99.15 347	99.40 177	89.11 351	97.75 291	99.45 289	88.93 288	98.98 260	98.26 231	89.47 327	97.73 282

v148		96.29 269	95.84 268	97.63 268	97.74 328	96.53 283	100.00 1	99.07 317	93.52 314	98.01 279	99.42 291	91.22 254	98.60 296	96.37 287	87.22 343	97.75 253

AUN-MVS		96.26 271	95.67 281	98.06 246	99.68 154	95.60 292	99.82 255	99.42 127	96.78 202	99.88 148	99.80 234	94.84 215	99.47 229	97.48 256	73.29 370	99.12 230

FMVSNet2		96.22 272	95.60 283	98.06 246	99.53 197	98.33 206	99.45 310	99.27 244	93.71 306	98.03 276	98.84 326	84.23 329	98.10 331	93.97 316	93.40 280	97.73 282

LF4IMVS		96.19 273	96.18 254	96.23 315	98.26 307	92.09 341	100.00 1	97.89 364	97.82 118	97.94 282	99.87 216	82.71 338	99.38 239	97.41 259	93.71 276	97.20 340

v1192		96.18 274	95.49 287	98.26 226	98.01 318	98.15 218	99.99 190	99.08 313	93.36 318	98.54 248	98.97 319	89.47 281	98.89 269	91.15 337	90.82 315	97.75 253

testgi		96.18 274	95.93 265	96.93 297	98.98 271	94.20 323	100.00 1	99.07 317	97.16 178	96.06 331	99.86 218	84.08 332	97.79 344	90.38 344	97.80 211	98.81 234

ppachtmachnet_test		96.17 276	95.89 266	97.02 291	97.61 333	95.24 295	99.99 190	99.24 255	93.31 320	96.71 321	99.62 270	94.34 221	98.07 333	89.87 346	92.30 295	97.75 253

v1921920		96.16 277	95.50 285	98.14 236	97.88 325	97.96 232	99.99 190	99.07 317	93.33 319	98.60 244	99.24 299	89.37 282	98.71 287	91.28 335	90.74 317	97.75 253

Baseline_NR-MVSNet		96.16 277	95.70 277	97.56 273	98.28 306	96.79 278	100.00 1	97.86 365	91.93 336	97.63 294	99.47 288	92.14 248	98.35 315	97.13 266	86.83 346	97.54 327

v10		96.14 279	95.50 285	98.07 242	98.19 312	97.96 232	99.83 252	99.07 317	92.10 335	98.07 275	98.94 321	91.07 259	98.61 294	92.41 330	89.82 323	97.63 318

OurMVSNet-221017-0		96.14 279	95.98 263	96.62 307	97.49 341	93.44 329	99.92 237	98.16 354	95.86 249	97.65 293	99.95 204	85.71 321	98.78 279	94.93 305	94.18 274	97.64 317

GBi-Net		96.07 281	95.80 271	96.89 299	99.53 197	94.87 300	99.18 339	99.27 244	93.71 306	98.53 249	98.81 327	84.23 329	98.07 333	95.31 299	93.60 277	97.72 289

test1		96.07 281	95.80 271	96.89 299	99.53 197	94.87 300	99.18 339	99.27 244	93.71 306	98.53 249	98.81 327	84.23 329	98.07 333	95.31 299	93.60 277	97.72 289

v7n		96.06 283	95.42 293	97.99 256	97.58 336	97.35 258	99.86 248	99.11 305	92.81 331	97.91 284	99.49 286	90.99 261	98.92 265	92.51 327	88.49 335	97.70 298

PEN-MVS		96.01 284	95.48 289	97.58 272	97.74 328	97.26 264	99.90 241	99.29 230	94.55 287	96.79 318	99.55 281	87.38 305	97.84 343	96.92 273	87.24 342	97.65 314

v1240		95.96 285	95.25 294	98.07 242	97.91 322	97.87 240	99.96 223	99.07 317	93.24 322	98.64 242	98.96 320	88.98 287	98.61 294	89.58 350	90.92 314	97.75 253

pmmvs5		95.94 286	95.61 282	96.95 295	97.42 344	94.66 312	100.00 1	98.08 358	93.60 312	97.05 310	99.43 290	87.02 308	98.46 311	95.76 290	92.12 296	97.72 289

PatchT		95.90 287	94.95 301	98.75 199	99.03 261	98.39 199	99.08 355	99.32 218	85.52 362	99.96 110	94.99 366	97.94 139	98.05 337	80.20 371	98.47 171	99.81 187

USDC		95.90 287	95.70 277	96.50 310	98.60 292	92.56 339	100.00 1	98.30 352	97.77 122	96.92 312	99.94 208	81.25 345	99.45 234	93.54 320	94.96 265	97.49 330

pm-mvs1		95.76 289	95.01 299	98.00 254	98.23 309	97.45 254	99.24 331	99.04 330	93.13 325	95.93 333	99.72 241	86.28 314	98.84 274	95.62 295	87.92 338	97.72 289

SixPastTwentyTwo		95.71 290	95.49 287	96.38 312	97.42 344	93.01 332	99.84 251	98.23 353	94.75 280	95.98 332	99.97 184	85.35 323	98.43 312	94.71 306	93.17 282	97.69 302

MS-PatchMatch		95.66 291	95.87 267	95.05 322	97.80 327	89.25 354	98.88 361	99.30 226	96.35 234	96.86 315	99.01 314	81.35 344	99.43 235	93.30 322	99.98 105	96.46 354

DTE-MVSNet		95.52 292	94.99 300	97.08 288	97.49 341	96.45 284	100.00 1	99.25 250	93.82 305	96.17 329	99.57 279	87.81 300	97.18 349	94.57 307	86.26 349	97.62 320

TinyColmap		95.50 293	95.12 298	96.64 306	98.69 288	93.00 333	99.40 316	97.75 367	96.40 232	96.14 330	99.87 216	79.47 349	99.50 225	93.62 319	94.72 268	97.40 335

K. test v3		95.46 294	95.14 297	96.40 311	97.53 338	93.40 330	99.99 190	99.23 259	95.49 266	92.70 354	99.73 240	84.26 328	98.12 326	93.94 317	93.38 281	97.68 304

FMVSNet5		95.32 295	95.43 292	94.99 324	99.39 235	92.99 334	99.25 330	99.24 255	90.45 345	97.44 303	98.45 341	95.78 200	94.39 370	87.02 357	91.88 301	97.59 324

UniMVSNet_ETH3D		95.28 296	94.41 302	97.89 262	98.91 276	95.14 297	99.13 349	99.35 209	92.11 334	97.17 309	99.66 256	70.28 368	99.36 240	97.88 244	95.18 253	99.16 228

RPMNet		95.26 297	93.82 305	99.56 132	99.31 239	98.86 176	99.13 349	99.42 127	79.82 371	99.96 110	95.13 364	95.69 202	99.98 112	77.54 375	98.40 175	99.84 174

DSMNet-mixed		95.18 298	95.21 296	95.08 321	96.03 355	90.21 352	99.65 288	93.64 383	92.91 327	98.34 260	97.40 355	90.05 274	95.51 367	91.02 338	97.86 205	99.51 224

test_fmvs2		95.17 299	95.23 295	95.01 323	98.95 275	88.99 356	99.99 190	97.77 366	97.79 120	98.58 245	99.70 246	73.36 362	99.34 243	95.88 289	95.03 261	96.70 351

TransMVSNet (Re)		94.78 300	93.72 306	97.93 260	98.34 300	97.88 238	99.23 336	97.98 362	91.60 337	94.55 343	99.71 243	87.89 299	98.36 314	89.30 352	84.92 350	97.56 326

FMVSNet1		94.45 301	93.63 308	96.89 299	98.87 282	94.87 300	99.18 339	99.27 244	90.95 343	97.31 305	98.81 327	72.89 364	98.07 333	92.61 325	92.81 286	97.72 289

test_0402		94.35 302	93.70 307	96.32 313	97.92 321	93.60 326	99.61 294	98.85 347	88.19 357	94.68 342	99.48 287	80.01 347	98.58 300	89.39 351	95.15 256	96.77 349

UnsupCasMVSNet_eth		94.25 303	93.89 304	95.34 320	97.63 331	92.13 340	99.73 277	99.36 200	94.88 277	92.78 351	98.63 335	82.72 337	96.53 357	94.57 307	84.73 351	97.36 336

KD-MVS_2432*1600		94.15 304	93.08 313	97.35 279	99.53 197	97.83 242	99.63 291	99.19 274	92.88 328	96.29 326	97.68 352	98.84 109	96.70 353	89.73 347	63.92 375	97.53 328

miper_refine_blended		94.15 304	93.08 313	97.35 279	99.53 197	97.83 242	99.63 291	99.19 274	92.88 328	96.29 326	97.68 352	98.84 109	96.70 353	89.73 347	63.92 375	97.53 328

MVS-HIRNet		94.12 306	92.73 319	98.29 223	99.33 238	95.95 286	99.38 318	99.19 274	74.54 374	98.26 268	86.34 378	86.07 316	99.06 254	91.60 334	99.87 123	99.85 173

new_pmnet		94.11 307	93.47 310	96.04 317	96.60 352	92.82 335	99.97 218	98.91 343	90.21 347	95.26 336	98.05 350	85.89 319	98.14 324	84.28 362	92.01 298	97.16 341

pmmvs6		93.64 308	92.87 316	95.94 318	97.47 343	91.41 346	98.92 359	99.02 332	87.84 358	95.01 339	99.61 272	77.24 356	98.77 282	94.33 310	86.41 348	97.63 318

Patchmatch-RL test		93.49 309	93.63 308	93.05 340	91.78 371	83.41 365	98.21 369	96.95 374	91.58 338	91.05 356	97.64 354	99.40 55	95.83 365	94.11 315	81.95 360	99.91 138

Anonymous20231206		93.45 310	93.17 312	94.30 332	95.00 365	89.69 353	99.98 212	98.43 351	93.30 321	94.50 345	98.59 336	90.52 266	95.73 366	77.46 376	90.73 318	97.48 332

Anonymous20240521		93.29 311	92.76 318	94.90 327	95.64 361	91.27 347	99.97 218	98.82 348	87.04 359	94.71 341	98.19 347	83.86 333	96.80 352	84.04 363	92.56 292	96.64 352

dmvs_testset		93.27 312	95.48 289	86.65 352	98.74 287	68.42 378	99.92 237	98.91 343	96.19 241	93.28 350	100.00 1	91.06 260	91.67 377	89.64 349	91.54 305	99.86 172

test20.03		93.11 313	92.85 317	93.88 337	95.19 364	91.83 342	100.00 1	98.87 346	93.68 309	92.76 352	98.88 325	89.20 284	92.71 375	77.88 374	89.19 330	97.09 343

test_vis1_rt		93.10 314	92.93 315	93.58 338	99.63 171	85.07 362	99.99 190	93.71 382	97.49 154	90.96 357	97.10 356	60.40 373	99.95 138	99.24 178	97.90 203	95.72 361

APD_test1		93.07 315	94.14 303	89.85 346	99.18 247	72.49 373	99.76 269	98.90 345	92.86 330	96.35 325	99.94 208	75.56 358	99.91 155	86.73 358	97.98 198	97.15 342

EG-PatchMatch MVS		92.94 316	92.49 320	94.29 333	95.87 357	87.07 360	99.07 357	98.11 357	93.19 323	88.98 363	98.66 334	70.89 366	99.08 253	92.43 329	95.21 251	96.72 350

MDA-MVSNet_test_wron		92.61 317	91.09 325	97.19 287	96.71 351	97.26 264	100.00 1	99.14 293	88.61 353	67.90 380	98.32 346	89.03 285	96.57 356	90.47 343	89.59 325	97.74 276

YYNet1		92.44 318	90.92 326	97.03 290	96.20 353	97.06 271	99.99 190	99.14 293	88.21 356	67.93 379	98.43 343	88.63 291	96.28 360	90.64 339	89.08 331	97.74 276

MIMVSNet1		91.96 319	91.20 322	94.23 334	94.94 366	91.69 344	99.34 322	99.22 261	88.23 355	94.18 347	98.45 341	75.52 359	93.41 374	79.37 372	91.49 307	97.60 323

TDRefinement		91.93 320	90.48 328	96.27 314	81.60 382	92.65 338	99.10 352	97.61 370	93.96 304	93.77 348	99.85 222	80.03 346	99.53 221	97.82 246	70.59 372	96.63 353

OpenMVS_ROB	88.34 20	91.89 321	91.12 323	94.19 335	95.55 362	87.63 359	99.26 329	98.03 359	86.61 361	90.65 361	96.82 358	70.14 369	98.78 279	86.54 359	96.50 232	96.15 356

N_pmnet		91.88 322	93.37 311	87.40 351	97.24 348	66.33 381	99.90 241	91.05 385	89.77 350	95.65 335	98.58 337	90.05 274	98.11 328	85.39 360	92.72 287	97.75 253

pmmvs-eth3d		91.73 323	90.67 327	94.92 326	91.63 373	92.71 337	99.90 241	98.54 350	91.19 340	88.08 365	95.50 362	79.31 351	96.13 362	90.55 342	81.32 362	95.91 360

MDA-MVSNet-bldmvs		91.65 324	89.94 331	96.79 305	96.72 350	96.70 280	99.42 315	98.94 340	88.89 352	66.97 382	98.37 344	81.43 343	95.91 364	89.24 353	89.46 328	97.75 253

KD-MVS_self_test		91.16 325	90.09 330	94.35 331	94.44 367	91.27 347	99.74 272	99.08 313	90.82 344	94.53 344	94.91 367	86.11 315	94.78 369	82.67 365	68.52 373	96.99 345

CL-MVSNet_self_test		91.07 326	90.35 329	93.24 339	93.27 368	89.16 355	99.55 300	99.25 250	92.34 333	95.23 337	97.05 357	88.86 290	93.59 373	80.67 369	66.95 374	96.96 346

test_method		91.04 327	91.10 324	90.85 343	98.34 300	77.63 369	100.00 1	98.93 342	76.69 372	96.25 328	98.52 339	70.44 367	97.98 339	89.02 355	91.74 302	96.92 347

CMPMVS	66.12 22	90.65 328	92.04 321	86.46 353	96.18 354	66.87 380	98.03 370	99.38 192	83.38 367	85.49 369	99.55 281	77.59 354	98.80 278	94.44 309	94.31 273	93.72 369
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs3		90.62 329	89.36 333	94.40 330	90.53 376	91.49 345	100.00 1	96.73 375	84.21 365	93.65 349	96.65 359	82.56 340	94.83 368	82.28 366	77.62 367	96.89 348

new-patchmatchnet		90.30 330	89.46 332	92.84 341	90.77 375	88.55 358	99.83 252	98.80 349	90.07 349	87.86 366	95.00 365	78.77 352	94.30 371	84.86 361	79.15 364	95.68 363

UnsupCasMVSNet_bld		89.50 331	88.00 335	93.99 336	95.30 363	88.86 357	98.52 366	99.28 236	85.50 363	87.80 367	94.11 368	61.63 372	96.96 351	90.63 340	79.26 363	96.15 356

mvsany_test3		89.36 332	88.96 334	90.56 344	91.95 370	78.97 368	99.74 272	96.59 378	96.84 198	89.25 362	96.07 360	52.59 375	97.11 350	95.17 302	82.44 358	95.58 364

PM-MVS		88.39 333	87.41 336	91.31 342	91.73 372	82.02 367	99.79 261	96.62 376	91.06 342	90.71 360	95.73 361	48.60 377	95.96 363	90.56 341	81.91 361	95.97 359

test_fmvs3		87.19 334	87.02 337	87.71 350	92.69 369	76.64 370	99.96 223	97.27 371	93.55 313	90.82 359	94.03 369	38.00 383	92.19 376	93.49 321	83.35 357	94.32 366

test_f		86.87 335	86.06 338	89.28 347	91.45 374	76.37 371	99.87 247	97.11 372	91.10 341	88.46 364	93.05 371	38.31 382	96.66 355	91.77 333	83.46 356	94.82 365

Gipuma		84.73 336	83.50 341	88.40 349	97.50 339	82.21 366	88.87 376	99.05 327	65.81 376	85.71 368	90.49 373	53.70 374	96.31 359	78.64 373	91.74 302	86.67 375
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
testf1		84.40 337	84.79 339	83.23 357	95.71 358	58.71 387	98.79 363	97.75 367	81.58 368	84.94 370	98.07 348	45.33 379	97.73 345	77.09 377	83.85 353	93.24 370

APD_test2		84.40 337	84.79 339	83.23 357	95.71 358	58.71 387	98.79 363	97.75 367	81.58 368	84.94 370	98.07 348	45.33 379	97.73 345	77.09 377	83.85 353	93.24 370

testmvs		80.17 339	81.95 342	74.80 362	58.54 389	59.58 386	100.00 1	87.14 388	76.09 373	99.61 176	100.00 1	67.06 370	74.19 385	98.84 198	50.30 379	90.64 374

test_vis3_rt		79.61 340	78.19 345	83.86 356	88.68 377	69.56 377	99.81 256	82.19 390	86.78 360	68.57 378	84.51 381	25.06 387	98.26 319	89.18 354	78.94 365	83.75 378

EGC-MVSNET		79.46 341	74.04 349	95.72 319	96.00 356	92.73 336	99.09 354	99.04 330	5.08 386	16.72 386	98.71 331	73.03 363	98.74 285	82.05 367	96.64 229	95.69 362

test123		79.44 342	79.23 344	80.05 360	80.03 383	71.72 374	100.00 1	77.93 391	62.52 377	94.81 340	99.69 249	78.21 353	74.53 384	92.57 326	27.33 384	93.90 367

PMMVS2		79.15 343	77.28 346	84.76 355	82.34 381	72.66 372	99.70 282	95.11 381	71.68 375	84.78 372	90.87 372	32.05 385	89.99 378	75.53 379	63.45 377	91.64 372

LCM-MVSNet		79.01 344	76.93 347	85.27 354	78.28 384	68.01 379	96.57 373	98.03 359	55.10 380	82.03 373	93.27 370	31.99 386	93.95 372	82.72 364	74.37 369	93.84 368

FPMVS		77.92 345	79.45 343	73.34 364	76.87 385	46.81 390	98.24 368	99.05 327	59.89 379	73.55 375	98.34 345	36.81 384	86.55 379	80.96 368	91.35 311	86.65 376

tmp_tt		75.80 346	74.26 348	80.43 359	52.91 391	53.67 389	87.42 378	97.98 362	61.80 378	67.04 381	100.00 1	76.43 357	96.40 358	96.47 283	28.26 383	91.23 373

E-PMN		70.72 347	70.06 350	72.69 365	83.92 380	65.48 383	99.95 229	92.72 384	49.88 382	72.30 376	86.26 379	47.17 378	77.43 382	53.83 383	44.49 380	75.17 382

EMVS		69.88 348	69.09 351	72.24 366	84.70 379	65.82 382	99.96 223	87.08 389	49.82 383	71.51 377	84.74 380	49.30 376	75.32 383	50.97 384	43.71 381	75.59 381

MVE	68.59 21	67.22 349	64.68 353	74.84 361	74.67 387	62.32 385	95.84 374	90.87 386	50.98 381	58.72 383	81.05 383	12.20 391	78.95 381	61.06 382	56.75 378	83.24 379
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ANet_high		66.05 350	63.44 354	73.88 363	61.14 388	63.45 384	95.68 375	87.18 387	79.93 370	47.35 384	80.68 384	22.35 388	72.33 386	61.24 381	35.42 382	85.88 377

PMVS	60.66 23	65.98 351	65.05 352	68.75 367	55.06 390	38.40 391	88.19 377	96.98 373	48.30 384	44.82 385	88.52 376	12.22 390	86.49 380	67.58 380	83.79 355	81.35 380
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
wuyk23d		28.28 352	29.73 356	23.92 368	75.89 386	32.61 392	66.50 379	12.88 392	16.09 385	14.59 387	16.59 386	12.35 389	32.36 387	39.36 385	13.36 385	6.79 383

cdsmvs_eth3d_5k		24.41 353	32.55 355	0.00 369	0.00 392	0.00 393	0.00 380	99.39 190	0.00 387	0.00 388	100.00 1	93.55 229	0.00 388	0.00 386	0.00 386	0.00 384

ab-mvs-re		8.33 354	11.11 357	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	100.00 1	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

pcd_1.5k_mvsjas		8.24 355	10.99 358	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.14 388	98.75 116	0.00 388	0.00 386	0.00 386	0.00 384

test_blank		0.07 356	0.09 359	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.79 387	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

uanet_test		0.01 357	0.02 360	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.14 388	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

DCPMVS		0.01 357	0.02 360	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.14 388	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

sosnet-low-res		0.01 357	0.02 360	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.14 388	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

sosnet		0.01 357	0.02 360	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.14 388	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

uncertanet		0.01 357	0.02 360	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.14 388	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

Regformer		0.01 357	0.02 360	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.14 388	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

uanet		0.01 357	0.02 360	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.14 388	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

FOURS1					100.00 1	99.97 21	100.00 1	99.42 127	98.52 68	100.00 1

MSC_two_6792asdad				100.00 1	100.00 1	100.00 1		99.42 127					100.00 1	100.00 1	100.00 1	100.00 1

PC_three_1452									98.80 52	100.00 1	100.00 1	99.54 26	100.00 1	100.00 1	100.00 1	100.00 1

No_MVS				100.00 1	100.00 1	100.00 1		99.42 127					100.00 1	100.00 1	100.00 1	100.00 1

test_one_0601					100.00 1	99.99 5		99.42 127	98.72 58	100.00 1	100.00 1	99.60 17

eth-test2					0.00 392

eth-test					0.00 392

ZD-MVS					100.00 1	99.98 17		99.80 42	97.31 170	100.00 1	100.00 1	99.32 61	99.99 93	100.00 1	100.00 1

RE-MVS-def			99.55 55		99.99 49	99.91 51	100.00 1	99.42 127	97.62 136	100.00 1	100.00 1	98.94 100		99.99 58	100.00 1	100.00 1

IU-MVS					100.00 1	99.99 5		99.42 127	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 26	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_TWO								99.42 127	99.03 19	100.00 1	100.00 1	99.56 23	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_ONE					100.00 1	99.99 5		99.42 127	99.03 19	100.00 1	100.00 1	99.50 37	100.00 1

9.14			99.57 49		99.99 49		100.00 1	99.42 127	97.54 147	100.00 1	100.00 1	99.15 82	99.99 93	100.00 1	100.00 1

save fliter					99.99 49	99.93 43	100.00 1	99.42 127	98.93 35

test_0728_THIRD									98.79 54	100.00 1	100.00 1	99.61 16	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	99.42 127					100.00 1	100.00 1	100.00 1	100.00 1

test0726					100.00 1	99.99 5	100.00 1	99.42 127	99.04 14	100.00 1	100.00 1	99.53 29

GSMVS																99.91 138

test_part2					100.00 1	99.99 5				100.00 1

sam_mvs1												99.29 69				99.91 138

sam_mvs												99.33 58

ambc				88.45 348	86.84 378	70.76 376	97.79 372	98.02 361		90.91 358	95.14 363	38.69 381	98.51 306	94.97 304	84.23 352	96.09 358

MTGPA								99.42 127

test_post1							99.32 323				88.24 377	99.33 58	99.59 199	98.31 226

test_post											89.05 375	99.49 39	99.59 199

patchmatchnet-post											97.79 351	99.41 54	99.54 216

GG-mvs-BLEND				99.59 125	99.54 194	99.49 118	99.17 344	99.52 68		99.96 110	99.68 253	100.00 1	99.33 244	99.71 124	99.99 97	99.96 113

MTMP							100.00 1	99.18 281

gm-plane-assit					99.52 204	97.26 264			95.86 249		100.00 1		99.43 235	98.76 203

test9_res														100.00 1	100.00 1	100.00 1

TEST9					100.00 1	99.95 32	100.00 1	99.42 127	97.65 132	100.00 1	100.00 1	99.53 29	99.97 117

test_8					100.00 1	99.91 51	100.00 1	99.42 127	97.70 127	100.00 1	100.00 1	99.51 33	99.98 112

agg_prior2														100.00 1	100.00 1	100.00 1

agg_prior					100.00 1	99.88 72		99.42 127		100.00 1			99.97 117

TestCases				98.99 184	99.93 100	97.35 258		99.40 177	97.08 184	99.09 208	99.98 176	93.37 230	99.95 138	96.94 271	99.84 127	99.68 215

test_prior4						99.93 43	100.00 1

test_prior2							100.00 1		98.82 50	100.00 1	100.00 1	99.47 43		100.00 1	100.00 1

test_prior				99.90 70	100.00 1	99.75 90		99.73 55					99.97 117			100.00 1

旧先验2							100.00 1		98.11 96	100.00 1			100.00 1	99.67 138

新几何2							100.00 1

新几何1				99.99 12	100.00 1	99.96 24		99.81 41	97.89 113	100.00 1	100.00 1	99.20 77	100.00 1	97.91 243	100.00 1	100.00 1

旧先验1					99.99 49	99.88 72		99.82 39			100.00 1	99.27 72			100.00 1	100.00 1

无先验							100.00 1	99.80 42	97.98 104				100.00 1	99.33 170		100.00 1

原ACMM2							100.00 1

原ACMM1				99.93 65	100.00 1	99.80 86		99.66 62	98.18 87	100.00 1	100.00 1	99.43 50	100.00 1	99.50 161	100.00 1	100.00 1

test222					99.99 49	99.90 58	100.00 1	99.69 61	97.66 131	100.00 1	100.00 1	99.30 68			100.00 1	100.00 1

testdata2													100.00 1	97.36 262

segment_acmp												99.55 25

testdata				99.66 116	99.99 49	98.97 173		99.73 55	97.96 109	100.00 1	100.00 1	99.42 52	100.00 1	99.28 175	100.00 1	100.00 1

testdata1							100.00 1		98.77 57

test12				99.95 51	99.99 49	99.89 65		99.42 127		100.00 1		99.24 74	99.97 117		100.00 1	100.00 1

plane_prior7					99.00 267	94.78 310

plane_prior6					99.06 259	94.80 306						88.58 294

plane_prior5								99.40 177					99.55 213	99.79 109	95.57 238	97.76 242

plane_prior4											99.97 184

plane_prior3						94.79 309			99.03 19	99.08 210

plane_prior2							100.00 1		99.00 26

plane_prior1					99.02 262

plane_prior						94.80 306	100.00 1		99.03 19						95.58 234

n2								0.00 393

nn								0.00 393

door-mid								96.32 379

lessismore_v0				96.05 316	97.55 337	91.80 343		99.22 261		91.87 355	99.91 212	83.50 335	98.68 288	92.48 328	90.42 321	97.68 304

LGP-MVS_train				97.28 283	98.85 284	94.60 315		99.37 194	97.35 164	98.85 227	99.98 176	86.66 311	99.56 208	99.55 154	95.26 246	97.70 298

test11								99.42 127

door								96.13 380

HQP5-MVS						94.82 303

HQP-NCC					99.07 255		100.00 1		99.04 14	99.17 200

ACMP_Plane					99.07 255		100.00 1		99.04 14	99.17 200

BP-MVS														99.79 109

HQP4-MVS										99.17 200			99.57 204			97.77 240

HQP3-MVS								99.40 177							95.58 234

HQP2-MVS												88.61 292

NP-MVS					99.07 255	94.81 305					99.97 184

MDTV_nov1_ep13_2view						99.24 145	99.56 299		96.31 237	99.96 110		98.86 107		98.92 194		99.89 151

MDTV_nov1_ep13			98.94 116		99.53 197	98.36 204	99.39 317	99.46 90	96.54 223	99.99 96	99.63 266	98.92 103	99.86 162	98.30 229	98.71 164

ACMMP++_ref															94.58 272

ACMMP++															95.17 255

Test By Simon												99.10 84

ITE_SJBPF				96.84 302	98.96 273	93.49 328		98.12 356	98.12 95	98.35 259	99.97 184	84.45 326	99.56 208	95.63 294	95.25 248	97.49 330

DeepMVS_CX				89.98 345	98.90 277	71.46 375		99.18 281	97.61 140	96.92 312	99.83 225	86.07 316	99.83 170	96.02 288	97.65 217	98.65 236

High-resolution multi-view benchmark