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 8	100.00 1	100.00 1	99.60 21	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 11	100.00 1	100.00 1	99.59 24	100.00 1	100.00 1	100.00 1	100.00 1

CHOSEN 280x420		99.85 3	99.87 1	99.80 117	99.99 49	99.97 21	99.97 273	99.98 16	98.96 34	100.00 1	100.00 1	99.96 4	99.42 304	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 71	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 11	100.00 1	100.00 1	99.39 64	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	99.44 119	99.06 13	100.00 1	100.00 1	99.56 27	99.99 102	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	99.42 147	99.03 21	100.00 1	100.00 1	99.50 41	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	99.42 147	99.04 16	100.00 1	100.00 1	99.53 33	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	99.43 128	99.05 15	100.00 1	100.00 1	99.45 50	99.99 102	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 54	99.96 144	100.00 1	99.21 84	100.00 1	100.00 1	100.00 1	99.99 117

DVP-MVS++		99.81 11	99.75 14	100.00 1	100.00 1	99.99 5	100.00 1	99.42 147	98.79 73	100.00 1	100.00 1	99.54 30	100.00 1	100.00 1	100.00 1	100.00 1

MSP-MVS		99.81 11	99.77 9	99.94 68	100.00 1	99.86 83	100.00 1	99.42 147	98.87 57	100.00 1	100.00 1	99.65 19	99.96 159	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	99.42 147	99.01 26	100.00 1	100.00 1	99.33 66	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	99.42 147	98.91 49	100.00 1	100.00 1	99.22 83	100.00 1	100.00 1	100.00 1	100.00 1
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
XVS		99.79 14	99.73 17	99.98 23	100.00 1	99.94 41	100.00 1	99.75 52	98.67 81	100.00 1	100.00 1	99.16 88	100.00 1	100.00 1	100.00 1	100.00 1

SteuartSystems-ACMMP		99.78 16	99.71 20	99.98 23	99.76 162	99.95 32	100.00 1	99.42 147	98.69 79	100.00 1	100.00 1	99.52 36	99.99 102	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 98	99.01 333	99.95 32	100.00 1	99.75 52	99.37 3	99.99 123	100.00 1	99.76 12	99.60 260	100.00 1	100.00 1	100.00 1

reproduce_model		99.76 18	99.69 22	99.98 23	99.96 98	99.93 47	100.00 1	99.42 147	98.81 69	100.00 1	100.00 1	98.98 107	100.00 1	100.00 1	100.00 1	100.00 1

reproduce-ours		99.76 18	99.69 22	99.98 23	99.96 98	99.94 41	100.00 1	99.42 147	98.82 65	100.00 1	100.00 1	98.99 104	100.00 1	100.00 1	100.00 1	100.00 1

our_new_method		99.76 18	99.69 22	99.98 23	99.96 98	99.94 41	100.00 1	99.42 147	98.82 65	100.00 1	100.00 1	98.99 104	100.00 1	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	97.99 128	99.99 123	100.00 1	99.72 14	100.00 1	99.96 100	100.00 1	100.00 1

PAPR		99.76 18	99.68 28	99.99 12	100.00 1	99.96 24	100.00 1	99.47 79	98.16 114	100.00 1	100.00 1	99.51 37	100.00 1	100.00 1	100.00 1	100.00 1

DeepC-MVS_fast	98.92 1	99.75 23	99.67 30	99.99 12	99.99 49	99.96 24	99.73 350	99.52 72	99.06 13	100.00 1	100.00 1	98.80 129	100.00 1	99.95 106	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 23	99.68 28	99.97 35	100.00 1	99.91 57	99.98 266	99.47 79	99.09 10	100.00 1	100.00 1	98.59 139	100.00 1	99.95 106	100.00 1	100.00 1

HFP-MVS		99.74 25	99.67 30	99.96 46	100.00 1	99.89 71	100.00 1	99.76 49	97.95 136	100.00 1	100.00 1	99.31 71	100.00 1	99.99 71	100.00 1	100.00 1

ACMMPR		99.74 25	99.67 30	99.96 46	100.00 1	99.89 71	100.00 1	99.76 49	97.95 136	100.00 1	100.00 1	99.29 77	100.00 1	99.99 71	100.00 1	100.00 1

PAPM_NR		99.74 25	99.66 33	99.99 12	100.00 1	99.96 24	100.00 1	99.47 79	97.87 141	100.00 1	100.00 1	99.60 21	100.00 1	100.00 1	100.00 1	100.00 1

CDPH-MVS		99.73 28	99.64 37	99.99 12	100.00 1	99.97 21	100.00 1	99.42 147	98.02 126	100.00 1	100.00 1	99.32 69	99.99 102	100.00 1	100.00 1	100.00 1

MVS_0304		99.72 29	99.65 34	99.93 72	99.99 49	99.79 95	100.00 1	99.91 35	99.17 6	100.00 1	100.00 1	97.84 167	100.00 1	100.00 1	99.95 122	100.00 1

region2R		99.72 29	99.64 37	99.97 35	100.00 1	99.90 64	100.00 1	99.74 55	97.86 142	100.00 1	100.00 1	99.19 86	100.00 1	99.99 71	100.00 1	100.00 1

API-MVS		99.72 29	99.70 21	99.79 121	99.97 92	99.37 165	99.96 280	99.94 22	98.48 91	100.00 1	100.00 1	98.92 118	100.00 1	100.00 1	100.00 1	100.00 1

CNLPA		99.72 29	99.65 34	99.91 77	99.97 92	99.72 108	100.00 1	99.47 79	98.43 94	99.88 194	100.00 1	99.14 91	100.00 1	99.97 98	100.00 1	100.00 1

ZNCC-MVS		99.71 33	99.62 44	99.97 35	99.99 49	99.90 64	100.00 1	99.79 45	97.97 132	99.97 137	100.00 1	98.97 109	100.00 1	99.94 108	100.00 1	100.00 1

train_agg		99.71 33	99.63 41	99.97 35	100.00 1	99.95 32	100.00 1	99.42 147	97.70 155	100.00 1	100.00 1	99.51 37	99.97 142	100.00 1	100.00 1	100.00 1

MVS_111021_HR		99.71 33	99.63 41	99.93 72	99.95 102	99.83 90	100.00 1	100.00 1	98.89 53	100.00 1	100.00 1	97.85 165	99.95 172	100.00 1	100.00 1	100.00 1

EI-MVSNet-Vis-set		99.70 36	99.64 37	99.87 91	100.00 1	99.64 120	99.98 266	99.44 119	98.35 104	99.99 123	100.00 1	99.04 101	99.96 159	99.98 86	100.00 1	100.00 1

MVS_111021_LR		99.70 36	99.65 34	99.88 89	99.96 98	99.70 113	100.00 1	99.97 17	98.96 34	100.00 1	100.00 1	97.93 159	99.95 172	99.99 71	100.00 1	100.00 1

PLC	98.56 2	99.70 36	99.74 16	99.58 166	100.00 1	98.79 222	100.00 1	99.54 71	98.58 86	99.96 144	100.00 1	99.59 24	100.00 1	100.00 1	100.00 1	99.94 144
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
SMA-MVS		99.69 39	99.59 47	99.98 23	99.99 49	99.93 47	100.00 1	99.43 128	97.50 186	100.00 1	100.00 1	99.43 55	100.00 1	100.00 1	100.00 1	100.00 1
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
EI-MVSNet-UG-set		99.69 39	99.63 41	99.87 91	99.99 49	99.64 120	99.95 287	99.44 119	98.35 104	100.00 1	100.00 1	98.98 107	99.97 142	99.98 86	100.00 1	100.00 1

PGM-MVS		99.69 39	99.61 45	99.95 55	99.99 49	99.85 86	100.00 1	99.58 67	97.69 157	100.00 1	100.00 1	99.44 51	100.00 1	99.79 136	100.00 1	100.00 1

mPP-MVS		99.69 39	99.60 46	99.97 35	100.00 1	99.91 57	100.00 1	99.42 147	97.91 138	100.00 1	100.00 1	99.04 101	100.00 1	100.00 1	100.00 1	100.00 1

SR-MVS		99.68 43	99.58 49	99.98 23	100.00 1	99.95 32	100.00 1	99.64 64	97.59 174	100.00 1	100.00 1	98.99 104	99.99 102	100.00 1	100.00 1	100.00 1

MTAPA		99.68 43	99.59 47	99.97 35	99.99 49	99.91 57	100.00 1	99.42 147	98.32 106	99.94 177	100.00 1	98.65 135	100.00 1	99.96 100	100.00 1	100.00 1

APD-MVS		99.68 43	99.58 49	99.97 35	99.99 49	99.96 24	100.00 1	99.42 147	97.53 181	100.00 1	100.00 1	99.27 80	99.97 142	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 46	99.57 52	99.97 35	99.98 88	99.92 54	100.00 1	99.42 147	97.83 143	100.00 1	100.00 1	98.89 121	100.00 1	99.98 86	100.00 1	100.00 1

CP-MVS		99.67 46	99.58 49	99.95 55	100.00 1	99.84 88	100.00 1	99.42 147	97.77 150	100.00 1	100.00 1	99.07 95	100.00 1	100.00 1	100.00 1	100.00 1

SF-MVS		99.66 48	99.57 52	99.95 55	99.99 49	99.85 86	100.00 1	99.42 147	97.67 158	100.00 1	100.00 1	99.05 98	99.99 102	100.00 1	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 49	99.55 59	99.97 35	99.99 49	99.91 57	100.00 1	99.48 78	97.54 178	100.00 1	100.00 1	98.97 109	99.99 102	99.98 86	100.00 1	100.00 1

ACMMP		99.65 49	99.57 52	99.89 84	99.99 49	99.66 118	99.75 344	99.73 56	98.16 114	99.75 220	100.00 1	98.90 120	100.00 1	99.96 100	99.88 144	100.00 1
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
lecture		99.64 51	99.53 62	99.98 23	99.99 49	99.93 47	100.00 1	99.47 79	98.53 87	100.00 1	100.00 1	97.88 163	100.00 1	99.98 86	99.92 133	100.00 1

GST-MVS		99.64 51	99.53 62	99.95 55	100.00 1	99.86 83	100.00 1	99.79 45	97.72 153	99.95 174	100.00 1	98.39 148	100.00 1	99.96 100	99.99 103	100.00 1

PS-MVSNAJ		99.64 51	99.57 52	99.85 98	99.78 159	99.81 92	99.95 287	99.42 147	98.38 98	100.00 1	100.00 1	98.75 131	100.00 1	99.88 118	99.99 103	99.74 269

F-COLMAP		99.64 51	99.64 37	99.67 147	99.99 49	99.07 196	100.00 1	99.44 119	98.30 107	99.90 189	100.00 1	99.18 87	99.99 102	99.91 113	100.00 1	99.94 144

fmvsm_l_conf0.5_n_a		99.63 55	99.55 59	99.86 94	99.83 127	99.58 128	100.00 1	99.36 226	98.98 30	100.00 1	100.00 1	97.85 165	99.99 102	100.00 1	99.94 126	100.00 1

fmvsm_l_conf0.5_n		99.63 55	99.56 57	99.86 94	99.81 136	99.59 126	100.00 1	99.36 226	98.98 30	100.00 1	100.00 1	97.92 160	99.99 102	100.00 1	99.95 122	100.00 1

MM		99.63 55	99.52 65	99.94 68	99.99 49	99.82 91	100.00 1	99.97 17	99.11 8	100.00 1	100.00 1	96.65 217	100.00 1	100.00 1	99.97 116	100.00 1

SR-MVS-dyc-post		99.63 55	99.52 65	99.97 35	99.99 49	99.91 57	100.00 1	99.42 147	97.62 166	100.00 1	100.00 1	98.65 135	99.99 102	99.99 71	100.00 1	100.00 1

DPM-MVS		99.63 55	99.51 67	100.00 1	99.90 114	100.00 1	100.00 1	99.43 128	99.00 27	100.00 1	100.00 1	99.58 26	100.00 1	97.64 314	100.00 1	100.00 1

EPNet		99.62 60	99.69 22	99.42 191	99.99 49	98.37 256	100.00 1	99.89 37	98.83 63	100.00 1	100.00 1	98.97 109	100.00 1	99.90 114	99.61 178	99.89 179
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DELS-MVS		99.62 60	99.56 57	99.82 106	99.92 110	99.45 154	100.00 1	99.78 47	98.92 46	99.73 224	100.00 1	97.70 174	100.00 1	99.93 110	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 62	99.50 68	99.97 35	99.98 88	99.92 54	100.00 1	99.42 147	97.53 181	99.77 217	100.00 1	98.77 130	100.00 1	99.99 71	100.00 1	99.99 117
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MP-MVS		99.61 62	99.49 70	99.98 23	99.99 49	99.94 41	100.00 1	99.42 147	97.82 145	99.99 123	100.00 1	98.20 151	100.00 1	99.99 71	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 62	99.69 22	99.35 204	99.99 49	98.06 284	100.00 1	99.36 226	99.83 2	100.00 1	100.00 1	98.95 113	99.99 102	100.00 1	99.11 191	100.00 1

HPM-MVS_fast		99.60 65	99.49 70	99.91 77	99.99 49	99.78 96	100.00 1	99.42 147	97.09 222	100.00 1	100.00 1	98.95 113	99.96 159	99.98 86	100.00 1	100.00 1

HPM-MVS		99.59 66	99.50 68	99.89 84	100.00 1	99.70 113	100.00 1	99.42 147	97.46 190	100.00 1	100.00 1	98.60 138	99.96 159	99.99 71	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 67	99.48 73	99.85 98	99.86 121	99.54 135	100.00 1	99.36 226	98.94 40	100.00 1	100.00 1	97.97 157	100.00 1	99.88 118	99.28 186	100.00 1

BP-MVS1		99.56 68	99.48 73	99.79 121	99.48 270	99.61 123	100.00 1	99.32 250	97.34 202	99.94 177	100.00 1	99.74 13	99.89 198	99.75 150	99.72 166	99.87 203

test_fmvsmconf_n		99.56 68	99.46 76	99.86 94	99.68 179	99.58 128	100.00 1	99.31 259	98.92 46	99.88 194	100.00 1	97.35 193	99.99 102	99.98 86	99.99 103	100.00 1

test_fmvsm_n_1920		99.55 70	99.49 70	99.73 136	99.85 123	99.19 187	100.00 1	99.41 196	98.87 57	100.00 1	100.00 1	97.34 194	100.00 1	99.98 86	99.90 140	100.00 1

WTY-MVS		99.54 71	99.40 78	99.95 55	99.81 136	99.93 47	100.00 1	100.00 1	97.98 130	99.84 198	100.00 1	98.94 115	99.98 133	99.86 122	98.21 242	99.94 144

test_yl		99.51 72	99.37 83	99.95 55	99.82 130	99.90 64	100.00 1	99.47 79	97.48 188	100.00 1	100.00 1	99.80 6	100.00 1	99.98 86	97.75 279	99.94 144

DCV-MVSNet		99.51 72	99.37 83	99.95 55	99.82 130	99.90 64	100.00 1	99.47 79	97.48 188	100.00 1	100.00 1	99.80 6	100.00 1	99.98 86	97.75 279	99.94 144

xiu_mvs_v2_base		99.51 72	99.41 77	99.82 106	99.70 171	99.73 106	99.92 303	99.40 200	98.15 116	100.00 1	100.00 1	98.50 143	100.00 1	99.85 124	99.13 190	99.74 269

HY-MVS	96.53 9	99.50 75	99.35 88	99.96 46	99.81 136	99.93 47	99.64 363	100.00 1	97.97 132	99.84 198	99.85 288	98.94 115	99.99 102	99.86 122	98.23 241	99.95 139

PHI-MVS		99.50 75	99.39 79	99.82 106	100.00 1	99.45 154	100.00 1	99.94 22	96.38 297	100.00 1	100.00 1	98.18 152	100.00 1	100.00 1	100.00 1	100.00 1

CPTT-MVS		99.49 77	99.38 80	99.85 98	100.00 1	99.54 135	100.00 1	99.42 147	97.58 175	99.98 131	100.00 1	97.43 191	100.00 1	99.99 71	100.00 1	100.00 1

MAR-MVS		99.49 77	99.36 86	99.89 84	99.97 92	99.66 118	99.74 345	99.95 19	97.89 139	100.00 1	100.00 1	96.71 216	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 79	99.38 80	99.75 132	99.89 116	99.51 142	99.45 384	100.00 1	98.38 98	99.83 201	100.00 1	98.86 122	99.81 229	99.25 229	98.78 200	99.94 144

PVSNet_Blended		99.48 79	99.36 86	99.83 104	99.98 88	99.60 124	100.00 1	100.00 1	97.79 148	100.00 1	100.00 1	96.57 219	99.99 102	100.00 1	99.88 144	99.90 172

NormalMVS		99.47 81	99.48 73	99.43 188	99.99 49	98.55 239	99.94 295	99.28 279	98.39 96	100.00 1	100.00 1	98.44 145	99.98 133	99.36 218	99.92 133	99.75 262

test_fmvsmvis_n_1920		99.46 82	99.37 83	99.73 136	98.88 350	99.18 189	100.00 1	99.26 299	98.85 59	99.79 214	100.00 1	97.70 174	100.00 1	99.98 86	99.86 150	100.00 1

testing3-2		99.45 83	99.31 91	99.86 94	99.70 171	99.73 106	100.00 1	99.47 79	97.46 190	99.97 137	99.97 236	99.48 47	100.00 1	99.78 142	97.99 258	99.85 208

sss		99.45 83	99.34 90	99.80 117	99.76 162	99.50 144	100.00 1	99.91 35	97.72 153	99.98 131	99.94 266	98.45 144	100.00 1	99.53 208	98.75 203	99.89 179

AdaColmap		99.44 85	99.26 99	99.95 55	100.00 1	99.86 83	99.70 356	99.99 13	98.53 87	99.90 189	100.00 1	95.34 239	100.00 1	99.92 111	100.00 1	100.00 1

balanced_conf03		99.43 86	99.28 93	99.85 98	99.68 179	99.68 116	99.97 273	99.28 279	97.03 228	99.96 144	99.97 236	97.90 161	99.93 189	99.77 144	100.00 1	99.94 144

thisisatest0515		99.42 87	99.31 91	99.74 133	99.59 222	99.55 132	100.00 1	99.46 97	96.65 272	99.92 184	100.00 1	99.44 51	99.85 217	99.09 243	99.63 177	99.81 229

myMVS_eth3d28		99.41 88	99.28 93	99.80 117	99.69 174	99.53 137	100.00 1	99.43 128	97.12 221	99.98 131	99.97 236	99.41 61	100.00 1	99.81 135	98.07 255	99.88 192

CANet		99.40 89	99.24 105	99.89 84	99.99 49	99.76 100	100.00 1	99.73 56	98.40 95	99.78 216	100.00 1	95.28 240	99.96 159	100.00 1	99.99 103	99.96 133

GDP-MVS		99.39 90	99.26 99	99.77 129	99.53 241	99.55 132	100.00 1	99.11 375	97.14 217	99.96 144	100.00 1	99.83 5	99.89 198	98.47 277	99.26 187	99.87 203

MVSMamba_PlusPlus		99.39 90	99.25 101	99.80 117	99.68 179	99.59 126	99.99 238	99.30 265	96.66 271	99.96 144	99.97 236	97.89 162	99.92 192	99.76 146	100.00 1	99.90 172

114514_t		99.39 90	99.25 101	99.81 111	99.97 92	99.48 152	100.00 1	99.42 147	95.53 331	100.00 1	100.00 1	98.37 149	99.95 172	99.97 98	100.00 1	100.00 1

fmvsm_l_conf0.5_n_3		99.38 93	99.20 114	99.92 76	99.80 149	99.78 96	100.00 1	99.35 237	98.94 40	100.00 1	100.00 1	94.77 256	99.99 102	99.99 71	99.92 133	100.00 1

alignmvs		99.38 93	99.21 110	99.91 77	99.73 167	99.92 54	100.00 1	99.51 76	97.61 170	100.00 1	100.00 1	99.06 96	99.93 189	99.83 128	97.12 291	99.90 172

1314		99.38 93	99.19 115	99.96 46	98.88 350	99.89 71	99.24 405	99.93 30	98.88 54	98.79 301	100.00 1	97.02 200	100.00 1	100.00 1	100.00 1	100.00 1

thisisatest0530		99.37 96	99.27 95	99.69 143	99.59 222	99.41 160	100.00 1	99.46 97	96.46 288	99.90 189	100.00 1	99.44 51	99.85 217	98.97 248	99.58 179	99.80 248

UBG		99.36 97	99.27 95	99.63 154	99.63 206	99.01 205	100.00 1	99.43 128	96.99 231	100.00 1	99.92 272	99.69 17	99.99 102	99.74 151	98.06 256	99.88 192

fmvsm_l_conf0.5_n_9		99.35 98	99.15 120	99.95 55	99.83 127	99.84 88	100.00 1	99.30 265	98.92 46	100.00 1	100.00 1	94.32 270	100.00 1	100.00 1	99.93 130	100.00 1

xiu_mvs_v1_base_debu		99.35 98	99.21 110	99.79 121	99.67 188	99.71 109	99.78 335	99.36 226	98.13 118	100.00 1	100.00 1	97.00 204	100.00 1	99.83 128	99.07 192	99.66 283

xiu_mvs_v1_base		99.35 98	99.21 110	99.79 121	99.67 188	99.71 109	99.78 335	99.36 226	98.13 118	100.00 1	100.00 1	97.00 204	100.00 1	99.83 128	99.07 192	99.66 283

xiu_mvs_v1_base_debi		99.35 98	99.21 110	99.79 121	99.67 188	99.71 109	99.78 335	99.36 226	98.13 118	100.00 1	100.00 1	97.00 204	100.00 1	99.83 128	99.07 192	99.66 283

fmvsm_s_conf0.5_n_8		99.34 102	99.14 122	99.91 77	99.83 127	99.74 104	100.00 1	99.38 216	98.94 40	100.00 1	100.00 1	94.25 272	99.99 102	100.00 1	99.91 138	100.00 1

ETV-MVS		99.34 102	99.24 105	99.64 153	99.58 227	99.33 168	100.00 1	99.25 303	97.57 176	99.96 144	100.00 1	97.44 190	99.79 234	99.70 165	99.65 174	99.81 229

tttt0517		99.34 102	99.23 108	99.67 147	99.57 231	99.38 162	100.00 1	99.46 97	96.33 302	99.89 192	100.00 1	99.44 51	99.84 221	98.93 250	99.46 183	99.78 258

CS-MVS		99.33 105	99.27 95	99.50 174	99.99 49	99.00 208	100.00 1	99.13 367	97.26 210	99.96 144	100.00 1	97.79 170	99.64 258	99.64 183	99.67 171	99.87 203

PVSNet_Blended_VisFu		99.33 105	99.18 118	99.78 126	99.82 130	99.49 148	100.00 1	99.95 19	97.36 199	99.63 232	100.00 1	96.45 223	99.95 172	99.79 136	99.65 174	99.89 179

fmvsm_s_conf0.5_n_a		99.32 107	99.15 120	99.81 111	99.80 149	99.47 153	100.00 1	99.35 237	98.22 109	100.00 1	100.00 1	95.21 244	99.99 102	99.96 100	99.86 150	99.98 120

HyFIR lowres test		99.32 107	99.24 105	99.58 166	99.95 102	99.26 177	100.00 1	99.99 13	96.72 260	99.29 260	99.91 275	99.49 43	99.47 294	99.74 151	98.08 254	100.00 1

SPE-MVS-test		99.31 109	99.27 95	99.43 188	99.99 49	98.77 223	100.00 1	99.19 332	97.24 211	99.96 144	100.00 1	97.56 182	99.70 255	99.68 173	99.81 160	99.82 220

LS3D		99.31 109	99.13 123	99.87 91	99.99 49	99.71 109	99.55 374	99.46 97	97.32 205	99.82 209	100.00 1	96.85 211	99.97 142	99.14 237	100.00 1	99.92 157

SymmetryMVS		99.30 111	99.25 101	99.45 183	99.79 154	98.55 239	99.94 295	99.47 79	98.39 96	100.00 1	100.00 1	98.44 145	99.98 133	99.36 218	97.83 272	99.83 214

fmvsm_s_conf0.5_n_6		99.30 111	99.12 125	99.84 103	99.24 314	99.56 130	100.00 1	99.31 259	98.90 52	100.00 1	100.00 1	94.75 258	99.97 142	99.98 86	99.88 144	100.00 1

PVSNet	94.91 18	99.30 111	99.25 101	99.44 185	100.00 1	98.32 263	100.00 1	99.86 38	98.04 125	100.00 1	100.00 1	96.10 227	100.00 1	99.55 203	99.73 165	100.00 1

UWE-MVS-28		99.29 114	99.23 108	99.48 179	99.73 167	98.86 217	100.00 1	99.43 128	96.97 233	99.99 123	99.83 291	99.43 55	99.77 240	99.35 221	98.31 232	99.80 248

lupinMVS		99.29 114	99.16 119	99.69 143	99.45 283	99.49 148	100.00 1	99.15 354	97.45 192	99.97 137	100.00 1	96.76 212	99.76 244	99.67 176	100.00 1	99.81 229

CSCG		99.28 116	99.35 88	99.05 238	99.99 49	97.15 330	100.00 1	99.47 79	97.44 194	99.42 247	100.00 1	97.83 169	100.00 1	99.99 71	100.00 1	100.00 1

thres200		99.27 117	99.04 133	99.96 46	99.81 136	99.90 64	100.00 1	99.94 22	97.31 207	99.83 201	99.96 253	97.04 197	100.00 1	99.62 190	97.88 267	99.98 120

OMC-MVS		99.27 117	99.38 80	98.96 246	99.95 102	97.06 334	100.00 1	99.40 200	98.83 63	99.88 194	100.00 1	97.01 201	99.86 210	99.47 213	99.84 155	99.97 127

testing11		99.26 119	99.19 115	99.46 181	99.64 204	98.61 235	100.00 1	99.43 128	96.94 235	99.92 184	99.94 266	99.43 55	99.97 142	99.67 176	97.79 277	99.82 220

EIA-MVS		99.26 119	99.19 115	99.45 183	99.63 206	98.75 224	100.00 1	99.27 292	96.93 236	99.95 174	100.00 1	97.47 187	99.79 234	99.74 151	99.72 166	99.82 220

tfpn200view9		99.26 119	99.03 134	99.96 46	99.81 136	99.89 71	100.00 1	99.94 22	97.23 213	99.83 201	99.96 253	97.04 197	100.00 1	99.59 197	97.85 269	99.98 120

thres400		99.26 119	99.03 134	99.95 55	99.81 136	99.89 71	100.00 1	99.94 22	97.23 213	99.83 201	99.96 253	97.04 197	100.00 1	99.59 197	97.85 269	99.97 127

test_fmvsmconf0.1_n		99.25 123	99.05 132	99.82 106	98.92 346	99.55 132	100.00 1	99.23 313	98.91 49	99.75 220	99.97 236	94.79 255	99.94 185	99.94 108	99.99 103	99.97 127

thres100view900		99.25 123	99.01 136	99.95 55	99.81 136	99.87 80	100.00 1	99.94 22	97.13 219	99.83 201	99.96 253	97.01 201	100.00 1	99.59 197	97.85 269	99.98 120

EPMVS		99.25 123	99.13 123	99.60 160	99.60 218	99.20 186	99.60 369	100.00 1	96.93 236	99.92 184	99.36 368	99.05 98	99.71 254	98.77 259	98.94 197	99.90 172

thres600view7		99.24 126	99.00 139	99.95 55	99.81 136	99.87 80	100.00 1	99.94 22	97.13 219	99.83 201	99.96 253	97.01 201	100.00 1	99.54 206	97.77 278	99.97 127

MVS		99.22 127	98.96 145	99.98 23	99.00 337	99.95 32	99.24 405	99.94 22	98.14 117	98.88 291	100.00 1	95.63 236	100.00 1	99.85 124	100.00 1	100.00 1

guyue		99.21 128	99.07 130	99.62 156	99.55 236	99.29 172	100.00 1	99.32 250	97.66 159	99.96 144	100.00 1	95.84 231	99.84 221	99.63 188	99.67 171	99.75 262

fmvsm_s_conf0.5_n		99.21 128	99.01 136	99.83 104	99.84 124	99.53 137	100.00 1	99.38 216	98.29 108	100.00 1	100.00 1	93.62 280	99.99 102	99.99 71	99.93 130	99.98 120

EC-MVSNet		99.19 130	99.09 129	99.48 179	99.42 287	99.07 196	100.00 1	99.21 327	96.95 234	99.96 144	100.00 1	96.88 210	99.48 292	99.64 183	99.79 164	99.88 192

testing91		99.18 131	99.10 127	99.41 192	99.60 218	98.43 248	100.00 1	99.43 128	96.76 251	99.82 209	99.92 272	99.05 98	99.98 133	99.62 190	97.67 283	99.81 229

testing99		99.18 131	99.10 127	99.41 192	99.60 218	98.43 248	100.00 1	99.43 128	96.76 251	99.84 198	99.92 272	99.06 96	99.98 133	99.62 190	97.67 283	99.81 229

UWE-MVS		99.18 131	99.06 131	99.51 171	99.67 188	98.80 221	100.00 1	99.43 128	96.80 248	99.93 183	99.86 283	99.79 8	99.94 185	97.78 310	98.33 229	99.80 248

ETVMVS		99.16 134	98.98 142	99.69 143	99.67 188	99.56 130	100.00 1	99.45 105	96.36 299	99.98 131	99.95 260	98.65 135	99.64 258	99.11 241	97.63 286	99.88 192

FE-MVS		99.16 134	98.99 141	99.66 150	99.65 198	99.18 189	99.58 371	99.43 128	95.24 343	99.91 187	99.59 342	99.37 65	99.97 142	98.31 284	99.81 160	99.83 214

testing222		99.14 136	98.94 150	99.73 136	99.67 188	99.51 142	100.00 1	99.43 128	96.90 241	99.99 123	99.90 277	98.55 141	99.86 210	98.85 254	97.18 290	99.81 229

PMMVS		99.12 137	98.97 144	99.58 166	99.57 231	98.98 210	100.00 1	99.30 265	97.14 217	99.96 144	100.00 1	96.53 222	99.82 226	99.70 165	98.49 213	99.94 144

jason		99.11 138	98.96 145	99.59 162	99.17 317	99.31 171	100.00 1	99.13 367	97.38 198	99.83 201	100.00 1	95.54 237	99.72 252	99.57 202	99.97 116	99.74 269
jason: jason.
EPP-MVSNet		99.10 139	99.00 139	99.40 196	99.51 258	98.68 230	99.92 303	99.43 128	95.47 337	99.65 231	100.00 1	99.51 37	99.76 244	99.53 208	98.00 257	99.75 262

TESTMET0.1,1		99.08 140	98.96 145	99.44 185	99.63 206	99.38 162	100.00 1	99.45 105	95.53 331	99.48 241	100.00 1	99.71 15	99.02 325	96.84 342	99.99 103	99.91 161

IS-MVSNet		99.08 140	98.91 155	99.59 162	99.65 198	99.38 162	99.78 335	99.24 309	96.70 266	99.51 239	100.00 1	98.44 145	99.52 285	98.47 277	98.39 221	99.88 192

LuminaMVS		99.07 142	98.92 154	99.50 174	98.87 353	99.12 194	99.92 303	99.22 318	97.45 192	99.82 209	99.98 224	96.29 225	99.85 217	99.71 161	99.05 195	99.52 291

UA-Net		99.06 143	98.83 162	99.74 133	99.52 253	99.40 161	99.08 432	99.45 105	97.64 163	99.83 201	100.00 1	95.80 232	99.94 185	98.35 282	99.80 163	99.88 192

3Dnovator	95.63 14	99.06 143	98.76 170	99.96 46	98.86 355	99.90 64	99.98 266	99.93 30	98.95 37	98.49 321	100.00 1	92.91 293	100.00 1	99.71 161	100.00 1	100.00 1

mvsmamba		99.05 145	98.98 142	99.27 225	99.57 231	98.10 280	100.00 1	99.28 279	95.92 317	99.96 144	99.97 236	96.73 215	99.89 198	99.72 157	99.65 174	99.81 229

fmvsm_s_conf0.5_n_9		99.04 146	98.78 167	99.81 111	99.86 121	99.44 157	100.00 1	99.32 250	98.94 40	100.00 1	100.00 1	91.00 322	99.99 102	100.00 1	99.94 126	100.00 1

patch_mono-2		99.04 146	99.79 6	96.81 374	99.92 110	90.47 426	100.00 1	99.41 196	98.95 37	100.00 1	100.00 1	99.78 9	100.00 1	100.00 1	100.00 1	99.95 139

VNet		99.04 146	98.75 171	99.90 81	99.81 136	99.75 101	99.50 380	99.47 79	98.36 102	100.00 1	99.99 216	94.66 260	100.00 1	99.90 114	97.09 292	99.96 133

AstraMVS		99.03 149	99.01 136	99.09 235	99.46 279	97.66 308	100.00 1	99.23 313	97.83 143	99.95 174	100.00 1	95.52 238	99.86 210	99.74 151	99.39 185	99.74 269

sasdasda		99.03 149	98.73 174	99.94 68	99.75 164	99.95 32	100.00 1	99.30 265	97.64 163	100.00 1	100.00 1	95.22 242	99.97 142	99.76 146	96.90 297	99.91 161

canonicalmvs		99.03 149	98.73 174	99.94 68	99.75 164	99.95 32	100.00 1	99.30 265	97.64 163	100.00 1	100.00 1	95.22 242	99.97 142	99.76 146	96.90 297	99.91 161

test-LLR		99.03 149	98.91 155	99.40 196	99.40 294	99.28 174	100.00 1	99.45 105	96.70 266	99.42 247	99.12 380	99.31 71	99.01 326	96.82 343	99.99 103	99.91 161

PatchmatchNet		99.03 149	98.96 145	99.26 226	99.49 267	98.33 261	99.38 392	99.45 105	96.64 273	99.96 144	99.58 344	99.49 43	99.50 290	97.63 315	99.00 196	99.93 155
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
3Dnovator+	95.58 15	99.03 149	98.71 179	99.96 46	98.99 340	99.89 71	100.00 1	99.51 76	98.96 34	98.32 332	100.00 1	92.78 295	100.00 1	99.87 121	100.00 1	100.00 1

CANet_DTU		99.02 155	98.90 158	99.41 192	99.88 118	98.71 228	100.00 1	99.29 273	98.84 61	100.00 1	100.00 1	94.02 275	100.00 1	98.08 293	99.96 120	99.52 291

PatchMatch-RL		99.02 155	98.78 167	99.74 133	99.99 49	99.29 172	100.00 1	100.00 1	98.38 98	99.89 192	99.81 298	93.14 290	99.99 102	97.85 304	99.98 113	99.95 139

MGCFI-Net		99.01 157	98.70 181	99.93 72	99.74 166	99.94 41	100.00 1	99.29 273	97.60 173	100.00 1	100.00 1	95.10 248	99.96 159	99.74 151	96.85 299	99.91 161

fmvsm_s_conf0.5_n_5		99.00 158	98.70 181	99.88 89	99.81 136	99.64 120	100.00 1	99.26 299	98.78 76	99.97 137	100.00 1	90.65 329	99.99 102	100.00 1	99.89 141	99.99 117

FA-MVS(test-final)		99.00 158	98.75 171	99.73 136	99.63 206	99.43 158	99.83 324	99.43 128	95.84 323	99.52 238	99.37 367	97.84 167	99.96 159	97.63 315	99.68 169	99.79 254

CHOSEN 1792x2688		99.00 158	98.91 155	99.25 227	99.90 114	97.79 304	100.00 1	99.99 13	98.79 73	98.28 335	100.00 1	93.63 279	99.95 172	99.66 181	99.95 122	100.00 1

DeepC-MVS	97.84 5	99.00 158	98.80 166	99.60 160	99.93 107	99.03 201	100.00 1	99.40 200	98.61 85	99.33 258	100.00 1	92.23 306	99.95 172	99.74 151	99.96 120	99.83 214
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
fmvsm_s_conf0.5_n_3		98.99 162	98.69 183	99.89 84	99.70 171	99.69 115	100.00 1	99.39 213	98.93 44	100.00 1	100.00 1	90.20 337	99.99 102	100.00 1	99.95 122	100.00 1

baseline2		98.99 162	98.93 152	99.18 231	99.26 313	99.15 192	100.00 1	99.46 97	96.71 265	96.79 391	100.00 1	99.42 59	99.25 315	98.75 261	99.94 126	99.15 302

QAPM		98.99 162	98.66 186	99.96 46	99.01 333	99.87 80	99.88 316	99.93 30	97.99 128	98.68 306	100.00 1	93.17 288	100.00 1	99.32 225	100.00 1	100.00 1

Vis-MVSNet (Re-imp)		98.99 162	98.89 159	99.29 219	99.64 204	98.89 216	99.98 266	99.31 259	96.74 256	99.48 241	100.00 1	98.11 154	99.10 321	98.39 280	98.34 226	99.89 179

fmvsm_s_conf0.5_n_7		98.98 166	98.85 161	99.37 202	99.67 188	98.34 260	100.00 1	99.31 259	98.97 32	100.00 1	100.00 1	91.70 311	99.97 142	99.99 71	99.97 116	99.80 248

fmvsm_s_conf0.5_n_4		98.98 166	98.74 173	99.68 146	99.81 136	99.50 144	100.00 1	99.26 299	98.91 49	100.00 1	100.00 1	90.87 326	99.97 142	99.99 71	99.81 160	99.57 288

tpmrst		98.98 166	98.93 152	99.14 234	99.61 215	97.74 305	99.52 378	99.36 226	96.05 314	99.98 131	99.64 330	99.04 101	99.86 210	98.94 249	98.19 245	99.82 220

test-mter		98.96 169	98.82 163	99.40 196	99.40 294	99.28 174	100.00 1	99.45 105	95.44 342	99.42 247	99.12 380	99.70 16	99.01 326	96.82 343	99.99 103	99.91 161

diffmvs		98.96 169	98.73 174	99.63 154	99.54 238	99.16 191	100.00 1	99.18 339	97.33 204	99.96 144	100.00 1	94.60 262	99.91 194	99.66 181	98.33 229	99.82 220
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		98.96 169	98.95 149	99.01 242	99.48 270	98.36 258	99.93 301	99.37 220	96.79 249	99.31 259	99.83 291	99.77 11	98.91 338	98.07 295	97.98 259	99.77 259
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
fmvsm_s_conf0.1_n_2		98.95 172	98.69 183	99.73 136	99.61 215	99.74 104	100.00 1	99.23 313	98.95 37	99.97 137	100.00 1	90.92 325	99.97 142	100.00 1	99.58 179	99.47 294

mamv4		98.95 172	99.11 126	98.46 274	99.68 179	95.67 358	99.14 425	99.27 292	96.43 289	99.94 177	99.97 236	97.79 170	99.88 206	99.77 144	100.00 1	99.84 210

MVSFormer		98.94 174	98.82 163	99.28 222	99.45 283	99.49 148	100.00 1	99.13 367	95.46 338	99.97 137	100.00 1	96.76 212	98.59 369	98.63 269	100.00 1	99.74 269

MVS_Test		98.93 175	98.65 187	99.77 129	99.62 213	99.50 144	99.99 238	99.19 332	95.52 333	99.96 144	99.86 283	96.54 221	99.98 133	98.65 266	98.48 214	99.82 220

diffmvs_AUTHOR		98.92 176	98.73 174	99.49 178	99.48 270	98.81 220	99.94 295	99.14 361	97.24 211	99.96 144	100.00 1	94.85 253	99.87 209	99.67 176	98.31 232	99.79 254

baseline1		98.91 177	98.61 192	99.81 111	99.71 169	99.77 99	99.78 335	99.44 119	97.51 185	98.81 299	99.99 216	98.25 150	99.76 244	98.60 272	95.41 313	99.89 179

1112_ss		98.91 177	98.71 179	99.51 171	99.69 174	98.75 224	99.99 238	99.15 354	96.82 246	98.84 296	100.00 1	97.45 188	99.89 198	98.66 264	97.75 279	99.89 179

fmvsm_s_conf0.5_n_2		98.90 179	98.57 197	99.90 81	99.79 154	99.78 96	100.00 1	99.25 303	98.97 32	100.00 1	100.00 1	89.22 355	99.99 102	100.00 1	99.88 144	99.92 157

MSDG		98.90 179	98.63 190	99.70 142	99.92 110	99.25 179	100.00 1	99.37 220	95.71 325	99.40 253	100.00 1	96.58 218	99.95 172	96.80 345	99.94 126	99.91 161

dcpmvs_2		98.87 181	99.53 62	96.90 368	99.87 120	90.88 424	99.94 295	99.07 389	98.20 112	100.00 1	100.00 1	98.69 134	99.86 210	100.00 1	100.00 1	99.95 139

viewmanbaseed2359cas		98.86 182	98.68 185	99.40 196	99.51 258	98.51 247	99.98 266	99.22 318	97.05 227	99.72 225	100.00 1	94.77 256	99.89 198	99.58 200	98.31 232	99.81 229

DP-MVS		98.86 182	98.54 200	99.81 111	99.97 92	99.45 154	99.52 378	99.40 200	94.35 367	98.36 327	100.00 1	96.13 226	99.97 142	99.12 240	100.00 1	100.00 1

CostFormer		98.84 184	98.77 169	99.04 240	99.41 289	97.58 311	99.67 361	99.35 237	94.66 356	99.96 144	99.36 368	99.28 79	99.74 249	99.41 216	97.81 274	99.81 229

Test_1112_low_res		98.83 185	98.60 194	99.51 171	99.69 174	98.75 224	99.99 238	99.14 361	96.81 247	98.84 296	99.06 384	97.45 188	99.89 198	98.66 264	97.75 279	99.89 179

BH-w/o		98.82 186	98.81 165	98.88 251	99.62 213	96.71 341	100.00 1	99.28 279	97.09 222	98.81 299	100.00 1	94.91 252	99.96 159	99.54 206	100.00 1	99.96 133

mvs_anonymous		98.80 187	98.60 194	99.38 201	99.57 231	99.24 181	100.00 1	99.21 327	95.87 318	98.92 288	99.82 295	96.39 224	99.03 324	99.13 239	98.50 212	99.88 192

fmvsm_s_conf0.1_n		98.77 188	98.42 213	99.82 106	99.47 275	99.52 141	100.00 1	99.27 292	97.53 181	100.00 1	100.00 1	89.73 347	99.96 159	99.84 127	99.93 130	99.97 127

SSM_0404		98.76 189	98.56 198	99.35 204	99.53 241	98.65 233	99.80 333	99.15 354	96.53 281	99.47 244	100.00 1	94.38 267	99.76 244	99.64 183	98.59 208	99.64 287

TAMVS		98.76 189	98.73 174	98.86 252	99.44 285	97.69 306	99.57 372	99.34 244	96.57 278	99.12 271	99.81 298	98.83 126	99.16 319	97.97 301	97.91 265	99.73 278

OpenMVS	95.20 17	98.76 189	98.41 215	99.78 126	98.89 349	99.81 92	99.99 238	99.76 49	98.02 126	98.02 350	100.00 1	91.44 313	100.00 1	99.63 188	99.97 116	99.55 289

RRT-MVS		98.75 192	98.52 203	99.44 185	99.65 198	98.57 238	99.90 309	99.08 384	96.51 285	99.96 144	99.95 260	92.59 301	99.96 159	99.60 195	99.45 184	99.81 229

SSM_0407		98.72 193	98.52 203	99.33 212	99.53 241	98.52 244	99.88 316	99.15 354	96.53 281	98.95 284	100.00 1	94.38 267	99.72 252	99.64 183	98.62 205	99.75 262

dp		98.72 193	98.61 192	99.03 241	99.53 241	97.39 317	99.45 384	99.39 213	95.62 328	99.94 177	99.52 354	98.83 126	99.82 226	96.77 348	98.42 218	99.89 179

fmvsm_s_conf0.1_n_a		98.71 195	98.36 225	99.78 126	99.09 323	99.42 159	100.00 1	99.26 299	97.42 196	100.00 1	100.00 1	89.78 345	99.96 159	99.82 133	99.85 153	99.97 127

PVSNet_BlendedMVS		98.71 195	98.62 191	98.98 245	99.98 88	99.60 124	100.00 1	100.00 1	97.23 213	100.00 1	99.03 390	96.57 219	99.99 102	100.00 1	94.75 338	97.35 411

ADS-MVSNet		98.70 197	98.51 206	99.28 222	99.51 258	98.39 253	99.24 405	99.44 119	95.52 333	99.96 144	99.70 314	97.57 180	99.58 266	97.11 333	98.54 210	99.88 192

baseline		98.69 198	98.45 210	99.41 192	99.52 253	98.67 231	100.00 1	99.17 348	97.03 228	99.13 270	100.00 1	93.17 288	99.74 249	99.70 165	98.34 226	99.81 229

PCF-MVS	98.23 3	98.69 198	98.37 223	99.62 156	99.78 159	99.02 203	99.23 412	99.06 397	96.43 289	98.08 344	100.00 1	94.72 259	99.95 172	98.16 291	99.91 138	99.90 172
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
casdiffmvs		98.65 200	98.38 221	99.46 181	99.52 253	98.74 227	100.00 1	99.15 354	96.91 239	99.05 280	100.00 1	92.75 296	99.83 223	99.70 165	98.38 223	99.81 229
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		98.64 201	98.39 219	99.40 196	99.50 263	98.60 236	100.00 1	99.22 318	96.85 244	99.10 273	100.00 1	92.75 296	99.78 239	99.71 161	98.35 225	99.81 229
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		98.64 201	98.58 196	98.81 256	99.42 287	97.12 331	99.69 358	99.37 220	93.63 384	99.94 177	99.67 322	98.96 112	99.47 294	98.62 271	97.95 263	99.83 214

BH-untuned		98.64 201	98.65 187	98.60 266	99.59 222	96.17 348	100.00 1	99.28 279	96.67 270	98.41 324	100.00 1	94.52 263	99.83 223	99.41 216	100.00 1	99.81 229

mamba_0408		98.63 204	98.40 216	99.34 206	99.53 241	98.52 244	99.24 405	99.16 349	96.43 289	98.95 284	99.98 224	94.47 264	99.76 244	99.21 235	98.62 205	99.75 262

test_cas_vis1_n_1920		98.63 204	98.25 232	99.77 129	99.69 174	99.32 169	100.00 1	99.31 259	98.84 61	99.96 144	100.00 1	87.42 378	99.99 102	99.14 237	99.86 150	100.00 1

KinetiMVS		98.61 206	98.26 231	99.65 152	99.46 279	99.24 181	99.96 280	99.44 119	97.54 178	99.99 123	99.99 216	90.83 327	99.95 172	97.18 331	99.92 133	99.75 262

reproduce_monomvs		98.61 206	98.54 200	98.82 253	99.97 92	99.28 174	100.00 1	99.33 247	98.51 90	97.87 358	99.24 374	99.98 3	99.45 300	99.02 246	92.93 355	97.74 348

test_fmvsmconf0.01_n		98.60 208	98.24 235	99.67 147	96.90 427	99.21 185	99.99 238	99.04 402	98.80 70	99.57 236	99.96 253	90.12 339	99.91 194	99.89 116	99.89 141	99.90 172

SSM_04072		98.59 209	98.40 216	99.15 232	99.53 241	98.52 244	99.24 405	99.16 349	96.43 289	98.95 284	99.98 224	94.47 264	99.19 318	99.21 235	98.62 205	99.75 262

tpmvs		98.59 209	98.38 221	99.23 228	99.69 174	97.90 296	99.31 400	99.47 79	94.52 361	99.68 229	99.28 372	97.64 177	99.89 198	97.71 312	98.17 247	99.89 179

Effi-MVS+		98.58 211	98.24 235	99.61 158	99.60 218	99.26 177	97.85 451	99.10 378	96.22 309	99.97 137	99.89 278	93.75 277	99.77 240	99.43 214	98.34 226	99.81 229

MVSTER		98.58 211	98.52 203	98.77 258	99.65 198	99.68 116	100.00 1	99.29 273	95.63 327	98.65 307	99.80 301	99.78 9	98.88 344	98.59 273	95.31 317	97.73 355

viewmacassd2359aftdt		98.57 213	98.31 228	99.33 212	99.49 267	98.31 265	99.89 313	99.21 327	96.87 243	99.10 273	100.00 1	92.48 304	99.88 206	99.50 210	98.28 236	99.81 229

viewmambaseed2359dif		98.57 213	98.34 227	99.28 222	99.46 279	98.23 270	100.00 1	99.16 349	96.26 305	99.11 272	100.00 1	93.12 291	99.79 234	99.61 193	98.33 229	99.80 248

CVMVSNet		98.56 215	98.47 209	98.82 253	99.11 320	97.67 307	99.74 345	99.47 79	97.57 176	99.06 279	100.00 1	95.72 234	98.97 332	98.21 290	97.33 289	99.83 214

kuosan		98.55 216	98.53 202	98.62 264	99.66 196	96.16 349	100.00 1	99.44 119	93.93 377	99.81 213	99.98 224	97.58 178	99.81 229	98.08 293	98.28 236	99.89 179

MonoMVSNet		98.55 216	98.64 189	98.26 292	98.21 386	95.76 356	99.94 295	99.16 349	96.23 306	99.47 244	99.24 374	96.75 214	99.22 316	99.61 193	99.17 188	99.81 229

AllTest		98.55 216	98.40 216	98.99 243	99.93 107	97.35 320	100.00 1	99.40 200	97.08 224	99.09 275	99.98 224	93.37 284	99.95 172	96.94 337	99.84 155	99.68 281

DeepPCF-MVS	98.03 4	98.54 219	99.72 19	94.98 404	99.99 49	84.94 443	100.00 1	99.42 147	99.98 1	100.00 1	100.00 1	98.11 154	100.00 1	100.00 1	100.00 1	100.00 1

EPNet_dtu		98.53 220	98.23 238	99.43 188	99.92 110	99.01 205	99.96 280	99.47 79	98.80 70	99.96 144	99.96 253	98.56 140	99.30 312	87.78 435	99.68 169	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
myMVS_eth3d		98.52 221	98.51 206	98.53 270	99.50 263	97.98 289	100.00 1	99.57 68	96.23 306	98.07 345	100.00 1	99.09 94	97.81 420	96.17 356	97.96 261	99.82 220

Vis-MVSNet		98.52 221	98.25 232	99.34 206	99.68 179	98.55 239	99.68 360	99.41 196	97.34 202	99.94 177	100.00 1	90.38 336	99.70 255	99.03 245	98.84 198	99.76 261
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Effi-MVS+-dtu		98.51 223	98.86 160	97.47 342	99.77 161	94.21 394	100.00 1	98.94 414	97.61 170	99.91 187	98.75 408	95.89 229	99.51 287	99.36 218	99.48 182	98.68 308

SDMVSNet		98.49 224	98.08 247	99.73 136	99.82 130	99.53 137	99.99 238	99.45 105	97.62 166	99.38 255	99.86 283	90.06 342	99.88 206	99.92 111	96.61 303	99.79 254

BH-RMVSNet		98.46 225	98.08 247	99.59 162	99.61 215	99.19 187	100.00 1	99.28 279	97.06 226	98.95 284	100.00 1	88.99 358	99.82 226	98.83 257	100.00 1	99.77 259

testing3		98.44 226	98.37 223	98.65 262	99.51 258	98.32 263	100.00 1	99.62 66	96.43 289	97.93 354	99.99 216	99.11 92	97.81 420	94.88 378	97.80 275	99.82 220

ECVR-MVS		98.43 227	98.14 241	99.32 216	99.89 116	98.21 273	99.46 382	100.00 1	98.38 98	99.47 244	100.00 1	87.91 371	99.80 233	99.35 221	98.78 200	99.94 144

cascas		98.43 227	98.07 249	99.50 174	99.65 198	99.02 203	100.00 1	99.22 318	94.21 370	99.72 225	99.98 224	92.03 309	99.93 189	99.68 173	98.12 252	99.54 290

test1111		98.42 229	98.12 242	99.29 219	99.88 118	98.15 275	99.46 382	100.00 1	98.36 102	99.42 247	100.00 1	87.91 371	99.79 234	99.31 226	98.78 200	99.94 144

ab-mvs		98.42 229	98.02 253	99.61 158	99.71 169	99.00 208	99.10 429	99.64 64	96.70 266	99.04 281	99.81 298	90.64 330	99.98 133	99.64 183	97.93 264	99.84 210

UGNet		98.41 231	98.11 243	99.31 218	99.54 238	98.55 239	99.18 415	100.00 1	98.64 84	99.79 214	99.04 387	87.61 376	100.00 1	99.30 227	99.89 141	99.40 297
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+		98.40 232	98.02 253	99.55 170	99.63 206	99.06 198	100.00 1	99.15 354	95.07 345	99.42 247	99.95 260	93.26 287	99.73 251	97.44 322	98.24 240	99.87 203

Fast-Effi-MVS+-dtu		98.38 233	98.56 198	97.82 332	99.58 227	94.44 391	100.00 1	99.16 349	96.75 253	99.51 239	99.63 334	95.03 250	99.60 260	97.71 312	99.67 171	99.42 296

IMVS_0403		98.37 234	98.39 219	98.29 287	99.38 298	95.36 361	99.97 273	99.18 339	96.72 260	99.68 229	100.00 1	94.61 261	99.77 240	97.84 305	98.15 248	99.74 269

test_fmvs1		98.37 234	98.04 251	99.34 206	99.84 124	98.07 282	100.00 1	99.00 409	98.85 59	100.00 1	100.00 1	85.11 399	99.96 159	99.69 172	99.88 144	100.00 1

IMVS_0407		98.36 236	98.42 213	98.19 298	99.38 298	95.36 361	99.73 350	99.18 339	96.72 260	99.58 234	100.00 1	95.17 246	99.47 294	97.84 305	98.15 248	99.74 269

miper_enhance_ethall		98.33 237	98.27 230	98.51 271	99.66 196	99.04 200	100.00 1	99.22 318	97.53 181	98.51 319	99.38 366	99.49 43	98.75 354	98.02 297	92.61 358	97.76 315

icg_test_0407_2		98.30 238	98.45 210	97.85 331	99.38 298	95.36 361	99.99 238	99.18 339	96.72 260	99.58 234	100.00 1	95.17 246	98.45 382	97.84 305	98.15 248	99.74 269

SCA		98.30 238	97.98 255	99.23 228	99.41 289	98.25 269	99.99 238	99.45 105	96.91 239	99.76 219	99.58 344	89.65 349	99.54 279	98.31 284	98.79 199	99.91 161

XVG-OURS		98.30 238	98.36 225	98.13 306	99.58 227	95.91 352	100.00 1	99.36 226	98.69 79	99.23 263	100.00 1	91.20 317	99.92 192	99.34 223	97.82 273	98.56 311

dongtai		98.29 241	98.25 232	98.42 278	99.58 227	95.86 354	100.00 1	99.44 119	93.46 390	99.69 228	99.97 236	97.53 183	99.51 287	96.28 355	98.27 239	99.89 179

COLMAP_ROB	97.10 7	98.29 241	98.17 240	98.65 262	99.94 105	97.39 317	99.30 401	99.40 200	95.64 326	97.75 364	100.00 1	92.69 300	99.95 172	98.89 252	99.92 133	98.62 310
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ADS-MVSNet2		98.28 243	98.51 206	97.62 338	99.51 258	95.03 370	99.24 405	99.41 196	95.52 333	99.96 144	99.70 314	97.57 180	97.94 417	97.11 333	98.54 210	99.88 192

XVG-OURS-SEG-HR		98.27 244	98.31 228	98.14 303	99.59 222	95.92 351	100.00 1	99.36 226	98.48 91	99.21 264	100.00 1	89.27 354	99.94 185	99.76 146	99.17 188	98.56 311

tpm		98.24 245	98.22 239	98.32 286	99.13 319	95.79 355	99.53 377	99.12 373	95.20 344	99.96 144	99.36 368	97.58 178	99.28 314	97.41 324	96.67 301	99.88 192

VortexMVS		98.23 246	98.11 243	98.59 267	99.56 235	99.37 165	99.95 287	99.03 405	96.47 287	98.69 304	99.55 350	95.91 228	98.66 359	99.01 247	94.80 337	97.73 355

cl22		98.23 246	98.11 243	98.58 269	99.82 130	99.01 205	100.00 1	99.28 279	96.92 238	98.33 331	99.21 377	98.09 156	98.97 332	98.72 262	92.61 358	97.76 315

WBMVS		98.19 248	98.10 246	98.47 273	99.63 206	99.03 201	100.00 1	99.32 250	95.46 338	98.39 326	99.40 365	99.69 17	98.61 364	98.64 267	92.39 363	97.76 315

TR-MVS		98.14 249	97.74 264	99.33 212	99.59 222	98.28 267	99.27 402	99.21 327	96.42 294	99.15 269	99.94 266	88.87 361	99.79 234	98.88 253	98.29 235	99.93 155

Elysia		98.12 250	97.72 267	99.34 206	99.30 308	98.96 213	99.95 287	99.28 279	96.64 273	99.75 220	99.99 216	88.71 363	99.81 229	95.99 358	99.84 155	99.26 298

StellarMVS		98.12 250	97.72 267	99.34 206	99.30 308	98.96 213	99.95 287	99.28 279	96.64 273	99.75 220	99.99 216	88.71 363	99.81 229	95.99 358	99.84 155	99.26 298

test0.0.03 1		98.12 250	98.03 252	98.39 280	99.11 320	98.07 282	100.00 1	99.93 30	96.70 266	96.91 387	99.95 260	99.31 71	98.19 396	91.93 408	98.44 216	98.91 306

GeoE		98.06 253	97.65 271	99.29 219	99.47 275	98.41 250	100.00 1	99.19 332	94.85 350	98.88 291	100.00 1	91.21 316	99.59 262	97.02 335	98.19 245	99.88 192

tpm cat1		98.05 254	97.76 263	98.92 248	99.50 263	97.10 333	99.77 340	99.30 265	90.20 425	99.72 225	98.71 409	97.71 173	99.86 210	96.75 349	98.20 244	99.81 229

PS-MVSNAJss		98.03 255	98.06 250	97.94 325	97.63 408	97.33 323	99.89 313	99.23 313	96.27 304	98.03 348	99.59 342	98.75 131	98.78 349	98.52 275	94.61 341	97.70 371

CR-MVSNet		98.02 256	97.71 269	98.93 247	99.31 305	98.86 217	99.13 426	99.00 409	96.53 281	99.96 144	98.98 394	96.94 207	98.10 406	91.18 413	98.40 219	99.84 210

viewmsd2359difaftdt		97.98 257	97.89 257	98.27 289	99.47 275	94.99 371	99.99 238	99.22 318	96.74 256	99.24 262	100.00 1	90.14 338	99.90 197	99.49 212	96.73 300	99.90 172

EI-MVSNet		97.98 257	97.93 256	98.16 302	99.11 320	97.84 301	99.74 345	99.29 273	94.39 366	98.65 307	100.00 1	97.21 195	98.88 344	97.62 318	95.31 317	97.75 326

FIs		97.95 259	97.73 266	98.62 264	98.53 369	99.24 181	100.00 1	99.43 128	96.74 256	97.87 358	99.82 295	95.27 241	98.89 341	98.78 258	93.07 352	97.74 348

SD_0403		97.92 260	98.43 212	96.39 382	99.68 179	89.74 431	99.92 303	99.34 244	96.75 253	99.39 254	99.93 271	93.54 283	99.51 287	99.11 241	98.21 242	99.92 157

IMVS_0404		97.87 261	97.89 257	97.81 333	99.38 298	95.36 361	99.84 322	99.18 339	96.72 260	98.41 324	100.00 1	91.43 314	98.32 389	97.84 305	98.15 248	99.74 269

Anonymous202405211		97.87 261	97.53 273	98.90 249	99.81 136	96.70 342	99.35 395	99.46 97	92.98 401	98.83 298	99.99 216	90.63 331	100.00 1	99.70 165	97.03 293	100.00 1

FC-MVSNet-test		97.84 263	97.63 272	98.45 276	98.30 379	99.05 199	100.00 1	99.43 128	96.63 277	97.61 370	99.82 295	95.19 245	98.57 372	98.64 267	93.05 353	97.73 355

Patchmatch-test		97.83 264	97.42 276	99.06 236	99.08 324	97.66 308	98.66 443	99.21 327	93.65 383	98.25 339	99.58 344	99.47 48	99.57 267	90.25 423	98.59 208	99.95 139

sd_testset		97.81 265	97.48 274	98.79 257	99.82 130	96.80 339	99.32 397	99.45 105	97.62 166	99.38 255	99.86 283	85.56 397	99.77 240	99.72 157	96.61 303	99.79 254

miper_ehance_all_eth		97.81 265	97.66 270	98.23 294	99.49 267	98.37 256	99.99 238	99.11 375	94.78 351	98.25 339	99.21 377	98.18 152	98.57 372	97.35 328	92.61 358	97.76 315

test_vis1_n_1920		97.77 267	97.24 288	99.34 206	99.79 154	98.04 286	100.00 1	99.25 303	98.88 54	100.00 1	100.00 1	77.52 431	100.00 1	99.88 118	99.85 153	100.00 1

HQP-MVS		97.73 268	97.85 260	97.39 344	99.07 325	94.82 375	100.00 1	99.40 200	99.04 16	99.17 265	99.97 236	88.61 366	99.57 267	99.79 136	95.58 307	97.77 313

GA-MVS		97.72 269	97.27 286	99.06 236	99.24 314	97.93 295	100.00 1	99.24 309	95.80 324	98.99 283	99.64 330	89.77 346	99.36 307	95.12 375	97.62 287	99.89 179

HQP_MVS		97.71 270	97.82 262	97.37 345	99.00 337	94.80 378	100.00 1	99.40 200	99.00 27	99.08 277	99.97 236	88.58 368	99.55 276	99.79 136	95.57 311	97.76 315

nrg030		97.64 271	97.27 286	98.75 259	98.34 374	99.53 137	100.00 1	99.22 318	96.21 310	98.27 337	99.95 260	94.40 266	98.98 330	99.23 232	89.78 397	97.75 326

TAPA-MVS	96.40 10	97.64 271	97.37 280	98.45 276	99.94 105	95.70 357	100.00 1	99.40 200	97.65 161	99.53 237	100.00 1	99.31 71	99.66 257	80.48 450	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CLD-MVS		97.64 271	97.74 264	97.36 346	99.01 333	94.76 383	100.00 1	99.34 244	99.30 4	99.00 282	99.97 236	87.49 377	99.57 267	99.96 100	95.58 307	97.75 326
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
D2MVS		97.63 274	97.83 261	97.05 359	98.83 358	94.60 387	100.00 1	99.82 40	96.89 242	98.28 335	99.03 390	94.05 273	99.47 294	98.58 274	94.97 335	97.09 417

c3_l		97.58 275	97.42 276	98.06 313	99.48 270	98.16 274	99.96 280	99.10 378	94.54 360	98.13 343	99.20 379	97.87 164	98.25 394	97.28 329	91.20 385	97.75 326

IterMVS-LS		97.56 276	97.44 275	97.92 328	99.38 298	97.90 296	99.89 313	99.10 378	94.41 365	98.32 332	99.54 353	97.21 195	98.11 403	97.50 320	91.62 377	97.75 326
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test_djsdf		97.55 277	97.38 279	98.07 309	97.50 416	97.99 288	100.00 1	99.13 367	95.46 338	98.47 322	99.85 288	92.01 310	98.59 369	98.63 269	95.36 315	97.62 394

dmvs_re		97.54 278	97.88 259	96.54 379	99.55 236	90.35 427	99.86 319	99.46 97	97.00 230	99.41 252	100.00 1	90.78 328	99.30 312	99.60 195	95.24 322	99.96 133

cl____		97.54 278	97.32 282	98.18 299	99.47 275	98.14 277	100.00 1	99.10 378	94.16 373	97.60 371	99.63 334	97.52 184	98.65 361	96.47 350	91.97 371	97.76 315

IB-MVS	96.24 12	97.54 278	96.95 293	99.33 212	99.67 188	98.10 280	100.00 1	99.47 79	97.42 196	99.26 261	99.69 317	98.83 126	99.89 198	99.43 214	78.77 447	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		97.52 281	97.35 281	98.05 317	99.46 279	98.11 278	100.00 1	99.10 378	94.21 370	97.62 369	99.63 334	97.65 176	98.29 391	96.47 350	91.98 370	97.76 315

eth_miper_zixun_eth		97.47 282	97.28 284	98.06 313	99.41 289	97.94 294	99.62 367	99.08 384	94.46 364	98.19 342	99.56 349	96.91 209	98.50 377	96.78 346	91.49 380	97.74 348

test_fmvs1_n		97.43 283	96.86 296	99.15 232	99.68 179	97.48 314	99.99 238	98.98 412	98.82 65	100.00 1	100.00 1	74.85 438	99.96 159	99.67 176	99.70 168	100.00 1

LFMVS		97.42 284	96.62 305	99.81 111	99.80 149	99.50 144	99.16 421	99.56 70	94.48 363	100.00 1	100.00 1	79.35 425	100.00 1	99.89 116	97.37 288	99.94 144

miper_lstm_enhance		97.40 285	97.28 284	97.75 335	99.48 270	97.52 312	100.00 1	99.07 389	94.08 374	98.01 351	99.61 340	97.38 192	97.98 415	96.44 353	91.47 382	97.76 315

RPSCF		97.37 286	98.24 235	94.76 407	99.80 149	84.57 444	99.99 238	99.05 399	94.95 348	99.82 209	100.00 1	94.03 274	100.00 1	98.15 292	98.38 223	99.70 279

ACMM	97.17 6	97.37 286	97.40 278	97.29 351	99.01 333	94.64 386	100.00 1	99.25 303	98.07 124	98.44 323	99.98 224	87.38 379	99.55 276	99.25 229	95.19 325	97.69 376
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LPG-MVS_test		97.31 288	97.32 282	97.28 352	98.85 356	94.60 387	100.00 1	99.37 220	97.35 200	98.85 294	99.98 224	86.66 385	99.56 271	99.55 203	95.26 319	97.70 371

FMVSNet3		97.30 289	96.95 293	98.37 282	99.65 198	99.25 179	99.71 354	99.28 279	94.23 368	98.53 316	98.91 401	93.30 286	98.11 403	95.31 371	93.60 346	97.73 355

UniMVSNet (Re)		97.29 290	96.85 297	98.59 267	98.49 370	99.13 193	100.00 1	99.42 147	96.52 284	98.24 341	98.90 402	94.93 251	98.89 341	97.54 319	87.61 416	97.75 326

OPM-MVS		97.21 291	97.18 291	97.32 349	98.08 392	94.66 384	100.00 1	99.28 279	98.65 83	98.92 288	99.98 224	86.03 393	99.56 271	98.28 288	95.41 313	97.72 362
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMP	97.00 8	97.19 292	97.16 292	97.27 354	98.97 342	94.58 390	100.00 1	99.32 250	97.97 132	97.45 375	99.98 224	85.79 395	99.56 271	99.70 165	95.24 322	97.67 382
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
pmmvs4		97.17 293	96.80 298	98.27 289	97.68 407	98.64 234	100.00 1	99.18 339	94.22 369	98.55 314	99.71 311	93.67 278	98.47 380	95.66 365	92.57 361	97.71 370

anonymousdsp		97.16 294	96.88 295	98.00 321	97.08 426	98.06 284	99.81 328	99.15 354	94.58 358	97.84 360	99.62 338	90.49 333	98.60 367	97.98 298	95.32 316	97.33 412

UniMVSNet_NR-MVSNet		97.16 294	96.80 298	98.22 295	98.38 373	98.41 250	100.00 1	99.45 105	96.14 312	97.76 361	99.64 330	95.05 249	98.50 377	97.98 298	86.84 422	97.75 326

XXY-MVS		97.14 296	96.63 304	98.67 261	98.65 363	98.92 215	99.54 376	99.29 273	95.57 330	97.63 367	99.83 291	87.79 375	99.35 309	98.39 280	92.95 354	97.75 326

WR-MVS		97.09 297	96.64 303	98.46 274	98.43 371	99.09 195	99.97 273	99.33 247	95.62 328	97.76 361	99.67 322	91.17 318	98.56 374	98.49 276	89.28 403	97.74 348

JIA-IIPM		97.09 297	96.34 319	99.36 203	98.88 350	98.59 237	99.81 328	99.43 128	84.81 442	99.96 144	90.34 455	98.55 141	99.52 285	97.00 336	98.28 236	99.98 120

jajsoiax		97.07 299	96.79 300	97.89 329	97.28 424	97.12 331	99.95 287	99.19 332	96.55 279	97.31 378	99.69 317	87.35 381	98.91 338	98.70 263	95.12 330	97.66 383

MIMVSNet		97.06 300	96.73 301	98.05 317	99.38 298	96.64 344	98.47 447	99.35 237	93.41 391	99.48 241	98.53 416	89.66 348	97.70 426	94.16 388	98.11 253	99.80 248

X-MVStestdata		97.04 301	96.06 330	99.98 23	100.00 1	99.94 41	100.00 1	99.75 52	98.67 81	100.00 1	66.97 466	99.16 88	100.00 1	100.00 1	100.00 1	100.00 1

h-mvs33		97.03 302	96.53 308	98.51 271	99.79 154	95.90 353	99.45 384	99.45 105	98.21 110	100.00 1	99.78 305	97.49 185	99.99 102	99.72 157	74.92 449	99.65 286

VPA-MVSNet		97.03 302	96.43 314	98.82 253	98.64 364	99.32 169	99.38 392	99.47 79	96.73 259	98.91 290	98.94 399	87.00 383	99.40 305	99.23 232	89.59 398	97.76 315

WB-MVSnew		97.02 304	97.24 288	96.37 384	99.44 285	97.36 319	100.00 1	99.43 128	96.12 313	99.35 257	99.89 278	93.60 281	98.42 384	88.91 434	98.39 221	93.33 449

mvs_tets		97.00 305	96.69 302	97.94 325	97.41 423	97.27 325	99.60 369	99.18 339	96.51 285	97.35 377	99.69 317	86.53 387	98.91 338	98.84 255	95.09 331	97.65 388

gg-mvs-nofinetune		96.95 306	96.10 328	99.50 174	99.41 289	99.36 167	99.07 434	99.52 72	83.69 444	99.96 144	83.60 463	100.00 1	99.20 317	99.68 173	99.99 103	99.96 133

Anonymous20240529		96.93 307	96.22 324	99.05 238	99.79 154	97.30 324	99.16 421	99.47 79	88.51 431	98.69 304	100.00 1	83.50 410	100.00 1	99.83 128	97.02 294	99.83 214

DU-MVS		96.93 307	96.49 311	98.22 295	98.31 377	98.41 250	100.00 1	99.37 220	96.41 295	97.76 361	99.65 326	92.14 307	98.50 377	97.98 298	86.84 422	97.75 326

Patchmtry		96.81 309	96.37 317	98.14 303	99.31 305	98.55 239	98.91 437	99.00 409	90.45 421	97.92 355	98.98 394	96.94 207	98.12 401	94.27 385	91.53 379	97.75 326

hse-mvs2		96.79 310	96.38 316	98.04 319	99.68 179	95.54 360	99.81 328	99.42 147	98.21 110	100.00 1	99.80 301	97.49 185	99.46 299	99.72 157	73.27 452	99.12 303

ACMH	96.25 11	96.77 311	96.62 305	97.21 355	98.96 343	94.43 392	99.64 363	99.33 247	97.43 195	96.55 396	99.97 236	83.52 409	99.54 279	99.07 244	95.13 329	97.66 383
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IterMVS		96.76 312	96.46 313	97.63 336	99.41 289	96.89 336	99.99 238	99.13 367	94.74 354	97.59 372	99.66 324	89.63 351	98.28 392	95.71 363	92.31 365	97.72 362
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CP-MVSNet		96.73 313	96.25 322	98.18 299	98.21 386	98.67 231	99.77 340	99.32 250	95.06 346	97.20 381	99.65 326	90.10 340	98.19 396	98.06 296	88.90 407	97.66 383

WR-MVS_H		96.73 313	96.32 321	97.95 324	98.26 383	97.88 298	99.72 353	99.43 128	95.06 346	96.99 384	98.68 411	93.02 292	98.53 375	97.43 323	88.33 412	97.43 407

IterMVS-SCA-FT		96.72 315	96.42 315	97.62 338	99.40 294	96.83 338	99.99 238	99.14 361	94.65 357	97.55 373	99.72 309	89.65 349	98.31 390	95.62 367	92.05 368	97.73 355

v2v482		96.70 316	96.18 325	98.27 289	98.04 393	98.39 253	100.00 1	99.13 367	94.19 372	98.58 312	99.08 383	90.48 334	98.67 358	95.69 364	90.44 393	97.75 326

test_vis1_n		96.69 317	95.81 341	99.32 216	99.14 318	97.98 289	99.97 273	98.98 412	98.45 93	100.00 1	100.00 1	66.44 452	99.99 102	99.78 142	99.57 181	100.00 1

V42		96.65 318	96.16 327	98.11 308	98.17 390	98.23 270	99.99 238	99.09 383	93.97 375	98.74 303	99.05 386	91.09 319	98.82 347	95.46 369	89.90 395	97.27 413

EU-MVSNet		96.63 319	96.53 308	96.94 366	97.59 412	96.87 337	99.76 342	99.47 79	96.35 300	96.85 389	99.78 305	92.57 302	96.27 440	95.33 370	91.08 386	97.68 378

NR-MVSNet		96.63 319	96.04 331	98.38 281	98.31 377	98.98 210	99.22 414	99.35 237	95.87 318	94.43 422	99.65 326	92.73 298	98.40 385	96.78 346	88.05 413	97.75 326

XVG-ACMP-BASELINE		96.60 321	96.52 310	96.84 372	98.41 372	93.29 404	99.99 238	99.32 250	97.76 152	98.51 319	99.29 371	81.95 416	99.54 279	98.40 279	95.03 332	97.68 378

VDD-MVS		96.58 322	95.99 333	98.34 284	99.52 253	95.33 365	99.18 415	99.38 216	96.64 273	99.77 217	100.00 1	72.51 443	100.00 1	100.00 1	96.94 296	99.70 279

tt0805		96.52 323	96.23 323	97.40 343	99.30 308	93.55 399	99.32 397	99.45 105	96.75 253	97.88 357	99.99 216	79.99 423	99.59 262	97.39 326	95.98 306	99.06 305

LCM-MVSNet-Re		96.52 323	97.21 290	94.44 408	99.27 311	85.80 441	99.85 321	96.61 458	95.98 315	92.75 431	98.48 418	93.97 276	97.55 427	99.58 200	98.43 217	99.98 120

our_test_3		96.51 325	96.35 318	96.98 364	97.61 410	95.05 369	99.98 266	99.01 408	94.68 355	96.77 393	99.06 384	95.87 230	98.14 399	91.81 409	92.37 364	97.75 326

MVP-Stereo		96.51 325	96.48 312	96.60 378	95.65 438	94.25 393	98.84 439	98.16 434	95.85 322	95.23 412	99.04 387	92.54 303	99.13 320	92.98 401	99.98 113	96.43 430
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
v1144		96.51 325	95.97 335	98.13 306	97.98 397	98.04 286	99.99 238	99.08 384	93.51 388	98.62 310	98.98 394	90.98 324	98.62 363	93.79 392	90.79 389	97.74 348

ACMH+	96.20 13	96.49 328	96.33 320	97.00 362	99.06 329	93.80 397	99.81 328	99.31 259	97.32 205	95.89 409	99.97 236	82.62 414	99.54 279	98.34 283	94.63 340	97.65 388

TranMVSNet+NR-MVSNet		96.45 329	96.01 332	97.79 334	98.00 396	97.62 310	100.00 1	99.35 237	95.98 315	97.31 378	99.64 330	90.09 341	98.00 413	96.89 341	86.80 425	97.75 326

ET-MVSNet_ETH3D		96.41 330	95.48 361	99.20 230	99.81 136	99.75 101	100.00 1	99.02 406	97.30 209	78.33 455	100.00 1	97.73 172	97.94 417	99.70 165	87.41 418	99.92 157

VPNet		96.41 330	95.76 346	98.33 285	98.61 365	98.30 266	99.48 381	99.45 105	96.98 232	98.87 293	99.88 280	81.57 417	98.93 336	99.22 234	87.82 415	97.76 315

PVSNet_0	93.57 19	96.41 330	95.74 347	98.41 279	99.84 124	95.22 367	100.00 1	100.00 1	98.08 123	97.55 373	99.78 305	84.40 402	100.00 1	100.00 1	81.99 439	100.00 1

v144192		96.40 333	95.81 341	98.17 301	97.89 400	98.11 278	99.99 238	99.06 397	93.39 392	98.75 302	99.09 382	90.43 335	98.66 359	93.10 400	90.55 392	97.75 326

VDDNet		96.39 334	95.55 356	98.90 249	99.27 311	97.45 315	99.15 423	99.92 34	91.28 414	99.98 131	100.00 1	73.55 439	100.00 1	99.85 124	96.98 295	99.24 300

tfpnnormal		96.36 335	95.69 352	98.37 282	98.55 367	98.71 228	99.69 358	99.45 105	93.16 399	96.69 395	99.71 311	88.44 370	98.99 329	94.17 386	91.38 383	97.41 408

v8		96.35 336	95.73 348	98.21 297	98.11 391	98.23 270	99.94 295	99.07 389	92.66 407	98.29 334	99.00 393	91.46 312	98.77 352	94.17 386	88.83 409	97.62 394

PS-CasMVS		96.34 337	95.78 345	98.03 320	98.18 389	98.27 268	99.71 354	99.32 250	94.75 352	96.82 390	99.65 326	86.98 384	98.15 398	97.74 311	88.85 408	97.66 383

LTVRE_ROB	95.29 16	96.32 338	96.10 328	96.99 363	98.55 367	93.88 396	99.45 384	99.28 279	94.50 362	96.46 397	99.52 354	84.86 400	99.48 292	97.26 330	95.03 332	97.59 398
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		96.29 339	95.70 349	98.07 309	99.80 149	97.49 313	99.15 423	99.40 200	89.11 428	97.75 364	99.45 361	88.93 360	98.98 330	98.26 289	89.47 400	97.73 355

v148		96.29 339	95.84 340	97.63 336	97.74 405	96.53 346	100.00 1	99.07 389	93.52 387	98.01 351	99.42 363	91.22 315	98.60 367	96.37 354	87.22 421	97.75 326

AUN-MVS		96.26 341	95.67 353	98.06 313	99.68 179	95.60 359	99.82 327	99.42 147	96.78 250	99.88 194	99.80 301	94.84 254	99.47 294	97.48 321	73.29 451	99.12 303

ttmdpeth		96.24 342	95.88 338	97.32 349	97.80 402	96.61 345	99.95 287	98.77 425	97.80 147	93.42 427	99.28 372	86.42 388	99.01 326	97.63 315	91.84 373	96.33 432

FMVSNet2		96.22 343	95.60 355	98.06 313	99.53 241	98.33 261	99.45 384	99.27 292	93.71 379	98.03 348	98.84 404	84.23 404	98.10 406	93.97 390	93.40 349	97.73 355

LF4IMVS		96.19 344	96.18 325	96.23 388	98.26 383	92.09 415	100.00 1	97.89 445	97.82 145	97.94 353	99.87 281	82.71 413	99.38 306	97.41 324	93.71 345	97.20 414

v1192		96.18 345	95.49 359	98.26 292	98.01 395	98.15 275	99.99 238	99.08 384	93.36 393	98.54 315	98.97 397	89.47 352	98.89 341	91.15 414	90.82 388	97.75 326

testgi		96.18 345	95.93 336	96.93 367	98.98 341	94.20 395	100.00 1	99.07 389	97.16 216	96.06 406	99.86 283	84.08 407	97.79 423	90.38 422	97.80 275	98.81 307

Syy-MVS		96.17 347	96.57 307	95.00 402	99.50 263	87.37 439	100.00 1	99.57 68	96.23 306	98.07 345	100.00 1	92.41 305	97.81 420	85.34 440	97.96 261	99.82 220

ppachtmachnet_test		96.17 347	95.89 337	97.02 361	97.61 410	95.24 366	99.99 238	99.24 309	93.31 395	96.71 394	99.62 338	94.34 269	98.07 408	89.87 424	92.30 366	97.75 326

v1921920		96.16 349	95.50 357	98.14 303	97.88 401	97.96 292	99.99 238	99.07 389	93.33 394	98.60 311	99.24 374	89.37 353	98.71 356	91.28 412	90.74 390	97.75 326

Baseline_NR-MVSNet		96.16 349	95.70 349	97.56 341	98.28 382	96.79 340	100.00 1	97.86 446	91.93 411	97.63 367	99.47 360	92.14 307	98.35 388	97.13 332	86.83 424	97.54 401

v10		96.14 351	95.50 357	98.07 309	98.19 388	97.96 292	99.83 324	99.07 389	92.10 410	98.07 345	98.94 399	91.07 320	98.61 364	92.41 407	89.82 396	97.63 392

OurMVSNet-221017-0		96.14 351	95.98 334	96.62 377	97.49 418	93.44 401	99.92 303	98.16 434	95.86 320	97.65 366	99.95 260	85.71 396	98.78 349	94.93 377	94.18 344	97.64 391

GBi-Net		96.07 353	95.80 343	96.89 369	99.53 241	94.87 372	99.18 415	99.27 292	93.71 379	98.53 316	98.81 405	84.23 404	98.07 408	95.31 371	93.60 346	97.72 362

test1		96.07 353	95.80 343	96.89 369	99.53 241	94.87 372	99.18 415	99.27 292	93.71 379	98.53 316	98.81 405	84.23 404	98.07 408	95.31 371	93.60 346	97.72 362

v7n		96.06 355	95.42 365	97.99 323	97.58 413	97.35 320	99.86 319	99.11 375	92.81 406	97.91 356	99.49 358	90.99 323	98.92 337	92.51 404	88.49 411	97.70 371

PEN-MVS		96.01 356	95.48 361	97.58 340	97.74 405	97.26 326	99.90 309	99.29 273	94.55 359	96.79 391	99.55 350	87.38 379	97.84 419	96.92 340	87.24 420	97.65 388

v1240		95.96 357	95.25 366	98.07 309	97.91 399	97.87 300	99.96 280	99.07 389	93.24 397	98.64 309	98.96 398	88.98 359	98.61 364	89.58 428	90.92 387	97.75 326

pmmvs5		95.94 358	95.61 354	96.95 365	97.42 421	94.66 384	100.00 1	98.08 438	93.60 385	97.05 383	99.43 362	87.02 382	98.46 381	95.76 361	92.12 367	97.72 362

PatchT		95.90 359	94.95 374	98.75 259	99.03 331	98.39 253	99.08 432	99.32 250	85.52 440	99.96 144	94.99 447	97.94 158	98.05 412	80.20 451	98.47 215	99.81 229

USDC		95.90 359	95.70 349	96.50 380	98.60 366	92.56 413	100.00 1	98.30 432	97.77 150	96.92 385	99.94 266	81.25 420	99.45 300	93.54 395	94.96 336	97.49 404

pm-mvs1		95.76 361	95.01 371	98.00 321	98.23 385	97.45 315	99.24 405	99.04 402	93.13 400	95.93 408	99.72 309	86.28 389	98.84 346	95.62 367	87.92 414	97.72 362

SixPastTwentyTwo		95.71 362	95.49 359	96.38 383	97.42 421	93.01 405	99.84 322	98.23 433	94.75 352	95.98 407	99.97 236	85.35 398	98.43 383	94.71 379	93.17 351	97.69 376

MS-PatchMatch		95.66 363	95.87 339	95.05 400	97.80 402	89.25 433	98.88 438	99.30 265	96.35 300	96.86 388	99.01 392	81.35 419	99.43 302	93.30 397	99.98 113	96.46 429

DTE-MVSNet		95.52 364	94.99 372	97.08 358	97.49 418	96.45 347	100.00 1	99.25 303	93.82 378	96.17 402	99.57 348	87.81 374	97.18 428	94.57 381	86.26 428	97.62 394

TinyColmap		95.50 365	95.12 370	96.64 376	98.69 362	93.00 406	99.40 390	97.75 448	96.40 296	96.14 403	99.87 281	79.47 424	99.50 290	93.62 394	94.72 339	97.40 409

K. test v3		95.46 366	95.14 369	96.40 381	97.53 415	93.40 402	99.99 238	99.23 313	95.49 336	92.70 432	99.73 308	84.26 403	98.12 401	93.94 391	93.38 350	97.68 378

SSC-MVS3.2		95.32 367	94.97 373	96.37 384	98.29 381	92.75 409	100.00 1	99.30 265	95.46 338	98.36 327	99.42 363	78.92 427	98.63 362	93.28 399	91.72 376	97.72 362

FMVSNet5		95.32 367	95.43 364	94.99 403	99.39 297	92.99 407	99.25 404	99.24 309	90.45 421	97.44 376	98.45 419	95.78 233	94.39 449	87.02 436	91.88 372	97.59 398

UniMVSNet_ETH3D		95.28 369	94.41 375	97.89 329	98.91 347	95.14 368	99.13 426	99.35 237	92.11 409	97.17 382	99.66 324	70.28 447	99.36 307	97.88 303	95.18 326	99.16 301

RPMNet		95.26 370	93.82 379	99.56 169	99.31 305	98.86 217	99.13 426	99.42 147	79.82 449	99.96 144	95.13 445	95.69 235	99.98 133	77.54 455	98.40 219	99.84 210

DSMNet-mixed		95.18 371	95.21 368	95.08 399	96.03 433	90.21 428	99.65 362	93.64 464	92.91 402	98.34 330	97.40 435	90.05 343	95.51 446	91.02 415	97.86 268	99.51 293

test_fmvs2		95.17 372	95.23 367	95.01 401	98.95 345	88.99 435	99.99 238	97.77 447	97.79 148	98.58 312	99.70 314	73.36 440	99.34 310	95.88 360	95.03 332	96.70 425

TransMVSNet (Re)		94.78 373	93.72 380	97.93 327	98.34 374	97.88 298	99.23 412	97.98 443	91.60 412	94.55 419	99.71 311	87.89 373	98.36 387	89.30 430	84.92 430	97.56 400

mmtdpeth		94.58 374	94.18 376	95.81 394	98.82 360	91.09 423	99.99 238	98.61 429	96.38 297	100.00 1	97.23 436	76.52 434	99.85 217	99.82 133	80.22 443	96.48 428

FMVSNet1		94.45 375	93.63 382	96.89 369	98.87 353	94.87 372	99.18 415	99.27 292	90.95 418	97.31 378	98.81 405	72.89 442	98.07 408	92.61 402	92.81 356	97.72 362

test_0402		94.35 376	93.70 381	96.32 386	97.92 398	93.60 398	99.61 368	98.85 421	88.19 434	94.68 417	99.48 359	80.01 422	98.58 371	89.39 429	95.15 328	96.77 423

MVStest1		94.27 377	93.30 386	97.19 356	98.83 358	97.18 329	99.93 301	98.79 424	86.80 437	84.88 452	99.04 387	94.32 270	98.25 394	90.55 419	86.57 426	96.12 435

UnsupCasMVSNet_eth		94.25 378	93.89 378	95.34 397	97.63 408	92.13 414	99.73 350	99.36 226	94.88 349	92.78 429	98.63 413	82.72 412	96.53 436	94.57 381	84.73 431	97.36 410

KD-MVS_2432*1600		94.15 379	93.08 388	97.35 347	99.53 241	97.83 302	99.63 365	99.19 332	92.88 403	96.29 399	97.68 432	98.84 124	96.70 432	89.73 425	63.92 456	97.53 402

miper_refine_blended		94.15 379	93.08 388	97.35 347	99.53 241	97.83 302	99.63 365	99.19 332	92.88 403	96.29 399	97.68 432	98.84 124	96.70 432	89.73 425	63.92 456	97.53 402

MVS-HIRNet		94.12 381	92.73 395	98.29 287	99.33 304	95.95 350	99.38 392	99.19 332	74.54 455	98.26 338	86.34 459	86.07 391	99.06 323	91.60 411	99.87 149	99.85 208

new_pmnet		94.11 382	93.47 384	96.04 392	96.60 430	92.82 408	99.97 273	98.91 417	90.21 424	95.26 411	98.05 430	85.89 394	98.14 399	84.28 442	92.01 369	97.16 415

mvs5depth		93.81 383	93.00 390	96.23 388	94.25 446	93.33 403	97.43 453	98.07 439	93.47 389	94.15 424	99.58 344	77.52 431	98.97 332	93.64 393	88.92 406	96.39 431

pmmvs6		93.64 384	92.87 392	95.94 393	97.47 420	91.41 420	98.92 436	99.02 406	87.84 435	95.01 414	99.61 340	77.24 433	98.77 352	94.33 384	86.41 427	97.63 392

Patchmatch-RL test		93.49 385	93.63 382	93.05 419	91.78 450	83.41 445	98.21 449	96.95 455	91.58 413	91.05 434	97.64 434	99.40 63	95.83 444	94.11 389	81.95 440	99.91 161

Anonymous20231206		93.45 386	93.17 387	94.30 411	95.00 443	89.69 432	99.98 266	98.43 431	93.30 396	94.50 421	98.59 414	90.52 332	95.73 445	77.46 456	90.73 391	97.48 406

Anonymous20240521		93.29 387	92.76 394	94.90 406	95.64 439	91.27 421	99.97 273	98.82 422	87.04 436	94.71 416	98.19 425	83.86 408	96.80 431	84.04 443	92.56 362	96.64 426

dmvs_testset		93.27 388	95.48 361	86.65 431	98.74 361	68.42 460	99.92 303	98.91 417	96.19 311	93.28 428	100.00 1	91.06 321	91.67 456	89.64 427	91.54 378	99.86 207

test20.03		93.11 389	92.85 393	93.88 416	95.19 442	91.83 416	100.00 1	98.87 420	93.68 382	92.76 430	98.88 403	89.20 356	92.71 454	77.88 454	89.19 404	97.09 417

test_vis1_rt		93.10 390	92.93 391	93.58 417	99.63 206	85.07 442	99.99 238	93.71 463	97.49 187	90.96 435	97.10 437	60.40 454	99.95 172	99.24 231	97.90 266	95.72 439

APD_test1		93.07 391	94.14 377	89.85 425	99.18 316	72.49 453	99.76 342	98.90 419	92.86 405	96.35 398	99.94 266	75.56 436	99.91 194	86.73 437	97.98 259	97.15 416

EG-PatchMatch MVS		92.94 392	92.49 396	94.29 412	95.87 435	87.07 440	99.07 434	98.11 437	93.19 398	88.98 441	98.66 412	70.89 445	99.08 322	92.43 406	95.21 324	96.72 424

MDA-MVSNet_test_wron		92.61 393	91.09 403	97.19 356	96.71 429	97.26 326	100.00 1	99.14 361	88.61 430	67.90 461	98.32 424	89.03 357	96.57 435	90.47 421	89.59 398	97.74 348

sc_t1		92.52 394	91.34 398	96.09 390	97.80 402	89.86 430	98.61 444	99.12 373	77.73 450	96.09 404	99.79 304	68.64 449	98.94 335	96.94 337	87.31 419	99.46 295

YYNet1		92.44 395	90.92 404	97.03 360	96.20 431	97.06 334	99.99 238	99.14 361	88.21 433	67.93 460	98.43 421	88.63 365	96.28 439	90.64 416	89.08 405	97.74 348

tt0320		92.36 396	91.28 399	95.58 396	98.30 379	90.65 425	98.69 442	99.14 361	76.73 451	96.07 405	99.50 357	72.28 444	98.39 386	93.29 398	87.56 417	97.70 371

MIMVSNet1		91.96 397	91.20 400	94.23 413	94.94 444	91.69 418	99.34 396	99.22 318	88.23 432	94.18 423	98.45 419	75.52 437	93.41 453	79.37 452	91.49 380	97.60 397

TDRefinement		91.93 398	90.48 407	96.27 387	81.60 463	92.65 412	99.10 429	97.61 451	93.96 376	93.77 425	99.85 288	80.03 421	99.53 284	97.82 309	70.59 453	96.63 427

OpenMVS_ROB	88.34 20	91.89 399	91.12 401	94.19 414	95.55 440	87.63 438	99.26 403	98.03 440	86.61 439	90.65 439	96.82 439	70.14 448	98.78 349	86.54 438	96.50 305	96.15 433

N_pmnet		91.88 400	93.37 385	87.40 430	97.24 425	66.33 463	99.90 309	91.05 466	89.77 427	95.65 410	98.58 415	90.05 343	98.11 403	85.39 439	92.72 357	97.75 326

pmmvs-eth3d		91.73 401	90.67 405	94.92 405	91.63 452	92.71 411	99.90 309	98.54 430	91.19 415	88.08 443	95.50 443	79.31 426	96.13 441	90.55 419	81.32 442	95.91 438

tt0320-xc		91.69 402	90.50 406	95.26 398	98.04 393	90.12 429	98.60 445	98.70 427	76.63 453	94.66 418	99.52 354	68.57 450	97.99 414	94.61 380	85.18 429	97.66 383

MDA-MVSNet-bldmvs		91.65 403	89.94 411	96.79 375	96.72 428	96.70 342	99.42 389	98.94 414	88.89 429	66.97 463	98.37 422	81.43 418	95.91 443	89.24 431	89.46 401	97.75 326

KD-MVS_self_test		91.16 404	90.09 409	94.35 410	94.44 445	91.27 421	99.74 345	99.08 384	90.82 419	94.53 420	94.91 448	86.11 390	94.78 448	82.67 445	68.52 454	96.99 419

CL-MVSNet_self_test		91.07 405	90.35 408	93.24 418	93.27 447	89.16 434	99.55 374	99.25 303	92.34 408	95.23 412	97.05 438	88.86 362	93.59 452	80.67 449	66.95 455	96.96 420

test_method		91.04 406	91.10 402	90.85 422	98.34 374	77.63 449	100.00 1	98.93 416	76.69 452	96.25 401	98.52 417	70.44 446	97.98 415	89.02 433	91.74 374	96.92 421

CMPMVS	66.12 22	90.65 407	92.04 397	86.46 432	96.18 432	66.87 462	98.03 450	99.38 216	83.38 445	85.49 449	99.55 350	77.59 430	98.80 348	94.44 383	94.31 343	93.72 447
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs3		90.62 408	89.36 414	94.40 409	90.53 457	91.49 419	100.00 1	96.73 456	84.21 443	93.65 426	96.65 440	82.56 415	94.83 447	82.28 446	77.62 448	96.89 422

new-patchmatchnet		90.30 409	89.46 413	92.84 420	90.77 455	88.55 437	99.83 324	98.80 423	90.07 426	87.86 444	95.00 446	78.77 428	94.30 450	84.86 441	79.15 445	95.68 441

UnsupCasMVSNet_bld		89.50 410	88.00 416	93.99 415	95.30 441	88.86 436	98.52 446	99.28 279	85.50 441	87.80 445	94.11 449	61.63 453	96.96 430	90.63 417	79.26 444	96.15 433

mvsany_test3		89.36 411	88.96 415	90.56 423	91.95 449	78.97 448	99.74 345	96.59 459	96.84 245	89.25 440	96.07 441	52.59 456	97.11 429	95.17 374	82.44 438	95.58 442

PM-MVS		88.39 412	87.41 417	91.31 421	91.73 451	82.02 447	99.79 334	96.62 457	91.06 417	90.71 438	95.73 442	48.60 458	95.96 442	90.56 418	81.91 441	95.97 437

WB-MVS		88.24 413	90.09 409	82.68 438	91.56 453	69.51 458	100.00 1	98.73 426	90.72 420	87.29 446	98.12 426	92.87 294	85.01 460	62.19 461	89.34 402	93.54 448

SSC-MVS		87.61 414	89.47 412	82.04 439	90.63 456	68.77 459	99.99 238	98.66 428	90.34 423	86.70 447	98.08 427	92.72 299	84.12 461	59.41 464	88.71 410	93.22 452

test_fmvs3		87.19 415	87.02 418	87.71 429	92.69 448	76.64 450	99.96 280	97.27 452	93.55 386	90.82 437	94.03 450	38.00 464	92.19 455	93.49 396	83.35 437	94.32 444

test_f		86.87 416	86.06 419	89.28 426	91.45 454	76.37 451	99.87 318	97.11 453	91.10 416	88.46 442	93.05 452	38.31 463	96.66 434	91.77 410	83.46 436	94.82 443

Gipuma		84.73 417	83.50 422	88.40 428	97.50 416	82.21 446	88.87 457	99.05 399	65.81 457	85.71 448	90.49 454	53.70 455	96.31 438	78.64 453	91.74 374	86.67 456
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
testf1		84.40 418	84.79 420	83.23 436	95.71 436	58.71 469	98.79 440	97.75 448	81.58 446	84.94 450	98.07 428	45.33 460	97.73 424	77.09 457	83.85 433	93.24 450

APD_test2		84.40 418	84.79 420	83.23 436	95.71 436	58.71 469	98.79 440	97.75 448	81.58 446	84.94 450	98.07 428	45.33 460	97.73 424	77.09 457	83.85 433	93.24 450

testmvs		80.17 420	81.95 423	74.80 443	58.54 470	59.58 468	100.00 1	87.14 469	76.09 454	99.61 233	100.00 1	67.06 451	74.19 466	98.84 255	50.30 460	90.64 455

test_vis3_rt		79.61 421	78.19 426	83.86 435	88.68 458	69.56 457	99.81 328	82.19 471	86.78 438	68.57 459	84.51 462	25.06 468	98.26 393	89.18 432	78.94 446	83.75 459

EGC-MVSNET		79.46 422	74.04 430	95.72 395	96.00 434	92.73 410	99.09 431	99.04 402	5.08 467	16.72 467	98.71 409	73.03 441	98.74 355	82.05 447	96.64 302	95.69 440

test123		79.44 423	79.23 425	80.05 441	80.03 464	71.72 454	100.00 1	77.93 472	62.52 458	94.81 415	99.69 317	78.21 429	74.53 465	92.57 403	27.33 465	93.90 445

PMMVS2		79.15 424	77.28 427	84.76 434	82.34 462	72.66 452	99.70 356	95.11 462	71.68 456	84.78 453	90.87 453	32.05 466	89.99 457	75.53 459	63.45 458	91.64 453

LCM-MVSNet		79.01 425	76.93 428	85.27 433	78.28 465	68.01 461	96.57 454	98.03 440	55.10 461	82.03 454	93.27 451	31.99 467	93.95 451	82.72 444	74.37 450	93.84 446

FPMVS		77.92 426	79.45 424	73.34 445	76.87 466	46.81 472	98.24 448	99.05 399	59.89 460	73.55 456	98.34 423	36.81 465	86.55 458	80.96 448	91.35 384	86.65 457

tmp_tt		75.80 427	74.26 429	80.43 440	52.91 472	53.67 471	87.42 459	97.98 443	61.80 459	67.04 462	100.00 1	76.43 435	96.40 437	96.47 350	28.26 464	91.23 454

E-PMN		70.72 428	70.06 431	72.69 446	83.92 461	65.48 465	99.95 287	92.72 465	49.88 463	72.30 457	86.26 460	47.17 459	77.43 463	53.83 465	44.49 461	75.17 463

EMVS		69.88 429	69.09 432	72.24 447	84.70 460	65.82 464	99.96 280	87.08 470	49.82 464	71.51 458	84.74 461	49.30 457	75.32 464	50.97 466	43.71 462	75.59 462

MVE	68.59 21	67.22 430	64.68 434	74.84 442	74.67 468	62.32 467	95.84 455	90.87 467	50.98 462	58.72 464	81.05 464	12.20 472	78.95 462	61.06 463	56.75 459	83.24 460
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ANet_high		66.05 431	63.44 435	73.88 444	61.14 469	63.45 466	95.68 456	87.18 468	79.93 448	47.35 465	80.68 465	22.35 469	72.33 467	61.24 462	35.42 463	85.88 458

PMVS	60.66 23	65.98 432	65.05 433	68.75 448	55.06 471	38.40 473	88.19 458	96.98 454	48.30 465	44.82 466	88.52 457	12.22 471	86.49 459	67.58 460	83.79 435	81.35 461
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
wuyk23d		28.28 433	29.73 437	23.92 449	75.89 467	32.61 474	66.50 460	12.88 473	16.09 466	14.59 468	16.59 467	12.35 470	32.36 468	39.36 467	13.36 466	6.79 464

cdsmvs_eth3d_5k		24.41 434	32.55 436	0.00 450	0.00 473	0.00 475	0.00 461	99.39 213	0.00 468	0.00 469	100.00 1	93.55 282	0.00 469	0.00 468	0.00 467	0.00 465

ab-mvs-re		8.33 435	11.11 438	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	100.00 1	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

pcd_1.5k_mvsjas		8.24 436	10.99 439	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.14 469	98.75 131	0.00 469	0.00 468	0.00 467	0.00 465

test_blank		0.07 437	0.09 440	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.79 468	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

mmdepth		0.01 438	0.02 441	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.14 469	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

monomultidepth		0.01 438	0.02 441	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.14 469	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

uanet_test		0.01 438	0.02 441	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.14 469	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

DCPMVS		0.01 438	0.02 441	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.14 469	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

sosnet-low-res		0.01 438	0.02 441	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.14 469	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

sosnet		0.01 438	0.02 441	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.14 469	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

uncertanet		0.01 438	0.02 441	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.14 469	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

Regformer		0.01 438	0.02 441	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.14 469	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

uanet		0.01 438	0.02 441	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.14 469	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

WAC-MVS						97.98 289								95.74 362

FOURS1					100.00 1	99.97 21	100.00 1	99.42 147	98.52 89	100.00 1

MSC_two_6792asdad				100.00 1	100.00 1	100.00 1		99.42 147					100.00 1	100.00 1	100.00 1	100.00 1

PC_three_1452									98.80 70	100.00 1	100.00 1	99.54 30	100.00 1	100.00 1	100.00 1	100.00 1

No_MVS				100.00 1	100.00 1	100.00 1		99.42 147					100.00 1	100.00 1	100.00 1	100.00 1

test_one_0601					100.00 1	99.99 5		99.42 147	98.72 78	100.00 1	100.00 1	99.60 21

eth-test2					0.00 473

eth-test					0.00 473

ZD-MVS					100.00 1	99.98 17		99.80 43	97.31 207	100.00 1	100.00 1	99.32 69	99.99 102	100.00 1	100.00 1

RE-MVS-def			99.55 59		99.99 49	99.91 57	100.00 1	99.42 147	97.62 166	100.00 1	100.00 1	98.94 115		99.99 71	100.00 1	100.00 1

IU-MVS					100.00 1	99.99 5		99.42 147	99.12 7	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 30	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_TWO								99.42 147	99.03 21	100.00 1	100.00 1	99.56 27	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_ONE					100.00 1	99.99 5		99.42 147	99.03 21	100.00 1	100.00 1	99.50 41	100.00 1

9.14			99.57 52		99.99 49		100.00 1	99.42 147	97.54 178	100.00 1	100.00 1	99.15 90	99.99 102	100.00 1	100.00 1

save fliter					99.99 49	99.93 47	100.00 1	99.42 147	98.93 44

test_0728_THIRD									98.79 73	100.00 1	100.00 1	99.61 20	100.00 1	100.00 1	100.00 1	100.00 1

test_0728_SECOND				100.00 1	99.99 49	99.99 5	100.00 1	99.42 147					100.00 1	100.00 1	100.00 1	100.00 1

test0726					100.00 1	99.99 5	100.00 1	99.42 147	99.04 16	100.00 1	100.00 1	99.53 33

GSMVS																99.91 161

test_part2					100.00 1	99.99 5				100.00 1

sam_mvs1												99.29 77				99.91 161

sam_mvs												99.33 66

ambc				88.45 427	86.84 459	70.76 456	97.79 452	98.02 442		90.91 436	95.14 444	38.69 462	98.51 376	94.97 376	84.23 432	96.09 436

MTGPA								99.42 147

test_post1							99.32 397				88.24 458	99.33 66	99.59 262	98.31 284

test_post											89.05 456	99.49 43	99.59 262

patchmatchnet-post											97.79 431	99.41 61	99.54 279

GG-mvs-BLEND				99.59 162	99.54 238	99.49 148	99.17 420	99.52 72		99.96 144	99.68 321	100.00 1	99.33 311	99.71 161	99.99 103	99.96 133

MTMP							100.00 1	99.18 339

gm-plane-assit					99.52 253	97.26 326			95.86 320		100.00 1		99.43 302	98.76 260

test9_res														100.00 1	100.00 1	100.00 1

TEST9					100.00 1	99.95 32	100.00 1	99.42 147	97.65 161	100.00 1	100.00 1	99.53 33	99.97 142

test_8					100.00 1	99.91 57	100.00 1	99.42 147	97.70 155	100.00 1	100.00 1	99.51 37	99.98 133

agg_prior2														100.00 1	100.00 1	100.00 1

agg_prior					100.00 1	99.88 78		99.42 147		100.00 1			99.97 142

TestCases				98.99 243	99.93 107	97.35 320		99.40 200	97.08 224	99.09 275	99.98 224	93.37 284	99.95 172	96.94 337	99.84 155	99.68 281

test_prior4						99.93 47	100.00 1

test_prior2							100.00 1		98.82 65	100.00 1	100.00 1	99.47 48		100.00 1	100.00 1

test_prior				99.90 81	100.00 1	99.75 101		99.73 56					99.97 142			100.00 1

旧先验2							100.00 1		98.11 122	100.00 1			100.00 1	99.67 176

新几何2							100.00 1

新几何1				99.99 12	100.00 1	99.96 24		99.81 42	97.89 139	100.00 1	100.00 1	99.20 85	100.00 1	97.91 302	100.00 1	100.00 1

旧先验1					99.99 49	99.88 78		99.82 40			100.00 1	99.27 80			100.00 1	100.00 1

无先验							100.00 1	99.80 43	97.98 130				100.00 1	99.33 224		100.00 1

原ACMM2							100.00 1

原ACMM1				99.93 72	100.00 1	99.80 94		99.66 63	98.18 113	100.00 1	100.00 1	99.43 55	100.00 1	99.50 210	100.00 1	100.00 1

test222					99.99 49	99.90 64	100.00 1	99.69 62	97.66 159	100.00 1	100.00 1	99.30 76			100.00 1	100.00 1

testdata2													100.00 1	97.36 327

segment_acmp												99.55 29

testdata				99.66 150	99.99 49	98.97 212		99.73 56	97.96 135	100.00 1	100.00 1	99.42 59	100.00 1	99.28 228	100.00 1	100.00 1

testdata1							100.00 1		98.77 77

test12				99.95 55	99.99 49	99.89 71		99.42 147		100.00 1		99.24 82	99.97 142		100.00 1	100.00 1

plane_prior7					99.00 337	94.78 382

plane_prior6					99.06 329	94.80 378						88.58 368

plane_prior5								99.40 200					99.55 276	99.79 136	95.57 311	97.76 315

plane_prior4											99.97 236

plane_prior3						94.79 381			99.03 21	99.08 277

plane_prior2							100.00 1		99.00 27

plane_prior1					99.02 332

plane_prior						94.80 378	100.00 1		99.03 21						95.58 307

n2								0.00 474

nn								0.00 474

door-mid								96.32 460

lessismore_v0				96.05 391	97.55 414	91.80 417		99.22 318		91.87 433	99.91 275	83.50 410	98.68 357	92.48 405	90.42 394	97.68 378

LGP-MVS_train				97.28 352	98.85 356	94.60 387		99.37 220	97.35 200	98.85 294	99.98 224	86.66 385	99.56 271	99.55 203	95.26 319	97.70 371

test11								99.42 147

door								96.13 461

HQP5-MVS						94.82 375

HQP-NCC					99.07 325		100.00 1		99.04 16	99.17 265

ACMP_Plane					99.07 325		100.00 1		99.04 16	99.17 265

BP-MVS														99.79 136

HQP4-MVS										99.17 265			99.57 267			97.77 313

HQP3-MVS								99.40 200							95.58 307

HQP2-MVS												88.61 366

NP-MVS					99.07 325	94.81 377					99.97 236

MDTV_nov1_ep13_2view						99.24 181	99.56 373		96.31 303	99.96 144		98.86 122		98.92 251		99.89 179

MDTV_nov1_ep13			98.94 150		99.53 241	98.36 258	99.39 391	99.46 97	96.54 280	99.99 123	99.63 334	98.92 118	99.86 210	98.30 287	98.71 204

ACMMP++_ref															94.58 342

ACMMP++															95.17 327

Test By Simon												99.10 93

ITE_SJBPF				96.84 372	98.96 343	93.49 400		98.12 436	98.12 121	98.35 329	99.97 236	84.45 401	99.56 271	95.63 366	95.25 321	97.49 404

DeepMVS_CX				89.98 424	98.90 348	71.46 455		99.18 339	97.61 170	96.92 385	99.83 291	86.07 391	99.83 223	96.02 357	97.65 285	98.65 309

High-resolution multi-view benchmark