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	97.31 163	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	99.42 126	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		99.42 126	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								99.42 126	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	99.31 220	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	99.42 126	97.67 121	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	99.42 126	97.39 154	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	99.42 126	97.97 94	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	99.42 126	97.54 139	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	97.71 117	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	99.42 126	97.58 135	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	99.42 126	99.04 14	100.00 1	100.00 1	99.53 23	100.00 1	100.00 1	100.00 1	100.00 1

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	99.42 126					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	97.59 133	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	99.43 118	97.50 145	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	99.42 126	98.91 35	100.00 1	100.00 1	99.22 76	100.00 1	100.00 1	100.00 1	100.00 1

CHOSEN 280x420		99.85 3	99.87 1	99.80 104	99.99 54	99.97 18	99.97 213	99.98 13	98.96 28	100.00 1	100.00 1	99.96 3	99.42 223	100.00 1	100.00 1	100.00 1

CANet		99.40 86	99.24 94	99.89 85	99.99 54	99.76 98	100.00 1	99.73 54	98.40 63	99.78 161	100.00 1	95.28 205	99.96 131	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	99.42 126	98.87 39	100.00 1	100.00 1	99.65 12	99.96 131	100.00 1	100.00 1	100.00 1

TSAR-MVS + MP.		99.82 9	99.77 9	99.99 9	100.00 1	99.96 20	100.00 1	99.43 118	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	99.42 126	97.70 118	100.00 1	100.00 1	99.51 28	99.97 117	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	99.42 126	97.72 114	100.00 1	100.00 1	99.51 28	99.97 117	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	99.96 110	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	99.75 100	100.00 1	99.73 54	98.82 43	100.00 1	100.00 1	99.47 39	99.97 117	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		97.04 224	96.06 248	99.98 22	100.00 1	99.94 37	100.00 1	99.75 49	98.67 51	100.00 1	66.97 356	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	98.88 263	99.89 68	99.24 303	99.93 26	98.88 37	98.79 220	100.00 1	97.02 172	100.00 1	100.00 1	100.00 1	100.00 1

VDD-MVS		96.58 241	95.99 251	98.34 214	99.52 194	95.33 280	99.18 312	99.38 189	96.64 203	99.77 162	100.00 1	72.51 343	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	99.42 126	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	99.44 108	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	99.42 126	98.02 88	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	99.36 197	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	99.42 126	97.91 101	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	99.42 126	97.53 141	100.00 1	100.00 1	99.27 70	99.97 117	100.00 1	100.00 1	100.00 1
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
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	99.42 126	97.77 111	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	99.76 140	99.95 29	100.00 1	99.42 126	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	99.60 118	100.00 1	100.00 1	97.23 166	100.00 1	99.03 295	96.57 187	99.99 89	100.00 1	94.75 251	97.35 321

PVSNet_Blended		99.48 82	99.36 84	99.83 96	99.98 92	99.60 118	100.00 1	100.00 1	97.79 110	100.00 1	100.00 1	96.57 187	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	97.87 105	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 75	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	97.85 149	99.95 137	100.00 1	100.00 1	100.00 1

API-MVS		99.72 32	99.70 20	99.79 106	99.97 96	99.37 139	99.96 216	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	99.01 247	99.95 29	100.00 1	99.75 49	99.37 3	99.99 97	100.00 1	99.76 8	99.60 188	100.00 1	100.00 1	100.00 1

PHI-MVS		99.50 78	99.39 79	99.82 97	100.00 1	99.45 131	100.00 1	99.94 18	96.38 217	100.00 1	100.00 1	98.18 140	100.00 1	100.00 1	100.00 1	100.00 1

PVSNet_0	93.57 19	96.41 248	95.74 263	98.41 208	99.84 117	95.22 282	100.00 1	100.00 1	98.08 84	97.55 284	99.78 223	84.40 311	100.00 1	100.00 1	81.99 337	100.00 1

DeepPCF-MVS	98.03 4	98.54 162	99.72 18	94.98 309	99.99 54	84.94 341	100.00 1	99.42 126	99.98 1	100.00 1	100.00 1	98.11 143	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	98.79 179	100.00 1	99.54 67	98.58 56	99.96 110	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	99.66 114	99.74 255	99.95 15	97.89 102	100.00 1	100.00 1	96.71 185	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	97.59 133	100.00 1	100.00 1	98.65 125	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	99.42 126	97.62 127	100.00 1	100.00 1	98.65 125	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	99.42 126	97.62 127	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	99.42 126	97.53 141	99.77 162	100.00 1	98.77 121	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 99	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	97.86 106	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 85	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	99.44 108	98.40 63	100.00 1	100.00 1	99.03 97	99.97 117	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	99.44 108	98.40 63	100.00 1	100.00 1	99.03 97	99.97 117	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	99.44 108	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	99.44 108	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 99	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	99.42 126	97.82 108	99.99 97	100.00 1	98.20 139	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	99.70 110	100.00 1	99.42 126	97.46 148	100.00 1	100.00 1	98.60 129	99.96 131	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	99.54 121	100.00 1	99.42 126	97.58 135	99.98 102	100.00 1	97.43 164	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	99.70 110	100.00 1	99.97 14	98.96 28	100.00 1	100.00 1	97.93 147	99.95 137	99.99 58	100.00 1	100.00 1

CSCG		99.28 102	99.35 86	99.05 174	99.99 54	97.15 257	100.00 1	99.47 77	97.44 151	99.42 180	100.00 1	97.83 150	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	97.48 146	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	97.48 146	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	99.42 126	97.83 107	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	99.64 116	99.95 221	99.44 108	98.35 69	100.00 1	100.00 1	98.98 100	99.97 117	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	99.64 116	99.98 207	99.44 108	98.35 69	99.99 97	100.00 1	99.04 93	99.96 131	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	97.54 139	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	99.42 126	97.09 175	100.00 1	100.00 1	98.95 106	99.96 131	99.98 75	100.00 1	100.00 1

114514_t		99.39 87	99.25 92	99.81 100	99.97 96	99.48 130	100.00 1	99.42 126	95.53 243	100.00 1	100.00 1	98.37 137	99.95 137	99.97 82	100.00 1	100.00 1

CNLPA		99.72 32	99.65 34	99.91 79	99.97 96	99.72 105	100.00 1	99.47 77	98.43 60	99.88 147	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	97.72 114	99.95 131	100.00 1	98.39 136	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	99.42 126	98.32 71	99.94 133	100.00 1	98.65 125	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	99.42 126	98.32 71	99.94 133	100.00 1	98.65 125	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 90	99.99 97	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	99.66 114	99.75 254	99.73 54	98.16 75	99.75 165	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		97.64 196	97.74 193	97.36 267	99.01 247	94.76 297	100.00 1	99.34 211	99.30 4	99.00 205	99.97 177	87.49 291	99.57 193	99.96 84	95.58 223	97.75 238
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	99.73 258	99.52 69	99.06 11	100.00 1	100.00 1	98.80 120	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	99.98 207	99.47 77	99.09 8	100.00 1	100.00 1	98.59 130	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 94	99.97 106	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	99.45 131	100.00 1	99.78 43	98.92 34	99.73 166	100.00 1	97.70 153	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	99.70 263	99.99 10	98.53 57	99.90 142	100.00 1	95.34 204	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	99.07 162	100.00 1	99.44 108	98.30 73	99.90 142	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	99.75 100	99.50 284	99.47 77	98.36 68	100.00 1	99.99 166	94.66 214	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		97.42 207	96.62 227	99.81 100	99.80 132	99.50 123	99.16 318	99.56 66	94.48 272	100.00 1	100.00 1	79.35 332	100.00 1	99.89 98	97.37 212	99.94 124

PS-MVSNAJ		99.64 58	99.57 57	99.85 93	99.78 136	99.81 93	99.95 221	99.42 126	98.38 66	100.00 1	100.00 1	98.75 122	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	98.99 255	99.89 68	100.00 1	99.51 73	98.96 28	98.32 247	100.00 1	92.78 236	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 92	99.84 149	100.00 1	98.94 108	99.98 112	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	99.64 271	100.00 1	97.97 94	99.84 149	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	99.70 146	99.73 104	99.92 227	99.40 173	98.15 77	100.00 1	100.00 1	98.50 133	100.00 1	99.85 103	99.13 149	99.74 198

VDDNet		96.39 252	95.55 271	98.90 185	99.27 229	97.45 244	99.15 320	99.92 30	91.28 316	99.98 102	100.00 1	73.55 341	100.00 1	99.85 103	96.98 218	99.24 216

MVS		99.22 111	98.96 118	99.98 22	99.00 252	99.95 29	99.24 303	99.94 18	98.14 78	98.88 211	100.00 1	95.63 202	100.00 1	99.85 103	100.00 1	100.00 1

Anonymous20240529		96.93 228	96.22 242	99.05 174	99.79 135	97.30 252	99.16 318	99.47 77	88.51 329	98.69 224	100.00 1	83.50 318	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	99.67 151	99.71 106	99.78 246	99.36 197	98.13 79	100.00 1	100.00 1	97.00 176	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	99.67 151	99.71 106	99.78 246	99.36 197	98.13 79	100.00 1	100.00 1	97.00 176	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	99.67 151	99.71 106	99.78 246	99.36 197	98.13 79	100.00 1	100.00 1	97.00 176	100.00 1	99.83 106	99.07 151	99.66 207

alignmvs		99.38 88	99.21 100	99.91 79	99.73 143	99.92 49	100.00 1	99.51 73	97.61 129	100.00 1	100.00 1	99.06 89	99.93 150	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 98	100.00 1	99.42 126	97.21 169	100.00 1	100.00 1	98.12 142	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	97.69 120	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	97.37 266	99.00 252	94.80 292	100.00 1	99.40 173	99.00 25	99.08 200	99.97 177	88.58 284	99.55 202	99.79 112	95.57 227	97.76 228

plane_prior5								99.40 173					99.55 202	99.79 112	95.57 227	97.76 228

BP-MVS														99.79 112

PVSNet_Blended_VisFu		99.33 96	99.18 106	99.78 110	99.82 118	99.49 126	100.00 1	99.95 15	97.36 156	99.63 171	100.00 1	96.45 191	99.95 137	99.79 112	99.65 140	99.89 150

HQP-MVS		97.73 193	97.85 189	97.39 265	99.07 239	94.82 289	100.00 1	99.40 173	99.04 14	99.17 191	99.97 177	88.61 282	99.57 193	99.79 112	95.58 223	97.77 226

canonicalmvs		99.03 121	98.73 141	99.94 73	99.75 142	99.95 29	100.00 1	99.30 223	97.64 125	100.00 1	100.00 1	95.22 207	99.97 117	99.76 118	96.90 220	99.91 135

XVG-OURS-SEG-HR		98.27 179	98.31 170	98.14 229	99.59 174	95.92 276	100.00 1	99.36 197	98.48 58	99.21 190	100.00 1	89.27 274	99.94 148	99.76 118	99.17 148	98.56 224

EIA-MVS		99.26 105	99.19 104	99.45 144	99.63 163	98.75 180	100.00 1	99.27 240	96.93 182	99.95 131	100.00 1	97.47 160	99.79 174	99.74 120	99.72 137	99.82 177

HyFIR lowres test		99.32 98	99.24 94	99.58 134	99.95 103	99.26 147	100.00 1	99.99 10	96.72 195	99.29 187	99.91 202	99.49 35	99.47 217	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	99.03 166	100.00 1	99.40 173	98.61 55	99.33 185	100.00 1	92.23 242	99.95 137	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
GG-mvs-BLEND				99.59 130	99.54 186	99.49 126	99.17 317	99.52 69		99.96 110	99.68 237	100.00 1	99.33 229	99.71 123	99.99 107	99.96 116

3Dnovator	95.63 14	99.06 118	98.76 139	99.96 46	98.86 266	99.90 60	99.98 207	99.93 26	98.95 31	98.49 239	100.00 1	92.91 235	100.00 1	99.71 123	100.00 1	100.00 1

ET-MVSNet_ETH3D		96.41 248	95.48 276	99.20 169	99.81 122	99.75 100	100.00 1	99.02 315	97.30 165	78.33 345	100.00 1	97.73 151	97.94 322	99.70 125	87.41 324	99.92 133

ETV-MVS		99.34 94	99.24 94	99.64 123	99.58 179	99.33 141	100.00 1	99.25 246	97.57 137	99.96 110	100.00 1	97.44 163	99.79 174	99.70 125	99.65 140	99.81 181

Anonymous202405211		97.87 189	97.53 199	98.90 185	99.81 122	96.70 268	99.35 295	99.46 92	92.98 307	98.83 217	99.99 166	90.63 257	100.00 1	99.70 125	97.03 216	100.00 1

casdiffmvs		98.65 154	98.38 166	99.46 143	99.52 194	98.74 183	100.00 1	99.15 273	96.91 185	99.05 203	100.00 1	92.75 237	99.83 167	99.70 125	98.38 174	99.81 181

baseline		98.69 152	98.45 162	99.41 149	99.52 194	98.67 187	100.00 1	99.17 271	97.03 180	99.13 196	100.00 1	93.17 231	99.74 181	99.70 125	98.34 176	99.81 181

PMMVS		99.12 113	98.97 117	99.58 134	99.57 182	98.98 172	100.00 1	99.30 223	97.14 172	99.96 110	100.00 1	96.53 190	99.82 170	99.70 125	98.49 165	99.94 124

ACMP	97.00 8	97.19 215	97.16 215	97.27 272	98.97 257	94.58 304	100.00 1	99.32 215	97.97 94	97.45 286	99.98 169	85.79 306	99.56 197	99.70 125	95.24 238	97.67 294
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
gg-mvs-nofinetune		96.95 227	96.10 246	99.50 141	99.41 214	99.36 140	99.07 330	99.52 69	83.69 340	99.96 110	83.60 353	100.00 1	99.20 233	99.68 132	99.99 107	99.96 116

cascas		98.43 168	98.07 182	99.50 141	99.65 156	99.02 167	100.00 1	99.22 255	94.21 279	99.72 167	99.98 169	92.03 245	99.93 150	99.68 132	98.12 189	99.54 211

CS-MVS		99.33 96	99.23 97	99.65 122	99.63 163	99.18 157	100.00 1	99.27 240	97.45 149	99.96 110	100.00 1	97.22 166	99.87 159	99.67 134	99.86 131	99.90 144

旧先验2							100.00 1		98.11 83	100.00 1			100.00 1	99.67 134

lupinMVS		99.29 101	99.16 107	99.69 117	99.45 210	99.49 126	100.00 1	99.15 273	97.45 149	99.97 106	100.00 1	96.76 183	99.76 178	99.67 134	100.00 1	99.81 181

diffmvs		98.96 133	98.73 141	99.63 124	99.54 186	99.16 158	100.00 1	99.18 266	97.33 160	99.96 110	100.00 1	94.60 215	99.91 154	99.66 137	98.33 180	99.82 177

CHOSEN 1792x2688		99.00 127	98.91 126	99.25 165	99.90 114	97.79 235	100.00 1	99.99 10	98.79 46	98.28 250	100.00 1	93.63 225	99.95 137	99.66 137	99.95 122	100.00 1

ab-mvs		98.42 169	98.02 185	99.61 126	99.71 144	99.00 171	99.10 326	99.64 63	96.70 197	99.04 204	99.81 219	90.64 256	99.98 112	99.64 139	97.93 195	99.84 170

OpenMVS	95.20 17	98.76 147	98.41 163	99.78 110	98.89 262	99.81 93	99.99 189	99.76 45	98.02 88	98.02 264	100.00 1	91.44 248	100.00 1	99.63 140	99.97 118	99.55 210

thres200		99.27 103	99.04 110	99.96 46	99.81 122	99.90 60	100.00 1	99.94 18	97.31 163	99.83 151	99.96 186	97.04 169	100.00 1	99.62 141	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	97.13 173	99.83 151	99.96 186	97.01 173	100.00 1	99.59 142	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	97.23 166	99.83 151	99.96 186	97.04 169	100.00 1	99.59 142	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	97.23 166	99.83 151	99.96 186	97.04 169	100.00 1	99.59 142	97.85 199	99.97 113

LCM-MVSNet-Re		96.52 242	97.21 213	94.44 312	99.27 229	85.80 340	99.85 238	96.61 349	95.98 228	92.75 330	98.48 321	93.97 222	97.55 327	99.58 145	98.43 169	99.98 108

jason		99.11 114	98.96 118	99.59 130	99.17 233	99.31 143	100.00 1	99.13 283	97.38 155	99.83 151	100.00 1	95.54 203	99.72 184	99.57 146	99.97 118	99.74 198
jason: jason.
LPG-MVS_test		97.31 211	97.32 207	97.28 270	98.85 267	94.60 301	100.00 1	99.37 191	97.35 157	98.85 213	99.98 169	86.66 298	99.56 197	99.55 147	95.26 235	97.70 283

LGP-MVS_train				97.28 270	98.85 267	94.60 301		99.37 191	97.35 157	98.85 213	99.98 169	86.66 298	99.56 197	99.55 147	95.26 235	97.70 283

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 87	100.00 1	100.00 1	96.10 194	100.00 1	99.55 147	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	97.13 173	99.83 151	99.96 186	97.01 173	100.00 1	99.54 150	97.77 205	99.97 113

BH-w/o		98.82 145	98.81 135	98.88 187	99.62 167	96.71 267	100.00 1	99.28 232	97.09 175	98.81 218	100.00 1	94.91 212	99.96 131	99.54 150	100.00 1	99.96 116

sss		99.45 83	99.34 88	99.80 104	99.76 140	99.50 123	100.00 1	99.91 31	97.72 114	99.98 102	99.94 197	98.45 134	100.00 1	99.53 152	98.75 158	99.89 150

EPP-MVSNet		99.10 115	99.00 114	99.40 151	99.51 199	98.68 186	99.92 227	99.43 118	95.47 249	99.65 170	100.00 1	99.51 28	99.76 178	99.53 152	98.00 192	99.75 197

原ACMM1				99.93 76	100.00 1	99.80 95		99.66 62	98.18 74	100.00 1	100.00 1	99.43 47	100.00 1	99.50 154	100.00 1	100.00 1

OMC-MVS		99.27 103	99.38 80	98.96 182	99.95 103	97.06 261	100.00 1	99.40 173	98.83 41	99.88 147	100.00 1	97.01 173	99.86 160	99.47 155	99.84 132	99.97 113

Effi-MVS+		98.58 158	98.24 173	99.61 126	99.60 171	99.26 147	97.85 343	99.10 291	96.22 224	99.97 106	99.89 204	93.75 223	99.77 177	99.43 156	98.34 176	99.81 181

IB-MVS	96.24 12	97.54 203	96.95 216	99.33 158	99.67 151	98.10 218	100.00 1	99.47 77	97.42 153	99.26 188	99.69 233	98.83 117	99.89 155	99.43 156	78.77 343	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	99.41 214	97.58 241	99.67 269	99.35 206	94.66 264	99.96 110	99.36 277	99.28 69	99.74 181	99.41 158	97.81 203	99.81 181

BH-untuned		98.64 155	98.65 147	98.60 199	99.59 174	96.17 273	100.00 1	99.28 232	96.67 201	98.41 242	100.00 1	94.52 216	99.83 167	99.41 158	100.00 1	99.81 181

Effi-MVS+-dtu		98.51 165	98.86 131	97.47 264	99.77 138	94.21 308	100.00 1	98.94 320	97.61 129	99.91 141	98.75 313	95.89 195	99.51 213	99.36 160	99.48 146	98.68 221

mvs-test1		98.89 141	98.99 116	98.60 199	99.77 138	95.96 274	100.00 1	98.94 320	97.61 129	99.93 138	99.92 201	95.89 195	99.93 150	99.36 160	99.50 145	99.90 144

XVG-OURS		98.30 175	98.36 169	98.13 232	99.58 179	95.91 277	100.00 1	99.36 197	98.69 49	99.23 189	100.00 1	91.20 250	99.92 153	99.34 162	97.82 202	98.56 224

无先验							100.00 1	99.80 39	97.98 92				100.00 1	99.33 163		100.00 1

1121		99.63 62	99.51 70	99.99 9	99.99 54	99.96 20	99.24 303	99.74 52	97.89 102	100.00 1	100.00 1	99.39 53	100.00 1	99.33 163	100.00 1	100.00 1

QAPM		98.99 129	98.66 146	99.96 46	99.01 247	99.87 81	99.88 236	99.93 26	97.99 90	98.68 225	100.00 1	93.17 231	100.00 1	99.32 165	100.00 1	100.00 1

UGNet		98.41 170	98.11 179	99.31 160	99.54 186	98.55 192	99.18 312	100.00 1	98.64 54	99.79 160	99.04 293	87.61 290	100.00 1	99.30 166	99.89 127	99.40 215
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	98.97 174		99.73 54	97.96 98	100.00 1	100.00 1	99.42 49	100.00 1	99.28 167	100.00 1	100.00 1

ACMM	97.17 6	97.37 209	97.40 203	97.29 269	99.01 247	94.64 300	100.00 1	99.25 246	98.07 85	98.44 241	99.98 169	87.38 292	99.55 202	99.25 168	95.19 240	97.69 287
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
nrg030		97.64 196	97.27 211	98.75 193	98.34 282	99.53 122	100.00 1	99.22 255	96.21 225	98.27 252	99.95 193	94.40 217	98.98 244	99.23 169	89.78 306	97.75 238

VPA-MVSNet		97.03 225	96.43 234	98.82 189	98.64 272	99.32 142	99.38 292	99.47 77	96.73 194	98.91 210	98.94 304	87.00 296	99.40 224	99.23 169	89.59 307	97.76 228

VPNet		96.41 248	95.76 262	98.33 215	98.61 273	98.30 207	99.48 285	99.45 99	96.98 181	98.87 212	99.88 205	81.57 325	98.93 248	99.22 171	87.82 322	97.76 228

LS3D		99.31 99	99.13 108	99.87 90	99.99 54	99.71 106	99.55 279	99.46 92	97.32 161	99.82 158	100.00 1	96.85 182	99.97 117	99.14 172	100.00 1	99.92 133

mvs_anonymous		98.80 146	98.60 153	99.38 154	99.57 182	99.24 151	100.00 1	99.21 260	95.87 230	98.92 208	99.82 216	96.39 192	99.03 239	99.13 173	98.50 164	99.88 161

DP-MVS		98.86 142	98.54 157	99.81 100	99.97 96	99.45 131	99.52 282	99.40 173	94.35 276	98.36 243	100.00 1	96.13 193	99.97 117	99.12 174	100.00 1	100.00 1

DWT-MVSNet_test		99.22 111	99.22 99	99.22 168	99.56 185	97.98 224	99.89 233	99.39 186	97.20 170	99.96 110	100.00 1	99.52 26	99.82 170	99.11 175	98.34 176	99.87 167

thisisatest0515		99.42 85	99.31 89	99.74 113	99.59 174	99.55 120	100.00 1	99.46 92	96.65 202	99.92 139	100.00 1	99.44 43	99.85 164	99.09 176	99.63 142	99.81 181

ACMH	96.25 11	96.77 231	96.62 227	97.21 273	98.96 258	94.43 306	99.64 271	99.33 213	97.43 152	96.55 307	99.97 177	83.52 317	99.54 205	99.07 177	95.13 244	97.66 295
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	99.68 150	98.55 192	99.68 268	99.41 171	97.34 159	99.94 133	100.00 1	90.38 262	99.70 186	99.03 178	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	99.59 174	99.41 134	100.00 1	99.46 92	96.46 212	99.90 142	100.00 1	99.44 43	99.85 164	98.97 179	99.58 144	99.80 191

tpmrst		98.98 132	98.93 124	99.14 171	99.61 169	97.74 236	99.52 282	99.36 197	96.05 227	99.98 102	99.64 246	99.04 93	99.86 160	98.94 180	98.19 187	99.82 177

tttt0517		99.34 94	99.23 97	99.67 119	99.57 182	99.38 136	100.00 1	99.46 92	96.33 220	99.89 145	100.00 1	99.44 43	99.84 166	98.93 181	99.46 147	99.78 193

MDTV_nov1_ep13_2view						99.24 151	99.56 278		96.31 221	99.96 110		98.86 116		98.92 182		99.89 150

RRT_test8_iter05		98.32 174	98.23 175	98.60 199	99.65 156	99.23 154	100.00 1	99.09 297	95.65 237	98.07 260	99.93 200	99.25 72	98.82 260	98.90 183	93.50 263	97.75 238

COLMAP_ROB	97.10 7	98.29 177	98.17 178	98.65 197	99.94 106	97.39 246	99.30 299	99.40 173	95.64 238	97.75 275	100.00 1	92.69 239	99.95 137	98.89 184	99.92 125	98.62 223
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	99.59 174	98.28 208	99.27 300	99.21 260	96.42 214	99.15 195	99.94 197	88.87 280	99.79 174	98.88 185	98.29 181	99.93 131

mvs_tets		97.00 226	96.69 224	97.94 249	97.41 324	97.27 253	99.60 275	99.18 266	96.51 211	97.35 288	99.69 233	86.53 300	98.91 250	98.84 186	95.09 246	97.65 300

testmvs		80.17 314	81.95 317	74.80 333	58.54 358	59.58 357	100.00 1	87.14 358	76.09 344	99.61 173	100.00 1	67.06 348	74.19 355	98.84 186	50.30 349	90.64 345

BH-RMVSNet		98.46 167	98.08 181	99.59 130	99.61 169	99.19 156	100.00 1	99.28 232	97.06 179	98.95 207	100.00 1	88.99 277	99.82 170	98.83 188	100.00 1	99.77 194

FIs		97.95 188	97.73 195	98.62 198	98.53 277	99.24 151	100.00 1	99.43 118	96.74 192	97.87 270	99.82 216	95.27 206	98.89 254	98.78 189	93.07 267	97.74 262

EPMVS		99.25 108	99.13 108	99.60 128	99.60 171	99.20 155	99.60 275	100.00 1	96.93 182	99.92 139	99.36 277	99.05 90	99.71 185	98.77 190	98.94 155	99.90 144

gm-plane-assit					99.52 194	97.26 254			95.86 232		100.00 1		99.43 221	98.76 191

baseline2		98.99 129	98.93 124	99.18 170	99.26 231	99.15 159	100.00 1	99.46 92	96.71 196	96.79 302	100.00 1	99.42 49	99.25 232	98.75 192	99.94 123	99.15 218

cl-mvsnet2		98.23 181	98.11 179	98.58 203	99.82 118	99.01 169	100.00 1	99.28 232	96.92 184	98.33 246	99.21 283	98.09 145	98.97 246	98.72 193	92.61 272	97.76 228

jajsoiax		97.07 222	96.79 222	97.89 253	97.28 325	97.12 258	99.95 221	99.19 263	96.55 207	97.31 289	99.69 233	87.35 294	98.91 250	98.70 194	95.12 245	97.66 295

Test_1112_low_res		98.83 144	98.60 153	99.51 139	99.69 147	98.75 180	99.99 189	99.14 278	96.81 189	98.84 215	99.06 290	97.45 161	99.89 155	98.66 195	97.75 206	99.89 150

1112_ss		98.91 138	98.71 144	99.51 139	99.69 147	98.75 180	99.99 189	99.15 273	96.82 188	98.84 215	100.00 1	97.45 161	99.89 155	98.66 195	97.75 206	99.89 150

MVS_Test		98.93 137	98.65 147	99.77 112	99.62 167	99.50 123	99.99 189	99.19 263	95.52 245	99.96 110	99.86 208	96.54 189	99.98 112	98.65 197	98.48 166	99.82 177

FC-MVSNet-test		97.84 190	97.63 198	98.45 206	98.30 286	99.05 164	100.00 1	99.43 118	96.63 205	97.61 281	99.82 216	95.19 208	98.57 285	98.64 198	93.05 268	97.73 269

MVSFormer		98.94 136	98.82 133	99.28 162	99.45 210	99.49 126	100.00 1	99.13 283	95.46 250	99.97 106	100.00 1	96.76 183	98.59 282	98.63 199	100.00 1	99.74 198

test_djsdf		97.55 202	97.38 204	98.07 235	97.50 317	97.99 223	100.00 1	99.13 283	95.46 250	98.47 240	99.85 210	92.01 246	98.59 282	98.63 199	95.36 231	97.62 306

tpm2		98.64 155	98.58 155	98.81 191	99.42 213	97.12 258	99.69 266	99.37 191	93.63 293	99.94 133	99.67 238	98.96 105	99.47 217	98.62 201	97.95 194	99.83 173

baseline1		98.91 138	98.61 151	99.81 100	99.71 144	99.77 97	99.78 246	99.44 108	97.51 144	98.81 218	99.99 166	98.25 138	99.76 178	98.60 202	95.41 229	99.89 150

MVSTER		98.58 158	98.52 158	98.77 192	99.65 156	99.68 112	100.00 1	99.29 227	95.63 239	98.65 226	99.80 222	99.78 6	98.88 257	98.59 203	95.31 233	97.73 269

D2MVS		97.63 199	97.83 190	97.05 276	98.83 269	94.60 301	100.00 1	99.82 36	96.89 187	98.28 250	99.03 295	94.05 219	99.47 217	98.58 204	94.97 249	97.09 326

PS-MVSNAJss		98.03 185	98.06 183	97.94 249	97.63 309	97.33 251	99.89 233	99.23 253	96.27 222	98.03 262	99.59 258	98.75 122	98.78 264	98.52 205	94.61 254	97.70 283

WR-MVS		97.09 220	96.64 225	98.46 205	98.43 279	99.09 161	99.97 213	99.33 213	95.62 240	97.76 272	99.67 238	91.17 251	98.56 287	98.49 206	89.28 311	97.74 262

IS-MVSNet		99.08 116	98.91 126	99.59 130	99.65 156	99.38 136	99.78 246	99.24 249	96.70 197	99.51 175	100.00 1	98.44 135	99.52 211	98.47 207	98.39 173	99.88 161

RRT_MVS		98.48 166	98.41 163	98.70 195	99.64 161	99.67 113	100.00 1	99.10 291	96.26 223	98.75 221	99.96 186	99.04 93	98.75 270	98.42 208	94.51 256	97.68 289

XVG-ACMP-BASELINE		96.60 240	96.52 230	96.84 288	98.41 280	93.29 317	99.99 189	99.32 215	97.76 113	98.51 237	99.29 280	81.95 324	99.54 205	98.40 209	95.03 247	97.68 289

XXY-MVS		97.14 219	96.63 226	98.67 196	98.65 271	98.92 175	99.54 280	99.29 227	95.57 242	97.63 278	99.83 213	87.79 289	99.35 228	98.39 210	92.95 269	97.75 238

Vis-MVSNet (Re-imp)		98.99 129	98.89 130	99.29 161	99.64 161	98.89 176	99.98 207	99.31 220	96.74 192	99.48 177	100.00 1	98.11 143	99.10 236	98.39 210	98.34 176	99.89 150

UA-Net		99.06 118	98.83 132	99.74 113	99.52 194	99.40 135	99.08 328	99.45 99	97.64 125	99.83 151	100.00 1	95.80 198	99.94 148	98.35 212	99.80 135	99.88 161

ACMH+	96.20 13	96.49 246	96.33 239	97.00 279	99.06 243	93.80 311	99.81 242	99.31 220	97.32 161	95.89 314	99.97 177	82.62 322	99.54 205	98.34 213	94.63 253	97.65 300

test_post1							99.32 297				88.24 349	99.33 55	99.59 190	98.31 214

SCA		98.30 175	97.98 187	99.23 166	99.41 214	98.25 210	99.99 189	99.45 99	96.91 185	99.76 164	99.58 259	89.65 269	99.54 205	98.31 214	98.79 157	99.91 135

MDTV_nov1_ep13			98.94 123		99.53 189	98.36 202	99.39 291	99.46 92	96.54 208	99.99 97	99.63 250	98.92 111	99.86 160	98.30 216	98.71 159

OPM-MVS		97.21 214	97.18 214	97.32 268	98.08 296	94.66 298	100.00 1	99.28 232	98.65 53	98.92 208	99.98 169	86.03 304	99.56 197	98.28 217	95.41 229	97.72 275

Anonymous20231211		96.29 257	95.70 265	98.07 235	99.80 132	97.49 243	99.15 320	99.40 173	89.11 326	97.75 275	99.45 273	88.93 279	98.98 244	98.26 218	89.47 309	97.73 269

CVMVSNet		98.56 160	98.47 161	98.82 189	99.11 235	97.67 238	99.74 255	99.47 77	97.57 137	99.06 202	100.00 1	95.72 200	98.97 246	98.21 219	97.33 213	99.83 173

PCF-MVS	98.23 3	98.69 152	98.37 168	99.62 125	99.78 136	99.02 167	99.23 309	99.06 309	96.43 213	98.08 259	100.00 1	94.72 213	99.95 137	98.16 220	99.91 126	99.90 144
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
RPSCF		97.37 209	98.24 173	94.76 311	99.80 132	84.57 342	99.99 189	99.05 311	94.95 257	99.82 158	100.00 1	94.03 220	100.00 1	98.15 221	98.38 174	99.70 203

CANet_DTU		99.02 125	98.90 129	99.41 149	99.88 116	98.71 184	100.00 1	99.29 227	98.84 40	100.00 1	100.00 1	94.02 221	100.00 1	98.08 222	99.96 120	99.52 212

CDS-MVSNet		98.96 133	98.95 122	99.01 178	99.48 205	98.36 202	99.93 226	99.37 191	96.79 190	99.31 186	99.83 213	99.77 7	98.91 250	98.07 223	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		96.73 233	96.25 241	98.18 225	98.21 291	98.67 187	99.77 251	99.32 215	95.06 255	97.20 292	99.65 242	90.10 263	98.19 303	98.06 224	88.90 314	97.66 295

miper_enhance_ethall		98.33 173	98.27 171	98.51 204	99.66 155	99.04 165	100.00 1	99.22 255	97.53 141	98.51 237	99.38 276	99.49 35	98.75 270	98.02 225	92.61 272	97.76 228

anonymousdsp		97.16 217	96.88 218	98.00 245	97.08 327	98.06 220	99.81 242	99.15 273	94.58 266	97.84 271	99.62 254	90.49 259	98.60 280	97.98 226	95.32 232	97.33 322

UniMVSNet_NR-MVSNet		97.16 217	96.80 220	98.22 222	98.38 281	98.41 195	100.00 1	99.45 99	96.14 226	97.76 272	99.64 246	95.05 209	98.50 290	97.98 226	86.84 327	97.75 238

DU-MVS		96.93 228	96.49 231	98.22 222	98.31 284	98.41 195	100.00 1	99.37 191	96.41 215	97.76 272	99.65 242	92.14 243	98.50 290	97.98 226	86.84 327	97.75 238

TAMVS		98.76 147	98.73 141	98.86 188	99.44 212	97.69 237	99.57 277	99.34 211	96.57 206	99.12 197	99.81 219	98.83 117	99.16 234	97.97 229	97.91 196	99.73 202

新几何1				99.99 9	100.00 1	99.96 20		99.81 38	97.89 102	100.00 1	100.00 1	99.20 79	100.00 1	97.91 230	100.00 1	100.00 1

UniMVSNet_ETH3D		95.28 283	94.41 288	97.89 253	98.91 260	95.14 283	99.13 322	99.35 206	92.11 311	97.17 293	99.66 240	70.28 345	99.36 226	97.88 231	95.18 241	99.16 217

PatchMatch-RL		99.02 125	98.78 137	99.74 113	99.99 54	99.29 144	100.00 1	100.00 1	98.38 66	99.89 145	99.81 219	93.14 233	99.99 89	97.85 232	99.98 115	99.95 121

TDRefinement		91.93 302	90.48 309	96.27 299	81.60 351	92.65 323	99.10 326	97.61 344	93.96 285	93.77 326	99.85 210	80.03 329	99.53 210	97.82 233	70.59 346	96.63 331

PS-CasMVS		96.34 255	95.78 261	98.03 244	98.18 293	98.27 209	99.71 261	99.32 215	94.75 260	96.82 301	99.65 242	86.98 297	98.15 305	97.74 234	88.85 315	97.66 295

Fast-Effi-MVS+-dtu		98.38 172	98.56 156	97.82 255	99.58 179	94.44 305	100.00 1	99.16 272	96.75 191	99.51 175	99.63 250	95.03 210	99.60 188	97.71 235	99.67 139	99.42 214

tpmvs		98.59 157	98.38 166	99.23 166	99.69 147	97.90 229	99.31 298	99.47 77	94.52 269	99.68 169	99.28 281	97.64 155	99.89 155	97.71 235	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	99.43 118	99.00 25	100.00 1	100.00 1	99.58 18	100.00 1	97.64 237	100.00 1	100.00 1

PatchmatchNet		99.03 121	98.96 118	99.26 164	99.49 203	98.33 204	99.38 292	99.45 99	96.64 203	99.96 110	99.58 259	99.49 35	99.50 214	97.63 238	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	98.16 228	99.11 235	97.84 234	99.74 255	99.29 227	94.39 275	98.65 226	100.00 1	97.21 167	98.88 257	97.62 239	95.31 233	97.75 238

UniMVSNet (Re)		97.29 213	96.85 219	98.59 202	98.49 278	99.13 160	100.00 1	99.42 126	96.52 210	98.24 256	98.90 307	94.93 211	98.89 254	97.54 240	87.61 323	97.75 238

IterMVS-LS		97.56 201	97.44 200	97.92 252	99.38 223	97.90 229	99.89 233	99.10 291	94.41 274	98.32 247	99.54 267	97.21 167	98.11 310	97.50 241	91.62 287	97.75 238
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Fast-Effi-MVS+		98.40 171	98.02 185	99.55 138	99.63 163	99.06 163	100.00 1	99.15 273	95.07 254	99.42 180	99.95 193	93.26 230	99.73 183	97.44 242	98.24 183	99.87 167

WR-MVS_H		96.73 233	96.32 240	97.95 248	98.26 288	97.88 231	99.72 260	99.43 118	95.06 255	96.99 295	98.68 315	93.02 234	98.53 288	97.43 243	88.33 318	97.43 317

tpm		98.24 180	98.22 177	98.32 216	99.13 234	95.79 278	99.53 281	99.12 288	95.20 253	99.96 110	99.36 277	97.58 156	99.28 231	97.41 244	96.67 221	99.88 161

LF4IMVS		96.19 260	96.18 243	96.23 300	98.26 288	92.09 326	100.00 1	97.89 341	97.82 108	97.94 267	99.87 206	82.71 321	99.38 225	97.41 244	93.71 259	97.20 324

testdata2													100.00 1	97.36 246

miper_ehance_all_eth		97.81 192	97.66 197	98.23 221	99.49 203	98.37 200	99.99 189	99.11 289	94.78 259	98.25 254	99.21 283	98.18 140	98.57 285	97.35 247	92.61 272	97.76 228

cl_fuxian		97.58 200	97.42 201	98.06 239	99.48 205	98.16 213	99.96 216	99.10 291	94.54 268	98.13 258	99.20 285	97.87 148	98.25 302	97.28 248	91.20 294	97.75 238

LTVRE_ROB	95.29 16	96.32 256	96.10 246	96.99 280	98.55 275	93.88 310	99.45 286	99.28 232	94.50 271	96.46 308	99.52 268	84.86 309	99.48 216	97.26 249	95.03 247	97.59 310
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
testing_2		90.79 307	88.26 313	98.35 213	89.11 346	98.56 191	99.70 263	99.14 278	93.70 290	73.80 346	94.06 342	55.19 350	98.76 269	97.17 250	92.50 276	97.74 262

Baseline_NR-MVSNet		96.16 264	95.70 265	97.56 263	98.28 287	96.79 266	100.00 1	97.86 342	91.93 313	97.63 278	99.47 272	92.14 243	98.35 298	97.13 251	86.83 329	97.54 313

ADS-MVSNet2		98.28 178	98.51 159	97.62 260	99.51 199	95.03 285	99.24 303	99.41 171	95.52 245	99.96 110	99.70 231	97.57 157	97.94 322	97.11 252	98.54 162	99.88 161

ADS-MVSNet		98.70 151	98.51 159	99.28 162	99.51 199	98.39 197	99.24 303	99.44 108	95.52 245	99.96 110	99.70 231	97.57 157	99.58 192	97.11 252	98.54 162	99.88 161

test_part1		94.20 291	93.33 297	96.79 290	99.01 247	93.70 312	99.12 325	99.36 197	84.32 338	95.62 316	99.56 263	78.07 336	98.91 250	97.05 254	87.88 321	97.75 238

JIA-IIPM		97.09 220	96.34 238	99.36 155	98.88 263	98.59 190	99.81 242	99.43 118	84.81 337	99.96 110	90.34 346	98.55 132	99.52 211	97.00 255	98.28 182	99.98 108

AllTest		98.55 161	98.40 165	98.99 179	99.93 108	97.35 248	100.00 1	99.40 173	97.08 177	99.09 198	99.98 169	93.37 227	99.95 137	96.94 256	99.84 132	99.68 205

TestCases				98.99 179	99.93 108	97.35 248		99.40 173	97.08 177	99.09 198	99.98 169	93.37 227	99.95 137	96.94 256	99.84 132	99.68 205

PEN-MVS		96.01 271	95.48 276	97.58 262	97.74 306	97.26 254	99.90 230	99.29 227	94.55 267	96.79 302	99.55 265	87.38 292	97.84 324	96.92 258	87.24 325	97.65 300

TranMVSNet+NR-MVSNet		96.45 247	96.01 250	97.79 256	98.00 299	97.62 240	100.00 1	99.35 206	95.98 228	97.31 289	99.64 246	90.09 264	98.00 320	96.89 259	86.80 330	97.75 238

TESTMET0.1,1		99.08 116	98.96 118	99.44 145	99.63 163	99.38 136	100.00 1	99.45 99	95.53 243	99.48 177	100.00 1	99.71 10	99.02 240	96.84 260	99.99 107	99.91 135

test-LLR		99.03 121	98.91 126	99.40 151	99.40 219	99.28 145	100.00 1	99.45 99	96.70 197	99.42 180	99.12 286	99.31 60	99.01 241	96.82 261	99.99 107	99.91 135

test-mter		98.96 133	98.82 133	99.40 151	99.40 219	99.28 145	100.00 1	99.45 99	95.44 252	99.42 180	99.12 286	99.70 11	99.01 241	96.82 261	99.99 107	99.91 135

MSDG		98.90 140	98.63 149	99.70 116	99.92 111	99.25 149	100.00 1	99.37 191	95.71 236	99.40 184	100.00 1	96.58 186	99.95 137	96.80 263	99.94 123	99.91 135

eth_miper_zixun_eth		97.47 206	97.28 209	98.06 239	99.41 214	97.94 227	99.62 273	99.08 299	94.46 273	98.19 257	99.56 263	96.91 181	98.50 290	96.78 264	91.49 289	97.74 262

NR-MVSNet		96.63 238	96.04 249	98.38 210	98.31 284	98.98 172	99.22 311	99.35 206	95.87 230	94.43 324	99.65 242	92.73 238	98.40 296	96.78 264	88.05 319	97.75 238

dp		98.72 149	98.61 151	99.03 177	99.53 189	97.39 246	99.45 286	99.39 186	95.62 240	99.94 133	99.52 268	98.83 117	99.82 170	96.77 266	98.42 170	99.89 150

tpm cat1		98.05 184	97.76 192	98.92 184	99.50 202	97.10 260	99.77 251	99.30 223	90.20 323	99.72 167	98.71 314	97.71 152	99.86 160	96.75 267	98.20 186	99.81 181

cl-mvsnet_		97.54 203	97.32 207	98.18 225	99.47 208	98.14 215	100.00 1	99.10 291	94.16 282	97.60 282	99.63 250	97.52 159	98.65 276	96.47 268	91.97 284	97.76 228

cl-mvsnet1		97.52 205	97.35 206	98.05 242	99.46 209	98.11 216	100.00 1	99.10 291	94.21 279	97.62 280	99.63 250	97.65 154	98.29 300	96.47 268	91.98 283	97.76 228

tmp_tt		75.80 319	74.26 322	80.43 330	52.91 360	53.67 358	87.42 350	97.98 339	61.80 349	67.04 352	100.00 1	76.43 339	96.40 332	96.47 268	28.26 353	91.23 344

miper_lstm_enhance		97.40 208	97.28 209	97.75 257	99.48 205	97.52 242	100.00 1	99.07 302	94.08 283	98.01 265	99.61 256	97.38 165	97.98 321	96.44 271	91.47 291	97.76 228

v148		96.29 257	95.84 257	97.63 258	97.74 306	96.53 271	100.00 1	99.07 302	93.52 295	98.01 265	99.42 275	91.22 249	98.60 280	96.37 272	87.22 326	97.75 238

DeepMVS_CX				89.98 323	98.90 261	71.46 348		99.18 266	97.61 129	96.92 296	99.83 213	86.07 302	99.83 167	96.02 273	97.65 210	98.65 222

pmmvs5		95.94 273	95.61 269	96.95 282	97.42 322	94.66 298	100.00 1	98.08 335	93.60 294	97.05 294	99.43 274	87.02 295	98.46 294	95.76 274	92.12 280	97.72 275

IterMVS		96.76 232	96.46 233	97.63 258	99.41 214	96.89 263	99.99 189	99.13 283	94.74 262	97.59 283	99.66 240	89.63 271	98.28 301	95.71 275	92.31 278	97.72 275
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v2v482		96.70 236	96.18 243	98.27 218	98.04 297	98.39 197	100.00 1	99.13 283	94.19 281	98.58 231	99.08 289	90.48 260	98.67 274	95.69 276	90.44 302	97.75 238

pmmvs4		97.17 216	96.80 220	98.27 218	97.68 308	98.64 189	100.00 1	99.18 266	94.22 278	98.55 232	99.71 228	93.67 224	98.47 293	95.66 277	92.57 275	97.71 282

ITE_SJBPF				96.84 288	98.96 258	93.49 314		98.12 333	98.12 82	98.35 244	99.97 177	84.45 310	99.56 197	95.63 278	95.25 237	97.49 314

IterMVS-SCA-FT		96.72 235	96.42 235	97.62 260	99.40 219	96.83 265	99.99 189	99.14 278	94.65 265	97.55 284	99.72 226	89.65 269	98.31 299	95.62 279	92.05 281	97.73 269

pm-mvs1		95.76 276	95.01 284	98.00 245	98.23 290	97.45 244	99.24 303	99.04 314	93.13 306	95.93 313	99.72 226	86.28 301	98.84 259	95.62 279	87.92 320	97.72 275

V42		96.65 237	96.16 245	98.11 234	98.17 294	98.23 211	99.99 189	99.09 297	93.97 284	98.74 223	99.05 292	91.09 252	98.82 260	95.46 281	89.90 304	97.27 323

EU-MVSNet		96.63 238	96.53 229	96.94 283	97.59 313	96.87 264	99.76 253	99.47 77	96.35 218	96.85 300	99.78 223	92.57 240	96.27 335	95.33 282	91.08 295	97.68 289

GBi-Net		96.07 268	95.80 259	96.89 285	99.53 189	94.87 286	99.18 312	99.27 240	93.71 287	98.53 234	98.81 310	84.23 313	98.07 315	95.31 283	93.60 260	97.72 275

test1		96.07 268	95.80 259	96.89 285	99.53 189	94.87 286	99.18 312	99.27 240	93.71 287	98.53 234	98.81 310	84.23 313	98.07 315	95.31 283	93.60 260	97.72 275

FMVSNet3		97.30 212	96.95 216	98.37 211	99.65 156	99.25 149	99.71 261	99.28 232	94.23 277	98.53 234	98.91 306	93.30 229	98.11 310	95.31 283	93.60 260	97.73 269

MVS_0304		95.11 286	94.84 287	95.91 304	99.60 171	91.24 332	98.64 337	99.88 33	94.51 270	99.62 172	98.31 328	69.19 347	98.82 260	95.22 286	98.60 160	97.66 295

GA-MVS		97.72 194	97.27 211	99.06 172	99.24 232	97.93 228	100.00 1	99.24 249	95.80 235	98.99 206	99.64 246	89.77 267	99.36 226	95.12 287	97.62 211	99.89 150

ambc				88.45 324	86.84 347	70.76 349	97.79 344	98.02 338		90.91 334	95.14 337	38.69 355	98.51 289	94.97 288	84.23 335	96.09 336

OurMVSNet-221017-0		96.14 266	95.98 252	96.62 293	97.49 319	93.44 315	99.92 227	98.16 331	95.86 232	97.65 277	99.95 193	85.71 307	98.78 264	94.93 289	94.18 258	97.64 303

SixPastTwentyTwo		95.71 277	95.49 274	96.38 297	97.42 322	93.01 318	99.84 239	98.23 330	94.75 260	95.98 312	99.97 177	85.35 308	98.43 295	94.71 290	93.17 266	97.69 287

DTE-MVSNet		95.52 279	94.99 285	97.08 275	97.49 319	96.45 272	100.00 1	99.25 246	93.82 286	96.17 309	99.57 262	87.81 288	97.18 328	94.57 291	86.26 332	97.62 306

UnsupCasMVSNet_eth		94.25 290	93.89 289	95.34 305	97.63 309	92.13 325	99.73 258	99.36 197	94.88 258	92.78 328	98.63 317	82.72 320	96.53 331	94.57 291	84.73 334	97.36 320

CMPMVS	66.12 22	90.65 308	92.04 303	86.46 327	96.18 332	66.87 351	98.03 342	99.38 189	83.38 341	85.49 342	99.55 265	77.59 337	98.80 263	94.44 293	94.31 257	93.72 342
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs6		93.64 294	92.87 299	95.94 303	97.47 321	91.41 331	98.92 332	99.02 315	87.84 333	95.01 319	99.61 256	77.24 338	98.77 267	94.33 294	86.41 331	97.63 304

Patchmtry		96.81 230	96.37 236	98.14 229	99.31 226	98.55 192	98.91 333	99.00 318	90.45 320	97.92 268	98.98 299	96.94 179	98.12 308	94.27 295	91.53 288	97.75 238

tfpnnormal		96.36 253	95.69 268	98.37 211	98.55 275	98.71 184	99.69 266	99.45 99	93.16 305	96.69 306	99.71 228	88.44 286	98.99 243	94.17 296	91.38 292	97.41 318

v8		96.35 254	95.73 264	98.21 224	98.11 295	98.23 211	99.94 225	99.07 302	92.66 310	98.29 249	99.00 298	91.46 247	98.77 267	94.17 296	88.83 316	97.62 306

MIMVSNet		97.06 223	96.73 223	98.05 242	99.38 223	96.64 270	98.47 339	99.35 206	93.41 297	99.48 177	98.53 320	89.66 268	97.70 326	94.16 298	98.11 190	99.80 191

Patchmatch-RL test		93.49 295	93.63 293	93.05 320	91.78 341	83.41 343	98.21 341	96.95 346	91.58 315	91.05 333	97.64 331	99.40 52	95.83 339	94.11 299	81.95 338	99.91 135

FMVSNet2		96.22 259	95.60 270	98.06 239	99.53 189	98.33 204	99.45 286	99.27 240	93.71 287	98.03 262	98.84 309	84.23 313	98.10 313	93.97 300	93.40 264	97.73 269

K. test v3		95.46 281	95.14 282	96.40 296	97.53 316	93.40 316	99.99 189	99.23 253	95.49 248	92.70 331	99.73 225	84.26 312	98.12 308	93.94 301	93.38 265	97.68 289

v1144		96.51 243	95.97 253	98.13 232	97.98 300	98.04 222	99.99 189	99.08 299	93.51 296	98.62 229	98.98 299	90.98 255	98.62 277	93.79 302	90.79 298	97.74 262

TinyColmap		95.50 280	95.12 283	96.64 292	98.69 270	93.00 319	99.40 290	97.75 343	96.40 216	96.14 310	99.87 206	79.47 331	99.50 214	93.62 303	94.72 252	97.40 319

USDC		95.90 274	95.70 265	96.50 295	98.60 274	92.56 324	100.00 1	98.30 329	97.77 111	96.92 296	99.94 197	81.25 328	99.45 220	93.54 304	94.96 250	97.49 314

MS-PatchMatch		95.66 278	95.87 256	95.05 307	97.80 305	89.25 335	98.88 334	99.30 223	96.35 218	96.86 299	99.01 297	81.35 327	99.43 221	93.30 305	99.98 115	96.46 332

v144192		96.40 251	95.81 258	98.17 227	97.89 303	98.11 216	99.99 189	99.06 309	93.39 298	98.75 221	99.09 288	90.43 261	98.66 275	93.10 306	90.55 301	97.75 238

MVP-Stereo		96.51 243	96.48 232	96.60 294	95.65 335	94.25 307	98.84 335	98.16 331	95.85 234	95.23 318	99.04 293	92.54 241	99.13 235	92.98 307	99.98 115	96.43 333
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
FMVSNet1		94.45 288	93.63 293	96.89 285	98.87 265	94.87 286	99.18 312	99.27 240	90.95 319	97.31 289	98.81 310	72.89 342	98.07 315	92.61 308	92.81 270	97.72 275

test123		79.44 315	79.23 319	80.05 331	80.03 352	71.72 347	100.00 1	77.93 360	62.52 348	94.81 320	99.69 233	78.21 335	74.53 354	92.57 309	27.33 354	93.90 340

v7n		96.06 270	95.42 279	97.99 247	97.58 314	97.35 248	99.86 237	99.11 289	92.81 309	97.91 269	99.49 270	90.99 254	98.92 249	92.51 310	88.49 317	97.70 283

lessismore_v0				96.05 301	97.55 315	91.80 328		99.22 255		91.87 332	99.91 202	83.50 318	98.68 273	92.48 311	90.42 303	97.68 289

EG-PatchMatch MVS		92.94 298	92.49 302	94.29 315	95.87 334	87.07 339	99.07 330	98.11 334	93.19 304	88.98 337	98.66 316	70.89 344	99.08 237	92.43 312	95.21 239	96.72 330

v10		96.14 266	95.50 272	98.07 235	98.19 292	97.96 225	99.83 240	99.07 302	92.10 312	98.07 260	98.94 304	91.07 253	98.61 278	92.41 313	89.82 305	97.63 304

test0.0.03 1		98.12 183	98.03 184	98.39 209	99.11 235	98.07 219	100.00 1	99.93 26	96.70 197	96.91 298	99.95 193	99.31 60	98.19 303	91.93 314	98.44 168	98.91 219

our_test_3		96.51 243	96.35 237	96.98 281	97.61 311	95.05 284	99.98 207	99.01 317	94.68 263	96.77 304	99.06 290	95.87 197	98.14 306	91.81 315	92.37 277	97.75 238

MVS-HIRNet		94.12 292	92.73 301	98.29 217	99.33 225	95.95 275	99.38 292	99.19 263	74.54 345	98.26 253	86.34 350	86.07 302	99.06 238	91.60 316	99.87 130	99.85 169

v1921920		96.16 264	95.50 272	98.14 229	97.88 304	97.96 225	99.99 189	99.07 302	93.33 300	98.60 230	99.24 282	89.37 273	98.71 272	91.28 317	90.74 299	97.75 238

CR-MVSNet		98.02 186	97.71 196	98.93 183	99.31 226	98.86 177	99.13 322	99.00 318	96.53 209	99.96 110	98.98 299	96.94 179	98.10 313	91.18 318	98.40 171	99.84 170

v1192		96.18 261	95.49 274	98.26 220	98.01 298	98.15 214	99.99 189	99.08 299	93.36 299	98.54 233	98.97 302	89.47 272	98.89 254	91.15 319	90.82 297	97.75 238

DSMNet-mixed		95.18 285	95.21 281	95.08 306	96.03 333	90.21 333	99.65 270	93.64 353	92.91 308	98.34 245	97.40 332	90.05 265	95.51 341	91.02 320	97.86 198	99.51 213

YYNet1		92.44 300	90.92 307	97.03 277	96.20 331	97.06 261	99.99 189	99.14 278	88.21 331	67.93 350	98.43 324	88.63 281	96.28 334	90.64 321	89.08 313	97.74 262

UnsupCasMVSNet_bld		89.50 311	88.00 314	93.99 318	95.30 337	88.86 336	98.52 338	99.28 232	85.50 336	87.80 340	94.11 341	61.63 349	96.96 329	90.63 322	79.26 341	96.15 334

PM-MVS		88.39 312	87.41 315	91.31 322	91.73 342	82.02 345	99.79 245	96.62 348	91.06 318	90.71 335	95.73 335	48.60 353	95.96 337	90.56 323	81.91 339	95.97 337

pmmvs-eth3d		91.73 305	90.67 308	94.92 310	91.63 343	92.71 322	99.90 230	98.54 327	91.19 317	88.08 338	95.50 336	79.31 333	96.13 336	90.55 324	81.32 340	95.91 338

MDA-MVSNet_test_wron		92.61 299	91.09 306	97.19 274	96.71 329	97.26 254	100.00 1	99.14 278	88.61 328	67.90 351	98.32 327	89.03 276	96.57 330	90.47 325	89.59 307	97.74 262

testgi		96.18 261	95.93 254	96.93 284	98.98 256	94.20 309	100.00 1	99.07 302	97.16 171	96.06 311	99.86 208	84.08 316	97.79 325	90.38 326	97.80 204	98.81 220

Patchmatch-test		97.83 191	97.42 201	99.06 172	99.08 238	97.66 239	98.66 336	99.21 260	93.65 292	98.25 254	99.58 259	99.47 39	99.57 193	90.25 327	98.59 161	99.95 121

ppachtmachnet_test		96.17 263	95.89 255	97.02 278	97.61 311	95.24 281	99.99 189	99.24 249	93.31 301	96.71 305	99.62 254	94.34 218	98.07 315	89.87 328	92.30 279	97.75 238

v1240		95.96 272	95.25 280	98.07 235	97.91 302	97.87 233	99.96 216	99.07 302	93.24 303	98.64 228	98.96 303	88.98 278	98.61 278	89.58 329	90.92 296	97.75 238

test_0402		94.35 289	93.70 292	96.32 298	97.92 301	93.60 313	99.61 274	98.85 325	88.19 332	94.68 321	99.48 271	80.01 330	98.58 284	89.39 330	95.15 243	96.77 329

TransMVSNet (Re)		94.78 287	93.72 291	97.93 251	98.34 282	97.88 231	99.23 309	97.98 339	91.60 314	94.55 322	99.71 228	87.89 287	98.36 297	89.30 331	84.92 333	97.56 312

MDA-MVSNet-bldmvs		91.65 306	89.94 310	96.79 290	96.72 328	96.70 268	99.42 289	98.94 320	88.89 327	66.97 353	98.37 325	81.43 326	95.91 338	89.24 332	89.46 310	97.75 238

EPNet_dtu		98.53 163	98.23 175	99.43 147	99.92 111	99.01 169	99.96 216	99.47 77	98.80 45	99.96 110	99.96 186	98.56 131	99.30 230	87.78 333	99.68 138	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
FMVSNet5		95.32 282	95.43 278	94.99 308	99.39 222	92.99 320	99.25 302	99.24 249	90.45 320	97.44 287	98.45 322	95.78 199	94.39 343	87.02 334	91.88 285	97.59 310

OpenMVS_ROB	88.34 20	91.89 303	91.12 305	94.19 317	95.55 336	87.63 338	99.26 301	98.03 336	86.61 334	90.65 336	96.82 333	70.14 346	98.78 264	86.54 335	96.50 222	96.15 334

N_pmnet		91.88 304	93.37 296	87.40 326	97.24 326	66.33 352	99.90 230	91.05 355	89.77 325	95.65 315	98.58 319	90.05 265	98.11 310	85.39 336	92.72 271	97.75 238

new-patchmatchnet		90.30 310	89.46 311	92.84 321	90.77 344	88.55 337	99.83 240	98.80 326	90.07 324	87.86 339	95.00 339	78.77 334	94.30 344	84.86 337	79.15 342	95.68 339

new_pmnet		94.11 293	93.47 295	96.04 302	96.60 330	92.82 321	99.97 213	98.91 323	90.21 322	95.26 317	98.05 329	85.89 305	98.14 306	84.28 338	92.01 282	97.16 325

LCM-MVSNet		79.01 317	76.93 321	85.27 328	78.28 353	68.01 350	96.57 345	98.03 336	55.10 351	82.03 344	93.27 343	31.99 358	93.95 345	82.72 339	74.37 345	93.84 341

pmmvs3		90.62 309	89.36 312	94.40 313	90.53 345	91.49 330	100.00 1	96.73 347	84.21 339	93.65 327	96.65 334	82.56 323	94.83 342	82.28 340	77.62 344	96.89 328

FPMVS		77.92 318	79.45 318	73.34 335	76.87 354	46.81 359	98.24 340	99.05 311	59.89 350	73.55 347	98.34 326	36.81 356	86.55 349	80.96 341	91.35 293	86.65 347

TAPA-MVS	96.40 10	97.64 196	97.37 205	98.45 206	99.94 106	95.70 279	100.00 1	99.40 173	97.65 123	99.53 174	100.00 1	99.31 60	99.66 187	80.48 342	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
PatchT		95.90 274	94.95 286	98.75 193	99.03 245	98.39 197	99.08 328	99.32 215	85.52 335	99.96 110	94.99 340	97.94 146	98.05 319	80.20 343	98.47 167	99.81 181

MIMVSNet1		91.96 301	91.20 304	94.23 316	94.94 340	91.69 329	99.34 296	99.22 255	88.23 330	94.18 325	98.45 322	75.52 340	93.41 346	79.37 344	91.49 289	97.60 309

Gipuma		84.73 313	83.50 316	88.40 325	97.50 317	82.21 344	88.87 348	99.05 311	65.81 347	85.71 341	90.49 345	53.70 351	96.31 333	78.64 345	91.74 286	86.67 346
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
test20.03		93.11 297	92.85 300	93.88 319	95.19 338	91.83 327	100.00 1	98.87 324	93.68 291	92.76 329	98.88 308	89.20 275	92.71 347	77.88 346	89.19 312	97.09 326

RPMNet		95.26 284	93.82 290	99.56 137	99.31 226	98.86 177	99.13 322	99.42 126	79.82 343	99.96 110	95.13 338	95.69 201	99.98 112	77.54 347	98.40 171	99.84 170

Anonymous20231206		93.45 296	93.17 298	94.30 314	95.00 339	89.69 334	99.98 207	98.43 328	93.30 302	94.50 323	98.59 318	90.52 258	95.73 340	77.46 348	90.73 300	97.48 316

PMMVS2		79.15 316	77.28 320	84.76 329	82.34 350	72.66 346	99.70 263	95.11 352	71.68 346	84.78 343	90.87 344	32.05 357	89.99 348	75.53 349	63.45 347	91.64 343

PMVS	60.66 23	65.98 324	65.05 325	68.75 338	55.06 359	38.40 360	88.19 349	96.98 345	48.30 355	44.82 356	88.52 348	12.22 361	86.49 350	67.58 350	83.79 336	81.35 350
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
ANet_high		66.05 323	63.44 327	73.88 334	61.14 357	63.45 355	95.68 347	87.18 357	79.93 342	47.35 355	80.68 355	22.35 359	72.33 356	61.24 351	35.42 352	85.88 348

MVE	68.59 21	67.22 322	64.68 326	74.84 332	74.67 356	62.32 356	95.84 346	90.87 356	50.98 352	58.72 354	81.05 354	12.20 362	78.95 351	61.06 352	56.75 348	83.24 349
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN		70.72 320	70.06 323	72.69 336	83.92 349	65.48 354	99.95 221	92.72 354	49.88 353	72.30 348	86.26 351	47.17 354	77.43 352	53.83 353	44.49 350	75.17 352

EMVS		69.88 321	69.09 324	72.24 337	84.70 348	65.82 353	99.96 216	87.08 359	49.82 354	71.51 349	84.74 352	49.30 352	75.32 353	50.97 354	43.71 351	75.59 351

wuyk23d		28.28 325	29.73 329	23.92 339	75.89 355	32.61 361	66.50 351	12.88 361	16.09 356	14.59 357	16.59 357	12.35 360	32.36 357	39.36 355	13.36 355	6.79 353

uanet_test		0.01 329	0.02 332	0.00 340	0.00 361	0.00 362	0.00 352	0.00 362	0.00 357	0.00 358	0.14 358	0.00 363	0.00 358	0.00 356	0.00 356	0.00 354

cdsmvs_eth3d_5k		24.41 326	32.55 328	0.00 340	0.00 361	0.00 362	0.00 352	99.39 186	0.00 357	0.00 358	100.00 1	93.55 226	0.00 358	0.00 356	0.00 356	0.00 354

pcd_1.5k_mvsjas		8.24 328	10.99 331	0.00 340	0.00 361	0.00 362	0.00 352	0.00 362	0.00 357	0.00 358	0.14 358	98.75 122	0.00 358	0.00 356	0.00 356	0.00 354

sosnet-low-res		0.01 329	0.02 332	0.00 340	0.00 361	0.00 362	0.00 352	0.00 362	0.00 357	0.00 358	0.14 358	0.00 363	0.00 358	0.00 356	0.00 356	0.00 354

sosnet		0.01 329	0.02 332	0.00 340	0.00 361	0.00 362	0.00 352	0.00 362	0.00 357	0.00 358	0.14 358	0.00 363	0.00 358	0.00 356	0.00 356	0.00 354

uncertanet		0.01 329	0.02 332	0.00 340	0.00 361	0.00 362	0.00 352	0.00 362	0.00 357	0.00 358	0.14 358	0.00 363	0.00 358	0.00 356	0.00 356	0.00 354

Regformer		0.01 329	0.02 332	0.00 340	0.00 361	0.00 362	0.00 352	0.00 362	0.00 357	0.00 358	0.14 358	0.00 363	0.00 358	0.00 356	0.00 356	0.00 354

ab-mvs-re		8.33 327	11.11 330	0.00 340	0.00 361	0.00 362	0.00 352	0.00 362	0.00 357	0.00 358	100.00 1	0.00 363	0.00 358	0.00 356	0.00 356	0.00 354

uanet		0.01 329	0.02 332	0.00 340	0.00 361	0.00 362	0.00 352	0.00 362	0.00 357	0.00 358	0.14 358	0.00 363	0.00 358	0.00 356	0.00 356	0.00 354

test_241102_ONE					100.00 1	99.99 3		99.42 126	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	99.42 126	98.93 32

test0726					100.00 1	99.99 3	100.00 1	99.42 126	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								99.42 126

test_post											89.05 347	99.49 35	99.59 190

patchmatchnet-post											97.79 330	99.41 51	99.54 205

MTMP							100.00 1	99.18 266

TEST9					100.00 1	99.95 29	100.00 1	99.42 126	97.65 123	100.00 1	100.00 1	99.53 23	99.97 117

test_8					100.00 1	99.91 52	100.00 1	99.42 126	97.70 118	100.00 1	100.00 1	99.51 28	99.98 112

agg_prior					100.00 1	99.88 78		99.42 126		100.00 1			99.97 117

test_prior4						99.93 42	100.00 1

test_prior				99.90 82	100.00 1	99.75 100		99.73 54					99.97 117			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	97.66 122	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		99.42 126		100.00 1		99.24 73	99.97 117		100.00 1	100.00 1

plane_prior7					99.00 252	94.78 296

plane_prior6					99.06 243	94.80 292						88.58 284

plane_prior4											99.97 177

plane_prior3						94.79 295			99.03 19	99.08 200

plane_prior2							100.00 1		99.00 25

plane_prior1					99.02 246

plane_prior						94.80 292	100.00 1		99.03 19						95.58 223

n2								0.00 362

nn								0.00 362

door-mid								96.32 350

test11								99.42 126

door								96.13 351

HQP5-MVS						94.82 289

HQP-NCC					99.07 239		100.00 1		99.04 14	99.17 191

ACMP_Plane					99.07 239		100.00 1		99.04 14	99.17 191

HQP4-MVS										99.17 191			99.57 193			97.77 226

HQP3-MVS								99.40 173							95.58 223

HQP2-MVS												88.61 282

NP-MVS					99.07 239	94.81 291					99.97 177

ACMMP++_ref															94.58 255

ACMMP++															95.17 242

Test By Simon												99.10 87

High-resolution multi-view benchmark