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 92	99.99 49	99.97 21	99.97 212	99.98 16	98.96 28	100.00 1	100.00 1	99.96 5	99.42 230	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	99.44 108	99.06 11	100.00 1	100.00 1	99.56 23	99.99 90	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	99.42 124	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	99.42 124	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	99.43 114	99.05 13	100.00 1	100.00 1	99.45 45	99.99 90	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 38	99.96 107	100.00 1	99.21 76	100.00 1	100.00 1	100.00 1	99.99 98

DVP-MVS++		99.81 11	99.75 14	100.00 1	100.00 1	99.99 5	100.00 1	99.42 124	98.79 49	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	99.42 124	98.87 40	100.00 1	100.00 1	99.65 15	99.96 124	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	99.42 124	99.01 24	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	99.42 124	98.91 36	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 56	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	99.76 138	99.95 32	100.00 1	99.42 124	98.69 54	100.00 1	100.00 1	99.52 32	99.99 90	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 80	99.01 257	99.95 32	100.00 1	99.75 51	99.37 3	99.99 94	100.00 1	99.76 11	99.60 190	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 97	99.99 94	100.00 1	99.72 12	100.00 1	99.96 77	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 83	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	99.73 269	99.52 68	99.06 11	100.00 1	100.00 1	98.80 114	100.00 1	99.95 82	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	99.98 206	99.47 75	99.09 8	100.00 1	100.00 1	98.59 123	100.00 1	99.95 82	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	97.95 105	100.00 1	100.00 1	99.31 63	100.00 1	99.99 57	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	97.95 105	100.00 1	100.00 1	99.29 69	100.00 1	99.99 57	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	97.87 110	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	99.42 124	98.02 95	100.00 1	100.00 1	99.32 61	99.99 90	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	97.86 111	100.00 1	100.00 1	99.19 78	100.00 1	99.99 57	100.00 1	100.00 1

API-MVS		99.72 26	99.70 21	99.79 94	99.97 88	99.37 130	99.96 217	99.94 21	98.48 64	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 67	99.88 144	100.00 1	99.14 83	100.00 1	99.97 75	100.00 1	100.00 1

ZNCC-MVS		99.71 29	99.62 40	99.97 31	99.99 49	99.90 58	100.00 1	99.79 44	97.97 101	99.97 103	100.00 1	98.97 94	100.00 1	99.94 84	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	99.42 124	97.70 122	100.00 1	100.00 1	99.51 33	99.97 113	100.00 1	100.00 1	100.00 1

MVS_111021_HR		99.71 29	99.63 37	99.93 65	99.95 94	99.83 83	100.00 1	100.00 1	98.89 37	100.00 1	100.00 1	97.85 142	99.95 133	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	99.98 206	99.44 108	98.35 75	99.99 94	100.00 1	99.04 89	99.96 124	99.98 68	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 28	100.00 1	100.00 1	97.93 140	99.95 133	99.99 57	100.00 1	100.00 1

PLC	98.56 2	99.70 32	99.74 16	99.58 124	100.00 1	98.79 173	100.00 1	99.54 67	98.58 61	99.96 107	100.00 1	99.59 20	100.00 1	100.00 1	100.00 1	99.94 118
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 43	99.98 23	99.99 49	99.93 43	100.00 1	99.43 114	97.50 146	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
EI-MVSNet-UG-set		99.69 35	99.63 37	99.87 77	99.99 49	99.64 104	99.95 223	99.44 108	98.35 75	100.00 1	100.00 1	98.98 93	99.97 113	99.98 68	100.00 1	100.00 1

PGM-MVS		99.69 35	99.61 41	99.95 51	99.99 49	99.85 80	100.00 1	99.58 65	97.69 124	100.00 1	100.00 1	99.44 46	100.00 1	99.79 104	100.00 1	100.00 1

mPP-MVS		99.69 35	99.60 42	99.97 31	100.00 1	99.91 51	100.00 1	99.42 124	97.91 107	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 39	99.58 45	99.98 23	100.00 1	99.95 32	100.00 1	99.64 63	97.59 136	100.00 1	100.00 1	98.99 92	99.99 90	100.00 1	100.00 1	100.00 1

MTAPA		99.68 39	99.59 43	99.97 31	99.99 49	99.91 51	100.00 1	99.42 124	98.32 77	99.94 131	100.00 1	98.65 120	100.00 1	99.96 77	100.00 1	100.00 1

APD-MVS		99.68 39	99.58 45	99.97 31	99.99 49	99.96 24	100.00 1	99.42 124	97.53 142	100.00 1	100.00 1	99.27 72	99.97 113	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 42	99.57 48	99.97 31	99.98 84	99.92 48	100.00 1	99.42 124	97.83 112	100.00 1	100.00 1	98.89 106	100.00 1	99.98 68	100.00 1	100.00 1

CP-MVS		99.67 42	99.58 45	99.95 51	100.00 1	99.84 82	100.00 1	99.42 124	97.77 117	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 44	99.57 48	99.95 51	99.99 49	99.85 80	100.00 1	99.42 124	97.67 125	100.00 1	100.00 1	99.05 87	99.99 90	100.00 1	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 45	99.55 54	99.97 31	99.99 49	99.91 51	100.00 1	99.48 74	97.54 140	100.00 1	100.00 1	98.97 94	99.99 90	99.98 68	100.00 1	100.00 1

ACMMP		99.65 45	99.57 48	99.89 72	99.99 49	99.66 102	99.75 263	99.73 55	98.16 83	99.75 164	100.00 1	98.90 105	100.00 1	99.96 77	99.88 118	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 47	99.53 56	99.95 51	100.00 1	99.86 77	100.00 1	99.79 44	97.72 120	99.95 129	100.00 1	98.39 129	100.00 1	99.96 77	99.99 97	100.00 1

PS-MVSNAJ		99.64 47	99.57 48	99.85 80	99.78 135	99.81 84	99.95 223	99.42 124	98.38 69	100.00 1	100.00 1	98.75 116	100.00 1	99.88 91	99.99 97	99.74 199

F-COLMAP		99.64 47	99.64 33	99.67 109	99.99 49	99.07 154	100.00 1	99.44 108	98.30 78	99.90 139	100.00 1	99.18 79	99.99 90	99.91 87	100.00 1	99.94 118

SR-MVS-dyc-post		99.63 50	99.52 58	99.97 31	99.99 49	99.91 51	100.00 1	99.42 124	97.62 131	100.00 1	100.00 1	98.65 120	99.99 90	99.99 57	100.00 1	100.00 1

DPM-MVS		99.63 50	99.51 59	100.00 1	99.90 106	100.00 1	100.00 1	99.43 114	99.00 25	100.00 1	100.00 1	99.58 22	100.00 1	97.64 242	100.00 1	100.00 1

EPNet		99.62 52	99.69 22	99.42 141	99.99 49	98.37 197	100.00 1	99.89 35	98.83 43	100.00 1	100.00 1	98.97 94	100.00 1	99.90 88	99.61 139	99.89 145
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DELS-MVS		99.62 52	99.56 53	99.82 85	99.92 102	99.45 121	100.00 1	99.78 46	98.92 35	99.73 165	100.00 1	97.70 148	100.00 1	99.93 85	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 54	99.50 60	99.97 31	99.98 84	99.92 48	100.00 1	99.42 124	97.53 142	99.77 161	100.00 1	98.77 115	100.00 1	99.99 57	100.00 1	99.99 98
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MP-MVS		99.61 54	99.49 62	99.98 23	99.99 49	99.94 40	100.00 1	99.42 124	97.82 113	99.99 94	100.00 1	98.20 132	100.00 1	99.99 57	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 54	99.69 22	99.35 150	99.99 49	98.06 221	100.00 1	99.36 196	99.83 2	100.00 1	100.00 1	98.95 98	99.99 90	100.00 1	99.11 147	100.00 1

HPM-MVS_fast		99.60 57	99.49 62	99.91 67	99.99 49	99.78 87	100.00 1	99.42 124	97.09 175	100.00 1	100.00 1	98.95 98	99.96 124	99.98 68	100.00 1	100.00 1

HPM-MVS		99.59 58	99.50 60	99.89 72	100.00 1	99.70 99	100.00 1	99.42 124	97.46 150	100.00 1	100.00 1	98.60 122	99.96 124	99.99 57	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 59	99.48 64	99.85 80	99.86 113	99.54 109	100.00 1	99.36 196	98.94 33	100.00 1	100.00 1	97.97 138	100.00 1	99.88 91	99.28 144	100.00 1

WTY-MVS		99.54 60	99.40 66	99.95 51	99.81 120	99.93 43	100.00 1	100.00 1	97.98 99	99.84 147	100.00 1	98.94 100	99.98 108	99.86 94	98.21 185	99.94 118

test_yl		99.51 61	99.37 71	99.95 51	99.82 116	99.90 58	100.00 1	99.47 75	97.48 148	100.00 1	100.00 1	99.80 6	100.00 1	99.98 68	97.75 209	99.94 118

DCV-MVSNet		99.51 61	99.37 71	99.95 51	99.82 116	99.90 58	100.00 1	99.47 75	97.48 148	100.00 1	100.00 1	99.80 6	100.00 1	99.98 68	97.75 209	99.94 118

xiu_mvs_v2_base		99.51 61	99.41 65	99.82 85	99.70 144	99.73 93	99.92 231	99.40 173	98.15 85	100.00 1	100.00 1	98.50 126	100.00 1	99.85 96	99.13 146	99.74 199

HY-MVS	96.53 9	99.50 64	99.35 75	99.96 42	99.81 120	99.93 43	99.64 281	100.00 1	97.97 101	99.84 147	99.85 213	98.94 100	99.99 90	99.86 94	98.23 184	99.95 113

PHI-MVS		99.50 64	99.39 67	99.82 85	100.00 1	99.45 121	100.00 1	99.94 21	96.38 225	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 66	99.38 68	99.85 80	100.00 1	99.54 109	100.00 1	99.42 124	97.58 137	99.98 99	100.00 1	97.43 162	100.00 1	99.99 57	100.00 1	100.00 1

MAR-MVS		99.49 66	99.36 73	99.89 72	99.97 88	99.66 102	99.74 264	99.95 18	97.89 108	100.00 1	100.00 1	96.71 183	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 68	99.38 68	99.75 101	99.89 108	99.51 112	99.45 302	100.00 1	98.38 69	99.83 149	100.00 1	98.86 107	99.81 170	99.25 169	98.78 155	99.94 118

PVSNet_Blended		99.48 68	99.36 73	99.83 84	99.98 84	99.60 106	100.00 1	100.00 1	97.79 115	100.00 1	100.00 1	96.57 185	99.99 90	100.00 1	99.88 118	99.90 141

sss		99.45 70	99.34 77	99.80 92	99.76 138	99.50 113	100.00 1	99.91 34	97.72 120	99.98 99	99.94 201	98.45 127	100.00 1	99.53 152	98.75 158	99.89 145

AdaColmap		99.44 71	99.26 82	99.95 51	100.00 1	99.86 77	99.70 274	99.99 13	98.53 62	99.90 139	100.00 1	95.34 203	100.00 1	99.92 86	100.00 1	100.00 1

thisisatest0515		99.42 72	99.31 78	99.74 102	99.59 177	99.55 108	100.00 1	99.46 90	96.65 208	99.92 135	100.00 1	99.44 46	99.85 161	99.09 180	99.63 138	99.81 180

CANet		99.40 73	99.24 85	99.89 72	99.99 49	99.76 89	100.00 1	99.73 55	98.40 68	99.78 160	100.00 1	95.28 204	99.96 124	100.00 1	99.99 97	99.96 108

114514_t		99.39 74	99.25 83	99.81 88	99.97 88	99.48 120	100.00 1	99.42 124	95.53 252	100.00 1	100.00 1	98.37 130	99.95 133	99.97 75	100.00 1	100.00 1

alignmvs		99.38 75	99.21 89	99.91 67	99.73 141	99.92 48	100.00 1	99.51 72	97.61 133	100.00 1	100.00 1	99.06 86	99.93 147	99.83 99	97.12 217	99.90 141

1314		99.38 75	99.19 93	99.96 42	98.88 273	99.89 65	99.24 322	99.93 29	98.88 38	98.79 227	100.00 1	97.02 169	100.00 1	100.00 1	100.00 1	100.00 1

thisisatest0530		99.37 77	99.27 79	99.69 107	99.59 177	99.41 125	100.00 1	99.46 90	96.46 219	99.90 139	100.00 1	99.44 46	99.85 161	98.97 183	99.58 140	99.80 191

xiu_mvs_v1_base_debu		99.35 78	99.21 89	99.79 94	99.67 152	99.71 95	99.78 254	99.36 196	98.13 87	100.00 1	100.00 1	97.00 173	100.00 1	99.83 99	99.07 148	99.66 208

xiu_mvs_v1_base		99.35 78	99.21 89	99.79 94	99.67 152	99.71 95	99.78 254	99.36 196	98.13 87	100.00 1	100.00 1	97.00 173	100.00 1	99.83 99	99.07 148	99.66 208

xiu_mvs_v1_base_debi		99.35 78	99.21 89	99.79 94	99.67 152	99.71 95	99.78 254	99.36 196	98.13 87	100.00 1	100.00 1	97.00 173	100.00 1	99.83 99	99.07 148	99.66 208

ETV-MVS		99.34 81	99.24 85	99.64 113	99.58 182	99.33 132	100.00 1	99.25 244	97.57 138	99.96 107	100.00 1	97.44 161	99.79 172	99.70 121	99.65 136	99.81 180

tttt0517		99.34 81	99.23 88	99.67 109	99.57 185	99.38 127	100.00 1	99.46 90	96.33 228	99.89 142	100.00 1	99.44 46	99.84 163	98.93 185	99.46 143	99.78 194

CS-MVS		99.33 83	99.27 79	99.50 131	99.99 49	99.00 164	100.00 1	99.13 290	97.26 166	99.96 107	100.00 1	97.79 145	99.64 189	99.64 137	99.67 134	99.87 164

PVSNet_Blended_VisFu		99.33 83	99.18 95	99.78 98	99.82 116	99.49 116	100.00 1	99.95 18	97.36 156	99.63 170	100.00 1	96.45 189	99.95 133	99.79 104	99.65 136	99.89 145

HyFIR lowres test		99.32 85	99.24 85	99.58 124	99.95 94	99.26 138	100.00 1	99.99 13	96.72 200	99.29 189	99.91 205	99.49 39	99.47 222	99.74 113	98.08 192	100.00 1

CS-MVS-test		99.31 86	99.27 79	99.43 139	99.99 49	98.77 174	100.00 1	99.19 267	97.24 167	99.96 107	100.00 1	97.56 154	99.70 186	99.68 129	99.81 125	99.82 175

LS3D		99.31 86	99.13 97	99.87 77	99.99 49	99.71 95	99.55 292	99.46 90	97.32 161	99.82 157	100.00 1	96.85 180	99.97 113	99.14 177	100.00 1	99.92 130

PVSNet	94.91 18	99.30 88	99.25 83	99.44 137	100.00 1	98.32 203	100.00 1	99.86 37	98.04 94	100.00 1	100.00 1	96.10 192	100.00 1	99.55 147	99.73 129	100.00 1

lupinMVS		99.29 89	99.16 96	99.69 107	99.45 216	99.49 116	100.00 1	99.15 281	97.45 151	99.97 103	100.00 1	96.76 181	99.76 178	99.67 132	100.00 1	99.81 180

CSCG		99.28 90	99.35 75	99.05 173	99.99 49	97.15 261	100.00 1	99.47 75	97.44 152	99.42 181	100.00 1	97.83 144	100.00 1	99.99 57	100.00 1	100.00 1

thres200		99.27 91	99.04 100	99.96 42	99.81 120	99.90 58	100.00 1	99.94 21	97.31 163	99.83 149	99.96 190	97.04 166	100.00 1	99.62 141	97.88 200	99.98 100

OMC-MVS		99.27 91	99.38 68	98.96 181	99.95 94	97.06 265	100.00 1	99.40 173	98.83 43	99.88 144	100.00 1	97.01 170	99.86 156	99.47 155	99.84 122	99.97 105

EIA-MVS		99.26 93	99.19 93	99.45 136	99.63 165	98.75 175	100.00 1	99.27 239	96.93 183	99.95 129	100.00 1	97.47 158	99.79 172	99.74 113	99.72 130	99.82 175

tfpn200view9		99.26 93	99.03 101	99.96 42	99.81 120	99.89 65	100.00 1	99.94 21	97.23 168	99.83 149	99.96 190	97.04 166	100.00 1	99.59 142	97.85 202	99.98 100

thres400		99.26 93	99.03 101	99.95 51	99.81 120	99.89 65	100.00 1	99.94 21	97.23 168	99.83 149	99.96 190	97.04 166	100.00 1	99.59 142	97.85 202	99.97 105

thres100view900		99.25 96	99.01 103	99.95 51	99.81 120	99.87 74	100.00 1	99.94 21	97.13 173	99.83 149	99.96 190	97.01 170	100.00 1	99.59 142	97.85 202	99.98 100

EPMVS		99.25 96	99.13 97	99.60 118	99.60 174	99.20 146	99.60 287	100.00 1	96.93 183	99.92 135	99.36 285	99.05 87	99.71 185	98.77 194	98.94 152	99.90 141

thres600view7		99.24 98	99.00 104	99.95 51	99.81 120	99.87 74	100.00 1	99.94 21	97.13 173	99.83 149	99.96 190	97.01 170	100.00 1	99.54 150	97.77 208	99.97 105

MVS		99.22 99	98.96 108	99.98 23	99.00 261	99.95 32	99.24 322	99.94 21	98.14 86	98.88 217	100.00 1	95.63 201	100.00 1	99.85 96	100.00 1	100.00 1

DROMVSNet		99.19 100	99.09 99	99.48 134	99.42 219	99.07 154	100.00 1	99.21 263	96.95 182	99.96 107	100.00 1	96.88 179	99.48 220	99.64 137	99.79 128	99.88 156

FE-MVS		99.16 101	98.99 106	99.66 111	99.65 157	99.18 148	99.58 289	99.43 114	95.24 262	99.91 137	99.59 265	99.37 57	99.97 113	98.31 218	99.81 125	99.83 170

PMMVS		99.12 102	98.97 107	99.58 124	99.57 185	98.98 166	100.00 1	99.30 221	97.14 172	99.96 107	100.00 1	96.53 188	99.82 167	99.70 121	98.49 165	99.94 118

jason		99.11 103	98.96 108	99.59 120	99.17 242	99.31 134	100.00 1	99.13 290	97.38 155	99.83 149	100.00 1	95.54 202	99.72 184	99.57 146	99.97 108	99.74 199
jason: jason.
EPP-MVSNet		99.10 104	99.00 104	99.40 144	99.51 203	98.68 181	99.92 231	99.43 114	95.47 258	99.65 169	100.00 1	99.51 33	99.76 178	99.53 152	98.00 193	99.75 198

TESTMET0.1,1		99.08 105	98.96 108	99.44 137	99.63 165	99.38 127	100.00 1	99.45 97	95.53 252	99.48 177	100.00 1	99.71 13	99.02 248	96.84 267	99.99 97	99.91 132

IS-MVSNet		99.08 105	98.91 116	99.59 120	99.65 157	99.38 127	99.78 254	99.24 248	96.70 202	99.51 175	100.00 1	98.44 128	99.52 215	98.47 212	98.39 173	99.88 156

UA-Net		99.06 107	98.83 122	99.74 102	99.52 198	99.40 126	99.08 346	99.45 97	97.64 129	99.83 149	100.00 1	95.80 196	99.94 145	98.35 216	99.80 127	99.88 156

3Dnovator	95.63 14	99.06 107	98.76 130	99.96 42	98.86 276	99.90 58	99.98 206	99.93 29	98.95 31	98.49 247	100.00 1	92.91 236	100.00 1	99.71 118	100.00 1	100.00 1

patch_mono-2		99.04 109	99.79 6	96.81 297	99.92 102	90.47 344	100.00 1	99.41 170	98.95 31	100.00 1	100.00 1	99.78 8	100.00 1	100.00 1	100.00 1	99.95 113

VNet		99.04 109	98.75 132	99.90 70	99.81 120	99.75 90	99.50 298	99.47 75	98.36 73	100.00 1	99.99 165	94.66 214	100.00 1	99.90 88	97.09 218	99.96 108

canonicalmvs		99.03 111	98.73 134	99.94 63	99.75 140	99.95 32	100.00 1	99.30 221	97.64 129	100.00 1	100.00 1	95.22 206	99.97 113	99.76 111	96.90 223	99.91 132

test-LLR		99.03 111	98.91 116	99.40 144	99.40 226	99.28 136	100.00 1	99.45 97	96.70 202	99.42 181	99.12 294	99.31 63	99.01 249	96.82 268	99.99 97	99.91 132

PatchmatchNet		99.03 111	98.96 108	99.26 163	99.49 208	98.33 201	99.38 310	99.45 97	96.64 209	99.96 107	99.58 267	99.49 39	99.50 218	97.63 243	99.00 151	99.93 128
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
3Dnovator+	95.58 15	99.03 111	98.71 137	99.96 42	98.99 264	99.89 65	100.00 1	99.51 72	98.96 28	98.32 255	100.00 1	92.78 237	100.00 1	99.87 93	100.00 1	100.00 1

CANet_DTU		99.02 115	98.90 119	99.41 142	99.88 110	98.71 179	100.00 1	99.29 225	98.84 42	100.00 1	100.00 1	94.02 221	100.00 1	98.08 227	99.96 110	99.52 214

PatchMatch-RL		99.02 115	98.78 127	99.74 102	99.99 49	99.29 135	100.00 1	100.00 1	98.38 69	99.89 142	99.81 222	93.14 234	99.99 90	97.85 237	99.98 105	99.95 113

FA-MVS(test-final)		99.00 117	98.75 132	99.73 105	99.63 165	99.43 124	99.83 244	99.43 114	95.84 243	99.52 174	99.37 284	97.84 143	99.96 124	97.63 243	99.68 132	99.79 193

CHOSEN 1792x2688		99.00 117	98.91 116	99.25 164	99.90 106	97.79 238	100.00 1	99.99 13	98.79 49	98.28 258	100.00 1	93.63 225	99.95 133	99.66 135	99.95 112	100.00 1

DeepC-MVS	97.84 5	99.00 117	98.80 126	99.60 118	99.93 99	99.03 159	100.00 1	99.40 173	98.61 60	99.33 187	100.00 1	92.23 244	99.95 133	99.74 113	99.96 110	99.83 170
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
baseline2		98.99 120	98.93 114	99.18 168	99.26 239	99.15 151	100.00 1	99.46 90	96.71 201	96.79 311	100.00 1	99.42 52	99.25 240	98.75 196	99.94 113	99.15 220

QAPM		98.99 120	98.66 139	99.96 42	99.01 257	99.87 74	99.88 239	99.93 29	97.99 97	98.68 232	100.00 1	93.17 232	100.00 1	99.32 164	100.00 1	100.00 1

Vis-MVSNet (Re-imp)		98.99 120	98.89 120	99.29 158	99.64 163	98.89 170	99.98 206	99.31 219	96.74 197	99.48 177	100.00 1	98.11 135	99.10 244	98.39 214	98.34 177	99.89 145

tpmrst		98.98 123	98.93 114	99.14 170	99.61 172	97.74 239	99.52 296	99.36 196	96.05 234	99.98 99	99.64 253	99.04 89	99.86 156	98.94 184	98.19 187	99.82 175

test-mter		98.96 124	98.82 123	99.40 144	99.40 226	99.28 136	100.00 1	99.45 97	95.44 261	99.42 181	99.12 294	99.70 14	99.01 249	96.82 268	99.99 97	99.91 132

diffmvs		98.96 124	98.73 134	99.63 114	99.54 188	99.16 150	100.00 1	99.18 274	97.33 160	99.96 107	100.00 1	94.60 215	99.91 150	99.66 135	98.33 180	99.82 175
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		98.96 124	98.95 112	99.01 177	99.48 210	98.36 199	99.93 230	99.37 190	96.79 193	99.31 188	99.83 216	99.77 10	98.91 258	98.07 228	97.98 194	99.77 195
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MVSFormer		98.94 127	98.82 123	99.28 161	99.45 216	99.49 116	100.00 1	99.13 290	95.46 259	99.97 103	100.00 1	96.76 181	98.59 291	98.63 204	100.00 1	99.74 199

MVS_Test		98.93 128	98.65 140	99.77 100	99.62 170	99.50 113	99.99 185	99.19 267	95.52 254	99.96 107	99.86 211	96.54 187	99.98 108	98.65 201	98.48 166	99.82 175

baseline1		98.91 129	98.61 144	99.81 88	99.71 142	99.77 88	99.78 254	99.44 108	97.51 145	98.81 225	99.99 165	98.25 131	99.76 178	98.60 207	95.41 234	99.89 145

1112_ss		98.91 129	98.71 137	99.51 129	99.69 145	98.75 175	99.99 185	99.15 281	96.82 191	98.84 222	100.00 1	97.45 159	99.89 152	98.66 199	97.75 209	99.89 145

MSDG		98.90 131	98.63 142	99.70 106	99.92 102	99.25 140	100.00 1	99.37 190	95.71 246	99.40 186	100.00 1	96.58 184	99.95 133	96.80 270	99.94 113	99.91 132

dcpmvs_2		98.87 132	99.53 56	96.90 291	99.87 112	90.88 343	99.94 228	99.07 310	98.20 81	100.00 1	100.00 1	98.69 119	99.86 156	100.00 1	100.00 1	99.95 113

DP-MVS		98.86 133	98.54 150	99.81 88	99.97 88	99.45 121	99.52 296	99.40 173	94.35 287	98.36 251	100.00 1	96.13 191	99.97 113	99.12 179	100.00 1	100.00 1

CostFormer		98.84 134	98.77 128	99.04 175	99.41 221	97.58 244	99.67 279	99.35 205	94.66 275	99.96 107	99.36 285	99.28 71	99.74 181	99.41 158	97.81 206	99.81 180

Test_1112_low_res		98.83 135	98.60 146	99.51 129	99.69 145	98.75 175	99.99 185	99.14 286	96.81 192	98.84 222	99.06 298	97.45 159	99.89 152	98.66 199	97.75 209	99.89 145

BH-w/o		98.82 136	98.81 125	98.88 186	99.62 170	96.71 272	100.00 1	99.28 231	97.09 175	98.81 225	100.00 1	94.91 211	99.96 124	99.54 150	100.00 1	99.96 108

mvs_anonymous		98.80 137	98.60 146	99.38 148	99.57 185	99.24 142	100.00 1	99.21 263	95.87 238	98.92 213	99.82 219	96.39 190	99.03 247	99.13 178	98.50 164	99.88 156

TAMVS		98.76 138	98.73 134	98.86 187	99.44 218	97.69 240	99.57 290	99.34 210	96.57 213	99.12 199	99.81 222	98.83 111	99.16 242	97.97 234	97.91 198	99.73 203

OpenMVS	95.20 17	98.76 138	98.41 156	99.78 98	98.89 272	99.81 84	99.99 185	99.76 48	98.02 95	98.02 271	100.00 1	91.44 250	100.00 1	99.63 140	99.97 108	99.55 212

iter_conf05		98.73 140	98.77 128	98.60 197	99.65 157	99.22 145	100.00 1	99.22 254	96.68 206	98.98 211	99.97 177	99.99 3	98.84 266	99.29 167	95.11 252	97.75 244

iter_conf_final		98.72 141	98.76 130	98.59 199	99.64 163	99.17 149	100.00 1	99.22 254	96.63 211	99.02 208	99.97 177	99.98 4	98.84 266	99.22 174	95.18 246	97.76 233

dp		98.72 141	98.61 144	99.03 176	99.53 191	97.39 250	99.45 302	99.39 186	95.62 249	99.94 131	99.52 275	98.83 111	99.82 167	96.77 273	98.42 170	99.89 145

PVSNet_BlendedMVS		98.71 143	98.62 143	98.98 180	99.98 84	99.60 106	100.00 1	100.00 1	97.23 168	100.00 1	99.03 303	96.57 185	99.99 90	100.00 1	94.75 260	97.35 329

ADS-MVSNet		98.70 144	98.51 152	99.28 161	99.51 203	98.39 194	99.24 322	99.44 108	95.52 254	99.96 107	99.70 237	97.57 152	99.58 196	97.11 259	98.54 162	99.88 156

baseline		98.69 145	98.45 155	99.41 142	99.52 198	98.67 182	100.00 1	99.17 279	97.03 180	99.13 198	100.00 1	93.17 232	99.74 181	99.70 121	98.34 177	99.81 180

PCF-MVS	98.23 3	98.69 145	98.37 161	99.62 115	99.78 135	99.02 160	99.23 327	99.06 318	96.43 220	98.08 267	100.00 1	94.72 213	99.95 133	98.16 225	99.91 116	99.90 141
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
casdiffmvs		98.65 147	98.38 159	99.46 135	99.52 198	98.74 178	100.00 1	99.15 281	96.91 186	99.05 206	100.00 1	92.75 238	99.83 164	99.70 121	98.38 174	99.81 180
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		98.64 148	98.39 158	99.40 144	99.50 206	98.60 185	100.00 1	99.22 254	96.85 189	99.10 200	100.00 1	92.75 238	99.78 176	99.71 118	98.35 176	99.81 180
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		98.64 148	98.58 148	98.81 190	99.42 219	97.12 262	99.69 276	99.37 190	93.63 303	99.94 131	99.67 245	98.96 97	99.47 222	98.62 206	97.95 196	99.83 170

BH-untuned		98.64 148	98.65 140	98.60 197	99.59 177	96.17 278	100.00 1	99.28 231	96.67 207	98.41 250	100.00 1	94.52 216	99.83 164	99.41 158	100.00 1	99.81 180

tpmvs		98.59 151	98.38 159	99.23 165	99.69 145	97.90 230	99.31 317	99.47 75	94.52 280	99.68 168	99.28 289	97.64 150	99.89 152	97.71 240	98.17 189	99.89 145

Effi-MVS+		98.58 152	98.24 166	99.61 116	99.60 174	99.26 138	97.85 363	99.10 300	96.22 231	99.97 103	99.89 207	93.75 223	99.77 177	99.43 156	98.34 177	99.81 180

MVSTER		98.58 152	98.52 151	98.77 191	99.65 157	99.68 101	100.00 1	99.29 225	95.63 248	98.65 233	99.80 225	99.78 8	98.88 264	98.59 208	95.31 238	97.73 273

CVMVSNet		98.56 154	98.47 154	98.82 188	99.11 245	97.67 241	99.74 264	99.47 75	97.57 138	99.06 205	100.00 1	95.72 198	98.97 254	98.21 224	97.33 216	99.83 170

AllTest		98.55 155	98.40 157	98.99 178	99.93 99	97.35 252	100.00 1	99.40 173	97.08 177	99.09 201	99.98 169	93.37 227	99.95 133	96.94 263	99.84 122	99.68 206

DeepPCF-MVS	98.03 4	98.54 156	99.72 19	94.98 318	99.99 49	84.94 356	100.00 1	99.42 124	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		98.53 157	98.23 168	99.43 139	99.92 102	99.01 162	99.96 217	99.47 75	98.80 47	99.96 107	99.96 190	98.56 124	99.30 238	87.78 348	99.68 132	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Vis-MVSNet		98.52 158	98.25 165	99.34 151	99.68 148	98.55 187	99.68 278	99.41 170	97.34 159	99.94 131	100.00 1	90.38 265	99.70 186	99.03 182	98.84 153	99.76 197
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Effi-MVS+-dtu		98.51 159	98.86 121	97.47 267	99.77 137	94.21 315	100.00 1	98.94 333	97.61 133	99.91 137	98.75 321	95.89 194	99.51 217	99.36 160	99.48 142	98.68 226

BH-RMVSNet		98.46 160	98.08 175	99.59 120	99.61 172	99.19 147	100.00 1	99.28 231	97.06 179	98.95 212	100.00 1	88.99 280	99.82 167	98.83 192	100.00 1	99.77 195

ECVR-MVS		98.43 161	98.14 171	99.32 155	99.89 108	98.21 210	99.46 300	100.00 1	98.38 69	99.47 180	100.00 1	87.91 291	99.80 171	99.35 161	98.78 155	99.94 118

cascas		98.43 161	98.07 176	99.50 131	99.65 157	99.02 160	100.00 1	99.22 254	94.21 290	99.72 166	99.98 169	92.03 247	99.93 147	99.68 129	98.12 190	99.54 213

test1111		98.42 163	98.12 172	99.29 158	99.88 110	98.15 213	99.46 300	100.00 1	98.36 73	99.42 181	100.00 1	87.91 291	99.79 172	99.31 165	98.78 155	99.94 118

ab-mvs		98.42 163	98.02 181	99.61 116	99.71 142	99.00 164	99.10 343	99.64 63	96.70 202	99.04 207	99.81 222	90.64 259	99.98 108	99.64 137	97.93 197	99.84 167

UGNet		98.41 165	98.11 173	99.31 157	99.54 188	98.55 187	99.18 330	100.00 1	98.64 59	99.79 159	99.04 301	87.61 296	100.00 1	99.30 166	99.89 117	99.40 217
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+		98.40 166	98.02 181	99.55 128	99.63 165	99.06 156	100.00 1	99.15 281	95.07 264	99.42 181	99.95 197	93.26 230	99.73 183	97.44 249	98.24 183	99.87 164

Fast-Effi-MVS+-dtu		98.38 167	98.56 149	97.82 257	99.58 182	94.44 312	100.00 1	99.16 280	96.75 195	99.51 175	99.63 257	95.03 209	99.60 190	97.71 240	99.67 134	99.42 216

test_fmvs1		98.37 168	98.04 179	99.34 151	99.84 114	98.07 219	100.00 1	99.00 328	98.85 41	100.00 1	100.00 1	85.11 316	99.96 124	99.69 128	99.88 118	100.00 1

miper_enhance_ethall		98.33 169	98.27 164	98.51 202	99.66 156	99.04 158	100.00 1	99.22 254	97.53 142	98.51 245	99.38 283	99.49 39	98.75 277	98.02 230	92.61 281	97.76 233

SCA		98.30 170	97.98 183	99.23 165	99.41 221	98.25 207	99.99 185	99.45 97	96.91 186	99.76 163	99.58 267	89.65 272	99.54 209	98.31 218	98.79 154	99.91 132

XVG-OURS		98.30 170	98.36 162	98.13 232	99.58 182	95.91 281	100.00 1	99.36 196	98.69 54	99.23 191	100.00 1	91.20 253	99.92 149	99.34 162	97.82 205	98.56 229

COLMAP_ROB	97.10 7	98.29 172	98.17 170	98.65 195	99.94 97	97.39 250	99.30 318	99.40 173	95.64 247	97.75 284	100.00 1	92.69 241	99.95 133	98.89 187	99.92 115	98.62 228
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ADS-MVSNet2		98.28 173	98.51 152	97.62 263	99.51 203	95.03 292	99.24 322	99.41 170	95.52 254	99.96 107	99.70 237	97.57 152	97.94 334	97.11 259	98.54 162	99.88 156

XVG-OURS-SEG-HR		98.27 174	98.31 163	98.14 229	99.59 177	95.92 280	100.00 1	99.36 196	98.48 64	99.21 192	100.00 1	89.27 277	99.94 145	99.76 111	99.17 145	98.56 229

tpm		98.24 175	98.22 169	98.32 214	99.13 244	95.79 283	99.53 295	99.12 296	95.20 263	99.96 107	99.36 285	97.58 151	99.28 239	97.41 251	96.67 224	99.88 156

cl22		98.23 176	98.11 173	98.58 201	99.82 116	99.01 162	100.00 1	99.28 231	96.92 185	98.33 254	99.21 291	98.09 137	98.97 254	98.72 197	92.61 281	97.76 233

TR-MVS		98.14 177	97.74 190	99.33 153	99.59 177	98.28 205	99.27 319	99.21 263	96.42 221	99.15 197	99.94 201	88.87 283	99.79 172	98.88 188	98.29 181	99.93 128

mvsmamba		98.13 178	98.06 177	98.32 214	98.22 302	98.50 190	100.00 1	99.22 254	96.41 222	98.91 215	99.96 190	95.69 199	98.73 279	99.19 176	94.95 259	97.73 273

test0.0.03 1		98.12 179	98.03 180	98.39 208	99.11 245	98.07 219	100.00 1	99.93 29	96.70 202	96.91 307	99.95 197	99.31 63	98.19 314	91.93 324	98.44 168	98.91 224

GeoE		98.06 180	97.65 195	99.29 158	99.47 213	98.41 191	100.00 1	99.19 267	94.85 269	98.88 217	100.00 1	91.21 252	99.59 192	97.02 261	98.19 187	99.88 156

tpm cat1		98.05 181	97.76 188	98.92 183	99.50 206	97.10 264	99.77 259	99.30 221	90.20 340	99.72 166	98.71 322	97.71 147	99.86 156	96.75 274	98.20 186	99.81 180

PS-MVSNAJss		98.03 182	98.06 177	97.94 251	97.63 323	97.33 255	99.89 237	99.23 252	96.27 230	98.03 269	99.59 265	98.75 116	98.78 272	98.52 210	94.61 264	97.70 289

CR-MVSNet		98.02 183	97.71 193	98.93 182	99.31 233	98.86 171	99.13 340	99.00 328	96.53 216	99.96 107	98.98 307	96.94 176	98.10 324	91.18 329	98.40 171	99.84 167

EI-MVSNet		97.98 184	97.93 184	98.16 227	99.11 245	97.84 235	99.74 264	99.29 225	94.39 286	98.65 233	100.00 1	97.21 164	98.88 264	97.62 245	95.31 238	97.75 244

FIs		97.95 185	97.73 192	98.62 196	98.53 287	99.24 142	100.00 1	99.43 114	96.74 197	97.87 279	99.82 219	95.27 205	98.89 261	98.78 193	93.07 276	97.74 267

Anonymous202405211		97.87 186	97.53 198	98.90 184	99.81 120	96.70 273	99.35 313	99.46 90	92.98 318	98.83 224	99.99 165	90.63 260	100.00 1	99.70 121	97.03 219	100.00 1

FC-MVSNet-test		97.84 187	97.63 196	98.45 205	98.30 297	99.05 157	100.00 1	99.43 114	96.63 211	97.61 290	99.82 219	95.19 207	98.57 294	98.64 202	93.05 277	97.73 273

Patchmatch-test		97.83 188	97.42 200	99.06 171	99.08 248	97.66 242	98.66 356	99.21 263	93.65 302	98.25 262	99.58 267	99.47 43	99.57 197	90.25 338	98.59 161	99.95 113

miper_ehance_all_eth		97.81 189	97.66 194	98.23 220	99.49 208	98.37 197	99.99 185	99.11 298	94.78 270	98.25 262	99.21 291	98.18 133	98.57 294	97.35 255	92.61 281	97.76 233

RRT_MVS		97.77 190	97.76 188	97.78 259	97.89 315	97.06 265	100.00 1	99.29 225	95.74 245	98.00 274	99.97 177	95.94 193	98.55 297	98.87 189	94.18 267	97.72 280

HQP-MVS		97.73 191	97.85 185	97.39 269	99.07 249	94.82 296	100.00 1	99.40 173	99.04 14	99.17 193	99.97 177	88.61 286	99.57 197	99.79 104	95.58 228	97.77 231

GA-MVS		97.72 192	97.27 210	99.06 171	99.24 240	97.93 229	100.00 1	99.24 248	95.80 244	98.99 210	99.64 253	89.77 270	99.36 233	95.12 296	97.62 214	99.89 145

bld_raw_dy_0_64		97.71 193	97.56 197	98.15 228	97.83 318	98.16 211	99.95 223	99.12 296	95.95 237	98.73 230	99.97 177	93.19 231	98.63 285	98.64 202	94.69 262	97.66 300

HQP_MVS		97.71 193	97.82 187	97.37 270	99.00 261	94.80 299	100.00 1	99.40 173	99.00 25	99.08 203	99.97 177	88.58 288	99.55 206	99.79 104	95.57 232	97.76 233

nrg030		97.64 195	97.27 210	98.75 192	98.34 292	99.53 111	100.00 1	99.22 254	96.21 232	98.27 260	99.95 197	94.40 217	98.98 252	99.23 172	89.78 316	97.75 244

TAPA-MVS	96.40 10	97.64 195	97.37 204	98.45 205	99.94 97	95.70 284	100.00 1	99.40 173	97.65 127	99.53 173	100.00 1	99.31 63	99.66 188	80.48 362	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CLD-MVS		97.64 195	97.74 190	97.36 271	99.01 257	94.76 304	100.00 1	99.34 210	99.30 4	99.00 209	99.97 177	87.49 297	99.57 197	99.96 77	95.58 228	97.75 244
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
D2MVS		97.63 198	97.83 186	97.05 282	98.83 279	94.60 308	100.00 1	99.82 39	96.89 188	98.28 258	99.03 303	94.05 219	99.47 222	98.58 209	94.97 257	97.09 335

c3_l		97.58 199	97.42 200	98.06 239	99.48 210	98.16 211	99.96 217	99.10 300	94.54 279	98.13 266	99.20 293	97.87 141	98.25 313	97.28 256	91.20 304	97.75 244

IterMVS-LS		97.56 200	97.44 199	97.92 254	99.38 230	97.90 230	99.89 237	99.10 300	94.41 285	98.32 255	99.54 274	97.21 164	98.11 321	97.50 247	91.62 297	97.75 244
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test_djsdf		97.55 201	97.38 203	98.07 235	97.50 331	97.99 224	100.00 1	99.13 290	95.46 259	98.47 248	99.85 213	92.01 248	98.59 291	98.63 204	95.36 236	97.62 312

cl____		97.54 202	97.32 206	98.18 224	99.47 213	98.14 215	100.00 1	99.10 300	94.16 293	97.60 291	99.63 257	97.52 155	98.65 284	96.47 275	91.97 293	97.76 233

IB-MVS	96.24 12	97.54 202	96.95 215	99.33 153	99.67 152	98.10 218	100.00 1	99.47 75	97.42 154	99.26 190	99.69 240	98.83 111	99.89 152	99.43 156	78.77 358	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		97.52 204	97.35 205	98.05 243	99.46 215	98.11 216	100.00 1	99.10 300	94.21 290	97.62 289	99.63 257	97.65 149	98.29 310	96.47 275	91.98 292	97.76 233

eth_miper_zixun_eth		97.47 205	97.28 208	98.06 239	99.41 221	97.94 228	99.62 285	99.08 306	94.46 284	98.19 265	99.56 271	96.91 178	98.50 300	96.78 271	91.49 299	97.74 267

test_fmvs1_n		97.43 206	96.86 218	99.15 169	99.68 148	97.48 247	99.99 185	98.98 331	98.82 45	100.00 1	100.00 1	74.85 351	99.96 124	99.67 132	99.70 131	100.00 1

LFMVS		97.42 207	96.62 227	99.81 88	99.80 130	99.50 113	99.16 336	99.56 66	94.48 283	100.00 1	100.00 1	79.35 342	100.00 1	99.89 90	97.37 215	99.94 118

miper_lstm_enhance		97.40 208	97.28 208	97.75 260	99.48 210	97.52 245	100.00 1	99.07 310	94.08 294	98.01 272	99.61 263	97.38 163	97.98 332	96.44 278	91.47 301	97.76 233

RPSCF		97.37 209	98.24 166	94.76 321	99.80 130	84.57 357	99.99 185	99.05 320	94.95 267	99.82 157	100.00 1	94.03 220	100.00 1	98.15 226	98.38 174	99.70 204

ACMM	97.17 6	97.37 209	97.40 202	97.29 275	99.01 257	94.64 307	100.00 1	99.25 244	98.07 93	98.44 249	99.98 169	87.38 298	99.55 206	99.25 169	95.19 245	97.69 293
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LPG-MVS_test		97.31 211	97.32 206	97.28 276	98.85 277	94.60 308	100.00 1	99.37 190	97.35 157	98.85 220	99.98 169	86.66 304	99.56 201	99.55 147	95.26 240	97.70 289

FMVSNet3		97.30 212	96.95 215	98.37 210	99.65 157	99.25 140	99.71 272	99.28 231	94.23 288	98.53 242	98.91 314	93.30 229	98.11 321	95.31 291	93.60 270	97.73 273

UniMVSNet (Re)		97.29 213	96.85 219	98.59 199	98.49 288	99.13 152	100.00 1	99.42 124	96.52 217	98.24 264	98.90 315	94.93 210	98.89 261	97.54 246	87.61 332	97.75 244

OPM-MVS		97.21 214	97.18 213	97.32 274	98.08 308	94.66 305	100.00 1	99.28 231	98.65 58	98.92 213	99.98 169	86.03 311	99.56 201	98.28 222	95.41 234	97.72 280
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMP	97.00 8	97.19 215	97.16 214	97.27 278	98.97 266	94.58 311	100.00 1	99.32 214	97.97 101	97.45 295	99.98 169	85.79 313	99.56 201	99.70 121	95.24 243	97.67 299
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
pmmvs4		97.17 216	96.80 220	98.27 217	97.68 322	98.64 184	100.00 1	99.18 274	94.22 289	98.55 240	99.71 234	93.67 224	98.47 303	95.66 285	92.57 284	97.71 288

anonymousdsp		97.16 217	96.88 217	98.00 247	97.08 341	98.06 221	99.81 248	99.15 281	94.58 277	97.84 280	99.62 261	90.49 262	98.60 289	97.98 231	95.32 237	97.33 330

UniMVSNet_NR-MVSNet		97.16 217	96.80 220	98.22 221	98.38 291	98.41 191	100.00 1	99.45 97	96.14 233	97.76 281	99.64 253	95.05 208	98.50 300	97.98 231	86.84 336	97.75 244

XXY-MVS		97.14 219	96.63 226	98.67 194	98.65 281	98.92 169	99.54 294	99.29 225	95.57 251	97.63 287	99.83 216	87.79 295	99.35 235	98.39 214	92.95 278	97.75 244

WR-MVS		97.09 220	96.64 225	98.46 204	98.43 289	99.09 153	99.97 212	99.33 212	95.62 249	97.76 281	99.67 245	91.17 254	98.56 296	98.49 211	89.28 321	97.74 267

JIA-IIPM		97.09 220	96.34 240	99.36 149	98.88 273	98.59 186	99.81 248	99.43 114	84.81 356	99.96 107	90.34 366	98.55 125	99.52 215	97.00 262	98.28 182	99.98 100

jajsoiax		97.07 222	96.79 222	97.89 255	97.28 339	97.12 262	99.95 223	99.19 267	96.55 214	97.31 298	99.69 240	87.35 300	98.91 258	98.70 198	95.12 251	97.66 300

MIMVSNet		97.06 223	96.73 223	98.05 243	99.38 230	96.64 275	98.47 359	99.35 205	93.41 308	99.48 177	98.53 329	89.66 271	97.70 340	94.16 307	98.11 191	99.80 191

X-MVStestdata		97.04 224	96.06 251	99.98 23	100.00 1	99.94 40	100.00 1	99.75 51	98.67 56	100.00 1	66.97 377	99.16 80	100.00 1	100.00 1	100.00 1	100.00 1

h-mvs33		97.03 225	96.53 229	98.51 202	99.79 133	95.90 282	99.45 302	99.45 97	98.21 79	100.00 1	99.78 228	97.49 156	99.99 90	99.72 116	74.92 360	99.65 211

VPA-MVSNet		97.03 225	96.43 235	98.82 188	98.64 282	99.32 133	99.38 310	99.47 75	96.73 199	98.91 215	98.94 312	87.00 302	99.40 231	99.23 172	89.59 317	97.76 233

mvs_tets		97.00 227	96.69 224	97.94 251	97.41 338	97.27 257	99.60 287	99.18 274	96.51 218	97.35 297	99.69 240	86.53 306	98.91 258	98.84 190	95.09 253	97.65 306

gg-mvs-nofinetune		96.95 228	96.10 249	99.50 131	99.41 221	99.36 131	99.07 348	99.52 68	83.69 358	99.96 107	83.60 374	100.00 1	99.20 241	99.68 129	99.99 97	99.96 108

Anonymous20240529		96.93 229	96.22 245	99.05 173	99.79 133	97.30 256	99.16 336	99.47 75	88.51 346	98.69 231	100.00 1	83.50 327	100.00 1	99.83 99	97.02 220	99.83 170

DU-MVS		96.93 229	96.49 232	98.22 221	98.31 295	98.41 191	100.00 1	99.37 190	96.41 222	97.76 281	99.65 249	92.14 245	98.50 300	97.98 231	86.84 336	97.75 244

Patchmtry		96.81 231	96.37 238	98.14 229	99.31 233	98.55 187	98.91 351	99.00 328	90.45 337	97.92 276	98.98 307	96.94 176	98.12 319	94.27 304	91.53 298	97.75 244

hse-mvs2		96.79 232	96.38 237	98.04 245	99.68 148	95.54 286	99.81 248	99.42 124	98.21 79	100.00 1	99.80 225	97.49 156	99.46 226	99.72 116	73.27 363	99.12 221

ACMH	96.25 11	96.77 233	96.62 227	97.21 279	98.96 267	94.43 313	99.64 281	99.33 212	97.43 153	96.55 316	99.97 177	83.52 326	99.54 209	99.07 181	95.13 250	97.66 300
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IterMVS		96.76 234	96.46 234	97.63 261	99.41 221	96.89 268	99.99 185	99.13 290	94.74 273	97.59 292	99.66 247	89.63 274	98.28 311	95.71 283	92.31 287	97.72 280
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CP-MVSNet		96.73 235	96.25 243	98.18 224	98.21 303	98.67 182	99.77 259	99.32 214	95.06 265	97.20 301	99.65 249	90.10 266	98.19 314	98.06 229	88.90 324	97.66 300

WR-MVS_H		96.73 235	96.32 242	97.95 250	98.26 299	97.88 232	99.72 271	99.43 114	95.06 265	96.99 304	98.68 324	93.02 235	98.53 298	97.43 250	88.33 328	97.43 325

IterMVS-SCA-FT		96.72 237	96.42 236	97.62 263	99.40 226	96.83 270	99.99 185	99.14 286	94.65 276	97.55 293	99.72 232	89.65 272	98.31 309	95.62 287	92.05 290	97.73 273

v2v482		96.70 238	96.18 246	98.27 217	98.04 309	98.39 194	100.00 1	99.13 290	94.19 292	98.58 238	99.08 297	90.48 263	98.67 282	95.69 284	90.44 312	97.75 244

test_vis1_n		96.69 239	95.81 261	99.32 155	99.14 243	97.98 225	99.97 212	98.98 331	98.45 66	100.00 1	100.00 1	66.44 363	99.99 90	99.78 110	99.57 141	100.00 1

V42		96.65 240	96.16 248	98.11 234	98.17 306	98.23 208	99.99 185	99.09 305	93.97 295	98.74 229	99.05 300	91.09 255	98.82 269	95.46 289	89.90 314	97.27 331

EU-MVSNet		96.63 241	96.53 229	96.94 289	97.59 327	96.87 269	99.76 261	99.47 75	96.35 226	96.85 309	99.78 228	92.57 242	96.27 354	95.33 290	91.08 305	97.68 295

NR-MVSNet		96.63 241	96.04 252	98.38 209	98.31 295	98.98 166	99.22 329	99.35 205	95.87 238	94.43 339	99.65 249	92.73 240	98.40 306	96.78 271	88.05 329	97.75 244

XVG-ACMP-BASELINE		96.60 243	96.52 231	96.84 295	98.41 290	93.29 324	99.99 185	99.32 214	97.76 119	98.51 245	99.29 288	81.95 333	99.54 209	98.40 213	95.03 254	97.68 295

VDD-MVS		96.58 244	95.99 254	98.34 212	99.52 198	95.33 287	99.18 330	99.38 188	96.64 209	99.77 161	100.00 1	72.51 356	100.00 1	100.00 1	96.94 222	99.70 204

tt0805		96.52 245	96.23 244	97.40 268	99.30 236	93.55 320	99.32 315	99.45 97	96.75 195	97.88 278	99.99 165	79.99 340	99.59 192	97.39 253	95.98 227	99.06 223

LCM-MVSNet-Re		96.52 245	97.21 212	94.44 322	99.27 237	85.80 354	99.85 242	96.61 369	95.98 235	92.75 345	98.48 331	93.97 222	97.55 341	99.58 145	98.43 169	99.98 100

our_test_3		96.51 247	96.35 239	96.98 287	97.61 325	95.05 291	99.98 206	99.01 327	94.68 274	96.77 313	99.06 298	95.87 195	98.14 317	91.81 325	92.37 286	97.75 244

MVP-Stereo		96.51 247	96.48 233	96.60 301	95.65 352	94.25 314	98.84 353	98.16 346	95.85 242	95.23 330	99.04 301	92.54 243	99.13 243	92.98 317	99.98 105	96.43 347
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
v1144		96.51 247	95.97 256	98.13 232	97.98 312	98.04 223	99.99 185	99.08 306	93.51 307	98.62 236	98.98 307	90.98 258	98.62 286	93.79 311	90.79 308	97.74 267

ACMH+	96.20 13	96.49 250	96.33 241	97.00 285	99.06 253	93.80 318	99.81 248	99.31 219	97.32 161	95.89 327	99.97 177	82.62 331	99.54 209	98.34 217	94.63 263	97.65 306

TranMVSNet+NR-MVSNet		96.45 251	96.01 253	97.79 258	98.00 311	97.62 243	100.00 1	99.35 205	95.98 235	97.31 298	99.64 253	90.09 267	98.00 331	96.89 266	86.80 339	97.75 244

ET-MVSNet_ETH3D		96.41 252	95.48 281	99.20 167	99.81 120	99.75 90	100.00 1	99.02 325	97.30 165	78.33 366	100.00 1	97.73 146	97.94 334	99.70 121	87.41 333	99.92 130

VPNet		96.41 252	95.76 266	98.33 213	98.61 283	98.30 204	99.48 299	99.45 97	96.98 181	98.87 219	99.88 208	81.57 334	98.93 256	99.22 174	87.82 331	97.76 233

PVSNet_0	93.57 19	96.41 252	95.74 267	98.41 207	99.84 114	95.22 289	100.00 1	100.00 1	98.08 92	97.55 293	99.78 228	84.40 319	100.00 1	100.00 1	81.99 351	100.00 1

v144192		96.40 255	95.81 261	98.17 226	97.89 315	98.11 216	99.99 185	99.06 318	93.39 309	98.75 228	99.09 296	90.43 264	98.66 283	93.10 316	90.55 311	97.75 244

VDDNet		96.39 256	95.55 276	98.90 184	99.27 237	97.45 248	99.15 338	99.92 33	91.28 331	99.98 99	100.00 1	73.55 352	100.00 1	99.85 96	96.98 221	99.24 218

tfpnnormal		96.36 257	95.69 272	98.37 210	98.55 285	98.71 179	99.69 276	99.45 97	93.16 316	96.69 315	99.71 234	88.44 290	98.99 251	94.17 305	91.38 302	97.41 326

v8		96.35 258	95.73 268	98.21 223	98.11 307	98.23 208	99.94 228	99.07 310	92.66 324	98.29 257	99.00 306	91.46 249	98.77 275	94.17 305	88.83 326	97.62 312

PS-CasMVS		96.34 259	95.78 265	98.03 246	98.18 305	98.27 206	99.71 272	99.32 214	94.75 271	96.82 310	99.65 249	86.98 303	98.15 316	97.74 239	88.85 325	97.66 300

LTVRE_ROB	95.29 16	96.32 260	96.10 249	96.99 286	98.55 285	93.88 317	99.45 302	99.28 231	94.50 282	96.46 317	99.52 275	84.86 317	99.48 220	97.26 257	95.03 254	97.59 316
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		96.29 261	95.70 269	98.07 235	99.80 130	97.49 246	99.15 338	99.40 173	89.11 343	97.75 284	99.45 280	88.93 282	98.98 252	98.26 223	89.47 319	97.73 273

v148		96.29 261	95.84 260	97.63 261	97.74 320	96.53 276	100.00 1	99.07 310	93.52 306	98.01 272	99.42 282	91.22 251	98.60 289	96.37 279	87.22 335	97.75 244

AUN-MVS		96.26 263	95.67 273	98.06 239	99.68 148	95.60 285	99.82 247	99.42 124	96.78 194	99.88 144	99.80 225	94.84 212	99.47 222	97.48 248	73.29 362	99.12 221

FMVSNet2		96.22 264	95.60 275	98.06 239	99.53 191	98.33 201	99.45 302	99.27 239	93.71 298	98.03 269	98.84 317	84.23 321	98.10 324	93.97 309	93.40 273	97.73 273

LF4IMVS		96.19 265	96.18 246	96.23 307	98.26 299	92.09 334	100.00 1	97.89 356	97.82 113	97.94 275	99.87 209	82.71 330	99.38 232	97.41 251	93.71 269	97.20 332

v1192		96.18 266	95.49 279	98.26 219	98.01 310	98.15 213	99.99 185	99.08 306	93.36 310	98.54 241	98.97 310	89.47 275	98.89 261	91.15 330	90.82 307	97.75 244

testgi		96.18 266	95.93 257	96.93 290	98.98 265	94.20 316	100.00 1	99.07 310	97.16 171	96.06 324	99.86 211	84.08 324	97.79 337	90.38 337	97.80 207	98.81 225

ppachtmachnet_test		96.17 268	95.89 258	97.02 284	97.61 325	95.24 288	99.99 185	99.24 248	93.31 312	96.71 314	99.62 261	94.34 218	98.07 326	89.87 339	92.30 288	97.75 244

v1921920		96.16 269	95.50 277	98.14 229	97.88 317	97.96 226	99.99 185	99.07 310	93.33 311	98.60 237	99.24 290	89.37 276	98.71 280	91.28 328	90.74 309	97.75 244

Baseline_NR-MVSNet		96.16 269	95.70 269	97.56 266	98.28 298	96.79 271	100.00 1	97.86 357	91.93 328	97.63 287	99.47 279	92.14 245	98.35 308	97.13 258	86.83 338	97.54 319

v10		96.14 271	95.50 277	98.07 235	98.19 304	97.96 226	99.83 244	99.07 310	92.10 327	98.07 268	98.94 312	91.07 256	98.61 287	92.41 323	89.82 315	97.63 310

OurMVSNet-221017-0		96.14 271	95.98 255	96.62 300	97.49 333	93.44 322	99.92 231	98.16 346	95.86 240	97.65 286	99.95 197	85.71 314	98.78 272	94.93 298	94.18 267	97.64 309

GBi-Net		96.07 273	95.80 263	96.89 292	99.53 191	94.87 293	99.18 330	99.27 239	93.71 298	98.53 242	98.81 318	84.23 321	98.07 326	95.31 291	93.60 270	97.72 280

test1		96.07 273	95.80 263	96.89 292	99.53 191	94.87 293	99.18 330	99.27 239	93.71 298	98.53 242	98.81 318	84.23 321	98.07 326	95.31 291	93.60 270	97.72 280

v7n		96.06 275	95.42 284	97.99 249	97.58 328	97.35 252	99.86 241	99.11 298	92.81 323	97.91 277	99.49 277	90.99 257	98.92 257	92.51 320	88.49 327	97.70 289

PEN-MVS		96.01 276	95.48 281	97.58 265	97.74 320	97.26 258	99.90 234	99.29 225	94.55 278	96.79 311	99.55 272	87.38 298	97.84 336	96.92 265	87.24 334	97.65 306

v1240		95.96 277	95.25 285	98.07 235	97.91 314	97.87 234	99.96 217	99.07 310	93.24 314	98.64 235	98.96 311	88.98 281	98.61 287	89.58 342	90.92 306	97.75 244

pmmvs5		95.94 278	95.61 274	96.95 288	97.42 336	94.66 305	100.00 1	98.08 350	93.60 304	97.05 303	99.43 281	87.02 301	98.46 304	95.76 282	92.12 289	97.72 280

PatchT		95.90 279	94.95 292	98.75 192	99.03 255	98.39 194	99.08 346	99.32 214	85.52 354	99.96 107	94.99 358	97.94 139	98.05 330	80.20 363	98.47 167	99.81 180

USDC		95.90 279	95.70 269	96.50 302	98.60 284	92.56 332	100.00 1	98.30 344	97.77 117	96.92 305	99.94 201	81.25 337	99.45 227	93.54 313	94.96 258	97.49 322

pm-mvs1		95.76 281	95.01 290	98.00 247	98.23 301	97.45 248	99.24 322	99.04 323	93.13 317	95.93 326	99.72 232	86.28 307	98.84 266	95.62 287	87.92 330	97.72 280

SixPastTwentyTwo		95.71 282	95.49 279	96.38 304	97.42 336	93.01 325	99.84 243	98.23 345	94.75 271	95.98 325	99.97 177	85.35 315	98.43 305	94.71 299	93.17 275	97.69 293

MS-PatchMatch		95.66 283	95.87 259	95.05 315	97.80 319	89.25 347	98.88 352	99.30 221	96.35 226	96.86 308	99.01 305	81.35 336	99.43 228	93.30 315	99.98 105	96.46 346

DTE-MVSNet		95.52 284	94.99 291	97.08 281	97.49 333	96.45 277	100.00 1	99.25 244	93.82 297	96.17 322	99.57 270	87.81 294	97.18 342	94.57 300	86.26 341	97.62 312

TinyColmap		95.50 285	95.12 289	96.64 299	98.69 280	93.00 326	99.40 308	97.75 359	96.40 224	96.14 323	99.87 209	79.47 341	99.50 218	93.62 312	94.72 261	97.40 327

K. test v3		95.46 286	95.14 288	96.40 303	97.53 330	93.40 323	99.99 185	99.23 252	95.49 257	92.70 346	99.73 231	84.26 320	98.12 319	93.94 310	93.38 274	97.68 295

FMVSNet5		95.32 287	95.43 283	94.99 317	99.39 229	92.99 327	99.25 321	99.24 248	90.45 337	97.44 296	98.45 332	95.78 197	94.39 363	87.02 349	91.88 294	97.59 316

UniMVSNet_ETH3D		95.28 288	94.41 294	97.89 255	98.91 270	95.14 290	99.13 340	99.35 205	92.11 326	97.17 302	99.66 247	70.28 359	99.36 233	97.88 236	95.18 246	99.16 219

RPMNet		95.26 289	93.82 297	99.56 127	99.31 233	98.86 171	99.13 340	99.42 124	79.82 363	99.96 107	95.13 356	95.69 199	99.98 108	77.54 367	98.40 171	99.84 167

DSMNet-mixed		95.18 290	95.21 287	95.08 314	96.03 347	90.21 345	99.65 280	93.64 375	92.91 319	98.34 253	97.40 347	90.05 268	95.51 360	91.02 331	97.86 201	99.51 215

test_fmvs2		95.17 291	95.23 286	95.01 316	98.95 269	88.99 349	99.99 185	97.77 358	97.79 115	98.58 238	99.70 237	73.36 353	99.34 236	95.88 281	95.03 254	96.70 343

MVS_0304		95.11 292	94.84 293	95.91 311	99.60 174	91.24 342	98.64 357	99.88 36	94.51 281	99.62 171	98.31 338	69.19 361	98.82 269	95.22 294	98.60 160	97.66 300

TransMVSNet (Re)		94.78 293	93.72 298	97.93 253	98.34 292	97.88 232	99.23 327	97.98 354	91.60 329	94.55 336	99.71 234	87.89 293	98.36 307	89.30 344	84.92 342	97.56 318

FMVSNet1		94.45 294	93.63 300	96.89 292	98.87 275	94.87 293	99.18 330	99.27 239	90.95 335	97.31 298	98.81 318	72.89 355	98.07 326	92.61 318	92.81 279	97.72 280

test_0402		94.35 295	93.70 299	96.32 305	97.92 313	93.60 319	99.61 286	98.85 339	88.19 349	94.68 335	99.48 278	80.01 339	98.58 293	89.39 343	95.15 249	96.77 341

UnsupCasMVSNet_eth		94.25 296	93.89 296	95.34 313	97.63 323	92.13 333	99.73 269	99.36 196	94.88 268	92.78 343	98.63 326	82.72 329	96.53 350	94.57 300	84.73 343	97.36 328

KD-MVS_2432*1600		94.15 297	93.08 305	97.35 272	99.53 191	97.83 236	99.63 283	99.19 267	92.88 320	96.29 319	97.68 344	98.84 109	96.70 346	89.73 340	63.92 367	97.53 320

miper_refine_blended		94.15 297	93.08 305	97.35 272	99.53 191	97.83 236	99.63 283	99.19 267	92.88 320	96.29 319	97.68 344	98.84 109	96.70 346	89.73 340	63.92 367	97.53 320

MVS-HIRNet		94.12 299	92.73 311	98.29 216	99.33 232	95.95 279	99.38 310	99.19 267	74.54 366	98.26 261	86.34 370	86.07 309	99.06 246	91.60 327	99.87 121	99.85 166

new_pmnet		94.11 300	93.47 302	96.04 309	96.60 344	92.82 328	99.97 212	98.91 336	90.21 339	95.26 329	98.05 342	85.89 312	98.14 317	84.28 354	92.01 291	97.16 333

pmmvs6		93.64 301	92.87 308	95.94 310	97.47 335	91.41 339	98.92 350	99.02 325	87.84 350	95.01 332	99.61 263	77.24 347	98.77 275	94.33 303	86.41 340	97.63 310

Patchmatch-RL test		93.49 302	93.63 300	93.05 333	91.78 363	83.41 358	98.21 361	96.95 366	91.58 330	91.05 348	97.64 346	99.40 55	95.83 358	94.11 308	81.95 352	99.91 132

Anonymous20231206		93.45 303	93.17 304	94.30 325	95.00 357	89.69 346	99.98 206	98.43 343	93.30 313	94.50 338	98.59 327	90.52 261	95.73 359	77.46 368	90.73 310	97.48 324

Anonymous20240521		93.29 304	92.76 310	94.90 320	95.64 353	91.27 340	99.97 212	98.82 340	87.04 351	94.71 334	98.19 339	83.86 325	96.80 345	84.04 355	92.56 285	96.64 344

test20.03		93.11 305	92.85 309	93.88 330	95.19 356	91.83 335	100.00 1	98.87 338	93.68 301	92.76 344	98.88 316	89.20 278	92.71 368	77.88 366	89.19 322	97.09 335

test_vis1_rt		93.10 306	92.93 307	93.58 331	99.63 165	85.07 355	99.99 185	93.71 374	97.49 147	90.96 349	97.10 348	60.40 365	99.95 133	99.24 171	97.90 199	95.72 353

APD_test1		93.07 307	94.14 295	89.85 339	99.18 241	72.49 366	99.76 261	98.90 337	92.86 322	96.35 318	99.94 201	75.56 349	99.91 150	86.73 350	97.98 194	97.15 334

EG-PatchMatch MVS		92.94 308	92.49 312	94.29 326	95.87 349	87.07 353	99.07 348	98.11 349	93.19 315	88.98 355	98.66 325	70.89 357	99.08 245	92.43 322	95.21 244	96.72 342

MDA-MVSNet_test_wron		92.61 309	91.09 317	97.19 280	96.71 343	97.26 258	100.00 1	99.14 286	88.61 345	67.90 372	98.32 337	89.03 279	96.57 349	90.47 336	89.59 317	97.74 267

YYNet1		92.44 310	90.92 318	97.03 283	96.20 345	97.06 265	99.99 185	99.14 286	88.21 348	67.93 371	98.43 334	88.63 285	96.28 353	90.64 332	89.08 323	97.74 267

MIMVSNet1		91.96 311	91.20 314	94.23 327	94.94 358	91.69 337	99.34 314	99.22 254	88.23 347	94.18 340	98.45 332	75.52 350	93.41 367	79.37 364	91.49 299	97.60 315

TDRefinement		91.93 312	90.48 320	96.27 306	81.60 374	92.65 331	99.10 343	97.61 362	93.96 296	93.77 341	99.85 213	80.03 338	99.53 214	97.82 238	70.59 364	96.63 345

OpenMVS_ROB	88.34 20	91.89 313	91.12 315	94.19 328	95.55 354	87.63 352	99.26 320	98.03 351	86.61 353	90.65 353	96.82 350	70.14 360	98.78 272	86.54 351	96.50 226	96.15 348

N_pmnet		91.88 314	93.37 303	87.40 344	97.24 340	66.33 373	99.90 234	91.05 377	89.77 342	95.65 328	98.58 328	90.05 268	98.11 321	85.39 352	92.72 280	97.75 244

pmmvs-eth3d		91.73 315	90.67 319	94.92 319	91.63 365	92.71 330	99.90 234	98.54 342	91.19 332	88.08 357	95.50 354	79.31 343	96.13 355	90.55 335	81.32 354	95.91 352

MDA-MVSNet-bldmvs		91.65 316	89.94 323	96.79 298	96.72 342	96.70 273	99.42 307	98.94 333	88.89 344	66.97 374	98.37 335	81.43 335	95.91 357	89.24 345	89.46 320	97.75 244

KD-MVS_self_test		91.16 317	90.09 322	94.35 324	94.44 359	91.27 340	99.74 264	99.08 306	90.82 336	94.53 337	94.91 359	86.11 308	94.78 362	82.67 357	68.52 365	96.99 337

CL-MVSNet_self_test		91.07 318	90.35 321	93.24 332	93.27 360	89.16 348	99.55 292	99.25 244	92.34 325	95.23 330	97.05 349	88.86 284	93.59 366	80.67 361	66.95 366	96.96 338

test_method		91.04 319	91.10 316	90.85 336	98.34 292	77.63 362	100.00 1	98.93 335	76.69 364	96.25 321	98.52 330	70.44 358	97.98 332	89.02 347	91.74 295	96.92 339

CMPMVS	66.12 22	90.65 320	92.04 313	86.46 345	96.18 346	66.87 372	98.03 362	99.38 188	83.38 359	85.49 361	99.55 272	77.59 346	98.80 271	94.44 302	94.31 266	93.72 361
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs3		90.62 321	89.36 325	94.40 323	90.53 368	91.49 338	100.00 1	96.73 367	84.21 357	93.65 342	96.65 351	82.56 332	94.83 361	82.28 358	77.62 359	96.89 340

new-patchmatchnet		90.30 322	89.46 324	92.84 334	90.77 367	88.55 351	99.83 244	98.80 341	90.07 341	87.86 358	95.00 357	78.77 344	94.30 364	84.86 353	79.15 356	95.68 355

UnsupCasMVSNet_bld		89.50 323	88.00 327	93.99 329	95.30 355	88.86 350	98.52 358	99.28 231	85.50 355	87.80 359	94.11 360	61.63 364	96.96 344	90.63 333	79.26 355	96.15 348

mvsany_test3		89.36 324	88.96 326	90.56 337	91.95 362	78.97 361	99.74 264	96.59 370	96.84 190	89.25 354	96.07 352	52.59 367	97.11 343	95.17 295	82.44 350	95.58 356

PM-MVS		88.39 325	87.41 328	91.31 335	91.73 364	82.02 360	99.79 253	96.62 368	91.06 334	90.71 352	95.73 353	48.60 369	95.96 356	90.56 334	81.91 353	95.97 351

test_fmvs3		87.19 326	87.02 329	87.71 343	92.69 361	76.64 363	99.96 217	97.27 363	93.55 305	90.82 351	94.03 361	38.00 375	92.19 369	93.49 314	83.35 349	94.32 358

test_f		86.87 327	86.06 330	89.28 340	91.45 366	76.37 364	99.87 240	97.11 364	91.10 333	88.46 356	93.05 363	38.31 374	96.66 348	91.77 326	83.46 348	94.82 357

Gipuma		84.73 328	83.50 333	88.40 342	97.50 331	82.21 359	88.87 368	99.05 320	65.81 368	85.71 360	90.49 365	53.70 366	96.31 352	78.64 365	91.74 295	86.67 367
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
testf1		84.40 329	84.79 331	83.23 349	95.71 350	58.71 379	98.79 354	97.75 359	81.58 360	84.94 362	98.07 340	45.33 371	97.73 338	77.09 369	83.85 345	93.24 362

APD_test2		84.40 329	84.79 331	83.23 349	95.71 350	58.71 379	98.79 354	97.75 359	81.58 360	84.94 362	98.07 340	45.33 371	97.73 338	77.09 369	83.85 345	93.24 362

testmvs		80.17 331	81.95 334	74.80 354	58.54 381	59.58 378	100.00 1	87.14 380	76.09 365	99.61 172	100.00 1	67.06 362	74.19 377	98.84 190	50.30 371	90.64 366

test_vis3_rt		79.61 332	78.19 337	83.86 348	88.68 369	69.56 370	99.81 248	82.19 382	86.78 352	68.57 370	84.51 373	25.06 379	98.26 312	89.18 346	78.94 357	83.75 370

EGC-MVSNET		79.46 333	74.04 341	95.72 312	96.00 348	92.73 329	99.09 345	99.04 323	5.08 378	16.72 378	98.71 322	73.03 354	98.74 278	82.05 359	96.64 225	95.69 354

test123		79.44 334	79.23 336	80.05 352	80.03 375	71.72 367	100.00 1	77.93 383	62.52 369	94.81 333	99.69 240	78.21 345	74.53 376	92.57 319	27.33 376	93.90 359

PMMVS2		79.15 335	77.28 338	84.76 347	82.34 373	72.66 365	99.70 274	95.11 373	71.68 367	84.78 364	90.87 364	32.05 377	89.99 370	75.53 371	63.45 369	91.64 364

LCM-MVSNet		79.01 336	76.93 339	85.27 346	78.28 376	68.01 371	96.57 365	98.03 351	55.10 372	82.03 365	93.27 362	31.99 378	93.95 365	82.72 356	74.37 361	93.84 360

FPMVS		77.92 337	79.45 335	73.34 356	76.87 377	46.81 382	98.24 360	99.05 320	59.89 371	73.55 367	98.34 336	36.81 376	86.55 371	80.96 360	91.35 303	86.65 368

tmp_tt		75.80 338	74.26 340	80.43 351	52.91 383	53.67 381	87.42 370	97.98 354	61.80 370	67.04 373	100.00 1	76.43 348	96.40 351	96.47 275	28.26 375	91.23 365

E-PMN		70.72 339	70.06 342	72.69 357	83.92 372	65.48 375	99.95 223	92.72 376	49.88 374	72.30 368	86.26 371	47.17 370	77.43 374	53.83 375	44.49 372	75.17 374

EMVS		69.88 340	69.09 343	72.24 358	84.70 371	65.82 374	99.96 217	87.08 381	49.82 375	71.51 369	84.74 372	49.30 368	75.32 375	50.97 376	43.71 373	75.59 373

MVE	68.59 21	67.22 341	64.68 345	74.84 353	74.67 379	62.32 377	95.84 366	90.87 378	50.98 373	58.72 375	81.05 375	12.20 383	78.95 373	61.06 374	56.75 370	83.24 371
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ANet_high		66.05 342	63.44 346	73.88 355	61.14 380	63.45 376	95.68 367	87.18 379	79.93 362	47.35 376	80.68 376	22.35 380	72.33 378	61.24 373	35.42 374	85.88 369

PMVS	60.66 23	65.98 343	65.05 344	68.75 359	55.06 382	38.40 383	88.19 369	96.98 365	48.30 376	44.82 377	88.52 368	12.22 382	86.49 372	67.58 372	83.79 347	81.35 372
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
wuyk23d		28.28 344	29.73 348	23.92 360	75.89 378	32.61 384	66.50 371	12.88 384	16.09 377	14.59 379	16.59 378	12.35 381	32.36 379	39.36 377	13.36 377	6.79 375

cdsmvs_eth3d_5k		24.41 345	32.55 347	0.00 361	0.00 384	0.00 385	0.00 372	99.39 186	0.00 379	0.00 380	100.00 1	93.55 226	0.00 380	0.00 378	0.00 378	0.00 376

ab-mvs-re		8.33 346	11.11 349	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	100.00 1	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

pcd_1.5k_mvsjas		8.24 347	10.99 350	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	98.75 116	0.00 380	0.00 378	0.00 378	0.00 376

test_blank		0.07 348	0.09 351	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.79 379	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

uanet_test		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

DCPMVS		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

sosnet-low-res		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

sosnet		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

uncertanet		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

Regformer		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

uanet		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

FOURS1					100.00 1	99.97 21	100.00 1	99.42 124	98.52 63	100.00 1

MSC_two_6792asdad				100.00 1	100.00 1	100.00 1		99.42 124					100.00 1	100.00 1	100.00 1	100.00 1

PC_three_1452									98.80 47	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		99.42 124					100.00 1	100.00 1	100.00 1	100.00 1

test_one_0601					100.00 1	99.99 5		99.42 124	98.72 53	100.00 1	100.00 1	99.60 17

eth-test2					0.00 384

eth-test					0.00 384

ZD-MVS					100.00 1	99.98 17		99.80 42	97.31 163	100.00 1	100.00 1	99.32 61	99.99 90	100.00 1	100.00 1

RE-MVS-def			99.55 54		99.99 49	99.91 51	100.00 1	99.42 124	97.62 131	100.00 1	100.00 1	98.94 100		99.99 57	100.00 1	100.00 1

IU-MVS					100.00 1	99.99 5		99.42 124	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								99.42 124	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		99.42 124	99.03 19	100.00 1	100.00 1	99.50 37	100.00 1

9.14			99.57 48		99.99 49		100.00 1	99.42 124	97.54 140	100.00 1	100.00 1	99.15 82	99.99 90	100.00 1	100.00 1

save fliter					99.99 49	99.93 43	100.00 1	99.42 124	98.93 34

test_0728_THIRD									98.79 49	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	99.42 124					100.00 1	100.00 1	100.00 1	100.00 1

test0726					100.00 1	99.99 5	100.00 1	99.42 124	99.04 14	100.00 1	100.00 1	99.53 29

GSMVS																99.91 132

test_part2					100.00 1	99.99 5				100.00 1

sam_mvs1												99.29 69				99.91 132

sam_mvs												99.33 58

ambc				88.45 341	86.84 370	70.76 369	97.79 364	98.02 353		90.91 350	95.14 355	38.69 373	98.51 299	94.97 297	84.23 344	96.09 350

MTGPA								99.42 124

test_post1							99.32 315				88.24 369	99.33 58	99.59 192	98.31 218

test_post											89.05 367	99.49 39	99.59 192

patchmatchnet-post											97.79 343	99.41 54	99.54 209

GG-mvs-BLEND				99.59 120	99.54 188	99.49 116	99.17 335	99.52 68		99.96 107	99.68 244	100.00 1	99.33 237	99.71 118	99.99 97	99.96 108

MTMP							100.00 1	99.18 274

gm-plane-assit					99.52 198	97.26 258			95.86 240		100.00 1		99.43 228	98.76 195

test9_res														100.00 1	100.00 1	100.00 1

TEST9					100.00 1	99.95 32	100.00 1	99.42 124	97.65 127	100.00 1	100.00 1	99.53 29	99.97 113

test_8					100.00 1	99.91 51	100.00 1	99.42 124	97.70 122	100.00 1	100.00 1	99.51 33	99.98 108

agg_prior2														100.00 1	100.00 1	100.00 1

agg_prior					100.00 1	99.88 72		99.42 124		100.00 1			99.97 113

TestCases				98.99 178	99.93 99	97.35 252		99.40 173	97.08 177	99.09 201	99.98 169	93.37 227	99.95 133	96.94 263	99.84 122	99.68 206

test_prior4						99.93 43	100.00 1

test_prior2							100.00 1		98.82 45	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					99.97 113			100.00 1

旧先验2							100.00 1		98.11 91	100.00 1			100.00 1	99.67 132

新几何2							100.00 1

新几何1				99.99 12	100.00 1	99.96 24		99.81 41	97.89 108	100.00 1	100.00 1	99.20 77	100.00 1	97.91 235	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 99				100.00 1	99.33 163		100.00 1

原ACMM2							100.00 1

原ACMM1				99.93 65	100.00 1	99.80 86		99.66 62	98.18 82	100.00 1	100.00 1	99.43 50	100.00 1	99.50 154	100.00 1	100.00 1

test222					99.99 49	99.90 58	100.00 1	99.69 61	97.66 126	100.00 1	100.00 1	99.30 68			100.00 1	100.00 1

testdata2													100.00 1	97.36 254

segment_acmp												99.55 25

testdata				99.66 111	99.99 49	98.97 168		99.73 55	97.96 104	100.00 1	100.00 1	99.42 52	100.00 1	99.28 168	100.00 1	100.00 1

testdata1							100.00 1		98.77 52

test12				99.95 51	99.99 49	99.89 65		99.42 124		100.00 1		99.24 74	99.97 113		100.00 1	100.00 1

plane_prior7					99.00 261	94.78 303

plane_prior6					99.06 253	94.80 299						88.58 288

plane_prior5								99.40 173					99.55 206	99.79 104	95.57 232	97.76 233

plane_prior4											99.97 177

plane_prior3						94.79 302			99.03 19	99.08 203

plane_prior2							100.00 1		99.00 25

plane_prior1					99.02 256

plane_prior						94.80 299	100.00 1		99.03 19						95.58 228

n2								0.00 385

nn								0.00 385

door-mid								96.32 371

lessismore_v0				96.05 308	97.55 329	91.80 336		99.22 254		91.87 347	99.91 205	83.50 327	98.68 281	92.48 321	90.42 313	97.68 295

LGP-MVS_train				97.28 276	98.85 277	94.60 308		99.37 190	97.35 157	98.85 220	99.98 169	86.66 304	99.56 201	99.55 147	95.26 240	97.70 289

test11								99.42 124

door								96.13 372

HQP5-MVS						94.82 296

HQP-NCC					99.07 249		100.00 1		99.04 14	99.17 193

ACMP_Plane					99.07 249		100.00 1		99.04 14	99.17 193

BP-MVS														99.79 104

HQP4-MVS										99.17 193			99.57 197			97.77 231

HQP3-MVS								99.40 173							95.58 228

HQP2-MVS												88.61 286

NP-MVS					99.07 249	94.81 298					99.97 177

MDTV_nov1_ep13_2view						99.24 142	99.56 291		96.31 229	99.96 107		98.86 107		98.92 186		99.89 145

MDTV_nov1_ep13			98.94 113		99.53 191	98.36 199	99.39 309	99.46 90	96.54 215	99.99 94	99.63 257	98.92 103	99.86 156	98.30 221	98.71 159

ACMMP++_ref															94.58 265

ACMMP++															95.17 248

Test By Simon												99.10 84

ITE_SJBPF				96.84 295	98.96 267	93.49 321		98.12 348	98.12 90	98.35 252	99.97 177	84.45 318	99.56 201	95.63 286	95.25 242	97.49 322

DeepMVS_CX				89.98 338	98.90 271	71.46 368		99.18 274	97.61 133	96.92 305	99.83 216	86.07 309	99.83 164	96.02 280	97.65 213	98.65 227

High-resolution multi-view benchmark