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.

MG-MVS		87.11 25	86.27 31	89.62 5	97.79 1	76.27 3	94.96 32	94.49 35	78.74 51	83.87 49	92.94 87	64.34 66	96.94 80	75.19 106	94.09 24	95.66 32

MCST-MVS		91.08 1	91.46 2	89.94 2	97.66 2	73.37 7	97.13 1	95.58 13	89.33 1	85.77 28	96.26 10	72.84 10	99.38 1	92.64 4	95.93 5	97.08 4

DP-MVS Recon		82.73 80	81.65 85	85.98 69	97.31 3	67.06 89	95.15 26	91.99 131	69.08 207	76.50 108	93.89 71	54.48 172	98.20 24	70.76 142	85.66 105	92.69 129

CNVR-MVS		90.32 3	90.89 4	88.61 11	96.76 4	70.65 20	96.47 6	94.83 25	84.83 9	89.07 11	96.80 4	70.86 15	99.06 3	92.64 4	95.71 6	96.12 21

NCCC		89.07 8	89.46 8	87.91 17	96.60 5	69.05 43	96.38 7	94.64 32	84.42 10	86.74 23	96.20 11	66.56 39	98.76 11	89.03 18	94.56 20	95.92 28

AdaColmap		78.94 138	77.00 151	84.76 106	96.34 6	65.86 135	92.66 96	87.97 260	62.18 274	70.56 160	92.37 100	43.53 259	97.35 52	64.50 195	82.86 124	91.05 157

test_part2					96.29 7	68.16 64				90.78 4

v1.0		37.26 329	49.67 321	0.00 354	96.29 7	0.00 369	0.00 360	94.26 42	68.52 217	90.78 4	97.23 3	0.00 371	0.00 366	0.00 363	0.00 363	0.00 364

ESAPD		88.77 9	89.21 9	87.45 29	96.26 9	67.56 76	94.17 38	94.15 44	68.77 211	90.74 6	97.27 2	76.09 4	98.49 16	90.58 10	94.91 11	96.30 16

MAR-MVS		84.18 61	83.43 61	86.44 57	96.25 10	65.93 134	94.28 37	94.27 41	74.41 103	79.16 81	95.61 24	53.99 178	98.88 9	69.62 150	93.26 38	94.50 77
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
API-MVS		82.28 87	80.53 98	87.54 27	96.13 11	70.59 21	93.63 65	91.04 168	65.72 242	75.45 116	92.83 92	56.11 146	98.89 8	64.10 198	89.75 76	93.15 118

APDe-MVS		87.54 19	87.84 16	86.65 47	96.07 12	66.30 126	94.84 34	93.78 50	69.35 203	88.39 14	96.34 9	67.74 30	97.66 38	90.62 9	93.44 36	96.01 25

PAPR		85.15 49	84.47 50	87.18 35	96.02 13	68.29 60	91.85 130	93.00 95	76.59 77	79.03 82	95.00 42	61.59 89	97.61 42	78.16 89	89.00 79	95.63 34

APD-MVS		85.93 41	85.99 35	85.76 79	95.98 14	65.21 147	93.59 67	92.58 110	66.54 234	86.17 24	95.88 17	63.83 70	97.00 72	86.39 35	92.94 40	95.06 55
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
DeepC-MVS_fast	79.48 2	87.95 15	88.00 15	87.79 20	95.86 15	68.32 59	95.74 13	94.11 45	83.82 12	83.49 50	96.19 12	64.53 64	98.44 19	83.42 55	94.88 14	96.61 9
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DP-MVS		69.90 258	66.48 265	80.14 212	95.36 16	62.93 201	89.56 200	76.11 330	50.27 324	57.69 279	85.23 194	39.68 275	95.73 117	33.35 333	71.05 210	81.78 291

114514_t		79.17 134	77.67 136	83.68 131	95.32 17	65.53 143	92.85 88	91.60 146	63.49 263	67.92 206	90.63 120	46.65 242	95.72 121	67.01 171	83.54 122	89.79 168

Regformer-1		87.24 23	87.60 20	86.15 67	95.14 18	65.83 137	93.95 52	95.12 18	82.11 21	84.25 43	95.73 20	67.88 28	98.35 21	85.60 39	88.64 81	94.26 81

Regformer-2		87.00 27	87.43 22	85.71 82	95.14 18	64.73 159	93.95 52	94.95 22	81.69 26	84.03 47	95.73 20	67.35 33	98.19 25	85.40 41	88.64 81	94.20 83

HPM-MVS++		89.37 7	89.95 7	87.64 23	95.10 20	68.23 63	95.24 23	94.49 35	82.43 17	88.90 12	96.35 8	71.89 14	98.63 13	88.76 20	96.40 2	96.06 22

CSCG		86.87 29	86.26 32	88.72 9	95.05 21	70.79 19	93.83 61	95.33 15	68.48 219	77.63 95	94.35 62	73.04 9	98.45 18	84.92 44	93.71 32	96.92 6

LFMVS		84.34 58	82.73 74	89.18 8	94.76 22	73.25 8	94.99 31	91.89 135	71.90 160	82.16 56	93.49 77	47.98 232	97.05 67	82.55 59	84.82 109	97.25 2

CDPH-MVS		85.71 44	85.46 44	86.46 56	94.75 23	67.19 85	93.89 57	92.83 100	70.90 183	83.09 52	95.28 32	63.62 73	97.36 51	80.63 73	94.18 23	94.84 64

test_prior3		87.38 21	87.70 18	86.42 58	94.71 24	67.35 81	95.10 28	93.10 90	75.40 92	85.25 35	95.61 24	67.94 25	96.84 84	87.47 25	94.77 15	95.05 56

test_prior				86.42 58	94.71 24	67.35 81		93.10 90					96.84 84			95.05 56

test12				87.09 39	94.60 26	68.86 47		92.91 97		82.67 54		65.44 50	97.55 43		93.69 33	94.84 64

0601test		84.28 59	83.16 67	87.64 23	94.52 27	69.24 40	95.78 11	95.09 21	69.19 205	81.09 62	92.88 91	57.00 132	97.44 47	81.11 72	81.76 132	96.23 19

CANet		89.61 6	89.99 6	88.46 13	94.39 28	69.71 34	96.53 5	93.78 50	86.89 4	89.68 8	95.78 18	65.94 44	99.10 2	92.99 1	93.91 27	96.58 11

agg_prior3		86.93 28	87.08 26	86.48 55	94.21 29	66.95 94	94.14 42	93.40 74	71.80 167	84.86 37	95.13 39	66.16 41	97.25 61	89.09 15	94.90 12	95.25 49

test_8					94.19 30	67.19 85	94.15 41	93.42 73	71.87 162	85.38 33	95.35 28	68.19 22	96.95 79

TEST9					94.18 31	67.28 83	94.16 39	93.51 62	71.75 170	85.52 31	95.33 29	68.01 24	97.27 59

train_agg		87.21 24	87.42 23	86.60 49	94.18 31	67.28 83	94.16 39	93.51 62	71.87 162	85.52 31	95.33 29	68.19 22	97.27 59	89.09 15	94.90 12	95.25 49

Regformer-3		85.80 43	85.92 36	85.46 86	94.17 33	65.09 153	92.95 84	95.11 19	81.13 27	81.68 59	95.04 40	65.82 46	98.32 22	83.02 56	84.36 113	92.97 124

Regformer-4		85.45 46	85.69 42	84.73 108	94.17 33	63.23 194	92.95 84	94.83 25	80.66 29	81.29 61	95.04 40	65.12 52	98.08 28	82.74 57	84.36 113	92.88 128

agg_prior1		87.02 26	87.26 25	86.28 65	94.16 35	66.97 92	94.08 45	93.31 78	71.85 164	84.49 41	95.39 27	68.91 18	96.75 88	88.84 19	94.32 22	95.13 53

agg_prior					94.16 35	66.97 92		93.31 78		84.49 41			96.75 88

PAPM_NR		82.97 78	81.84 82	86.37 61	94.10 37	66.76 105	87.66 243	92.84 99	69.96 198	74.07 127	93.57 75	63.10 81	97.50 45	70.66 143	90.58 70	94.85 63

VNet		86.20 38	85.65 43	87.84 19	93.92 38	69.99 28	95.73 15	95.94 12	78.43 53	86.00 26	93.07 84	58.22 118	97.00 72	85.22 42	84.33 116	96.52 13

PVSNet_BlendedMVS		83.38 72	83.43 61	83.22 138	93.76 39	67.53 78	94.06 46	93.61 58	79.13 43	81.00 64	85.14 195	63.19 79	97.29 56	87.08 30	73.91 189	84.83 258

PVSNet_Blended		86.73 33	86.86 29	86.31 64	93.76 39	67.53 78	96.33 8	93.61 58	82.34 18	81.00 64	93.08 82	63.19 79	97.29 56	87.08 30	91.38 61	94.13 89

HFP-MVS		84.73 53	84.40 52	85.72 80	93.75 41	65.01 154	93.50 70	93.19 85	72.19 154	79.22 79	94.93 45	59.04 113	97.67 35	81.55 66	92.21 48	94.49 78

#test#		84.98 51	84.74 49	85.72 80	93.75 41	65.01 154	94.09 44	93.19 85	73.55 128	79.22 79	94.93 45	59.04 113	97.67 35	82.66 58	92.21 48	94.49 78

Anonymous202405211		77.96 159	75.33 179	85.87 72	93.73 43	64.52 161	94.85 33	85.36 294	62.52 272	76.11 109	90.18 127	29.43 324	97.29 56	68.51 160	77.24 168	95.81 29

SD-MVS		87.49 20	87.49 21	87.50 28	93.60 44	68.82 49	93.90 56	92.63 108	76.86 72	87.90 17	95.76 19	66.17 40	97.63 40	89.06 17	91.48 60	96.05 23

ACMMPR		84.37 56	84.06 54	85.28 94	93.56 45	64.37 170	93.50 70	93.15 88	72.19 154	78.85 85	94.86 49	56.69 139	97.45 46	81.55 66	92.20 50	94.02 97

region2R		84.36 57	84.03 55	85.36 92	93.54 46	64.31 172	93.43 73	92.95 96	72.16 157	78.86 84	94.84 50	56.97 133	97.53 44	81.38 69	92.11 52	94.24 82

TSAR-MVS + GP.		87.96 14	88.37 12	86.70 46	93.51 47	65.32 145	95.15 26	93.84 49	78.17 55	85.93 27	94.80 51	75.80 5	98.21 23	89.38 12	88.78 80	96.59 10

PHI-MVS		86.83 31	86.85 30	86.78 45	93.47 48	65.55 142	95.39 21	95.10 20	71.77 169	85.69 30	96.52 6	62.07 86	98.77 10	86.06 37	95.60 7	96.03 24

EPNet		87.84 17	88.38 11	86.23 66	93.30 49	66.05 130	95.26 22	94.84 24	87.09 3	88.06 15	94.53 55	66.79 36	97.34 53	83.89 52	91.68 56	95.29 44
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
SMA-MVS		88.14 11	88.31 14	87.66 22	93.25 50	68.72 50	93.85 58	94.03 46	74.18 113	91.74 2	96.72 5	65.61 49	98.48 17	89.29 14	96.08 3	95.79 30

XVS		83.87 67	83.47 59	85.05 99	93.22 51	63.78 181	92.92 86	92.66 106	73.99 115	78.18 89	94.31 65	55.25 152	97.41 48	79.16 81	91.58 58	93.95 99

X-MVStestdata		76.86 180	74.13 195	85.05 99	93.22 51	63.78 181	92.92 86	92.66 106	73.99 115	78.18 89	10.19 362	55.25 152	97.41 48	79.16 81	91.58 58	93.95 99

原ACMM1				84.42 117	93.21 53	64.27 175		93.40 74	65.39 243	79.51 77	92.50 95	58.11 120	96.69 90	65.27 189	93.96 25	92.32 139

MVS_111021_HR		86.19 39	85.80 39	87.37 31	93.17 54	69.79 32	93.99 50	93.76 53	79.08 45	78.88 83	93.99 69	62.25 85	98.15 26	85.93 38	91.15 64	94.15 88

CP-MVS		83.71 71	83.40 63	84.65 111	93.14 55	63.84 179	94.59 35	92.28 117	71.03 181	77.41 98	94.92 47	55.21 155	96.19 100	81.32 70	90.70 68	93.91 102

DELS-MVS		90.05 4	90.09 5	89.94 2	93.14 55	73.88 6	97.01 2	94.40 39	88.32 2	85.71 29	94.91 48	74.11 8	98.91 6	87.26 28	95.94 4	97.03 5
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
MVS_0304		88.39 10	88.35 13	88.50 12	93.01 57	70.11 25	95.90 10	92.20 124	86.27 6	88.70 13	95.92 16	56.76 135	99.02 4	92.68 3	93.76 30	96.37 15

DeepPCF-MVS	81.17 1	89.72 5	91.38 3	84.72 110	93.00 58	58.16 268	96.72 3	94.41 38	86.50 5	90.25 7	97.83 1	75.46 6	98.67 12	92.78 2	95.49 8	97.32 1

PLC	68.80 14	75.23 205	73.68 202	79.86 221	92.93 59	58.68 266	90.64 177	88.30 253	60.90 282	64.43 240	90.53 121	42.38 263	94.57 151	56.52 241	76.54 172	86.33 227
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
DWT-MVSNet_test		83.95 65	82.80 72	87.41 30	92.90 60	70.07 27	89.12 210	94.42 37	82.15 20	77.64 94	91.77 107	70.81 16	96.22 99	65.03 190	81.36 133	95.94 26

HSP-MVS		90.38 2	91.89 1	85.84 74	92.83 61	64.03 178	93.06 80	94.52 33	82.19 19	93.65 1	96.15 13	85.89 1	97.19 62	91.02 8	97.75 1	96.29 17

mPP-MVS		82.96 79	82.44 76	84.52 115	92.83 61	62.92 203	92.76 89	91.85 137	71.52 176	75.61 114	94.24 66	53.48 187	96.99 75	78.97 84	90.73 67	93.64 107

WTY-MVS		86.32 35	85.81 38	87.85 18	92.82 63	69.37 39	95.20 24	95.25 16	82.71 15	81.91 57	94.73 52	67.93 27	97.63 40	79.55 78	82.25 128	96.54 12

PGM-MVS		83.25 73	82.70 75	84.92 101	92.81 64	64.07 177	90.44 180	92.20 124	71.28 179	77.23 101	94.43 56	55.17 156	97.31 55	79.33 80	91.38 61	93.37 110

EI-MVSNet-Vis-set		83.77 69	83.67 56	84.06 122	92.79 65	63.56 190	91.76 135	94.81 27	79.65 36	77.87 91	94.09 67	63.35 77	97.90 31	79.35 79	79.36 143	90.74 159

MVSTER		82.47 84	82.05 79	83.74 127	92.68 66	69.01 44	91.90 127	93.21 82	79.83 32	72.14 149	85.71 192	74.72 7	94.72 148	75.72 102	72.49 199	87.50 202

MP-MVS		85.02 50	84.97 48	85.17 98	92.60 67	64.27 175	93.24 75	92.27 118	73.13 134	79.63 76	94.43 56	61.90 87	97.17 63	85.00 43	92.56 45	94.06 95
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
thres200		79.66 126	78.33 126	83.66 133	92.54 68	65.82 138	93.06 80	96.31 9	74.90 100	73.30 132	88.66 146	59.67 107	95.61 123	47.84 272	78.67 150	89.56 172

APD-MVS_3200maxsize		81.64 96	81.32 88	82.59 151	92.36 69	58.74 265	91.39 148	91.01 169	63.35 264	79.72 75	94.62 54	51.82 199	96.14 102	79.71 76	87.93 86	92.89 127

PatchFormer-LS_test		83.14 75	81.81 83	87.12 37	92.34 70	69.92 30	88.64 218	93.32 77	82.07 23	74.87 120	91.62 111	68.91 18	96.08 106	66.07 181	78.45 153	95.37 39

新几何1				84.73 108	92.32 71	64.28 174		91.46 152	59.56 292	79.77 74	92.90 89	56.95 134	96.57 93	63.40 203	92.91 41	93.34 111

1121		81.25 101	80.05 101	84.87 104	92.30 72	64.31 172	87.91 232	91.39 154	59.44 293	79.94 72	92.91 88	57.09 128	97.01 70	66.63 173	92.81 43	93.29 114

EI-MVSNet-UG-set		83.14 75	82.96 68	83.67 132	92.28 73	63.19 198	91.38 150	94.68 30	79.22 40	76.60 106	93.75 72	62.64 83	97.76 33	78.07 90	78.01 154	90.05 166

HPM-MVS		83.25 73	82.95 69	84.17 120	92.25 74	62.88 205	90.91 167	91.86 136	70.30 195	77.12 102	93.96 70	56.75 137	96.28 98	82.04 62	91.34 63	93.34 111
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
HY-MVS	76.49 5	84.28 59	83.36 65	87.02 41	92.22 75	67.74 71	84.65 269	94.50 34	79.15 42	82.23 55	87.93 159	66.88 35	96.94 80	80.53 74	82.20 129	96.39 14

tfpn200view9		78.79 142	77.43 142	82.88 142	92.21 76	64.49 162	92.05 114	96.28 10	73.48 129	71.75 154	88.26 154	60.07 104	95.32 132	45.16 282	77.58 159	88.83 176

thres400		78.68 145	77.43 142	82.43 156	92.21 76	64.49 162	92.05 114	96.28 10	73.48 129	71.75 154	88.26 154	60.07 104	95.32 132	45.16 282	77.58 159	87.48 203

PS-MVSNAJ		88.14 11	87.61 19	89.71 4	92.06 78	76.72 1	95.75 12	93.26 80	83.86 11	89.55 9	96.06 14	53.55 183	97.89 32	91.10 6	93.31 37	94.54 74

MSLP-MVS++		86.27 36	85.91 37	87.35 32	92.01 79	68.97 46	95.04 30	92.70 103	79.04 46	81.50 60	96.50 7	58.98 115	96.78 86	83.49 54	93.93 26	96.29 17

旧先验1					91.94 80	60.74 234		91.50 150			94.36 58	65.23 51			91.84 53	94.55 72

thres600view7		78.00 156	76.66 154	82.03 179	91.93 81	63.69 186	91.30 155	96.33 5	72.43 145	70.46 162	87.89 160	60.31 99	94.92 142	42.64 295	76.64 170	87.48 203

LS3D		69.17 266	66.40 266	77.50 268	91.92 82	56.12 290	85.12 266	80.37 323	46.96 331	56.50 285	87.51 168	37.25 292	93.71 199	32.52 338	79.40 142	82.68 285

GG-mvs-BLEND				86.53 54	91.91 83	69.67 36	75.02 323	94.75 28		78.67 87	90.85 116	77.91 2	94.56 152	72.25 125	93.74 31	95.36 40

tfpn111		78.00 156	76.62 155	82.13 173	91.89 84	63.21 195	91.19 161	96.33 5	72.28 149	70.45 163	87.89 160	60.31 99	94.91 143	42.61 296	76.64 170	88.27 188

conf200view11		78.32 153	77.01 149	82.27 166	91.89 84	63.21 195	91.19 161	96.33 5	72.28 149	70.45 163	87.89 160	60.31 99	95.32 132	45.16 282	77.58 159	88.27 188

thres100view900		78.37 151	77.01 149	82.46 152	91.89 84	63.21 195	91.19 161	96.33 5	72.28 149	70.45 163	87.89 160	60.31 99	95.32 132	45.16 282	77.58 159	88.83 176

zzz-MVS		84.73 53	84.47 50	85.50 84	91.89 84	65.16 148	91.55 143	92.23 119	75.32 94	80.53 67	95.21 37	56.06 147	97.16 64	84.86 45	92.55 46	94.18 84

MTAPA		83.91 66	83.38 64	85.50 84	91.89 84	65.16 148	81.75 290	92.23 119	75.32 94	80.53 67	95.21 37	56.06 147	97.16 64	84.86 45	92.55 46	94.18 84

canonicalmvs		86.85 30	86.25 33	88.66 10	91.80 89	71.92 10	93.54 69	91.71 142	80.26 31	87.55 18	95.25 35	63.59 75	96.93 82	88.18 21	84.34 115	97.11 3

TSAR-MVS + MP.		88.11 13	88.64 10	86.54 52	91.73 90	68.04 66	90.36 183	93.55 61	82.89 14	91.29 3	92.89 90	72.27 11	96.03 107	87.99 22	94.77 15	95.54 37

ACMMP		81.49 98	80.67 95	83.93 124	91.71 91	62.90 204	92.13 108	92.22 123	71.79 168	71.68 156	93.49 77	50.32 209	96.96 78	78.47 86	84.22 120	91.93 145
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
BH-RMVSNet		79.46 131	77.65 137	84.89 102	91.68 92	65.66 140	93.55 68	88.09 257	72.93 138	73.37 131	91.12 114	46.20 247	96.12 103	56.28 243	85.61 106	92.91 126

ACMMP_Plus		86.05 40	85.80 39	86.80 44	91.58 93	67.53 78	91.79 132	93.49 64	74.93 99	84.61 38	95.30 31	59.42 109	97.92 30	86.13 36	94.92 10	94.94 62

MVS_Test		84.16 62	83.20 66	87.05 40	91.56 94	69.82 31	89.99 192	92.05 129	77.77 59	82.84 53	86.57 181	63.93 69	96.09 104	74.91 112	89.18 78	95.25 49

HPM-MVS_fast		80.25 114	79.55 112	82.33 163	91.55 95	59.95 249	91.32 154	89.16 232	65.23 246	74.71 121	93.07 84	47.81 234	95.74 116	74.87 114	88.23 83	91.31 155

CPTT-MVS		79.59 128	79.16 120	80.89 205	91.54 96	59.80 251	92.10 110	88.54 250	60.42 285	72.96 134	93.28 79	48.27 228	92.80 220	78.89 85	86.50 100	90.06 165

CNLPA		74.31 220	72.30 223	80.32 209	91.49 97	61.66 222	90.85 168	80.72 322	56.67 307	63.85 244	90.64 118	46.75 240	90.84 266	53.79 251	75.99 175	88.47 184

view600		76.93 176	75.50 175	81.23 191	91.44 98	62.00 216	89.94 193	96.56 1	70.68 187	68.54 197	87.31 171	60.79 93	94.19 174	38.90 310	75.31 178	87.48 203

view800		76.93 176	75.50 175	81.23 191	91.44 98	62.00 216	89.94 193	96.56 1	70.68 187	68.54 197	87.31 171	60.79 93	94.19 174	38.90 310	75.31 178	87.48 203

conf0.05thres1000		76.93 176	75.50 175	81.23 191	91.44 98	62.00 216	89.94 193	96.56 1	70.68 187	68.54 197	87.31 171	60.79 93	94.19 174	38.90 310	75.31 178	87.48 203

tfpn		76.93 176	75.50 175	81.23 191	91.44 98	62.00 216	89.94 193	96.56 1	70.68 187	68.54 197	87.31 171	60.79 93	94.19 174	38.90 310	75.31 178	87.48 203

MP-MVS-pluss		85.24 47	85.13 47	85.56 83	91.42 102	65.59 141	91.54 144	92.51 113	74.56 102	80.62 66	95.64 23	59.15 112	97.00 72	86.94 32	93.80 28	94.07 94
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
gg-mvs-nofinetune		77.18 174	74.31 191	85.80 76	91.42 102	68.36 58	71.78 326	94.72 29	49.61 325	77.12 102	45.92 347	77.41 3	93.98 190	67.62 166	93.16 39	95.05 56

xiu_mvs_v2_base		87.92 16	87.38 24	89.55 7	91.41 104	76.43 2	95.74 13	93.12 89	83.53 13	89.55 9	95.95 15	53.45 188	97.68 34	91.07 7	92.62 44	94.54 74

alignmvs		87.28 22	86.97 27	88.24 15	91.30 105	71.14 18	95.61 17	93.56 60	79.30 38	87.07 22	95.25 35	68.43 20	96.93 82	87.87 23	84.33 116	96.65 8

EPMVS		78.49 150	75.98 163	86.02 68	91.21 106	69.68 35	80.23 303	91.20 160	75.25 96	72.48 144	78.11 275	54.65 169	93.69 200	57.66 240	83.04 123	94.69 67

FMVSNet3		77.73 162	76.04 162	82.80 143	91.20 107	68.99 45	91.87 128	91.99 131	73.35 132	67.04 217	83.19 213	56.62 140	92.14 239	59.80 230	69.34 222	87.28 214

Anonymous20240529		76.84 182	74.15 194	84.88 103	91.02 108	64.95 157	93.84 60	91.09 165	53.57 314	73.00 133	87.42 169	35.91 302	97.32 54	69.14 155	72.41 201	92.36 137

tpmvs		72.88 232	69.76 240	82.22 170	90.98 109	67.05 90	78.22 317	88.30 253	63.10 268	64.35 241	74.98 297	55.09 159	94.27 171	43.25 289	69.57 221	85.34 254

tfpn_ndepth		76.45 188	75.22 181	80.14 212	90.97 110	58.92 262	90.11 188	93.24 81	65.96 239	67.37 215	90.52 122	66.67 37	92.29 237	37.71 316	74.44 184	89.21 174

MVS		84.66 55	82.86 71	90.06 1	90.93 111	74.56 5	87.91 232	95.54 14	68.55 216	72.35 148	94.71 53	59.78 106	98.90 7	81.29 71	94.69 19	96.74 7

PVSNet	73.49 8	80.05 118	78.63 124	84.31 118	90.92 112	64.97 156	92.47 102	91.05 167	79.18 41	72.43 146	90.51 123	37.05 297	94.06 184	68.06 161	86.00 103	93.90 103

3Dnovator+	73.60 7	82.10 92	80.60 97	86.60 49	90.89 113	66.80 104	95.20 24	93.44 72	74.05 114	67.42 212	92.49 96	49.46 218	97.65 39	70.80 141	91.68 56	95.33 41

VDD-MVS		83.06 77	81.81 83	86.81 43	90.86 114	67.70 72	95.40 20	91.50 150	75.46 89	81.78 58	92.34 101	40.09 274	97.13 66	86.85 33	82.04 130	95.60 35

BH-w/o		80.49 111	79.30 117	84.05 123	90.83 115	64.36 171	93.60 66	89.42 223	74.35 108	69.09 187	90.15 128	55.23 154	95.61 123	64.61 193	86.43 101	92.17 143

casdiffmvs1		86.26 37	85.70 41	87.97 16	90.76 116	71.19 15	90.74 173	93.07 92	76.57 78	88.02 16	87.85 164	67.81 29	96.48 95	87.22 29	89.22 77	96.23 19

casdiffmvs		85.23 48	84.38 53	87.79 20	90.73 117	71.38 13	90.71 174	92.52 112	77.08 68	84.58 39	87.18 177	64.43 65	96.34 97	84.32 47	87.86 87	95.65 33

Anonymous20231211		73.08 228	70.39 235	81.13 197	90.62 118	63.33 192	91.40 147	90.06 203	51.84 319	64.46 239	80.67 252	36.49 299	94.07 183	63.83 199	64.17 263	85.98 239

TR-MVS		78.77 143	77.37 145	82.95 141	90.49 119	60.88 229	93.67 64	90.07 201	70.08 197	74.51 122	91.37 112	45.69 248	95.70 122	60.12 228	80.32 138	92.29 140

SteuartSystems-ACMMP		86.82 32	86.90 28	86.58 51	90.42 120	66.38 123	96.09 9	93.87 48	77.73 60	84.01 48	95.66 22	63.39 76	97.94 29	87.40 27	93.55 35	95.42 38
Skip Steuart: Steuart Systems R&D Blog.
TAPA-MVS	70.22 12	74.94 212	73.53 209	79.17 241	90.40 121	52.07 307	89.19 208	89.61 218	62.69 270	70.07 170	92.67 94	48.89 226	94.32 168	38.26 315	79.97 139	91.12 156
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
mvs_anonymous		81.36 100	79.99 103	85.46 86	90.39 122	68.40 56	86.88 257	90.61 179	74.41 103	70.31 168	84.67 200	63.79 71	92.32 236	73.13 116	85.70 104	95.67 31

tfpn1000		75.25 204	74.00 198	79.03 245	90.30 123	57.56 276	88.55 219	93.36 76	64.14 259	65.17 231	89.76 141	67.06 34	91.46 263	34.54 331	73.09 194	88.06 194

CANet_DTU		84.09 63	83.52 57	85.81 75	90.30 123	66.82 98	91.87 128	89.01 239	85.27 7	86.09 25	93.74 73	47.71 235	96.98 76	77.90 92	89.78 75	93.65 106

Fast-Effi-MVS+		81.14 102	80.01 102	84.51 116	90.24 125	65.86 135	94.12 43	89.15 233	73.81 122	75.37 117	88.26 154	57.26 127	94.53 156	66.97 172	84.92 108	93.15 118

tpmrst		80.57 108	79.14 121	84.84 105	90.10 126	68.28 61	81.70 291	89.72 216	77.63 62	75.96 110	79.54 268	64.94 62	92.71 223	75.43 104	77.28 167	93.55 108

PVSNet_Blended_VisFu		83.97 64	83.50 58	85.39 91	90.02 127	66.59 116	93.77 62	91.73 140	77.43 66	77.08 104	89.81 139	63.77 72	96.97 77	79.67 77	88.21 84	92.60 132

UGNet		79.87 122	78.68 123	83.45 137	89.96 128	61.51 224	92.13 108	90.79 172	76.83 73	78.85 85	86.33 184	38.16 283	96.17 101	67.93 163	87.17 91	92.67 130
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
CHOSEN 1792x2688		84.98 51	83.45 60	89.57 6	89.94 129	75.14 4	92.07 113	92.32 116	81.87 25	75.68 111	88.27 153	60.18 103	98.60 14	80.46 75	90.27 73	94.96 61

abl_6		79.82 123	79.20 119	81.70 185	89.85 130	58.34 267	88.47 221	90.07 201	62.56 271	77.71 93	93.08 82	47.65 236	96.78 86	77.94 91	85.45 107	89.99 167

BH-untuned		78.68 145	77.08 147	83.48 136	89.84 131	63.74 183	92.70 92	88.59 248	71.57 174	66.83 220	88.65 147	51.75 201	95.39 130	59.03 233	84.77 110	91.32 154

test222					89.77 132	61.60 223	89.55 201	89.42 223	56.83 306	77.28 100	92.43 98	52.76 192			91.14 65	93.09 120

PMMVS		81.98 94	82.04 80	81.78 181	89.76 133	56.17 289	91.13 164	90.69 175	77.96 57	80.09 71	93.57 75	46.33 245	94.99 138	81.41 68	87.46 90	94.17 86

conf0.01		74.95 210	73.61 203	78.96 246	89.65 134	56.94 282	87.72 236	93.45 65	65.14 247	65.68 223	89.99 132	65.09 53	91.67 249	35.16 323	70.61 211	88.27 188

conf0.002		74.95 210	73.61 203	78.96 246	89.65 134	56.94 282	87.72 236	93.45 65	65.14 247	65.68 223	89.99 132	65.09 53	91.67 249	35.16 323	70.61 211	88.27 188

thresconf0.02		74.92 213	73.61 203	78.85 249	89.65 134	56.94 282	87.72 236	93.45 65	65.14 247	65.68 223	89.99 132	65.09 53	91.67 249	35.16 323	70.61 211	87.94 195

tfpn_n400		74.92 213	73.61 203	78.85 249	89.65 134	56.94 282	87.72 236	93.45 65	65.14 247	65.68 223	89.99 132	65.09 53	91.67 249	35.16 323	70.61 211	87.94 195

tfpnconf		74.92 213	73.61 203	78.85 249	89.65 134	56.94 282	87.72 236	93.45 65	65.14 247	65.68 223	89.99 132	65.09 53	91.67 249	35.16 323	70.61 211	87.94 195

tfpnview11		74.92 213	73.61 203	78.85 249	89.65 134	56.94 282	87.72 236	93.45 65	65.14 247	65.68 223	89.99 132	65.09 53	91.67 249	35.16 323	70.61 211	87.94 195

QAPM		79.95 121	77.39 144	87.64 23	89.63 140	71.41 12	93.30 74	93.70 55	65.34 245	67.39 214	91.75 109	47.83 233	98.96 5	57.71 239	89.81 74	92.54 134

3Dnovator	73.91 6	82.69 83	80.82 93	88.31 14	89.57 141	71.26 14	92.60 97	94.39 40	78.84 48	67.89 207	92.48 97	48.42 227	98.52 15	68.80 159	94.40 21	95.15 52

Effi-MVS+		83.82 68	82.76 73	86.99 42	89.56 142	69.40 38	91.35 152	86.12 286	72.59 142	83.22 51	92.81 93	59.60 108	96.01 109	81.76 64	87.80 88	95.56 36

PatchmatchNet		77.46 164	74.63 185	85.96 70	89.55 143	70.35 23	79.97 307	89.55 219	72.23 152	70.94 159	76.91 287	57.03 130	92.79 221	54.27 249	81.17 134	94.74 66
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PatchMatch-RL		72.06 237	69.98 236	78.28 257	89.51 144	55.70 292	83.49 276	83.39 310	61.24 281	63.72 245	82.76 215	34.77 306	93.03 211	53.37 255	77.59 158	86.12 232

UA-Net		80.02 119	79.65 108	81.11 198	89.33 145	57.72 272	86.33 261	89.00 240	77.44 65	81.01 63	89.15 143	59.33 110	95.90 110	61.01 223	84.28 118	89.73 170

dp		75.01 208	72.09 225	83.76 126	89.28 146	66.22 129	79.96 308	89.75 211	71.16 180	67.80 209	77.19 283	51.81 200	92.54 228	50.39 262	71.44 208	92.51 135

tpmp4_e23		78.85 139	76.55 156	85.77 78	89.25 147	68.39 57	81.63 294	91.38 155	70.40 193	75.21 118	79.22 270	67.37 32	94.79 144	58.98 235	75.51 177	94.13 89

sss		82.71 82	82.38 77	83.73 129	89.25 147	59.58 254	92.24 106	94.89 23	77.96 57	79.86 73	92.38 99	56.70 138	97.05 67	77.26 96	80.86 137	94.55 72

MVSFormer		83.75 70	82.88 70	86.37 61	89.24 149	71.18 16	89.07 211	90.69 175	65.80 240	87.13 20	94.34 63	64.99 60	92.67 225	72.83 119	91.80 54	95.27 46

lupinMVS		87.74 18	87.77 17	87.63 26	89.24 149	71.18 16	96.57 4	92.90 98	82.70 16	87.13 20	95.27 33	64.99 60	95.80 113	89.34 13	91.80 54	95.93 27

IB-MVS	77.80 4	82.18 88	80.46 99	87.35 32	89.14 151	70.28 24	95.59 18	95.17 17	78.85 47	70.19 169	85.82 189	70.66 17	97.67 35	72.19 128	66.52 242	94.09 92
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
MDTV_nov1_ep13			72.61 219		89.06 152	68.48 54	80.33 301	90.11 200	71.84 165	71.81 153	75.92 294	53.01 190	93.92 193	48.04 271	73.38 190

testdata				81.34 189	89.02 153	57.72 272		89.84 209	58.65 297	85.32 34	94.09 67	57.03 130	93.28 207	69.34 153	90.56 71	93.03 122

CostFormer		82.33 86	81.15 89	85.86 73	89.01 154	68.46 55	82.39 287	93.01 93	75.59 87	80.25 70	81.57 236	72.03 13	94.96 139	79.06 83	77.48 164	94.16 87

GBi-Net		75.65 198	73.83 200	81.10 199	88.85 155	65.11 150	90.01 189	90.32 187	70.84 184	67.04 217	80.25 259	48.03 229	91.54 258	59.80 230	69.34 222	86.64 223

test1		75.65 198	73.83 200	81.10 199	88.85 155	65.11 150	90.01 189	90.32 187	70.84 184	67.04 217	80.25 259	48.03 229	91.54 258	59.80 230	69.34 222	86.64 223

FMVSNet2		76.07 192	74.01 197	82.26 169	88.85 155	67.66 73	91.33 153	91.61 145	70.84 184	65.98 222	82.25 223	48.03 229	92.00 244	58.46 236	68.73 228	87.10 216

DeepC-MVS	77.85 3	85.52 45	85.24 46	86.37 61	88.80 158	66.64 113	92.15 107	93.68 56	81.07 28	76.91 105	93.64 74	62.59 84	98.44 19	85.50 40	92.84 42	94.03 96
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
EPP-MVSNet		81.79 95	81.52 86	82.61 150	88.77 159	60.21 244	93.02 82	93.66 57	68.52 217	72.90 136	90.39 124	72.19 12	94.96 139	74.93 111	79.29 145	92.67 130

1112_ss		80.56 109	79.83 106	82.77 144	88.65 160	60.78 231	92.29 104	88.36 252	72.58 143	72.46 145	94.95 43	65.09 53	93.42 206	66.38 177	77.71 156	94.10 91

tpm cat1		75.30 203	72.21 224	84.58 113	88.52 161	67.77 70	78.16 318	88.02 258	61.88 278	68.45 202	76.37 288	60.65 97	94.03 188	53.77 252	74.11 186	91.93 145

LCM-MVSNet-Re		72.93 230	71.84 226	76.18 281	88.49 162	48.02 324	80.07 306	70.17 346	73.96 118	52.25 308	80.09 262	49.98 213	88.24 301	67.35 167	84.23 119	92.28 141

Vis-MVSNet		80.92 106	79.98 104	83.74 127	88.48 163	61.80 221	93.44 72	88.26 256	73.96 118	77.73 92	91.76 108	49.94 214	94.76 145	65.84 184	90.37 72	94.65 70
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Vis-MVSNet (Re-imp)		79.24 133	79.57 109	78.24 260	88.46 164	52.29 306	90.41 182	89.12 234	74.24 109	69.13 186	91.91 105	65.77 47	90.09 280	59.00 234	88.09 85	92.33 138

ab-mvs		80.18 115	78.31 127	85.80 76	88.44 165	65.49 144	83.00 284	92.67 105	71.82 166	77.36 99	85.01 196	54.50 170	96.59 91	76.35 101	75.63 176	95.32 43

gm-plane-assit					88.42 166	67.04 91			78.62 52		91.83 106		97.37 50	76.57 99

MVS_111021_LR		82.02 93	81.52 86	83.51 135	88.42 166	62.88 205	89.77 199	88.93 241	76.78 74	75.55 115	93.10 80	50.31 210	95.38 131	83.82 53	87.02 92	92.26 142

tpm2		79.80 124	77.95 133	85.34 93	88.28 168	68.26 62	81.56 295	91.42 153	70.11 196	77.59 97	80.50 254	67.40 31	94.26 173	67.34 168	77.35 165	93.51 109

Test_1112_low_res		79.56 129	78.60 125	82.43 156	88.24 169	60.39 240	92.09 111	87.99 259	72.10 158	71.84 152	87.42 169	64.62 63	93.04 210	65.80 185	77.30 166	93.85 104

PAPM		85.89 42	85.46 44	87.18 35	88.20 170	72.42 9	92.41 103	92.77 101	82.11 21	80.34 69	93.07 84	68.27 21	95.02 137	78.39 88	93.59 34	94.09 92

TESTMET0.1,1		82.41 85	81.98 81	83.72 130	88.08 171	63.74 183	92.70 92	93.77 52	79.30 38	77.61 96	87.57 167	58.19 119	94.08 182	73.91 115	86.68 96	93.33 113

ADS-MVSNet2		66.90 282	63.44 285	77.26 274	88.06 172	60.70 235	68.01 336	75.56 335	57.57 299	64.48 237	69.87 324	38.68 277	84.10 316	40.87 301	67.89 234	86.97 217

ADS-MVSNet		68.54 270	64.38 281	81.03 202	88.06 172	66.90 95	68.01 336	84.02 303	57.57 299	64.48 237	69.87 324	38.68 277	89.21 294	40.87 301	67.89 234	86.97 217

EPNet_dtu		78.80 141	79.26 118	77.43 270	88.06 172	49.71 320	91.96 120	91.95 134	77.67 61	76.56 107	91.28 113	58.51 117	90.20 275	56.37 242	80.95 136	92.39 136
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
diffmvs		81.52 97	80.44 100	84.76 106	87.98 175	65.79 139	86.97 255	88.84 243	76.57 78	78.24 88	85.79 191	58.10 121	94.55 153	77.40 95	84.11 121	93.95 99

IS-MVSNet		80.14 116	79.41 114	82.33 163	87.91 176	60.08 248	91.97 119	88.27 255	72.90 139	71.44 158	91.73 110	61.44 90	93.66 201	62.47 216	86.53 99	93.24 115

CLD-MVS		82.73 80	82.35 78	83.86 125	87.90 177	67.65 74	95.45 19	92.18 127	85.06 8	72.58 141	92.27 102	52.46 196	95.78 114	84.18 48	79.06 146	88.16 192
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
HyFIR lowres test		81.03 104	79.56 110	85.43 89	87.81 178	68.11 65	90.18 187	90.01 205	70.65 191	72.95 135	86.06 187	63.61 74	94.50 157	75.01 110	79.75 141	93.67 105

1314		80.70 107	78.95 122	85.94 71	87.77 179	67.56 76	87.91 232	92.55 111	72.17 156	67.44 211	93.09 81	50.27 211	97.04 69	71.68 131	87.64 89	93.23 116

HQP-NCC					87.54 180		94.06 46		79.80 33	74.18 123

ACMP_Plane					87.54 180		94.06 46		79.80 33	74.18 123

HQP-MVS		81.14 102	80.64 96	82.64 149	87.54 180	63.66 188	94.06 46	91.70 143	79.80 33	74.18 123	90.30 125	51.63 203	95.61 123	77.63 93	78.90 147	88.63 180

NP-MVS					87.41 183	63.04 199					90.30 125

plane_prior6					87.23 184	62.32 212						50.66 207

plane_prior1					87.15 185

cascas		78.18 154	75.77 166	85.41 90	87.14 186	69.11 42	92.96 83	91.15 162	66.71 233	70.47 161	86.07 186	37.49 291	96.48 95	70.15 146	79.80 140	90.65 160

CHOSEN 280x420		77.35 169	76.95 152	78.55 254	87.07 187	62.68 209	69.71 332	82.95 314	68.80 210	71.48 157	87.27 176	66.03 43	84.00 320	76.47 100	82.81 126	88.95 175

HQP_MVS		80.34 113	79.75 107	82.12 174	86.94 188	62.42 210	93.13 78	91.31 157	78.81 49	72.53 142	89.14 144	50.66 207	95.55 127	76.74 97	78.53 151	88.39 185

plane_prior7					86.94 188	61.51 224

test-LLR		80.10 117	79.56 110	81.72 183	86.93 190	61.17 226	92.70 92	91.54 147	71.51 177	75.62 112	86.94 178	53.83 179	92.38 233	72.21 126	84.76 111	91.60 148

test-mter		79.96 120	79.38 116	81.72 183	86.93 190	61.17 226	92.70 92	91.54 147	73.85 120	75.62 112	86.94 178	49.84 216	92.38 233	72.21 126	84.76 111	91.60 148

Patchmatch-test1		75.00 209	71.80 228	84.58 113	86.63 192	70.08 26	81.06 297	89.19 230	71.60 173	70.01 171	77.16 285	45.53 249	88.63 295	51.79 258	73.27 191	95.02 60

xiu_mvs_v1_base_debu		82.16 89	81.12 90	85.26 95	86.42 193	68.72 50	92.59 99	90.44 181	73.12 135	84.20 44	94.36 58	38.04 285	95.73 117	84.12 49	86.81 93	91.33 151

xiu_mvs_v1_base		82.16 89	81.12 90	85.26 95	86.42 193	68.72 50	92.59 99	90.44 181	73.12 135	84.20 44	94.36 58	38.04 285	95.73 117	84.12 49	86.81 93	91.33 151

xiu_mvs_v1_base_debi		82.16 89	81.12 90	85.26 95	86.42 193	68.72 50	92.59 99	90.44 181	73.12 135	84.20 44	94.36 58	38.04 285	95.73 117	84.12 49	86.81 93	91.33 151

F-COLMAP		70.66 252	68.44 251	77.32 272	86.37 196	55.91 291	88.00 228	86.32 281	56.94 305	57.28 282	88.07 158	33.58 308	92.49 230	51.02 260	68.37 230	83.55 267

CDS-MVSNet		81.43 99	80.74 94	83.52 134	86.26 197	64.45 165	92.09 111	90.65 178	75.83 86	73.95 129	89.81 139	63.97 68	92.91 217	71.27 135	82.82 125	93.20 117
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
VDDNet		80.50 110	78.26 128	87.21 34	86.19 198	69.79 32	94.48 36	91.31 157	60.42 285	79.34 78	90.91 115	38.48 281	96.56 94	82.16 60	81.05 135	95.27 46

jason		86.40 34	86.17 34	87.11 38	86.16 199	70.54 22	95.71 16	92.19 126	82.00 24	84.58 39	94.34 63	61.86 88	95.53 129	87.76 24	90.89 66	95.27 46
jason: jason.
PCF-MVS	73.15 9	79.29 132	77.63 138	84.29 119	86.06 200	65.96 133	87.03 251	91.10 164	69.86 199	69.79 176	90.64 118	57.54 126	96.59 91	64.37 197	82.29 127	90.32 163
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MS-PatchMatch		77.90 161	76.50 157	82.12 174	85.99 201	69.95 29	91.75 137	92.70 103	73.97 117	62.58 255	84.44 203	41.11 270	95.78 114	63.76 200	92.17 51	80.62 310

FIs		79.47 130	79.41 114	79.67 225	85.95 202	59.40 256	91.68 139	93.94 47	78.06 56	68.96 190	88.28 152	66.61 38	91.77 247	66.20 180	74.99 182	87.82 199

VPA-MVSNet		79.03 135	78.00 132	82.11 177	85.95 202	64.48 164	93.22 77	94.66 31	75.05 98	74.04 128	84.95 197	52.17 198	93.52 203	74.90 113	67.04 238	88.32 187

tpm		78.58 148	77.03 148	83.22 138	85.94 204	64.56 160	83.21 282	91.14 163	78.31 54	73.67 130	79.68 265	64.01 67	92.09 242	66.07 181	71.26 209	93.03 122

OpenMVS	70.45 11	78.54 149	75.92 164	86.41 60	85.93 205	71.68 11	92.74 90	92.51 113	66.49 235	64.56 236	91.96 104	43.88 258	98.10 27	54.61 247	90.65 69	89.44 173

OMC-MVS		78.67 147	77.91 135	80.95 204	85.76 206	57.40 277	88.49 220	88.67 246	73.85 120	72.43 146	92.10 103	49.29 220	94.55 153	72.73 121	77.89 155	90.91 158

EI-MVSNet		78.97 137	78.22 129	81.25 190	85.33 207	62.73 208	89.53 203	93.21 82	72.39 147	72.14 149	90.13 129	60.99 91	94.72 148	67.73 165	72.49 199	86.29 228

CVMVSNet		74.04 222	74.27 192	73.33 297	85.33 207	43.94 334	89.53 203	88.39 251	54.33 313	70.37 166	90.13 129	49.17 222	84.05 317	61.83 220	79.36 143	91.99 144

ACMH	63.93 17	68.62 268	64.81 274	80.03 216	85.22 209	63.25 193	87.72 236	84.66 298	60.83 283	51.57 311	79.43 269	27.29 330	94.96 139	41.76 297	64.84 257	81.88 290
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TAMVS		80.37 112	79.45 113	83.13 140	85.14 210	63.37 191	91.23 157	90.76 174	74.81 101	72.65 139	88.49 148	60.63 98	92.95 213	69.41 152	81.95 131	93.08 121

MSDG		69.54 264	65.73 268	80.96 203	85.11 211	63.71 185	84.19 271	83.28 311	56.95 304	54.50 292	84.03 204	31.50 317	96.03 107	42.87 293	69.13 225	83.14 278

ACMP	71.68 10	75.58 201	74.23 193	79.62 227	84.97 212	59.64 252	90.80 170	89.07 237	70.39 194	62.95 251	87.30 175	38.28 282	93.87 195	72.89 118	71.45 207	85.36 253
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
FC-MVSNet-test		77.99 158	78.08 131	77.70 265	84.89 213	55.51 293	90.27 185	93.75 54	76.87 71	66.80 221	87.59 166	65.71 48	90.23 274	62.89 211	73.94 188	87.37 210

PVSNet_0	68.08 15	71.81 239	68.32 253	82.27 166	84.68 214	62.31 213	88.68 216	90.31 190	75.84 85	57.93 276	80.65 253	37.85 288	94.19 174	69.94 147	29.05 349	90.31 164

WR-MVS		76.76 184	75.74 167	79.82 222	84.60 215	62.27 214	92.60 97	92.51 113	76.06 83	67.87 208	85.34 193	56.76 135	90.24 273	62.20 217	63.69 268	86.94 220

ACMH+	65.35 16	67.65 277	64.55 277	76.96 275	84.59 216	57.10 280	88.08 227	80.79 321	58.59 298	53.00 305	81.09 248	26.63 332	92.95 213	46.51 277	61.69 281	80.82 307

VPNet		78.82 140	77.53 140	82.70 146	84.52 217	66.44 122	93.93 54	92.23 119	80.46 30	72.60 140	88.38 151	49.18 221	93.13 209	72.47 124	63.97 266	88.55 182

IterMVS-LS		76.49 186	75.18 182	80.43 208	84.49 218	62.74 207	90.64 177	88.80 244	72.40 146	65.16 232	81.72 235	60.98 92	92.27 238	67.74 164	64.65 260	86.29 228
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
UniMVSNet_NR-MVSNet		78.15 155	77.55 139	79.98 217	84.46 219	60.26 242	92.25 105	93.20 84	77.50 64	68.88 191	86.61 180	66.10 42	92.13 240	66.38 177	62.55 270	87.54 201

FMVSNet5		68.04 274	65.66 269	75.18 285	84.43 220	57.89 269	83.54 275	86.26 283	61.83 279	53.64 302	73.30 301	37.15 295	85.08 313	48.99 267	61.77 277	82.56 287

MVS-HIRNet		60.25 306	55.55 312	74.35 290	84.37 221	56.57 288	71.64 327	74.11 339	34.44 348	45.54 330	42.24 350	31.11 320	89.81 287	40.36 304	76.10 174	76.67 332

LPG-MVS_test		75.82 197	74.58 187	79.56 229	84.31 222	59.37 257	90.44 180	89.73 214	69.49 201	64.86 233	88.42 149	38.65 279	94.30 169	72.56 122	72.76 196	85.01 256

LGP-MVS_train				79.56 229	84.31 222	59.37 257		89.73 214	69.49 201	64.86 233	88.42 149	38.65 279	94.30 169	72.56 122	72.76 196	85.01 256

ACMM	69.62 13	74.34 219	72.73 217	79.17 241	84.25 224	57.87 270	90.36 183	89.93 207	63.17 267	65.64 229	86.04 188	37.79 289	94.10 180	65.89 183	71.52 206	85.55 250
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
UniMVSNet (Re)		77.58 163	76.78 153	79.98 217	84.11 225	60.80 230	91.76 135	93.17 87	76.56 80	69.93 175	84.78 199	63.32 78	92.36 235	64.89 191	62.51 272	86.78 222

test_0402		64.54 292	61.09 297	74.92 286	84.10 226	60.75 233	87.95 229	79.71 325	52.03 318	52.41 307	77.20 282	32.21 314	91.64 255	23.14 348	61.03 284	72.36 338

LTVRE_ROB	59.60 19	66.27 285	63.54 284	74.45 289	84.00 227	51.55 309	67.08 339	83.53 307	58.78 296	54.94 290	80.31 257	34.54 307	93.23 208	40.64 303	68.03 232	78.58 326
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
Patchmatch-test		65.86 287	60.94 298	80.62 206	83.75 228	58.83 263	58.91 349	75.26 337	44.50 340	50.95 315	77.09 286	58.81 116	87.90 303	35.13 329	64.03 264	95.12 54

nrg030		80.93 105	79.86 105	84.13 121	83.69 229	68.83 48	93.23 76	91.20 160	75.55 88	75.06 119	88.22 157	63.04 82	94.74 147	81.88 63	66.88 239	88.82 178

GA-MVS		78.33 152	76.23 160	84.65 111	83.65 230	66.30 126	91.44 145	90.14 199	76.01 84	70.32 167	84.02 205	42.50 262	94.72 148	70.98 139	77.00 169	92.94 125

FMVSNet1		72.71 234	69.91 238	81.10 199	83.60 231	65.11 150	90.01 189	90.32 187	63.92 260	63.56 246	80.25 259	36.35 300	91.54 258	54.46 248	66.75 240	86.64 223

OPM-MVS		79.00 136	78.09 130	81.73 182	83.52 232	63.83 180	91.64 142	90.30 191	76.36 82	71.97 151	89.93 138	46.30 246	95.17 136	75.10 107	77.70 157	86.19 230

tfpnnormal		70.10 256	67.36 260	78.32 256	83.45 233	60.97 228	88.85 213	92.77 101	64.85 254	60.83 260	78.53 273	43.52 260	93.48 204	31.73 339	61.70 280	80.52 311

Effi-MVS+-dtu		76.14 191	75.28 180	78.72 253	83.22 234	55.17 295	89.87 197	87.78 261	75.42 90	67.98 205	81.43 237	45.08 252	92.52 229	75.08 108	71.63 204	88.48 183

mvs-test1		78.74 144	77.95 133	81.14 196	83.22 234	57.13 279	93.96 51	87.78 261	75.42 90	72.68 138	90.80 117	45.08 252	94.54 155	75.08 108	77.49 163	91.74 147

CR-MVSNet		73.79 225	70.82 234	82.70 146	83.15 236	67.96 67	70.25 329	84.00 304	73.67 126	69.97 173	72.41 309	57.82 123	89.48 291	52.99 256	73.13 192	90.64 161

RPMNet		69.58 263	65.21 273	82.70 146	83.15 236	67.96 67	70.25 329	86.15 285	46.83 333	69.97 173	65.10 334	56.48 143	89.48 291	35.79 322	73.13 192	90.64 161

DU-MVS		76.86 180	75.84 165	79.91 219	82.96 238	60.26 242	91.26 156	91.54 147	76.46 81	68.88 191	86.35 182	56.16 144	92.13 240	66.38 177	62.55 270	87.35 212

NR-MVSNet		76.05 193	74.59 186	80.44 207	82.96 238	62.18 215	90.83 169	91.73 140	77.12 67	60.96 259	86.35 182	59.28 111	91.80 246	60.74 224	61.34 283	87.35 212

XXY-MVS		77.94 160	76.44 158	82.43 156	82.60 240	64.44 166	92.01 116	91.83 138	73.59 127	70.00 172	85.82 189	54.43 173	94.76 145	69.63 149	68.02 233	88.10 193

TranMVSNet+NR-MVSNet		75.86 196	74.52 189	79.89 220	82.44 241	60.64 237	91.37 151	91.37 156	76.63 76	67.65 210	86.21 185	52.37 197	91.55 257	61.84 219	60.81 286	87.48 203

IterMVS		72.65 236	70.83 233	78.09 263	82.17 242	62.96 200	87.64 244	86.28 282	71.56 175	60.44 261	78.85 272	45.42 251	86.66 309	63.30 204	61.83 276	84.65 260
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Patchmtry		67.53 279	63.93 282	78.34 255	82.12 243	64.38 169	68.72 333	84.00 304	48.23 330	59.24 266	72.41 309	57.82 123	89.27 293	46.10 279	56.68 302	81.36 298

PatchT		69.11 267	65.37 272	80.32 209	82.07 244	63.68 187	67.96 338	87.62 263	50.86 323	69.37 183	65.18 333	57.09 128	88.53 299	41.59 299	66.60 241	88.74 179

Anonymous20240521		69.68 262	68.15 256	74.28 292	82.04 245	49.91 318	85.92 264	90.52 180	63.87 261	57.61 280	81.33 240	41.82 264	89.57 290	46.86 276	63.36 269	83.37 274

MIMVSNet		71.64 242	68.44 251	81.23 191	81.97 246	64.44 166	73.05 325	88.80 244	69.67 200	64.59 235	74.79 298	32.79 310	87.82 304	53.99 250	76.35 173	91.42 150

MVP-Stereo		77.12 175	76.23 160	79.79 223	81.72 247	66.34 125	89.29 205	90.88 170	70.56 192	62.01 258	82.88 214	49.34 219	94.13 179	65.55 187	93.80 28	78.88 323
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
semantic-postprocess				76.32 279	81.48 248	60.67 236		85.99 288	66.17 237	59.50 265	78.88 271	45.51 250	83.65 322	62.58 215	61.93 275	84.63 261

pcd1.5k->3k		31.17 333	31.85 331	29.12 347	81.48 248	0.00 369	0.00 360	91.79 139	0.00 364	0.00 366	0.00 366	41.05 271	0.00 366	0.00 363	72.34 202	87.36 211

COLMAP_ROB	57.96 20	62.98 301	59.65 301	72.98 300	81.44 250	53.00 304	83.75 273	75.53 336	48.34 329	48.81 320	81.40 239	24.14 334	90.30 270	32.95 335	60.52 288	75.65 334
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
JIA-IIPM		66.06 286	62.45 292	76.88 276	81.42 251	54.45 299	57.49 350	88.67 246	49.36 326	63.86 243	46.86 346	56.06 147	90.25 271	49.53 266	68.83 226	85.95 240

WR-MVS_H		70.59 253	69.94 237	72.53 303	81.03 252	51.43 310	87.35 248	92.03 130	67.38 230	60.23 262	80.70 250	55.84 151	83.45 324	46.33 278	58.58 296	82.72 283

DI_MVS_plusplus_test		79.78 125	77.50 141	86.62 48	80.90 253	69.46 37	90.69 175	91.97 133	77.00 69	59.07 269	82.34 221	46.82 239	95.88 111	82.14 61	86.59 98	94.53 76

Fast-Effi-MVS+-dtu		75.04 207	73.37 212	80.07 215	80.86 254	59.52 255	91.20 160	85.38 293	71.90 160	65.20 230	84.84 198	41.46 269	92.97 212	66.50 176	72.96 195	87.73 200

Baseline_NR-MVSNet		73.99 223	72.83 216	77.48 269	80.78 255	59.29 259	91.79 132	84.55 299	68.85 209	68.99 189	80.70 250	56.16 144	92.04 243	62.67 214	60.98 285	81.11 304

v18		71.94 238	69.43 241	79.50 231	80.74 256	66.82 98	88.16 226	86.66 272	68.95 208	55.55 286	72.66 304	55.03 161	90.15 276	64.78 192	52.30 314	81.54 292

test_normal		79.66 126	77.36 146	86.54 52	80.72 257	69.21 41	90.68 176	92.16 128	76.99 70	58.63 273	82.03 230	46.70 241	95.86 112	81.74 65	86.63 97	94.56 71

CP-MVSNet		70.50 255	69.91 238	72.26 306	80.71 258	51.00 313	87.23 249	90.30 191	67.84 224	59.64 264	82.69 216	50.23 212	82.30 331	51.28 259	59.28 290	83.46 271

v1neww		77.39 166	75.71 168	82.44 153	80.69 259	66.83 96	91.94 124	90.18 196	74.19 110	69.60 177	82.51 217	54.99 163	94.44 158	71.68 131	65.60 245	86.05 235

v7new		77.39 166	75.71 168	82.44 153	80.69 259	66.83 96	91.94 124	90.18 196	74.19 110	69.60 177	82.51 217	54.99 163	94.44 158	71.68 131	65.60 245	86.05 235

v8		75.35 202	73.26 213	81.61 186	80.67 261	66.82 98	89.54 202	89.27 227	71.65 171	63.30 249	80.30 258	54.99 163	94.06 184	67.33 169	62.33 273	83.94 264

v6		77.39 166	75.71 168	82.44 153	80.67 261	66.82 98	91.94 124	90.18 196	74.19 110	69.60 177	82.50 220	55.00 162	94.44 158	71.68 131	65.60 245	86.05 235

v16		71.81 239	69.26 243	79.47 232	80.66 263	66.81 102	87.93 230	86.63 274	68.70 214	55.35 288	72.51 305	54.75 167	90.12 278	64.51 194	52.28 315	81.47 293

PS-MVSNAJss		77.26 173	76.31 159	80.13 214	80.64 264	59.16 260	90.63 179	91.06 166	72.80 140	68.58 196	84.57 202	53.55 183	93.96 191	72.97 117	71.96 203	87.27 215

v1141		77.28 171	75.57 172	82.42 159	80.63 265	66.73 106	91.96 120	90.42 184	74.41 103	69.46 180	82.12 227	55.09 159	94.40 163	70.99 138	65.05 252	86.12 232

v17		71.77 241	69.20 244	79.46 233	80.62 266	66.81 102	87.93 230	86.63 274	68.71 213	55.25 289	72.49 306	54.72 168	90.11 279	64.50 195	51.97 316	81.47 293

divwei89l23v2f112		77.28 171	75.57 172	82.42 159	80.62 266	66.72 108	91.96 120	90.42 184	74.41 103	69.46 180	82.12 227	55.11 158	94.40 163	71.00 136	65.04 253	86.12 232

TransMVSNet (Re)		70.07 257	67.66 259	77.31 273	80.62 266	59.13 261	91.78 134	84.94 297	65.97 238	60.08 263	80.44 255	50.78 206	91.87 245	48.84 268	45.46 334	80.94 306

v1		77.29 170	75.57 172	82.42 159	80.61 269	66.73 106	91.96 120	90.42 184	74.41 103	69.46 180	82.12 227	55.14 157	94.40 163	71.00 136	65.04 253	86.13 231

v15		71.40 243	68.75 246	79.35 234	80.39 270	66.70 110	87.57 245	86.64 273	68.66 215	54.68 291	72.00 313	54.50 170	89.98 281	63.69 201	50.66 321	81.38 297

v2v482		77.42 165	75.65 171	82.73 145	80.38 271	67.13 88	91.85 130	90.23 193	75.09 97	69.37 183	83.39 211	53.79 181	94.44 158	71.77 129	65.00 256	86.63 226

v7		76.83 183	75.01 183	82.29 165	80.35 272	66.70 110	91.68 139	89.97 206	73.47 131	69.22 185	82.22 224	52.52 194	94.43 162	69.73 148	65.96 244	85.74 247

PS-CasMVS		69.86 259	69.13 245	72.07 309	80.35 272	50.57 315	87.02 252	89.75 211	67.27 231	59.19 267	82.28 222	46.58 243	82.24 332	50.69 261	59.02 293	83.39 273

v11		71.05 249	68.32 253	79.23 238	80.34 274	66.57 117	87.01 253	86.55 278	68.11 222	54.40 294	71.66 318	52.94 191	89.91 284	62.71 213	51.12 319	81.21 301

V14		71.29 245	68.61 248	79.31 235	80.34 274	66.65 112	87.39 247	86.61 276	68.41 220	54.49 293	71.91 314	54.25 175	89.96 282	63.50 202	50.62 322	81.33 299

v10		74.77 217	72.54 221	81.46 187	80.33 276	66.71 109	89.15 209	89.08 236	70.94 182	63.08 250	79.86 263	52.52 194	94.04 187	65.70 186	62.17 274	83.64 266

V9		71.16 246	68.46 250	79.27 237	80.26 277	66.60 114	87.21 250	86.56 277	68.17 221	54.26 296	71.81 316	54.00 177	89.93 283	63.28 205	50.57 323	81.27 300

test0.0.03 1		72.76 233	72.71 218	72.88 301	80.25 278	47.99 325	91.22 158	89.45 221	71.51 177	62.51 256	87.66 165	53.83 179	85.06 314	50.16 263	67.84 236	85.58 248

v1144		76.73 185	74.88 184	82.27 166	80.23 279	66.60 114	91.68 139	90.21 195	73.69 124	69.06 188	81.89 232	52.73 193	94.40 163	69.21 154	65.23 249	85.80 243

v12		71.02 250	68.29 255	79.22 239	80.18 280	66.53 119	87.01 253	86.54 279	67.90 223	54.00 299	71.70 317	53.66 182	89.91 284	63.09 207	50.51 324	81.21 301

v13		70.90 251	68.15 256	79.15 243	80.08 281	66.45 121	86.83 258	86.50 280	67.62 229	53.78 301	71.61 319	53.51 186	89.87 286	62.89 211	50.50 325	81.14 303

LP		56.71 313	51.64 317	71.91 311	80.08 281	60.33 241	61.72 344	75.61 334	43.87 342	43.76 336	60.30 340	30.46 322	84.05 317	22.94 349	46.06 333	71.34 339

v148		76.19 190	74.47 190	81.36 188	80.05 283	64.44 166	91.75 137	90.23 193	73.68 125	67.13 216	80.84 249	55.92 150	93.86 197	68.95 157	61.73 279	85.76 246

v1192		75.98 195	73.92 199	82.15 172	79.73 284	66.24 128	91.22 158	89.75 211	72.67 141	68.49 201	81.42 238	49.86 215	94.27 171	67.08 170	65.02 255	85.95 240

AllTest		61.66 302	58.06 303	72.46 304	79.57 285	51.42 311	80.17 304	68.61 348	51.25 321	45.88 326	81.23 242	19.86 342	86.58 310	38.98 308	57.01 300	79.39 320

TestCases				72.46 304	79.57 285	51.42 311		68.61 348	51.25 321	45.88 326	81.23 242	19.86 342	86.58 310	38.98 308	57.01 300	79.39 320

MDA-MVSNet-bldmvs		61.54 304	57.70 305	73.05 299	79.53 287	57.00 281	83.08 283	81.23 318	57.57 299	34.91 346	72.45 308	32.79 310	86.26 312	35.81 321	41.95 338	75.89 333

v144192		76.05 193	74.03 196	82.12 174	79.50 288	66.55 118	91.39 148	89.71 217	72.30 148	68.17 203	81.33 240	51.75 201	94.03 188	67.94 162	64.19 262	85.77 244

v1921920		75.63 200	73.49 210	82.06 178	79.38 289	66.35 124	91.07 166	89.48 220	71.98 159	67.99 204	81.22 244	49.16 223	93.90 194	66.56 175	64.56 261	85.92 242

PEN-MVS		69.46 265	68.56 249	72.17 308	79.27 290	49.71 320	86.90 256	89.24 229	67.24 232	59.08 268	82.51 217	47.23 238	83.54 323	48.42 270	57.12 298	83.25 275

v1240		75.21 206	72.98 215	81.88 180	79.20 291	66.00 132	90.75 172	89.11 235	71.63 172	67.41 213	81.22 244	47.36 237	93.87 195	65.46 188	64.72 259	85.77 244

pmmvs4		73.92 224	71.81 227	80.25 211	79.17 292	65.24 146	87.43 246	87.26 269	67.64 228	63.46 247	83.91 206	48.96 225	91.53 261	62.94 210	65.49 248	83.96 263

V42		76.46 187	74.55 188	82.19 171	79.14 293	67.82 69	90.26 186	89.42 223	73.75 123	68.63 195	81.89 232	51.31 205	94.09 181	71.69 130	64.84 257	84.66 259

testpf		57.17 311	56.93 308	57.88 332	79.13 294	42.40 335	34.23 356	85.97 289	52.64 316	47.66 324	66.50 328	36.33 301	79.65 339	53.60 253	56.31 303	51.60 350

pm-mvs1		72.89 231	71.09 232	78.26 259	79.10 295	57.62 274	90.80 170	89.30 226	67.66 226	62.91 252	81.78 234	49.11 224	92.95 213	60.29 227	58.89 295	84.22 262

our_test_3		68.29 272	64.69 276	79.11 244	78.92 296	64.85 158	88.40 223	85.06 295	60.32 287	52.68 306	76.12 290	40.81 272	89.80 289	44.25 288	55.65 304	82.67 286

ppachtmachnet_test		67.72 276	63.70 283	79.77 224	78.92 296	66.04 131	88.68 216	82.90 315	60.11 289	55.45 287	75.96 293	39.19 276	90.55 267	39.53 306	52.55 313	82.71 284

TinyColmap		60.32 305	56.42 311	72.00 310	78.78 298	53.18 303	78.36 316	75.64 333	52.30 317	41.59 341	75.82 295	14.76 348	88.35 300	35.84 320	54.71 309	74.46 335

SixPastTwentyTwo		64.92 290	61.78 296	74.34 291	78.74 299	49.76 319	83.42 279	79.51 326	62.86 269	50.27 316	77.35 279	30.92 321	90.49 269	45.89 280	47.06 331	82.78 280

EG-PatchMatch MVS		68.55 269	65.41 271	77.96 264	78.69 300	62.93 201	89.86 198	89.17 231	60.55 284	50.27 316	77.73 278	22.60 338	94.06 184	47.18 275	72.65 198	76.88 331

pmmvs5		73.35 227	71.52 229	78.86 248	78.64 301	60.61 238	91.08 165	86.90 270	67.69 225	63.32 248	83.64 207	44.33 257	90.53 268	62.04 218	66.02 243	85.46 251

XVG-OURS		74.25 221	72.46 222	79.63 226	78.45 302	57.59 275	80.33 301	87.39 264	63.86 262	68.76 193	89.62 142	40.50 273	91.72 248	69.00 156	74.25 185	89.58 171

XVG-OURS-SEG-HR		74.70 218	73.08 214	79.57 228	78.25 303	57.33 278	80.49 299	87.32 267	63.22 266	68.76 193	90.12 131	44.89 255	91.59 256	70.55 144	74.09 187	89.79 168

MDA-MVSNet_test_wron		63.78 298	60.16 299	74.64 287	78.15 304	60.41 239	83.49 276	84.03 302	56.17 310	39.17 343	71.59 321	37.22 293	83.24 327	42.87 293	48.73 328	80.26 314

YYNet1		63.76 299	60.14 300	74.62 288	78.06 305	60.19 245	83.46 278	83.99 306	56.18 309	39.25 342	71.56 322	37.18 294	83.34 325	42.90 292	48.70 329	80.32 313

DTE-MVSNet		68.46 271	67.33 261	71.87 312	77.94 306	49.00 323	86.16 263	88.58 249	66.36 236	58.19 274	82.21 225	46.36 244	83.87 321	44.97 286	55.17 306	82.73 282

USDC		67.43 281	64.51 278	76.19 280	77.94 306	55.29 294	78.38 315	85.00 296	73.17 133	48.36 321	80.37 256	21.23 340	92.48 231	52.15 257	64.02 265	80.81 308

jajsoiax		73.05 229	71.51 230	77.67 266	77.46 308	54.83 296	88.81 214	90.04 204	69.13 206	62.85 253	83.51 209	31.16 319	92.75 222	70.83 140	69.80 218	85.43 252

mvs_tets		72.71 234	71.11 231	77.52 267	77.41 309	54.52 298	88.45 222	89.76 210	68.76 212	62.70 254	83.26 212	29.49 323	92.71 223	70.51 145	69.62 220	85.34 254

N_pmnet		50.55 319	49.11 322	54.88 336	77.17 310	4.02 366	84.36 270	2.00 367	48.59 327	45.86 328	68.82 326	32.22 313	82.80 328	31.58 340	51.38 318	77.81 329

test_djsdf		73.76 226	72.56 220	77.39 271	77.00 311	53.93 300	89.07 211	90.69 175	65.80 240	63.92 242	82.03 230	43.14 261	92.67 225	72.83 119	68.53 229	85.57 249

OpenMVS_ROB	61.12 18	66.39 284	62.92 289	76.80 277	76.51 312	57.77 271	89.22 206	83.41 309	55.48 311	53.86 300	77.84 277	26.28 333	93.95 192	34.90 330	68.76 227	78.68 325

v7n		71.31 244	68.65 247	79.28 236	76.40 313	60.77 232	86.71 259	89.45 221	64.17 258	58.77 272	78.24 274	44.59 256	93.54 202	57.76 238	61.75 278	83.52 269

K. test v3		63.09 300	59.61 302	73.53 296	76.26 314	49.38 322	83.27 280	77.15 329	64.35 257	47.77 322	72.32 311	28.73 325	87.79 305	49.93 265	36.69 344	83.41 272

RPSCF		64.24 294	61.98 295	71.01 313	76.10 315	45.00 331	75.83 322	75.94 332	46.94 332	58.96 270	84.59 201	31.40 318	82.00 333	47.76 273	60.33 289	86.04 238

OurMVSNet-221017-0		64.68 291	62.17 294	72.21 307	76.08 316	47.35 328	80.67 298	81.02 320	56.19 308	51.60 310	79.66 266	27.05 331	88.56 298	53.60 253	53.63 311	80.71 309

Test4		76.45 188	73.45 211	85.45 88	76.07 317	67.61 75	88.38 224	90.83 171	76.71 75	53.06 304	79.65 267	31.61 316	94.35 167	78.47 86	86.22 102	94.40 80

v748		70.55 254	67.97 258	78.27 258	75.75 318	58.78 264	86.29 262	89.25 228	65.12 253	56.66 284	77.17 284	45.05 254	92.95 213	58.13 237	58.33 297	83.10 279

Anonymous20231206		67.53 279	65.78 267	72.79 302	74.95 319	47.59 327	88.23 225	87.32 267	61.75 280	58.07 275	77.29 281	37.79 289	87.29 307	42.91 291	63.71 267	83.48 270

ITE_SJBPF				70.43 314	74.44 320	47.06 329		77.32 328	60.16 288	54.04 298	83.53 208	23.30 337	84.01 319	43.07 290	61.58 282	80.21 315

EU-MVSNet		64.01 296	63.01 288	67.02 322	74.40 321	38.86 345	83.27 280	86.19 284	45.11 337	54.27 295	81.15 247	36.91 298	80.01 337	48.79 269	57.02 299	82.19 289

XVG-ACMP-BASELINE		68.04 274	65.53 270	75.56 283	74.06 322	52.37 305	78.43 314	85.88 290	62.03 275	58.91 271	81.21 246	20.38 341	91.15 265	60.69 225	68.18 231	83.16 277

anonymousdsp		71.14 247	69.37 242	76.45 278	72.95 323	54.71 297	84.19 271	88.88 242	61.92 277	62.15 257	79.77 264	38.14 284	91.44 264	68.90 158	67.45 237	83.21 276

lessismore_v0				73.72 295	72.93 324	47.83 326		61.72 356		45.86 328	73.76 300	28.63 327	89.81 287	47.75 274	31.37 348	83.53 268

pmmvs6		67.57 278	64.76 275	76.00 282	72.82 325	53.37 302	88.71 215	86.78 271	53.19 315	57.58 281	78.03 276	35.33 304	92.41 232	55.56 245	54.88 308	82.21 288

V4		69.80 260	67.02 263	78.15 261	71.86 326	60.10 246	82.02 288	87.39 264	64.48 255	57.78 278	75.98 291	41.49 267	92.90 218	63.00 208	59.16 291	81.44 296

v52		69.80 260	67.01 264	78.15 261	71.84 327	60.10 246	82.02 288	87.39 264	64.48 255	57.80 277	75.97 292	41.47 268	92.90 218	63.00 208	59.13 292	81.45 295

testgi		64.48 293	62.87 290	69.31 316	71.24 328	40.62 340	85.49 265	79.92 324	65.36 244	54.18 297	83.49 210	23.74 336	84.55 315	41.60 298	60.79 287	82.77 281

Patchmatch-RL test		68.17 273	64.49 279	79.19 240	71.22 329	53.93 300	70.07 331	71.54 345	69.22 204	56.79 283	62.89 336	56.58 141	88.61 296	69.53 151	52.61 312	95.03 59

Gipuma		34.91 330	31.44 332	45.30 341	70.99 330	39.64 344	19.85 359	72.56 342	20.10 355	16.16 356	21.47 358	5.08 361	71.16 349	13.07 355	43.70 337	25.08 356
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
UnsupCasMVSNet_eth		65.79 288	63.10 287	73.88 293	70.71 331	50.29 317	81.09 296	89.88 208	72.58 143	49.25 319	74.77 299	32.57 312	87.43 306	55.96 244	41.04 340	83.90 265

CMPMVS	48.56 21	66.77 283	64.41 280	73.84 294	70.65 332	50.31 316	77.79 319	85.73 292	45.54 336	44.76 332	82.14 226	35.40 303	90.14 277	63.18 206	74.54 183	81.07 305
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
test20.03		63.83 297	62.65 291	67.38 321	70.58 333	39.94 341	86.57 260	84.17 301	63.29 265	51.86 309	77.30 280	37.09 296	82.47 329	38.87 314	54.13 310	79.73 318

testing_2		71.09 248	67.32 262	82.40 162	69.82 334	66.52 120	83.64 274	90.77 173	72.21 153	45.12 331	71.07 323	27.60 329	93.74 198	75.71 103	69.96 217	86.95 219

MIMVSNet1		60.16 307	57.33 307	68.67 317	69.71 335	44.13 333	78.92 312	84.21 300	55.05 312	44.63 333	71.85 315	23.91 335	81.54 335	32.63 337	55.03 307	80.35 312

pmmvs-eth3d		65.53 289	62.32 293	75.19 284	69.39 336	59.59 253	82.80 285	83.43 308	62.52 272	51.30 313	72.49 306	32.86 309	87.16 308	55.32 246	50.73 320	78.83 324

test2356		64.16 295	63.28 286	66.81 323	69.37 337	39.86 343	87.76 235	86.02 287	59.83 291	53.54 303	73.23 302	34.94 305	80.67 336	39.66 305	65.20 250	79.89 316

UnsupCasMVSNet_bld		61.60 303	57.71 304	73.29 298	68.73 338	51.64 308	78.61 313	89.05 238	57.20 303	46.11 325	61.96 338	28.70 326	88.60 297	50.08 264	38.90 342	79.63 319

testus		59.36 309	57.51 306	64.90 325	66.72 339	37.56 346	84.98 267	81.09 319	57.46 302	47.72 323	72.76 303	11.43 352	78.78 343	36.56 317	58.91 294	78.36 328

new-patchmatchnet		59.30 310	56.48 310	67.79 319	65.86 340	44.19 332	82.47 286	81.77 316	59.94 290	43.65 337	66.20 330	27.67 328	81.68 334	39.34 307	41.40 339	77.50 330

PM-MVS		59.40 308	56.59 309	67.84 318	63.63 341	41.86 337	76.76 320	63.22 354	59.01 295	51.07 314	72.27 312	11.72 350	83.25 326	61.34 221	50.28 326	78.39 327

DSMNet-mixed		56.78 312	54.44 314	63.79 327	63.21 342	29.44 354	64.43 342	64.10 353	42.12 345	51.32 312	71.60 320	31.76 315	75.04 346	36.23 319	65.20 250	86.87 221

new_pmnet		49.31 320	46.44 323	57.93 331	62.84 343	40.74 339	68.47 335	62.96 355	36.48 347	35.09 345	57.81 342	14.97 347	72.18 347	32.86 336	46.44 332	60.88 348

LF4IMVS		54.01 318	52.12 316	59.69 330	62.41 344	39.91 342	68.59 334	68.28 350	42.96 343	44.55 334	75.18 296	14.09 349	68.39 350	41.36 300	51.68 317	70.78 340

1111		56.66 314	54.98 313	61.69 328	61.99 345	31.38 350	79.81 309	83.17 312	45.66 334	41.94 339	65.44 331	41.50 265	79.56 340	27.64 343	47.68 330	74.14 336

.test1245		46.52 323	49.68 320	37.02 345	61.99 345	31.38 350	79.81 309	83.17 312	45.66 334	41.94 339	65.44 331	41.50 265	79.56 340	27.64 343	0.01 361	0.13 362

ambc				69.61 315	61.38 347	41.35 338	49.07 353	85.86 291		50.18 318	66.40 329	10.16 353	88.14 302	45.73 281	44.20 335	79.32 322

test1235678		55.73 315	52.74 315	64.68 326	60.16 348	35.56 348	81.65 292	81.46 317	51.27 320	38.93 344	62.82 337	17.44 344	78.58 344	30.87 341	50.09 327	79.89 316

TDRefinement		55.28 317	51.58 318	66.39 324	59.53 349	46.15 330	76.23 321	72.80 341	44.60 339	42.49 338	76.28 289	15.29 346	82.39 330	33.20 334	43.75 336	70.62 341

pmmvs3		55.51 316	51.50 319	67.53 320	57.90 350	50.93 314	80.37 300	73.66 340	40.63 346	44.15 335	64.75 335	16.30 345	78.97 342	44.77 287	40.98 341	72.69 337

test12356		47.51 321	44.82 324	55.56 334	52.53 351	21.09 361	71.45 328	76.03 331	44.14 341	30.69 347	58.18 341	9.01 356	76.14 345	26.95 345	34.43 347	69.46 343

DeepMVS_CX				34.71 346	51.45 352	24.73 360		28.48 366	31.46 349	17.49 355	52.75 344	5.80 360	42.60 361	18.18 353	19.42 350	36.81 354

FPMVS		45.64 324	43.10 326	53.23 338	51.42 353	36.46 347	64.97 341	71.91 343	29.13 350	27.53 349	61.55 339	9.83 354	65.01 354	16.00 354	55.58 305	58.22 349

PNet_i23d		32.77 331	29.98 333	41.11 343	48.05 354	29.17 355	65.82 340	50.02 359	21.42 353	14.74 357	37.19 354	1.11 366	55.11 357	19.75 352	11.77 354	39.06 352

wuyk23d		11.30 340	10.95 341	12.33 351	48.05 354	19.89 362	25.89 358	1.92 368	3.58 360	3.12 363	1.37 363	0.64 367	15.77 363	6.23 360	7.77 360	1.35 360

testmv		46.98 322	43.53 325	57.35 333	47.75 356	30.41 353	74.99 324	77.69 327	42.84 344	28.03 348	53.36 343	8.18 357	71.18 348	24.36 347	34.55 345	70.46 342

PMMVS2		37.93 328	33.61 330	50.92 339	46.31 357	24.76 359	60.55 348	50.05 358	28.94 351	20.93 351	47.59 345	4.41 363	65.13 353	25.14 346	18.55 351	62.87 346

no-one		44.13 325	38.39 327	61.34 329	45.91 358	41.94 336	61.67 345	75.07 338	45.05 338	20.07 352	40.68 353	11.58 351	79.82 338	30.18 342	15.30 352	62.26 347

E-PMN		24.61 335	24.00 336	26.45 348	43.74 359	18.44 363	60.86 346	39.66 361	15.11 356	9.53 360	22.10 357	6.52 359	46.94 359	8.31 358	10.14 355	13.98 358

EMVS		23.76 337	23.20 338	25.46 349	41.52 360	16.90 364	60.56 347	38.79 364	14.62 357	8.99 361	20.24 361	7.35 358	45.82 360	7.25 359	9.46 357	13.64 359

LCM-MVSNet		40.54 326	35.79 328	54.76 337	36.92 361	30.81 352	51.41 351	69.02 347	22.07 352	24.63 350	45.37 348	4.56 362	65.81 352	33.67 332	34.50 346	67.67 344

ANet_high		40.27 327	35.20 329	55.47 335	34.74 362	34.47 349	63.84 343	71.56 344	48.42 328	18.80 354	41.08 351	9.52 355	64.45 355	20.18 351	8.66 359	67.49 345

MVE	24.84 23	24.35 336	19.77 340	38.09 344	34.56 363	26.92 358	26.57 357	38.87 363	11.73 359	11.37 359	27.44 355	1.37 365	50.42 358	11.41 356	14.60 353	36.93 353
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuykxyi23d		29.03 334	23.09 339	46.84 340	31.67 364	28.82 356	43.46 354	57.72 357	14.39 358	7.52 362	20.84 359	0.64 367	60.29 356	21.57 350	10.04 356	51.40 351

PMVS	26.43 22	31.84 332	28.16 334	42.89 342	25.87 365	27.58 357	50.92 352	49.78 360	21.37 354	14.17 358	40.81 352	2.01 364	66.62 351	9.61 357	38.88 343	34.49 355
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tmp_tt		22.26 338	23.75 337	17.80 350	5.23 366	12.06 365	35.26 355	39.48 362	2.82 361	18.94 353	44.20 349	22.23 339	24.64 362	36.30 318	9.31 358	16.69 357

testmvs		7.23 342	9.62 343	0.06 353	0.04 367	0.02 368	84.98 267	0.02 369	0.03 362	0.18 364	1.21 364	0.01 370	0.02 364	0.14 361	0.01 361	0.13 362

test123		6.92 343	9.21 344	0.08 352	0.03 368	0.05 367	81.65 292	0.01 370	0.02 363	0.14 365	0.85 365	0.03 369	0.02 364	0.12 362	0.00 363	0.16 361

cdsmvs_eth3d_5k		19.86 339	26.47 335	0.00 354	0.00 369	0.00 369	0.00 360	93.45 65	0.00 364	0.00 366	95.27 33	49.56 217	0.00 366	0.00 363	0.00 363	0.00 364

pcd_1.5k_mvsjas		4.46 344	5.95 345	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.00 366	53.55 183	0.00 366	0.00 363	0.00 363	0.00 364

sosnet-low-res		0.00 345	0.00 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.00 366	0.00 371	0.00 366	0.00 363	0.00 363	0.00 364

sosnet		0.00 345	0.00 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.00 366	0.00 371	0.00 366	0.00 363	0.00 363	0.00 364

uncertanet		0.00 345	0.00 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.00 366	0.00 371	0.00 366	0.00 363	0.00 363	0.00 364

Regformer		0.00 345	0.00 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.00 366	0.00 371	0.00 366	0.00 363	0.00 363	0.00 364

ab-mvs-re		7.91 341	10.55 342	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	94.95 43	0.00 371	0.00 366	0.00 363	0.00 363	0.00 364

uanet		0.00 345	0.00 346	0.00 354	0.00 369	0.00 369	0.00 360	0.00 371	0.00 364	0.00 366	0.00 366	0.00 371	0.00 366	0.00 363	0.00 363	0.00 364

GSMVS																94.68 68

test_part1				0.00 354		0.00 369	0.00 360	94.26 42				0.00 371	0.00 366	0.00 363	0.00 363	0.00 364

sam_mvs1												57.85 122				94.68 68

sam_mvs												54.91 166

MTGPA								92.23 119

test_post1							78.95 311				20.70 360	53.05 189	91.50 262	60.43 226

test_post											23.01 356	56.49 142	92.67 225

patchmatchnet-post											67.62 327	57.62 125	90.25 271

MTMP							93.77 62	32.52 365

test9_res														89.41 11	94.96 9	95.29 44

agg_prior2														86.41 34	94.75 18	95.33 41

test_prior4						67.18 87	93.92 55

test_prior2							95.10 28		75.40 92	85.25 35	95.61 24	67.94 25		87.47 25	94.77 15

旧先验2							92.00 118		59.37 294	87.54 19			93.47 205	75.39 105

新几何2							91.41 146

无先验							92.71 91	92.61 109	62.03 275				97.01 70	66.63 173		93.97 98

原ACMM2							92.01 116

testdata2													96.09 104	61.26 222

segment_acmp												65.94 44

testdata1							89.21 207		77.55 63

plane_prior5								91.31 157					95.55 127	76.74 97	78.53 151	88.39 185

plane_prior4											89.14 144

plane_prior3						61.95 220			79.09 44	72.53 142

plane_prior2							93.13 78		78.81 49

plane_prior						62.42 210	93.85 58		79.38 37						78.80 149

n2								0.00 371

nn								0.00 371

door-mid								66.01 352

test11								93.01 93

door								66.57 351

HQP5-MVS						63.66 188

BP-MVS														77.63 93

HQP4-MVS										74.18 123			95.61 123			88.63 180

HQP3-MVS								91.70 143							78.90 147

HQP2-MVS												51.63 203

MDTV_nov1_ep13_2view						59.90 250	80.13 305		67.65 227	72.79 137		54.33 174		59.83 229		92.58 133

ACMMP++_ref															71.63 204

ACMMP++															69.72 219

Test By Simon												54.21 176

High-resolution multi-view benchmark