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.

ZD-MVS					100.00 1	99.98 13		99.80 39	97.31 165	100.00 1	100.00 1	99.32 58	99.99 89	100.00 1	100.00 1

SED-MVS		99.83 7	99.77 9	100.00 1	100.00 1	99.99 3	100.00 1	99.42 127	99.03 19	100.00 1	100.00 1	99.50 33	100.00 1	100.00 1	100.00 1	100.00 1

IU-MVS					100.00 1	99.99 3		99.42 127	99.12 6	100.00 1				100.00 1	100.00 1	100.00 1

OPU-MVS				100.00 1	100.00 1	100.00 1	100.00 1				100.00 1	99.54 22	100.00 1	100.00 1	100.00 1	100.00 1

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

xxxxxxxxxxxxxcwj		99.77 18	99.70 20	99.97 31	99.99 54	99.93 42	100.00 1	99.31 222	98.93 32	100.00 1	100.00 1	99.05 90	99.99 89	100.00 1	100.00 1	100.00 1

SF-MVS		99.66 54	99.57 57	99.95 58	99.99 54	99.85 87	100.00 1	99.42 127	97.67 123	100.00 1	100.00 1	99.05 90	99.99 89	100.00 1	100.00 1	100.00 1

ETH3D cwj APD-0.16		99.63 62	99.53 66	99.94 73	99.97 96	99.82 92	100.00 1	99.42 127	97.39 156	100.00 1	100.00 1	98.98 100	99.99 89	100.00 1	100.00 1	100.00 1

ETH3 D test6400		99.68 47	99.59 50	99.97 31	99.99 54	99.93 42	100.00 1	99.42 127	97.97 96	100.00 1	100.00 1	98.90 113	99.99 89	100.00 1	100.00 1	100.00 1

9.14			99.57 57		99.99 54		100.00 1	99.42 127	97.54 141	100.00 1	100.00 1	99.15 84	99.99 89	100.00 1	100.00 1

testtj		99.70 39	99.61 47	99.99 9	100.00 1	99.98 13	100.00 1	99.53 68	97.71 119	100.00 1	100.00 1	99.23 74	100.00 1	100.00 1	100.00 1	100.00 1

ETH3D-3000-0.1		99.66 54	99.57 57	99.95 58	99.99 54	99.85 87	100.00 1	99.42 127	97.58 137	100.00 1	100.00 1	99.12 86	99.99 89	100.00 1	100.00 1	100.00 1

DVP-MVS		99.83 7	99.78 6	100.00 1	100.00 1	99.99 3	100.00 1	99.42 127	99.04 14	100.00 1	100.00 1	99.53 23	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
test_0728_THIRD									98.79 46	100.00 1	100.00 1	99.61 13	100.00 1	100.00 1	100.00 1	100.00 1

test_0728_SECOND				100.00 1	99.99 54	99.99 3	100.00 1	99.42 127					100.00 1	100.00 1	100.00 1	100.00 1

SR-MVS		99.68 47	99.58 54	99.98 22	100.00 1	99.95 29	100.00 1	99.64 63	97.59 135	100.00 1	100.00 1	98.99 99	99.99 89	100.00 1	100.00 1	100.00 1

SMA-MVS		99.69 43	99.59 50	99.98 22	99.99 54	99.93 42	100.00 1	99.43 119	97.50 147	100.00 1	100.00 1	99.43 47	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
DPE-MVS		99.79 14	99.73 16	99.99 9	99.99 54	99.98 13	100.00 1	99.42 127	98.91 35	100.00 1	100.00 1	99.22 76	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
CHOSEN 280x420		99.85 3	99.87 1	99.80 104	99.99 54	99.97 18	99.97 214	99.98 13	98.96 28	100.00 1	100.00 1	99.96 3	99.42 226	100.00 1	100.00 1	100.00 1

CANet		99.40 86	99.24 94	99.89 85	99.99 54	99.76 99	100.00 1	99.73 54	98.40 63	99.78 164	100.00 1	95.28 210	99.96 132	100.00 1	99.99 107	99.96 116

MSP-MVS		99.81 11	99.77 9	99.94 73	100.00 1	99.86 84	100.00 1	99.42 127	98.87 39	100.00 1	100.00 1	99.65 12	99.96 132	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
TSAR-MVS + MP.		99.82 9	99.77 9	99.99 9	100.00 1	99.96 20	100.00 1	99.43 119	99.05 13	100.00 1	100.00 1	99.45 42	99.99 89	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
test9_res														100.00 1	100.00 1	100.00 1

train_agg		99.71 35	99.63 42	99.97 31	100.00 1	99.95 29	100.00 1	99.42 127	97.70 120	100.00 1	100.00 1	99.51 28	99.97 118	100.00 1	100.00 1	100.00 1

agg_prior1		99.71 35	99.63 42	99.95 58	100.00 1	99.88 78	100.00 1	99.42 127	97.72 116	100.00 1	100.00 1	99.51 28	99.97 118	100.00 1	100.00 1	100.00 1

agg_prior2														100.00 1	100.00 1	100.00 1

HPM-MVS++		99.82 9	99.76 12	99.99 9	99.99 54	99.98 13	100.00 1	99.83 35	98.88 37	99.96 112	100.00 1	99.21 78	100.00 1	100.00 1	100.00 1	99.99 106

XVS		99.79 14	99.73 16	99.98 22	100.00 1	99.94 37	100.00 1	99.75 49	98.67 51	100.00 1	100.00 1	99.16 82	100.00 1	100.00 1	100.00 1	100.00 1

test_prior3		99.81 11	99.78 6	99.90 82	100.00 1	99.75 101	100.00 1	99.73 54	98.82 43	100.00 1	100.00 1	99.47 39	99.97 118	100.00 1	100.00 1	100.00 1

test_prior2							100.00 1		98.82 43	100.00 1	100.00 1	99.47 39		100.00 1	100.00 1

X-MVStestdata		97.04 225	96.06 252	99.98 22	100.00 1	99.94 37	100.00 1	99.75 49	98.67 51	100.00 1	66.97 364	99.16 82	100.00 1	100.00 1	100.00 1	100.00 1

1314		99.38 88	99.19 104	99.96 46	98.88 268	99.89 68	99.24 312	99.93 26	98.88 37	98.79 223	100.00 1	97.02 176	100.00 1	100.00 1	100.00 1	100.00 1

VDD-MVS		96.58 245	95.99 255	98.34 215	99.52 200	95.33 286	99.18 321	99.38 192	96.64 206	99.77 165	100.00 1	72.51 352	100.00 1	100.00 1	96.94 219	99.70 203

SD-MVS		99.81 11	99.75 14	99.99 9	99.99 54	99.96 20	100.00 1	99.42 127	99.01 24	100.00 1	100.00 1	99.33 55	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
MSLP-MVS++		99.89 1	99.85 2	99.99 9	100.00 1	99.96 20	100.00 1	99.95 15	99.11 7	100.00 1	100.00 1	99.60 14	100.00 1	100.00 1	100.00 1	100.00 1

APDe-MVS		99.84 6	99.78 6	99.99 9	100.00 1	99.98 13	100.00 1	99.44 109	99.06 11	100.00 1	100.00 1	99.56 19	99.99 89	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 3	100.00 1	99.73 54	99.19 5	100.00 1	100.00 1	99.31 60	100.00 1	100.00 1	100.00 1	100.00 1

CDPH-MVS		99.73 29	99.64 38	99.99 9	100.00 1	99.97 18	100.00 1	99.42 127	98.02 90	100.00 1	100.00 1	99.32 58	99.99 89	100.00 1	100.00 1	100.00 1

TSAR-MVS + GP.		99.61 68	99.69 22	99.35 156	99.99 54	98.06 220	100.00 1	99.36 200	99.83 2	100.00 1	100.00 1	98.95 106	99.99 89	100.00 1	99.11 150	100.00 1

mPP-MVS		99.69 43	99.60 49	99.97 31	100.00 1	99.91 52	100.00 1	99.42 127	97.91 103	100.00 1	100.00 1	99.04 93	100.00 1	100.00 1	100.00 1	100.00 1

APD-MVS		99.68 47	99.58 54	99.97 31	99.99 54	99.96 20	100.00 1	99.42 127	97.53 143	100.00 1	100.00 1	99.27 70	99.97 118	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
CNVR-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 3	100.00 1	99.77 44	99.07 9	100.00 1	100.00 1	99.39 53	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 3	100.00 1	99.71 60	99.07 9	100.00 1	100.00 1	99.59 16	100.00 1	100.00 1	100.00 1	100.00 1

CP-MVS		99.67 52	99.58 54	99.95 58	100.00 1	99.84 90	100.00 1	99.42 127	97.77 113	100.00 1	100.00 1	99.07 88	100.00 1	100.00 1	100.00 1	100.00 1

SteuartSystems-ACMMP		99.78 16	99.71 19	99.98 22	99.76 142	99.95 29	100.00 1	99.42 127	98.69 49	100.00 1	100.00 1	99.52 26	99.99 89	100.00 1	100.00 1	100.00 1
Skip Steuart: Steuart Systems R&D Blog.
PVSNet_BlendedMVS		98.71 150	98.62 150	98.98 181	99.98 92	99.60 119	100.00 1	100.00 1	97.23 168	100.00 1	99.03 299	96.57 191	99.99 89	100.00 1	94.75 251	97.35 326

PVSNet_Blended		99.48 82	99.36 84	99.83 96	99.98 92	99.60 119	100.00 1	100.00 1	97.79 112	100.00 1	100.00 1	96.57 191	99.99 89	100.00 1	99.88 128	99.90 144

PAPM_NR		99.74 26	99.66 33	99.99 9	100.00 1	99.96 20	100.00 1	99.47 77	97.87 107	100.00 1	100.00 1	99.60 14	100.00 1	100.00 1	100.00 1	100.00 1

PAPR		99.76 19	99.68 25	99.99 9	100.00 1	99.96 20	100.00 1	99.47 77	98.16 77	100.00 1	100.00 1	99.51 28	100.00 1	100.00 1	100.00 1	100.00 1

MVS_111021_HR		99.71 35	99.63 42	99.93 76	99.95 103	99.83 91	100.00 1	100.00 1	98.89 36	100.00 1	100.00 1	97.85 151	99.95 138	100.00 1	100.00 1	100.00 1

API-MVS		99.72 32	99.70 20	99.79 106	99.97 96	99.37 140	99.96 218	99.94 18	98.48 58	100.00 1	100.00 1	98.92 111	100.00 1	100.00 1	100.00 1	100.00 1

PAPM		99.78 16	99.76 12	99.85 93	99.01 253	99.95 29	100.00 1	99.75 49	99.37 3	99.99 99	100.00 1	99.76 8	99.60 189	100.00 1	100.00 1	100.00 1

PHI-MVS		99.50 78	99.39 79	99.82 97	100.00 1	99.45 132	100.00 1	99.94 18	96.38 220	100.00 1	100.00 1	98.18 142	100.00 1	100.00 1	100.00 1	100.00 1

PVSNet_0	93.57 19	96.41 252	95.74 267	98.41 210	99.84 117	95.22 288	100.00 1	100.00 1	98.08 86	97.55 288	99.78 225	84.40 320	100.00 1	100.00 1	81.99 338	100.00 1

DeepPCF-MVS	98.03 4	98.54 162	99.72 18	94.98 314	99.99 54	84.94 349	100.00 1	99.42 127	99.98 1	100.00 1	100.00 1	98.11 145	100.00 1	100.00 1	100.00 1	100.00 1

PLC	98.56 2	99.70 39	99.74 15	99.58 134	100.00 1	98.79 180	100.00 1	99.54 67	98.58 56	99.96 112	100.00 1	99.59 16	100.00 1	100.00 1	100.00 1	99.94 124
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MAR-MVS		99.49 80	99.36 84	99.89 85	99.97 96	99.66 115	99.74 259	99.95 15	97.89 104	100.00 1	100.00 1	96.71 189	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
test1172		99.64 58	99.53 66	99.96 46	100.00 1	99.90 60	100.00 1	99.51 73	97.59 135	100.00 1	100.00 1	98.65 127	99.99 89	99.99 58	100.00 1	100.00 1

SR-MVS-dyc-post		99.63 62	99.52 69	99.97 31	99.99 54	99.91 52	100.00 1	99.42 127	97.62 129	100.00 1	100.00 1	98.65 127	99.99 89	99.99 58	100.00 1	100.00 1

RE-MVS-def			99.55 64		99.99 54	99.91 52	100.00 1	99.42 127	97.62 129	100.00 1	100.00 1	98.94 108		99.99 58	100.00 1	100.00 1

MP-MVS-pluss		99.61 68	99.50 72	99.97 31	99.98 92	99.92 49	100.00 1	99.42 127	97.53 143	99.77 165	100.00 1	98.77 123	100.00 1	99.99 58	100.00 1	99.99 106
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HFP-MVS		99.74 26	99.67 30	99.96 46	100.00 1	99.89 68	100.00 1	99.76 45	97.95 101	100.00 1	100.00 1	99.31 60	100.00 1	99.99 58	100.00 1	100.00 1

region2R		99.72 32	99.64 38	99.97 31	100.00 1	99.90 60	100.00 1	99.74 52	97.86 108	100.00 1	100.00 1	99.19 80	100.00 1	99.99 58	100.00 1	100.00 1

#test#		99.75 21	99.68 25	99.96 46	100.00 1	99.89 68	100.00 1	99.76 45	98.07 87	100.00 1	100.00 1	99.31 60	100.00 1	99.99 58	100.00 1	100.00 1

Regformer-3		99.73 29	99.65 34	99.96 46	100.00 1	99.89 68	100.00 1	99.44 109	98.40 63	100.00 1	100.00 1	99.03 97	99.97 118	99.99 58	100.00 1	100.00 1

Regformer-4		99.73 29	99.65 34	99.95 58	100.00 1	99.89 68	100.00 1	99.44 109	98.40 63	100.00 1	100.00 1	99.03 97	99.97 118	99.99 58	100.00 1	100.00 1

Regformer-1		99.75 21	99.68 25	99.98 22	100.00 1	99.94 37	100.00 1	99.44 109	98.43 60	100.00 1	100.00 1	99.23 74	99.99 89	99.99 58	100.00 1	100.00 1

Regformer-2		99.75 21	99.68 25	99.97 31	100.00 1	99.94 37	100.00 1	99.44 109	98.42 62	100.00 1	100.00 1	99.22 76	99.99 89	99.99 58	100.00 1	100.00 1

ACMMPR		99.74 26	99.67 30	99.96 46	100.00 1	99.89 68	100.00 1	99.76 45	97.95 101	100.00 1	100.00 1	99.29 67	100.00 1	99.99 58	100.00 1	100.00 1

MP-MVS		99.61 68	99.49 74	99.98 22	99.99 54	99.94 37	100.00 1	99.42 127	97.82 110	99.99 99	100.00 1	98.20 141	100.00 1	99.99 58	100.00 1	100.00 1
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
HPM-MVS		99.59 72	99.50 72	99.89 85	100.00 1	99.70 111	100.00 1	99.42 127	97.46 150	100.00 1	100.00 1	98.60 131	99.96 132	99.99 58	100.00 1	100.00 1
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CPTT-MVS		99.49 80	99.38 80	99.85 93	100.00 1	99.54 122	100.00 1	99.42 127	97.58 137	99.98 104	100.00 1	97.43 168	100.00 1	99.99 58	100.00 1	100.00 1

MVS_111021_LR		99.70 39	99.65 34	99.88 89	99.96 102	99.70 111	100.00 1	99.97 14	98.96 28	100.00 1	100.00 1	97.93 149	99.95 138	99.99 58	100.00 1	100.00 1

CSCG		99.28 102	99.35 86	99.05 174	99.99 54	97.15 260	100.00 1	99.47 77	97.44 153	99.42 183	100.00 1	97.83 152	100.00 1	99.99 58	100.00 1	100.00 1

test_yl		99.51 75	99.37 82	99.95 58	99.82 118	99.90 60	100.00 1	99.47 77	97.48 148	100.00 1	100.00 1	99.80 4	100.00 1	99.98 75	97.75 206	99.94 124

DCV-MVSNet		99.51 75	99.37 82	99.95 58	99.82 118	99.90 60	100.00 1	99.47 77	97.48 148	100.00 1	100.00 1	99.80 4	100.00 1	99.98 75	97.75 206	99.94 124

ACMMP_NAP		99.67 52	99.57 57	99.97 31	99.98 92	99.92 49	100.00 1	99.42 127	97.83 109	100.00 1	100.00 1	98.89 115	100.00 1	99.98 75	100.00 1	100.00 1

EI-MVSNet-UG-set		99.69 43	99.63 42	99.87 90	99.99 54	99.64 117	99.95 223	99.44 109	98.35 69	100.00 1	100.00 1	98.98 100	99.97 118	99.98 75	100.00 1	100.00 1

EI-MVSNet-Vis-set		99.70 39	99.64 38	99.87 90	100.00 1	99.64 117	99.98 208	99.44 109	98.35 69	99.99 99	100.00 1	99.04 93	99.96 132	99.98 75	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 56	99.55 64	99.97 31	99.99 54	99.91 52	100.00 1	99.48 76	97.54 141	100.00 1	100.00 1	98.97 102	99.99 89	99.98 75	100.00 1	100.00 1

HPM-MVS_fast		99.60 71	99.49 74	99.91 79	99.99 54	99.78 96	100.00 1	99.42 127	97.09 177	100.00 1	100.00 1	98.95 106	99.96 132	99.98 75	100.00 1	100.00 1

114514_t		99.39 87	99.25 92	99.81 100	99.97 96	99.48 131	100.00 1	99.42 127	95.53 247	100.00 1	100.00 1	98.37 139	99.95 138	99.97 82	100.00 1	100.00 1

CNLPA		99.72 32	99.65 34	99.91 79	99.97 96	99.72 106	100.00 1	99.47 77	98.43 60	99.88 149	100.00 1	99.14 85	100.00 1	99.97 82	100.00 1	100.00 1

GST-MVS		99.64 58	99.53 66	99.95 58	100.00 1	99.86 84	100.00 1	99.79 41	97.72 116	99.95 133	100.00 1	98.39 138	100.00 1	99.96 84	99.99 107	100.00 1

zzz-MVS		99.68 47	99.59 50	99.97 31	99.99 54	99.91 52	100.00 1	99.42 127	98.32 71	99.94 135	100.00 1	98.65 127	100.00 1	99.96 84	100.00 1	100.00 1

MTAPA		99.68 47	99.59 50	99.97 31	99.99 54	99.91 52	100.00 1	99.42 127	98.32 71	99.94 135	100.00 1	98.65 127	100.00 1	99.96 84	100.00 1	100.00 1

DP-MVS Recon		99.76 19	99.69 22	99.98 22	100.00 1	99.95 29	100.00 1	99.52 69	97.99 92	99.99 99	100.00 1	99.72 9	100.00 1	99.96 84	100.00 1	100.00 1

ACMMP		99.65 56	99.57 57	99.89 85	99.99 54	99.66 115	99.75 258	99.73 54	98.16 77	99.75 168	100.00 1	98.90 113	100.00 1	99.96 84	99.88 128	100.00 1
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
CLD-MVS		97.64 197	97.74 193	97.36 271	99.01 253	94.76 303	100.00 1	99.34 213	99.30 4	99.00 208	99.97 177	87.49 299	99.57 194	99.96 84	95.58 223	97.75 242
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
DeepC-MVS_fast	98.92 1	99.75 21	99.67 30	99.99 9	99.99 54	99.96 20	99.73 263	99.52 69	99.06 11	100.00 1	100.00 1	98.80 122	100.00 1	99.95 90	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 21	99.68 25	99.97 31	100.00 1	99.91 52	99.98 208	99.47 77	99.09 8	100.00 1	100.00 1	98.59 132	100.00 1	99.95 90	100.00 1	100.00 1

ZNCC-MVS		99.71 35	99.62 46	99.97 31	99.99 54	99.90 60	100.00 1	99.79 41	97.97 96	99.97 108	100.00 1	98.97 102	100.00 1	99.94 92	100.00 1	100.00 1

DELS-MVS		99.62 66	99.56 63	99.82 97	99.92 111	99.45 132	100.00 1	99.78 43	98.92 34	99.73 169	100.00 1	97.70 155	100.00 1	99.93 93	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
AdaColmap		99.44 84	99.26 91	99.95 58	100.00 1	99.86 84	99.70 268	99.99 10	98.53 57	99.90 144	100.00 1	95.34 209	100.00 1	99.92 94	100.00 1	100.00 1

F-COLMAP		99.64 58	99.64 38	99.67 119	99.99 54	99.07 163	100.00 1	99.44 109	98.30 73	99.90 144	100.00 1	99.18 81	99.99 89	99.91 95	100.00 1	99.94 124

VNet		99.04 120	98.75 140	99.90 82	99.81 122	99.75 101	99.50 292	99.47 77	98.36 68	100.00 1	99.99 166	94.66 220	100.00 1	99.90 96	97.09 215	99.96 116

EPNet		99.62 66	99.69 22	99.42 148	99.99 54	98.37 200	100.00 1	99.89 32	98.83 41	100.00 1	100.00 1	98.97 102	100.00 1	99.90 96	99.61 143	99.89 150
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
LFMVS		97.42 208	96.62 228	99.81 100	99.80 132	99.50 124	99.16 327	99.56 66	94.48 276	100.00 1	100.00 1	79.35 342	100.00 1	99.89 98	97.37 212	99.94 124

PS-MVSNAJ		99.64 58	99.57 57	99.85 93	99.78 137	99.81 93	99.95 223	99.42 127	98.38 66	100.00 1	100.00 1	98.75 124	100.00 1	99.88 99	99.99 107	99.74 198

3Dnovator+	95.58 15	99.03 121	98.71 144	99.96 46	98.99 260	99.89 68	100.00 1	99.51 73	98.96 28	98.32 251	100.00 1	92.78 243	100.00 1	99.87 100	100.00 1	100.00 1

WTY-MVS		99.54 73	99.40 77	99.95 58	99.81 122	99.93 42	100.00 1	100.00 1	97.98 94	99.84 152	100.00 1	98.94 108	99.98 113	99.86 101	98.21 185	99.94 124

HY-MVS	96.53 9	99.50 78	99.35 86	99.96 46	99.81 122	99.93 42	99.64 275	100.00 1	97.97 96	99.84 152	99.85 210	98.94 108	99.99 89	99.86 101	98.23 184	99.95 121

xiu_mvs_v2_base		99.51 75	99.41 76	99.82 97	99.70 148	99.73 105	99.92 229	99.40 176	98.15 79	100.00 1	100.00 1	98.50 135	100.00 1	99.85 103	99.13 149	99.74 198

VDDNet		96.39 256	95.55 276	98.90 185	99.27 235	97.45 247	99.15 329	99.92 30	91.28 323	99.98 104	100.00 1	73.55 350	100.00 1	99.85 103	96.98 218	99.24 217

MVS		99.22 111	98.96 118	99.98 22	99.00 257	99.95 29	99.24 312	99.94 18	98.14 80	98.88 214	100.00 1	95.63 207	100.00 1	99.85 103	100.00 1	100.00 1

Anonymous20240529		96.93 231	96.22 246	99.05 174	99.79 135	97.30 255	99.16 327	99.47 77	88.51 337	98.69 227	100.00 1	83.50 328	100.00 1	99.83 106	97.02 217	99.83 173

xiu_mvs_v1_base_debu		99.35 91	99.21 100	99.79 106	99.67 155	99.71 107	99.78 250	99.36 200	98.13 81	100.00 1	100.00 1	97.00 180	100.00 1	99.83 106	99.07 151	99.66 207

xiu_mvs_v1_base		99.35 91	99.21 100	99.79 106	99.67 155	99.71 107	99.78 250	99.36 200	98.13 81	100.00 1	100.00 1	97.00 180	100.00 1	99.83 106	99.07 151	99.66 207

xiu_mvs_v1_base_debi		99.35 91	99.21 100	99.79 106	99.67 155	99.71 107	99.78 250	99.36 200	98.13 81	100.00 1	100.00 1	97.00 180	100.00 1	99.83 106	99.07 151	99.66 207

alignmvs		99.38 88	99.21 100	99.91 79	99.73 145	99.92 49	100.00 1	99.51 73	97.61 131	100.00 1	100.00 1	99.06 89	99.93 151	99.83 106	97.12 214	99.90 144

abl_6		99.53 74	99.40 77	99.92 78	100.00 1	99.76 99	100.00 1	99.42 127	97.21 171	100.00 1	100.00 1	98.12 144	100.00 1	99.82 111	100.00 1	100.00 1

PGM-MVS		99.69 43	99.61 47	99.95 58	99.99 54	99.85 87	100.00 1	99.58 65	97.69 122	100.00 1	100.00 1	99.44 43	100.00 1	99.79 112	100.00 1	100.00 1

HQP_MVS		97.71 195	97.82 191	97.37 270	99.00 257	94.80 298	100.00 1	99.40 176	99.00 25	99.08 203	99.97 177	88.58 292	99.55 203	99.79 112	95.57 227	97.76 231

plane_prior5								99.40 176					99.55 203	99.79 112	95.57 227	97.76 231

BP-MVS														99.79 112

PVSNet_Blended_VisFu		99.33 96	99.18 106	99.78 110	99.82 118	99.49 127	100.00 1	99.95 15	97.36 158	99.63 174	100.00 1	96.45 195	99.95 138	99.79 112	99.65 140	99.89 150

HQP-MVS		97.73 193	97.85 189	97.39 269	99.07 245	94.82 295	100.00 1	99.40 176	99.04 14	99.17 194	99.97 177	88.61 290	99.57 194	99.79 112	95.58 223	97.77 229

canonicalmvs		99.03 121	98.73 141	99.94 73	99.75 144	99.95 29	100.00 1	99.30 225	97.64 127	100.00 1	100.00 1	95.22 212	99.97 118	99.76 118	96.90 220	99.91 135

XVG-OURS-SEG-HR		98.27 179	98.31 170	98.14 230	99.59 178	95.92 279	100.00 1	99.36 200	98.48 58	99.21 193	100.00 1	89.27 281	99.94 149	99.76 118	99.17 148	98.56 227

EIA-MVS		99.26 105	99.19 104	99.45 144	99.63 167	98.75 181	100.00 1	99.27 243	96.93 184	99.95 133	100.00 1	97.47 164	99.79 175	99.74 120	99.72 137	99.82 177

HyFIR lowres test		99.32 98	99.24 94	99.58 134	99.95 103	99.26 148	100.00 1	99.99 10	96.72 198	99.29 190	99.91 202	99.49 35	99.47 218	99.74 120	98.08 191	100.00 1

DeepC-MVS	97.84 5	99.00 127	98.80 136	99.60 128	99.93 108	99.03 167	100.00 1	99.40 176	98.61 55	99.33 188	100.00 1	92.23 249	99.95 138	99.74 120	99.96 120	99.83 173
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
hse-mvs3		97.03 226	96.53 230	98.51 205	99.79 135	95.90 281	99.45 294	99.45 99	98.21 74	100.00 1	99.78 225	97.49 162	99.99 89	99.72 123	74.92 346	99.65 210

hse-mvs2		96.79 234	96.38 238	98.04 246	99.68 152	95.54 285	99.81 245	99.42 127	98.21 74	100.00 1	99.80 222	97.49 162	99.46 222	99.72 123	73.27 349	99.12 220

GG-mvs-BLEND				99.59 130	99.54 190	99.49 127	99.17 326	99.52 69		99.96 112	99.68 241	100.00 1	99.33 232	99.71 125	99.99 107	99.96 116

3Dnovator	95.63 14	99.06 118	98.76 139	99.96 46	98.86 271	99.90 60	99.98 208	99.93 26	98.95 31	98.49 242	100.00 1	92.91 242	100.00 1	99.71 125	100.00 1	100.00 1

ET-MVSNet_ETH3D		96.41 252	95.48 281	99.20 169	99.81 122	99.75 101	100.00 1	99.02 322	97.30 167	78.33 354	100.00 1	97.73 153	97.94 325	99.70 127	87.41 325	99.92 133

ETV-MVS		99.34 94	99.24 94	99.64 123	99.58 183	99.33 142	100.00 1	99.25 249	97.57 139	99.96 112	100.00 1	97.44 167	99.79 175	99.70 127	99.65 140	99.81 181

Anonymous202405211		97.87 189	97.53 200	98.90 185	99.81 122	96.70 271	99.35 304	99.46 92	92.98 310	98.83 220	99.99 166	90.63 264	100.00 1	99.70 127	97.03 216	100.00 1

casdiffmvs		98.65 154	98.38 166	99.46 143	99.52 200	98.74 184	100.00 1	99.15 280	96.91 187	99.05 206	100.00 1	92.75 244	99.83 168	99.70 127	98.38 174	99.81 181

baseline		98.69 152	98.45 162	99.41 149	99.52 200	98.67 188	100.00 1	99.17 278	97.03 182	99.13 199	100.00 1	93.17 237	99.74 182	99.70 127	98.34 176	99.81 181

PMMVS		99.12 113	98.97 117	99.58 134	99.57 186	98.98 173	100.00 1	99.30 225	97.14 174	99.96 112	100.00 1	96.53 194	99.82 171	99.70 127	98.49 165	99.94 124

ACMP	97.00 8	97.19 216	97.16 216	97.27 278	98.97 262	94.58 310	100.00 1	99.32 217	97.97 96	97.45 290	99.98 169	85.79 315	99.56 198	99.70 127	95.24 238	97.67 297
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
gg-mvs-nofinetune		96.95 230	96.10 250	99.50 141	99.41 220	99.36 141	99.07 338	99.52 69	83.69 348	99.96 112	83.60 361	100.00 1	99.20 236	99.68 134	99.99 107	99.96 116

cascas		98.43 168	98.07 182	99.50 141	99.65 160	99.02 168	100.00 1	99.22 260	94.21 283	99.72 170	99.98 169	92.03 252	99.93 151	99.68 134	98.12 189	99.54 212

CS-MVS		99.33 96	99.23 97	99.65 122	99.63 167	99.18 158	100.00 1	99.27 243	97.45 151	99.96 112	100.00 1	97.22 170	99.87 160	99.67 136	99.86 131	99.90 144

旧先验2							100.00 1		98.11 85	100.00 1			100.00 1	99.67 136

lupinMVS		99.29 101	99.16 107	99.69 117	99.45 216	99.49 127	100.00 1	99.15 280	97.45 151	99.97 108	100.00 1	96.76 187	99.76 179	99.67 136	100.00 1	99.81 181

diffmvs		98.96 133	98.73 141	99.63 124	99.54 190	99.16 159	100.00 1	99.18 273	97.33 162	99.96 112	100.00 1	94.60 221	99.91 155	99.66 139	98.33 180	99.82 177

CHOSEN 1792x2688		99.00 127	98.91 126	99.25 165	99.90 114	97.79 238	100.00 1	99.99 10	98.79 46	98.28 254	100.00 1	93.63 231	99.95 138	99.66 139	99.95 122	100.00 1

ab-mvs		98.42 169	98.02 185	99.61 126	99.71 146	99.00 172	99.10 334	99.64 63	96.70 200	99.04 207	99.81 219	90.64 263	99.98 113	99.64 141	97.93 195	99.84 170

OpenMVS	95.20 17	98.76 147	98.41 163	99.78 110	98.89 267	99.81 93	99.99 190	99.76 45	98.02 90	98.02 268	100.00 1	91.44 255	100.00 1	99.63 142	99.97 118	99.55 211

thres200		99.27 103	99.04 110	99.96 46	99.81 122	99.90 60	100.00 1	99.94 18	97.31 165	99.83 154	99.96 186	97.04 173	100.00 1	99.62 143	97.88 197	99.98 108

thres100view900		99.25 108	99.01 113	99.95 58	99.81 122	99.87 81	100.00 1	99.94 18	97.13 175	99.83 154	99.96 186	97.01 177	100.00 1	99.59 144	97.85 199	99.98 108

tfpn200view9		99.26 105	99.03 111	99.96 46	99.81 122	99.89 68	100.00 1	99.94 18	97.23 168	99.83 154	99.96 186	97.04 173	100.00 1	99.59 144	97.85 199	99.98 108

thres400		99.26 105	99.03 111	99.95 58	99.81 122	99.89 68	100.00 1	99.94 18	97.23 168	99.83 154	99.96 186	97.04 173	100.00 1	99.59 144	97.85 199	99.97 113

LCM-MVSNet-Re		96.52 246	97.21 214	94.44 318	99.27 235	85.80 348	99.85 240	96.61 357	95.98 231	92.75 339	98.48 325	93.97 228	97.55 330	99.58 147	98.43 169	99.98 108

jason		99.11 114	98.96 118	99.59 130	99.17 239	99.31 144	100.00 1	99.13 289	97.38 157	99.83 154	100.00 1	95.54 208	99.72 185	99.57 148	99.97 118	99.74 198
jason: jason.
LPG-MVS_test		97.31 212	97.32 208	97.28 276	98.85 272	94.60 307	100.00 1	99.37 194	97.35 159	98.85 216	99.98 169	86.66 306	99.56 198	99.55 149	95.26 235	97.70 286

LGP-MVS_train				97.28 276	98.85 272	94.60 307		99.37 194	97.35 159	98.85 216	99.98 169	86.66 306	99.56 198	99.55 149	95.26 235	97.70 286

PVSNet	94.91 18	99.30 100	99.25 92	99.44 145	100.00 1	98.32 206	100.00 1	99.86 34	98.04 89	100.00 1	100.00 1	96.10 199	100.00 1	99.55 149	99.73 136	100.00 1

thres600view7		99.24 110	99.00 114	99.95 58	99.81 122	99.87 81	100.00 1	99.94 18	97.13 175	99.83 154	99.96 186	97.01 177	100.00 1	99.54 152	97.77 205	99.97 113

BH-w/o		98.82 145	98.81 135	98.88 187	99.62 171	96.71 270	100.00 1	99.28 235	97.09 177	98.81 221	100.00 1	94.91 217	99.96 132	99.54 152	100.00 1	99.96 116

sss		99.45 83	99.34 88	99.80 104	99.76 142	99.50 124	100.00 1	99.91 31	97.72 116	99.98 104	99.94 197	98.45 136	100.00 1	99.53 154	98.75 158	99.89 150

EPP-MVSNet		99.10 115	99.00 114	99.40 151	99.51 205	98.68 187	99.92 229	99.43 119	95.47 253	99.65 173	100.00 1	99.51 28	99.76 179	99.53 154	98.00 192	99.75 197

原ACMM1				99.93 76	100.00 1	99.80 95		99.66 62	98.18 76	100.00 1	100.00 1	99.43 47	100.00 1	99.50 156	100.00 1	100.00 1

OMC-MVS		99.27 103	99.38 80	98.96 182	99.95 103	97.06 264	100.00 1	99.40 176	98.83 41	99.88 149	100.00 1	97.01 177	99.86 161	99.47 157	99.84 132	99.97 113

Effi-MVS+		98.58 158	98.24 173	99.61 126	99.60 175	99.26 148	97.85 351	99.10 297	96.22 227	99.97 108	99.89 204	93.75 229	99.77 178	99.43 158	98.34 176	99.81 181

IB-MVS	96.24 12	97.54 204	96.95 217	99.33 158	99.67 155	98.10 218	100.00 1	99.47 77	97.42 155	99.26 191	99.69 237	98.83 119	99.89 156	99.43 158	78.77 344	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
CostFormer		98.84 143	98.77 138	99.04 176	99.41 220	97.58 244	99.67 273	99.35 208	94.66 268	99.96 112	99.36 281	99.28 69	99.74 182	99.41 160	97.81 203	99.81 181

BH-untuned		98.64 155	98.65 147	98.60 200	99.59 178	96.17 276	100.00 1	99.28 235	96.67 204	98.41 246	100.00 1	94.52 222	99.83 168	99.41 160	100.00 1	99.81 181

Effi-MVS+-dtu		98.51 165	98.86 131	97.47 268	99.77 140	94.21 314	100.00 1	98.94 327	97.61 131	99.91 143	98.75 317	95.89 200	99.51 214	99.36 162	99.48 146	98.68 224

mvs-test1		98.89 141	98.99 116	98.60 200	99.77 140	95.96 277	100.00 1	98.94 327	97.61 131	99.93 140	99.92 201	95.89 200	99.93 151	99.36 162	99.50 145	99.90 144

XVG-OURS		98.30 175	98.36 169	98.13 233	99.58 183	95.91 280	100.00 1	99.36 200	98.69 49	99.23 192	100.00 1	91.20 257	99.92 154	99.34 164	97.82 202	98.56 227

无先验							100.00 1	99.80 39	97.98 94				100.00 1	99.33 165		100.00 1

1121		99.63 62	99.51 70	99.99 9	99.99 54	99.96 20	99.24 312	99.74 52	97.89 104	100.00 1	100.00 1	99.39 53	100.00 1	99.33 165	100.00 1	100.00 1

QAPM		98.99 129	98.66 146	99.96 46	99.01 253	99.87 81	99.88 238	99.93 26	97.99 92	98.68 228	100.00 1	93.17 237	100.00 1	99.32 167	100.00 1	100.00 1

UGNet		98.41 170	98.11 179	99.31 160	99.54 190	98.55 192	99.18 321	100.00 1	98.64 54	99.79 163	99.04 297	87.61 298	100.00 1	99.30 168	99.89 127	99.40 216
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
testdata				99.66 121	99.99 54	98.97 175		99.73 54	97.96 100	100.00 1	100.00 1	99.42 49	100.00 1	99.28 169	100.00 1	100.00 1

ACMM	97.17 6	97.37 210	97.40 204	97.29 275	99.01 253	94.64 306	100.00 1	99.25 249	98.07 87	98.44 245	99.98 169	87.38 300	99.55 203	99.25 170	95.19 240	97.69 290
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
nrg030		97.64 197	97.27 212	98.75 194	98.34 287	99.53 123	100.00 1	99.22 260	96.21 228	98.27 256	99.95 193	94.40 223	98.98 248	99.23 171	89.78 307	97.75 242

VPA-MVSNet		97.03 226	96.43 236	98.82 190	98.64 277	99.32 143	99.38 301	99.47 77	96.73 197	98.91 213	98.94 308	87.00 304	99.40 227	99.23 171	89.59 308	97.76 231

VPNet		96.41 252	95.76 266	98.33 216	98.61 278	98.30 207	99.48 293	99.45 99	96.98 183	98.87 215	99.88 205	81.57 335	98.93 252	99.22 173	87.82 323	97.76 231

LS3D		99.31 99	99.13 108	99.87 90	99.99 54	99.71 107	99.55 286	99.46 92	97.32 163	99.82 161	100.00 1	96.85 186	99.97 118	99.14 174	100.00 1	99.92 133

mvs_anonymous		98.80 146	98.60 153	99.38 154	99.57 186	99.24 152	100.00 1	99.21 265	95.87 233	98.92 211	99.82 216	96.39 196	99.03 242	99.13 175	98.50 164	99.88 161

DP-MVS		98.86 142	98.54 157	99.81 100	99.97 96	99.45 132	99.52 290	99.40 176	94.35 280	98.36 247	100.00 1	96.13 198	99.97 118	99.12 176	100.00 1	100.00 1

DWT-MVSNet_test		99.22 111	99.22 99	99.22 168	99.56 189	97.98 225	99.89 235	99.39 189	97.20 172	99.96 112	100.00 1	99.52 26	99.82 171	99.11 177	98.34 176	99.87 167

thisisatest0515		99.42 85	99.31 89	99.74 113	99.59 178	99.55 121	100.00 1	99.46 92	96.65 205	99.92 141	100.00 1	99.44 43	99.85 165	99.09 178	99.63 142	99.81 181

ACMH	96.25 11	96.77 235	96.62 228	97.21 279	98.96 263	94.43 312	99.64 275	99.33 215	97.43 154	96.55 312	99.97 177	83.52 327	99.54 206	99.07 179	95.13 244	97.66 298
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Vis-MVSNet		98.52 164	98.25 172	99.34 157	99.68 152	98.55 192	99.68 272	99.41 174	97.34 161	99.94 135	100.00 1	90.38 269	99.70 187	99.03 180	98.84 156	99.76 196
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
thisisatest0530		99.37 90	99.27 90	99.69 117	99.59 178	99.41 135	100.00 1	99.46 92	96.46 215	99.90 144	100.00 1	99.44 43	99.85 165	98.97 181	99.58 144	99.80 191

tpmrst		98.98 132	98.93 124	99.14 171	99.61 173	97.74 239	99.52 290	99.36 200	96.05 230	99.98 104	99.64 250	99.04 93	99.86 161	98.94 182	98.19 187	99.82 177

tttt0517		99.34 94	99.23 97	99.67 119	99.57 186	99.38 137	100.00 1	99.46 92	96.33 223	99.89 147	100.00 1	99.44 43	99.84 167	98.93 183	99.46 147	99.78 193

MDTV_nov1_ep13_2view						99.24 152	99.56 285		96.31 224	99.96 112		98.86 116		98.92 184		99.89 150

RRT_test8_iter05		98.32 174	98.23 175	98.60 200	99.65 160	99.23 155	100.00 1	99.09 303	95.65 241	98.07 264	99.93 200	99.25 72	98.82 263	98.90 185	93.50 263	97.75 242

COLMAP_ROB	97.10 7	98.29 177	98.17 178	98.65 198	99.94 106	97.39 249	99.30 308	99.40 176	95.64 242	97.75 279	100.00 1	92.69 246	99.95 138	98.89 186	99.92 125	98.62 226
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TR-MVS		98.14 182	97.74 193	99.33 158	99.59 178	98.28 208	99.27 309	99.21 265	96.42 217	99.15 198	99.94 197	88.87 287	99.79 175	98.88 187	98.29 181	99.93 131

mvs_tets		97.00 228	96.69 225	97.94 253	97.41 329	97.27 256	99.60 282	99.18 273	96.51 214	97.35 292	99.69 237	86.53 308	98.91 254	98.84 188	95.09 246	97.65 303

testmvs		80.17 322	81.95 325	74.80 341	58.54 366	59.58 365	100.00 1	87.14 366	76.09 352	99.61 176	100.00 1	67.06 357	74.19 363	98.84 188	50.30 357	90.64 353

BH-RMVSNet		98.46 167	98.08 181	99.59 130	99.61 173	99.19 157	100.00 1	99.28 235	97.06 181	98.95 210	100.00 1	88.99 284	99.82 171	98.83 190	100.00 1	99.77 194

FIs		97.95 188	97.73 195	98.62 199	98.53 282	99.24 152	100.00 1	99.43 119	96.74 195	97.87 274	99.82 216	95.27 211	98.89 257	98.78 191	93.07 268	97.74 265

EPMVS		99.25 108	99.13 108	99.60 128	99.60 175	99.20 156	99.60 282	100.00 1	96.93 184	99.92 141	99.36 281	99.05 90	99.71 186	98.77 192	98.94 155	99.90 144

gm-plane-assit					99.52 200	97.26 257			95.86 235		100.00 1		99.43 224	98.76 193

baseline2		98.99 129	98.93 124	99.18 170	99.26 237	99.15 160	100.00 1	99.46 92	96.71 199	96.79 307	100.00 1	99.42 49	99.25 235	98.75 194	99.94 123	99.15 219

cl-mvsnet2		98.23 181	98.11 179	98.58 204	99.82 118	99.01 170	100.00 1	99.28 235	96.92 186	98.33 250	99.21 287	98.09 147	98.97 250	98.72 195	92.61 273	97.76 231

jajsoiax		97.07 223	96.79 223	97.89 257	97.28 330	97.12 261	99.95 223	99.19 268	96.55 210	97.31 293	99.69 237	87.35 302	98.91 254	98.70 196	95.12 245	97.66 298

Test_1112_low_res		98.83 144	98.60 153	99.51 139	99.69 149	98.75 181	99.99 190	99.14 285	96.81 191	98.84 218	99.06 294	97.45 165	99.89 156	98.66 197	97.75 206	99.89 150

1112_ss		98.91 138	98.71 144	99.51 139	99.69 149	98.75 181	99.99 190	99.15 280	96.82 190	98.84 218	100.00 1	97.45 165	99.89 156	98.66 197	97.75 206	99.89 150

MVS_Test		98.93 137	98.65 147	99.77 112	99.62 171	99.50 124	99.99 190	99.19 268	95.52 249	99.96 112	99.86 208	96.54 193	99.98 113	98.65 199	98.48 166	99.82 177

FC-MVSNet-test		97.84 190	97.63 198	98.45 208	98.30 291	99.05 165	100.00 1	99.43 119	96.63 208	97.61 285	99.82 216	95.19 213	98.57 287	98.64 200	93.05 269	97.73 272

MVSFormer		98.94 136	98.82 133	99.28 162	99.45 216	99.49 127	100.00 1	99.13 289	95.46 254	99.97 108	100.00 1	96.76 187	98.59 284	98.63 201	100.00 1	99.74 198

test_djsdf		97.55 203	97.38 205	98.07 236	97.50 322	97.99 224	100.00 1	99.13 289	95.46 254	98.47 243	99.85 210	92.01 253	98.59 284	98.63 201	95.36 231	97.62 309

tpm2		98.64 155	98.58 155	98.81 192	99.42 219	97.12 261	99.69 270	99.37 194	93.63 296	99.94 135	99.67 242	98.96 105	99.47 218	98.62 203	97.95 194	99.83 173

baseline1		98.91 138	98.61 151	99.81 100	99.71 146	99.77 97	99.78 250	99.44 109	97.51 146	98.81 221	99.99 166	98.25 140	99.76 179	98.60 204	95.41 229	99.89 150

MVSTER		98.58 158	98.52 158	98.77 193	99.65 160	99.68 113	100.00 1	99.29 230	95.63 243	98.65 229	99.80 222	99.78 6	98.88 260	98.59 205	95.31 233	97.73 272

D2MVS		97.63 200	97.83 190	97.05 282	98.83 274	94.60 307	100.00 1	99.82 36	96.89 189	98.28 254	99.03 299	94.05 225	99.47 218	98.58 206	94.97 249	97.09 331

PS-MVSNAJss		98.03 185	98.06 183	97.94 253	97.63 314	97.33 254	99.89 235	99.23 258	96.27 225	98.03 266	99.59 262	98.75 124	98.78 267	98.52 207	94.61 254	97.70 286

WR-MVS		97.09 221	96.64 226	98.46 207	98.43 284	99.09 162	99.97 214	99.33 215	95.62 244	97.76 276	99.67 242	91.17 258	98.56 289	98.49 208	89.28 312	97.74 265

IS-MVSNet		99.08 116	98.91 126	99.59 130	99.65 160	99.38 137	99.78 250	99.24 254	96.70 200	99.51 178	100.00 1	98.44 137	99.52 212	98.47 209	98.39 173	99.88 161

RRT_MVS		98.48 166	98.41 163	98.70 196	99.64 165	99.67 114	100.00 1	99.10 297	96.26 226	98.75 224	99.96 186	99.04 93	98.75 272	98.42 210	94.51 256	97.68 292

XVG-ACMP-BASELINE		96.60 244	96.52 232	96.84 294	98.41 285	93.29 322	99.99 190	99.32 217	97.76 115	98.51 240	99.29 284	81.95 334	99.54 206	98.40 211	95.03 247	97.68 292

XXY-MVS		97.14 220	96.63 227	98.67 197	98.65 276	98.92 176	99.54 288	99.29 230	95.57 246	97.63 282	99.83 213	87.79 297	99.35 231	98.39 212	92.95 270	97.75 242

Vis-MVSNet (Re-imp)		98.99 129	98.89 130	99.29 161	99.64 165	98.89 177	99.98 208	99.31 222	96.74 195	99.48 180	100.00 1	98.11 145	99.10 239	98.39 212	98.34 176	99.89 150

UA-Net		99.06 118	98.83 132	99.74 113	99.52 200	99.40 136	99.08 336	99.45 99	97.64 127	99.83 154	100.00 1	95.80 203	99.94 149	98.35 214	99.80 135	99.88 161

ACMH+	96.20 13	96.49 250	96.33 243	97.00 285	99.06 249	93.80 317	99.81 245	99.31 222	97.32 163	95.89 321	99.97 177	82.62 332	99.54 206	98.34 215	94.63 253	97.65 303

test_post1							99.32 306				88.24 357	99.33 55	99.59 191	98.31 216

SCA		98.30 175	97.98 187	99.23 166	99.41 220	98.25 210	99.99 190	99.45 99	96.91 187	99.76 167	99.58 263	89.65 276	99.54 206	98.31 216	98.79 157	99.91 135

MDTV_nov1_ep13			98.94 123		99.53 193	98.36 202	99.39 300	99.46 92	96.54 211	99.99 99	99.63 254	98.92 111	99.86 161	98.30 218	98.71 159

OPM-MVS		97.21 215	97.18 215	97.32 274	98.08 301	94.66 304	100.00 1	99.28 235	98.65 53	98.92 211	99.98 169	86.03 313	99.56 198	98.28 219	95.41 229	97.72 278

Anonymous20231211		96.29 261	95.70 269	98.07 236	99.80 132	97.49 246	99.15 329	99.40 176	89.11 334	97.75 279	99.45 277	88.93 286	98.98 248	98.26 220	89.47 310	97.73 272

CVMVSNet		98.56 160	98.47 161	98.82 190	99.11 241	97.67 241	99.74 259	99.47 77	97.57 139	99.06 205	100.00 1	95.72 205	98.97 250	98.21 221	97.33 213	99.83 173

bset_n11_16_dypcd		97.66 196	97.54 199	98.04 246	96.88 333	98.04 222	100.00 1	99.25 249	95.72 239	98.47 243	99.73 228	96.23 197	98.34 301	98.18 222	93.37 266	97.74 265

PCF-MVS	98.23 3	98.69 152	98.37 168	99.62 125	99.78 137	99.02 168	99.23 318	99.06 316	96.43 216	98.08 263	100.00 1	94.72 219	99.95 138	98.16 223	99.91 126	99.90 144
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
RPSCF		97.37 210	98.24 173	94.76 317	99.80 132	84.57 350	99.99 190	99.05 318	94.95 261	99.82 161	100.00 1	94.03 226	100.00 1	98.15 224	98.38 174	99.70 203

CANet_DTU		99.02 125	98.90 129	99.41 149	99.88 116	98.71 185	100.00 1	99.29 230	98.84 40	100.00 1	100.00 1	94.02 227	100.00 1	98.08 225	99.96 120	99.52 213

CDS-MVSNet		98.96 133	98.95 122	99.01 178	99.48 211	98.36 202	99.93 228	99.37 194	96.79 192	99.31 189	99.83 213	99.77 7	98.91 254	98.07 226	97.98 193	99.77 194
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
CP-MVSNet		96.73 237	96.25 245	98.18 226	98.21 296	98.67 188	99.77 255	99.32 217	95.06 259	97.20 296	99.65 246	90.10 270	98.19 306	98.06 227	88.90 315	97.66 298

miper_enhance_ethall		98.33 173	98.27 171	98.51 205	99.66 159	99.04 166	100.00 1	99.22 260	97.53 143	98.51 240	99.38 280	99.49 35	98.75 272	98.02 228	92.61 273	97.76 231

test_part1		96.98 229	96.36 240	98.85 189	99.78 137	99.77 97	99.63 277	99.30 225	92.74 315	97.05 298	99.52 271	93.10 240	99.02 243	98.02 228	88.10 320	97.76 231

anonymousdsp		97.16 218	96.88 219	98.00 249	97.08 332	98.06 220	99.81 245	99.15 280	94.58 270	97.84 275	99.62 258	90.49 266	98.60 282	97.98 230	95.32 232	97.33 327

UniMVSNet_NR-MVSNet		97.16 218	96.80 221	98.22 223	98.38 286	98.41 195	100.00 1	99.45 99	96.14 229	97.76 276	99.64 250	95.05 214	98.50 292	97.98 230	86.84 328	97.75 242

DU-MVS		96.93 231	96.49 233	98.22 223	98.31 289	98.41 195	100.00 1	99.37 194	96.41 218	97.76 276	99.65 246	92.14 250	98.50 292	97.98 230	86.84 328	97.75 242

TAMVS		98.76 147	98.73 141	98.86 188	99.44 218	97.69 240	99.57 284	99.34 213	96.57 209	99.12 200	99.81 219	98.83 119	99.16 237	97.97 233	97.91 196	99.73 202

新几何1				99.99 9	100.00 1	99.96 20		99.81 38	97.89 104	100.00 1	100.00 1	99.20 79	100.00 1	97.91 234	100.00 1	100.00 1

UniMVSNet_ETH3D		95.28 288	94.41 293	97.89 257	98.91 265	95.14 289	99.13 331	99.35 208	92.11 318	97.17 297	99.66 244	70.28 354	99.36 229	97.88 235	95.18 241	99.16 218

PatchMatch-RL		99.02 125	98.78 137	99.74 113	99.99 54	99.29 145	100.00 1	100.00 1	98.38 66	99.89 147	99.81 219	93.14 239	99.99 89	97.85 236	99.98 115	99.95 121

TDRefinement		91.93 309	90.48 316	96.27 304	81.60 359	92.65 328	99.10 334	97.61 352	93.96 289	93.77 335	99.85 210	80.03 339	99.53 211	97.82 237	70.59 350	96.63 339

PS-CasMVS		96.34 259	95.78 265	98.03 248	98.18 298	98.27 209	99.71 266	99.32 217	94.75 264	96.82 306	99.65 246	86.98 305	98.15 308	97.74 238	88.85 316	97.66 298

Fast-Effi-MVS+-dtu		98.38 172	98.56 156	97.82 259	99.58 183	94.44 311	100.00 1	99.16 279	96.75 194	99.51 178	99.63 254	95.03 215	99.60 189	97.71 239	99.67 139	99.42 215

tpmvs		98.59 157	98.38 166	99.23 166	99.69 149	97.90 230	99.31 307	99.47 77	94.52 273	99.68 172	99.28 285	97.64 157	99.89 156	97.71 239	98.17 188	99.89 150

DPM-MVS		99.63 62	99.51 70	100.00 1	99.90 114	100.00 1	100.00 1	99.43 119	99.00 25	100.00 1	100.00 1	99.58 18	100.00 1	97.64 241	100.00 1	100.00 1

PatchmatchNet		99.03 121	98.96 118	99.26 164	99.49 209	98.33 204	99.38 301	99.45 99	96.64 206	99.96 112	99.58 263	99.49 35	99.50 215	97.63 242	99.00 154	99.93 131
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
EI-MVSNet		97.98 187	97.93 188	98.16 229	99.11 241	97.84 235	99.74 259	99.29 230	94.39 279	98.65 229	100.00 1	97.21 171	98.88 260	97.62 243	95.31 233	97.75 242

UniMVSNet (Re)		97.29 214	96.85 220	98.59 203	98.49 283	99.13 161	100.00 1	99.42 127	96.52 213	98.24 260	98.90 311	94.93 216	98.89 257	97.54 244	87.61 324	97.75 242

IterMVS-LS		97.56 202	97.44 201	97.92 256	99.38 229	97.90 230	99.89 235	99.10 297	94.41 278	98.32 251	99.54 270	97.21 171	98.11 313	97.50 245	91.62 288	97.75 242
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
AUN-MVS		96.26 263	95.67 273	98.06 240	99.68 152	95.60 284	99.82 244	99.42 127	96.78 193	99.88 149	99.80 222	94.84 218	99.47 218	97.48 246	73.29 348	99.12 220

Fast-Effi-MVS+		98.40 171	98.02 185	99.55 138	99.63 167	99.06 164	100.00 1	99.15 280	95.07 258	99.42 183	99.95 193	93.26 236	99.73 184	97.44 247	98.24 183	99.87 167

WR-MVS_H		96.73 237	96.32 244	97.95 252	98.26 293	97.88 232	99.72 265	99.43 119	95.06 259	96.99 300	98.68 319	93.02 241	98.53 290	97.43 248	88.33 319	97.43 322

tpm		98.24 180	98.22 177	98.32 217	99.13 240	95.79 282	99.53 289	99.12 294	95.20 257	99.96 112	99.36 281	97.58 158	99.28 234	97.41 249	96.67 221	99.88 161

LF4IMVS		96.19 265	96.18 247	96.23 305	98.26 293	92.09 331	100.00 1	97.89 349	97.82 110	97.94 271	99.87 206	82.71 331	99.38 228	97.41 249	93.71 259	97.20 329

testdata2													100.00 1	97.36 251

miper_ehance_all_eth		97.81 192	97.66 197	98.23 222	99.49 209	98.37 200	99.99 190	99.11 295	94.78 263	98.25 258	99.21 287	98.18 142	98.57 287	97.35 252	92.61 273	97.76 231

cl_fuxian		97.58 201	97.42 202	98.06 240	99.48 211	98.16 213	99.96 218	99.10 297	94.54 272	98.13 262	99.20 289	97.87 150	98.25 305	97.28 253	91.20 295	97.75 242

LTVRE_ROB	95.29 16	96.32 260	96.10 250	96.99 286	98.55 280	93.88 316	99.45 294	99.28 235	94.50 275	96.46 313	99.52 271	84.86 318	99.48 217	97.26 254	95.03 247	97.59 313
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
Baseline_NR-MVSNet		96.16 269	95.70 269	97.56 267	98.28 292	96.79 269	100.00 1	97.86 350	91.93 320	97.63 282	99.47 276	92.14 250	98.35 300	97.13 255	86.83 330	97.54 316

ADS-MVSNet2		98.28 178	98.51 159	97.62 264	99.51 205	95.03 291	99.24 312	99.41 174	95.52 249	99.96 112	99.70 235	97.57 159	97.94 325	97.11 256	98.54 162	99.88 161

ADS-MVSNet		98.70 151	98.51 159	99.28 162	99.51 205	98.39 197	99.24 312	99.44 109	95.52 249	99.96 112	99.70 235	97.57 159	99.58 193	97.11 256	98.54 162	99.88 161

JIA-IIPM		97.09 221	96.34 242	99.36 155	98.88 268	98.59 191	99.81 245	99.43 119	84.81 346	99.96 112	90.34 354	98.55 134	99.52 212	97.00 258	98.28 182	99.98 108

AllTest		98.55 161	98.40 165	98.99 179	99.93 108	97.35 251	100.00 1	99.40 176	97.08 179	99.09 201	99.98 169	93.37 233	99.95 138	96.94 259	99.84 132	99.68 205

TestCases				98.99 179	99.93 108	97.35 251		99.40 176	97.08 179	99.09 201	99.98 169	93.37 233	99.95 138	96.94 259	99.84 132	99.68 205

PEN-MVS		96.01 276	95.48 281	97.58 266	97.74 311	97.26 257	99.90 232	99.29 230	94.55 271	96.79 307	99.55 268	87.38 300	97.84 327	96.92 261	87.24 326	97.65 303

TranMVSNet+NR-MVSNet		96.45 251	96.01 254	97.79 260	98.00 304	97.62 243	100.00 1	99.35 208	95.98 231	97.31 293	99.64 250	90.09 271	98.00 323	96.89 262	86.80 331	97.75 242

TESTMET0.1,1		99.08 116	98.96 118	99.44 145	99.63 167	99.38 137	100.00 1	99.45 99	95.53 247	99.48 180	100.00 1	99.71 10	99.02 243	96.84 263	99.99 107	99.91 135

test-LLR		99.03 121	98.91 126	99.40 151	99.40 225	99.28 146	100.00 1	99.45 99	96.70 200	99.42 183	99.12 290	99.31 60	99.01 245	96.82 264	99.99 107	99.91 135

test-mter		98.96 133	98.82 133	99.40 151	99.40 225	99.28 146	100.00 1	99.45 99	95.44 256	99.42 183	99.12 290	99.70 11	99.01 245	96.82 264	99.99 107	99.91 135

MSDG		98.90 140	98.63 149	99.70 116	99.92 111	99.25 150	100.00 1	99.37 194	95.71 240	99.40 187	100.00 1	96.58 190	99.95 138	96.80 266	99.94 123	99.91 135

eth_miper_zixun_eth		97.47 207	97.28 210	98.06 240	99.41 220	97.94 228	99.62 280	99.08 305	94.46 277	98.19 261	99.56 267	96.91 185	98.50 292	96.78 267	91.49 290	97.74 265

NR-MVSNet		96.63 242	96.04 253	98.38 212	98.31 289	98.98 173	99.22 320	99.35 208	95.87 233	94.43 333	99.65 246	92.73 245	98.40 298	96.78 267	88.05 321	97.75 242

dp		98.72 149	98.61 151	99.03 177	99.53 193	97.39 249	99.45 294	99.39 189	95.62 244	99.94 135	99.52 271	98.83 119	99.82 171	96.77 269	98.42 170	99.89 150

tpm cat1		98.05 184	97.76 192	98.92 184	99.50 208	97.10 263	99.77 255	99.30 225	90.20 331	99.72 170	98.71 318	97.71 154	99.86 161	96.75 270	98.20 186	99.81 181

cl-mvsnet_		97.54 204	97.32 208	98.18 226	99.47 214	98.14 215	100.00 1	99.10 297	94.16 286	97.60 286	99.63 254	97.52 161	98.65 278	96.47 271	91.97 285	97.76 231

cl-mvsnet1		97.52 206	97.35 207	98.05 244	99.46 215	98.11 216	100.00 1	99.10 297	94.21 283	97.62 284	99.63 254	97.65 156	98.29 303	96.47 271	91.98 284	97.76 231

tmp_tt		75.80 327	74.26 330	80.43 338	52.91 368	53.67 366	87.42 358	97.98 347	61.80 357	67.04 360	100.00 1	76.43 348	96.40 338	96.47 271	28.26 361	91.23 352

miper_lstm_enhance		97.40 209	97.28 210	97.75 261	99.48 211	97.52 245	100.00 1	99.07 309	94.08 287	98.01 269	99.61 260	97.38 169	97.98 324	96.44 274	91.47 292	97.76 231

v148		96.29 261	95.84 261	97.63 262	97.74 311	96.53 274	100.00 1	99.07 309	93.52 298	98.01 269	99.42 279	91.22 256	98.60 282	96.37 275	87.22 327	97.75 242

DeepMVS_CX				89.98 331	98.90 266	71.46 356		99.18 273	97.61 131	96.92 301	99.83 213	86.07 311	99.83 168	96.02 276	97.65 210	98.65 225

pmmvs5		95.94 278	95.61 274	96.95 288	97.42 327	94.66 304	100.00 1	98.08 343	93.60 297	97.05 298	99.43 278	87.02 303	98.46 296	95.76 277	92.12 281	97.72 278

IterMVS		96.76 236	96.46 235	97.63 262	99.41 220	96.89 266	99.99 190	99.13 289	94.74 266	97.59 287	99.66 244	89.63 278	98.28 304	95.71 278	92.31 279	97.72 278
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v2v482		96.70 240	96.18 247	98.27 219	98.04 302	98.39 197	100.00 1	99.13 289	94.19 285	98.58 234	99.08 293	90.48 267	98.67 276	95.69 279	90.44 303	97.75 242

pmmvs4		97.17 217	96.80 221	98.27 219	97.68 313	98.64 190	100.00 1	99.18 273	94.22 282	98.55 235	99.71 232	93.67 230	98.47 295	95.66 280	92.57 276	97.71 285

ITE_SJBPF				96.84 294	98.96 263	93.49 319		98.12 341	98.12 84	98.35 248	99.97 177	84.45 319	99.56 198	95.63 281	95.25 237	97.49 319

IterMVS-SCA-FT		96.72 239	96.42 237	97.62 264	99.40 225	96.83 268	99.99 190	99.14 285	94.65 269	97.55 288	99.72 230	89.65 276	98.31 302	95.62 282	92.05 282	97.73 272

pm-mvs1		95.76 281	95.01 289	98.00 249	98.23 295	97.45 247	99.24 312	99.04 321	93.13 309	95.93 320	99.72 230	86.28 309	98.84 262	95.62 282	87.92 322	97.72 278

V42		96.65 241	96.16 249	98.11 235	98.17 299	98.23 211	99.99 190	99.09 303	93.97 288	98.74 226	99.05 296	91.09 259	98.82 263	95.46 284	89.90 305	97.27 328

EU-MVSNet		96.63 242	96.53 230	96.94 289	97.59 318	96.87 267	99.76 257	99.47 77	96.35 221	96.85 305	99.78 225	92.57 247	96.27 341	95.33 285	91.08 296	97.68 292

GBi-Net		96.07 273	95.80 263	96.89 291	99.53 193	94.87 292	99.18 321	99.27 243	93.71 291	98.53 237	98.81 314	84.23 322	98.07 318	95.31 286	93.60 260	97.72 278

test1		96.07 273	95.80 263	96.89 291	99.53 193	94.87 292	99.18 321	99.27 243	93.71 291	98.53 237	98.81 314	84.23 322	98.07 318	95.31 286	93.60 260	97.72 278

FMVSNet3		97.30 213	96.95 217	98.37 213	99.65 160	99.25 150	99.71 266	99.28 235	94.23 281	98.53 237	98.91 310	93.30 235	98.11 313	95.31 286	93.60 260	97.73 272

MVS_0304		95.11 291	94.84 292	95.91 309	99.60 175	91.24 339	98.64 345	99.88 33	94.51 274	99.62 175	98.31 332	69.19 356	98.82 263	95.22 289	98.60 160	97.66 298

GA-MVS		97.72 194	97.27 212	99.06 172	99.24 238	97.93 229	100.00 1	99.24 254	95.80 238	98.99 209	99.64 250	89.77 274	99.36 229	95.12 290	97.62 211	99.89 150

ambc				88.45 332	86.84 355	70.76 357	97.79 352	98.02 346		90.91 343	95.14 345	38.69 363	98.51 291	94.97 291	84.23 336	96.09 344

OurMVSNet-221017-0		96.14 271	95.98 256	96.62 298	97.49 324	93.44 320	99.92 229	98.16 339	95.86 235	97.65 281	99.95 193	85.71 316	98.78 267	94.93 292	94.18 258	97.64 306

SixPastTwentyTwo		95.71 282	95.49 279	96.38 302	97.42 327	93.01 323	99.84 241	98.23 338	94.75 264	95.98 319	99.97 177	85.35 317	98.43 297	94.71 293	93.17 267	97.69 290

DTE-MVSNet		95.52 284	94.99 290	97.08 281	97.49 324	96.45 275	100.00 1	99.25 249	93.82 290	96.17 316	99.57 266	87.81 296	97.18 331	94.57 294	86.26 333	97.62 309

UnsupCasMVSNet_eth		94.25 295	93.89 294	95.34 310	97.63 314	92.13 330	99.73 263	99.36 200	94.88 262	92.78 337	98.63 321	82.72 330	96.53 337	94.57 294	84.73 335	97.36 325

CMPMVS	66.12 22	90.65 316	92.04 310	86.46 335	96.18 338	66.87 359	98.03 350	99.38 192	83.38 349	85.49 351	99.55 268	77.59 346	98.80 266	94.44 296	94.31 257	93.72 350
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs6		93.64 300	92.87 305	95.94 308	97.47 326	91.41 336	98.92 340	99.02 322	87.84 341	95.01 326	99.61 260	77.24 347	98.77 270	94.33 297	86.41 332	97.63 307

Patchmtry		96.81 233	96.37 239	98.14 230	99.31 232	98.55 192	98.91 341	99.00 325	90.45 328	97.92 272	98.98 303	96.94 183	98.12 311	94.27 298	91.53 289	97.75 242

tfpnnormal		96.36 257	95.69 272	98.37 213	98.55 280	98.71 185	99.69 270	99.45 99	93.16 308	96.69 311	99.71 232	88.44 294	98.99 247	94.17 299	91.38 293	97.41 323

v8		96.35 258	95.73 268	98.21 225	98.11 300	98.23 211	99.94 227	99.07 309	92.66 316	98.29 253	99.00 302	91.46 254	98.77 270	94.17 299	88.83 317	97.62 309

MIMVSNet		97.06 224	96.73 224	98.05 244	99.38 229	96.64 273	98.47 347	99.35 208	93.41 300	99.48 180	98.53 324	89.66 275	97.70 329	94.16 301	98.11 190	99.80 191

Patchmatch-RL test		93.49 301	93.63 298	93.05 328	91.78 350	83.41 351	98.21 349	96.95 354	91.58 322	91.05 342	97.64 338	99.40 52	95.83 345	94.11 302	81.95 339	99.91 135

FMVSNet2		96.22 264	95.60 275	98.06 240	99.53 193	98.33 204	99.45 294	99.27 243	93.71 291	98.03 266	98.84 313	84.23 322	98.10 316	93.97 303	93.40 264	97.73 272

K. test v3		95.46 286	95.14 287	96.40 301	97.53 321	93.40 321	99.99 190	99.23 258	95.49 252	92.70 340	99.73 228	84.26 321	98.12 311	93.94 304	93.38 265	97.68 292

v1144		96.51 247	95.97 257	98.13 233	97.98 305	98.04 222	99.99 190	99.08 305	93.51 299	98.62 232	98.98 303	90.98 262	98.62 279	93.79 305	90.79 299	97.74 265

TinyColmap		95.50 285	95.12 288	96.64 297	98.69 275	93.00 324	99.40 299	97.75 351	96.40 219	96.14 317	99.87 206	79.47 341	99.50 215	93.62 306	94.72 252	97.40 324

USDC		95.90 279	95.70 269	96.50 300	98.60 279	92.56 329	100.00 1	98.30 337	97.77 113	96.92 301	99.94 197	81.25 338	99.45 223	93.54 307	94.96 250	97.49 319

MS-PatchMatch		95.66 283	95.87 260	95.05 312	97.80 310	89.25 342	98.88 342	99.30 225	96.35 221	96.86 304	99.01 301	81.35 337	99.43 224	93.30 308	99.98 115	96.46 340

v144192		96.40 255	95.81 262	98.17 228	97.89 308	98.11 216	99.99 190	99.06 316	93.39 301	98.75 224	99.09 292	90.43 268	98.66 277	93.10 309	90.55 302	97.75 242

MVP-Stereo		96.51 247	96.48 234	96.60 299	95.65 341	94.25 313	98.84 343	98.16 339	95.85 237	95.23 324	99.04 297	92.54 248	99.13 238	92.98 310	99.98 115	96.43 341
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
FMVSNet1		94.45 293	93.63 298	96.89 291	98.87 270	94.87 292	99.18 321	99.27 243	90.95 326	97.31 293	98.81 314	72.89 351	98.07 318	92.61 311	92.81 271	97.72 278

test123		79.44 323	79.23 327	80.05 339	80.03 360	71.72 355	100.00 1	77.93 368	62.52 356	94.81 327	99.69 237	78.21 345	74.53 362	92.57 312	27.33 362	93.90 348

v7n		96.06 275	95.42 284	97.99 251	97.58 319	97.35 251	99.86 239	99.11 295	92.81 314	97.91 273	99.49 274	90.99 261	98.92 253	92.51 313	88.49 318	97.70 286

lessismore_v0				96.05 306	97.55 320	91.80 333		99.22 260		91.87 341	99.91 202	83.50 328	98.68 275	92.48 314	90.42 304	97.68 292

EG-PatchMatch MVS		92.94 305	92.49 309	94.29 322	95.87 340	87.07 347	99.07 338	98.11 342	93.19 307	88.98 346	98.66 320	70.89 353	99.08 240	92.43 315	95.21 239	96.72 337

v10		96.14 271	95.50 277	98.07 236	98.19 297	97.96 226	99.83 242	99.07 309	92.10 319	98.07 264	98.94 308	91.07 260	98.61 280	92.41 316	89.82 306	97.63 307

test0.0.03 1		98.12 183	98.03 184	98.39 211	99.11 241	98.07 219	100.00 1	99.93 26	96.70 200	96.91 303	99.95 193	99.31 60	98.19 306	91.93 317	98.44 168	98.91 222

our_test_3		96.51 247	96.35 241	96.98 287	97.61 316	95.05 290	99.98 208	99.01 324	94.68 267	96.77 309	99.06 294	95.87 202	98.14 309	91.81 318	92.37 278	97.75 242

MVS-HIRNet		94.12 298	92.73 308	98.29 218	99.33 231	95.95 278	99.38 301	99.19 268	74.54 353	98.26 257	86.34 358	86.07 311	99.06 241	91.60 319	99.87 130	99.85 169

v1921920		96.16 269	95.50 277	98.14 230	97.88 309	97.96 226	99.99 190	99.07 309	93.33 303	98.60 233	99.24 286	89.37 280	98.71 274	91.28 320	90.74 300	97.75 242

CR-MVSNet		98.02 186	97.71 196	98.93 183	99.31 232	98.86 178	99.13 331	99.00 325	96.53 212	99.96 112	98.98 303	96.94 183	98.10 316	91.18 321	98.40 171	99.84 170

v1192		96.18 266	95.49 279	98.26 221	98.01 303	98.15 214	99.99 190	99.08 305	93.36 302	98.54 236	98.97 306	89.47 279	98.89 257	91.15 322	90.82 298	97.75 242

DSMNet-mixed		95.18 290	95.21 286	95.08 311	96.03 339	90.21 340	99.65 274	93.64 361	92.91 311	98.34 249	97.40 339	90.05 272	95.51 347	91.02 323	97.86 198	99.51 214

YYNet1		92.44 307	90.92 314	97.03 283	96.20 337	97.06 264	99.99 190	99.14 285	88.21 339	67.93 358	98.43 328	88.63 289	96.28 340	90.64 324	89.08 314	97.74 265

UnsupCasMVSNet_bld		89.50 319	88.00 322	93.99 325	95.30 344	88.86 344	98.52 346	99.28 235	85.50 345	87.80 349	94.11 350	61.63 358	96.96 332	90.63 325	79.26 342	96.15 342

PM-MVS		88.39 320	87.41 323	91.31 330	91.73 351	82.02 353	99.79 249	96.62 356	91.06 325	90.71 344	95.73 343	48.60 361	95.96 343	90.56 326	81.91 340	95.97 345

pmmvs-eth3d		91.73 312	90.67 315	94.92 315	91.63 352	92.71 327	99.90 232	98.54 335	91.19 324	88.08 347	95.50 344	79.31 343	96.13 342	90.55 327	81.32 341	95.91 346

MDA-MVSNet_test_wron		92.61 306	91.09 313	97.19 280	96.71 335	97.26 257	100.00 1	99.14 285	88.61 336	67.90 359	98.32 331	89.03 283	96.57 336	90.47 328	89.59 308	97.74 265

testgi		96.18 266	95.93 258	96.93 290	98.98 261	94.20 315	100.00 1	99.07 309	97.16 173	96.06 318	99.86 208	84.08 325	97.79 328	90.38 329	97.80 204	98.81 223

Patchmatch-test		97.83 191	97.42 202	99.06 172	99.08 244	97.66 242	98.66 344	99.21 265	93.65 295	98.25 258	99.58 263	99.47 39	99.57 194	90.25 330	98.59 161	99.95 121

ppachtmachnet_test		96.17 268	95.89 259	97.02 284	97.61 316	95.24 287	99.99 190	99.24 254	93.31 304	96.71 310	99.62 258	94.34 224	98.07 318	89.87 331	92.30 280	97.75 242

KD-MVS_2432*1600		94.15 296	93.08 303	97.35 272	99.53 193	97.83 236	99.63 277	99.19 268	92.88 312	96.29 314	97.68 336	98.84 117	96.70 334	89.73 332	63.92 353	97.53 317

miper_refine_blended		94.15 296	93.08 303	97.35 272	99.53 193	97.83 236	99.63 277	99.19 268	92.88 312	96.29 314	97.68 336	98.84 117	96.70 334	89.73 332	63.92 353	97.53 317

v1240		95.96 277	95.25 285	98.07 236	97.91 307	97.87 234	99.96 218	99.07 309	93.24 306	98.64 231	98.96 307	88.98 285	98.61 280	89.58 334	90.92 297	97.75 242

test_0402		94.35 294	93.70 297	96.32 303	97.92 306	93.60 318	99.61 281	98.85 332	88.19 340	94.68 329	99.48 275	80.01 340	98.58 286	89.39 335	95.15 243	96.77 336

TransMVSNet (Re)		94.78 292	93.72 296	97.93 255	98.34 287	97.88 232	99.23 318	97.98 347	91.60 321	94.55 330	99.71 232	87.89 295	98.36 299	89.30 336	84.92 334	97.56 315

MDA-MVSNet-bldmvs		91.65 313	89.94 319	96.79 296	96.72 334	96.70 271	99.42 298	98.94 327	88.89 335	66.97 361	98.37 329	81.43 336	95.91 344	89.24 337	89.46 311	97.75 242

EPNet_dtu		98.53 163	98.23 175	99.43 147	99.92 111	99.01 170	99.96 218	99.47 77	98.80 45	99.96 112	99.96 186	98.56 133	99.30 233	87.78 338	99.68 138	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
FMVSNet5		95.32 287	95.43 283	94.99 313	99.39 228	92.99 325	99.25 311	99.24 254	90.45 328	97.44 291	98.45 326	95.78 204	94.39 350	87.02 339	91.88 286	97.59 313

OpenMVS_ROB	88.34 20	91.89 310	91.12 312	94.19 324	95.55 343	87.63 346	99.26 310	98.03 344	86.61 343	90.65 345	96.82 341	70.14 355	98.78 267	86.54 340	96.50 222	96.15 342

N_pmnet		91.88 311	93.37 301	87.40 334	97.24 331	66.33 360	99.90 232	91.05 363	89.77 333	95.65 322	98.58 323	90.05 272	98.11 313	85.39 341	92.72 272	97.75 242

new-patchmatchnet		90.30 318	89.46 320	92.84 329	90.77 353	88.55 345	99.83 242	98.80 334	90.07 332	87.86 348	95.00 347	78.77 344	94.30 351	84.86 342	79.15 343	95.68 347

new_pmnet		94.11 299	93.47 300	96.04 307	96.60 336	92.82 326	99.97 214	98.91 330	90.21 330	95.26 323	98.05 334	85.89 314	98.14 309	84.28 343	92.01 283	97.16 330

Anonymous20240521		93.29 303	92.76 307	94.90 316	95.64 342	91.27 337	99.97 214	98.82 333	87.04 342	94.71 328	98.19 333	83.86 326	96.80 333	84.04 344	92.56 277	96.64 338

LCM-MVSNet		79.01 325	76.93 329	85.27 336	78.28 361	68.01 358	96.57 353	98.03 344	55.10 359	82.03 353	93.27 351	31.99 366	93.95 352	82.72 345	74.37 347	93.84 349

DIV-MVS_2432*1600		91.16 314	90.09 318	94.35 320	94.44 348	91.27 337	99.74 259	99.08 305	90.82 327	94.53 331	94.91 349	86.11 310	94.78 349	82.67 346	68.52 351	96.99 333

pmmvs3		90.62 317	89.36 321	94.40 319	90.53 354	91.49 335	100.00 1	96.73 355	84.21 347	93.65 336	96.65 342	82.56 333	94.83 348	82.28 347	77.62 345	96.89 335

FPMVS		77.92 326	79.45 326	73.34 343	76.87 362	46.81 367	98.24 348	99.05 318	59.89 358	73.55 355	98.34 330	36.81 364	86.55 357	80.96 348	91.35 294	86.65 355

CL-MVSNet_2432*1600		91.07 315	90.35 317	93.24 327	93.27 349	89.16 343	99.55 286	99.25 249	92.34 317	95.23 324	97.05 340	88.86 288	93.59 353	80.67 349	66.95 352	96.96 334

TAPA-MVS	96.40 10	97.64 197	97.37 206	98.45 208	99.94 106	95.70 283	100.00 1	99.40 176	97.65 125	99.53 177	100.00 1	99.31 60	99.66 188	80.48 350	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
PatchT		95.90 279	94.95 291	98.75 194	99.03 251	98.39 197	99.08 336	99.32 217	85.52 344	99.96 112	94.99 348	97.94 148	98.05 322	80.20 351	98.47 167	99.81 181

MIMVSNet1		91.96 308	91.20 311	94.23 323	94.94 347	91.69 334	99.34 305	99.22 260	88.23 338	94.18 334	98.45 326	75.52 349	93.41 354	79.37 352	91.49 290	97.60 312

Gipuma		84.73 321	83.50 324	88.40 333	97.50 322	82.21 352	88.87 356	99.05 318	65.81 355	85.71 350	90.49 353	53.70 359	96.31 339	78.64 353	91.74 287	86.67 354
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
test20.03		93.11 304	92.85 306	93.88 326	95.19 345	91.83 332	100.00 1	98.87 331	93.68 294	92.76 338	98.88 312	89.20 282	92.71 355	77.88 354	89.19 313	97.09 331

RPMNet		95.26 289	93.82 295	99.56 137	99.31 232	98.86 178	99.13 331	99.42 127	79.82 351	99.96 112	95.13 346	95.69 206	99.98 113	77.54 355	98.40 171	99.84 170

Anonymous20231206		93.45 302	93.17 302	94.30 321	95.00 346	89.69 341	99.98 208	98.43 336	93.30 305	94.50 332	98.59 322	90.52 265	95.73 346	77.46 356	90.73 301	97.48 321

PMMVS2		79.15 324	77.28 328	84.76 337	82.34 358	72.66 354	99.70 268	95.11 360	71.68 354	84.78 352	90.87 352	32.05 365	89.99 356	75.53 357	63.45 355	91.64 351

PMVS	60.66 23	65.98 332	65.05 333	68.75 346	55.06 367	38.40 368	88.19 357	96.98 353	48.30 363	44.82 364	88.52 356	12.22 369	86.49 358	67.58 358	83.79 337	81.35 358
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
ANet_high		66.05 331	63.44 335	73.88 342	61.14 365	63.45 363	95.68 355	87.18 365	79.93 350	47.35 363	80.68 363	22.35 367	72.33 364	61.24 359	35.42 360	85.88 356

MVE	68.59 21	67.22 330	64.68 334	74.84 340	74.67 364	62.32 364	95.84 354	90.87 364	50.98 360	58.72 362	81.05 362	12.20 370	78.95 359	61.06 360	56.75 356	83.24 357
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN		70.72 328	70.06 331	72.69 344	83.92 357	65.48 362	99.95 223	92.72 362	49.88 361	72.30 356	86.26 359	47.17 362	77.43 360	53.83 361	44.49 358	75.17 360

EMVS		69.88 329	69.09 332	72.24 345	84.70 356	65.82 361	99.96 218	87.08 367	49.82 362	71.51 357	84.74 360	49.30 360	75.32 361	50.97 362	43.71 359	75.59 359

wuyk23d		28.28 333	29.73 337	23.92 347	75.89 363	32.61 369	66.50 359	12.88 369	16.09 364	14.59 365	16.59 365	12.35 368	32.36 365	39.36 363	13.36 363	6.79 361

uanet_test		0.01 337	0.02 340	0.00 348	0.00 369	0.00 370	0.00 360	0.00 370	0.00 365	0.00 366	0.14 366	0.00 371	0.00 366	0.00 364	0.00 364	0.00 362

cdsmvs_eth3d_5k		24.41 334	32.55 336	0.00 348	0.00 369	0.00 370	0.00 360	99.39 189	0.00 365	0.00 366	100.00 1	93.55 232	0.00 366	0.00 364	0.00 364	0.00 362

pcd_1.5k_mvsjas		8.24 336	10.99 339	0.00 348	0.00 369	0.00 370	0.00 360	0.00 370	0.00 365	0.00 366	0.14 366	98.75 124	0.00 366	0.00 364	0.00 364	0.00 362

sosnet-low-res		0.01 337	0.02 340	0.00 348	0.00 369	0.00 370	0.00 360	0.00 370	0.00 365	0.00 366	0.14 366	0.00 371	0.00 366	0.00 364	0.00 364	0.00 362

sosnet		0.01 337	0.02 340	0.00 348	0.00 369	0.00 370	0.00 360	0.00 370	0.00 365	0.00 366	0.14 366	0.00 371	0.00 366	0.00 364	0.00 364	0.00 362

uncertanet		0.01 337	0.02 340	0.00 348	0.00 369	0.00 370	0.00 360	0.00 370	0.00 365	0.00 366	0.14 366	0.00 371	0.00 366	0.00 364	0.00 364	0.00 362

Regformer		0.01 337	0.02 340	0.00 348	0.00 369	0.00 370	0.00 360	0.00 370	0.00 365	0.00 366	0.14 366	0.00 371	0.00 366	0.00 364	0.00 364	0.00 362

ab-mvs-re		8.33 335	11.11 338	0.00 348	0.00 369	0.00 370	0.00 360	0.00 370	0.00 365	0.00 366	100.00 1	0.00 371	0.00 366	0.00 364	0.00 364	0.00 362

uanet		0.01 337	0.02 340	0.00 348	0.00 369	0.00 370	0.00 360	0.00 370	0.00 365	0.00 366	0.14 366	0.00 371	0.00 366	0.00 364	0.00 364	0.00 362

test_241102_ONE					100.00 1	99.99 3		99.42 127	99.03 19	100.00 1	100.00 1	99.50 33	100.00 1

save fliter					99.99 54	99.93 42	100.00 1	99.42 127	98.93 32

test0726					100.00 1	99.99 3	100.00 1	99.42 127	99.04 14	100.00 1	100.00 1	99.53 23

GSMVS																99.91 135

test_part2					100.00 1	99.99 3				100.00 1

sam_mvs1												99.29 67				99.91 135

sam_mvs												99.33 55

MTGPA								99.42 127

test_post											89.05 355	99.49 35	99.59 191

patchmatchnet-post											97.79 335	99.41 51	99.54 206

MTMP							100.00 1	99.18 273

TEST9					100.00 1	99.95 29	100.00 1	99.42 127	97.65 125	100.00 1	100.00 1	99.53 23	99.97 118

test_8					100.00 1	99.91 52	100.00 1	99.42 127	97.70 120	100.00 1	100.00 1	99.51 28	99.98 113

agg_prior					100.00 1	99.88 78		99.42 127		100.00 1			99.97 118

test_prior4						99.93 42	100.00 1

test_prior				99.90 82	100.00 1	99.75 101		99.73 54					99.97 118			100.00 1

新几何2							100.00 1

旧先验1					99.99 54	99.88 78		99.82 36			100.00 1	99.27 70			100.00 1	100.00 1

原ACMM2							100.00 1

test222					99.99 54	99.90 60	100.00 1	99.69 61	97.66 124	100.00 1	100.00 1	99.30 66			100.00 1	100.00 1

segment_acmp												99.55 21

testdata1							100.00 1		98.77 48

test12				99.95 58	99.99 54	99.89 68		99.42 127		100.00 1		99.24 73	99.97 118		100.00 1	100.00 1

plane_prior7					99.00 257	94.78 302

plane_prior6					99.06 249	94.80 298						88.58 292

plane_prior4											99.97 177

plane_prior3						94.79 301			99.03 19	99.08 203

plane_prior2							100.00 1		99.00 25

plane_prior1					99.02 252

plane_prior						94.80 298	100.00 1		99.03 19						95.58 223

n2								0.00 370

nn								0.00 370

door-mid								96.32 358

test11								99.42 127

door								96.13 359

HQP5-MVS						94.82 295

HQP-NCC					99.07 245		100.00 1		99.04 14	99.17 194

ACMP_Plane					99.07 245		100.00 1		99.04 14	99.17 194

HQP4-MVS										99.17 194			99.57 194			97.77 229

HQP3-MVS								99.40 176							95.58 223

HQP2-MVS												88.61 290

NP-MVS					99.07 245	94.81 297					99.97 177

ACMMP++_ref															94.58 255

ACMMP++															95.17 242

Test By Simon												99.10 87

High-resolution multi-view benchmark