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	75.19 107	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 86	85.98 69	97.31 3	67.06 89	95.15 26	91.99 131	69.08 208	76.50 109	93.89 71	54.48 173	98.20 24	70.76 143	85.66 106	92.69 130

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		78.94 139	77.00 152	84.76 107	96.34 6	65.86 136	92.66 96	87.97 261	62.18 275	70.56 161	92.37 100	43.53 260	97.35 52	64.50 196	82.86 125	91.05 158

test_part2					96.29 7	68.16 64				90.78 4

v1.0		37.26 330	49.67 322	0.00 355	96.29 7	0.00 370	0.00 361	94.26 42	68.52 218	90.78 4	97.23 3	0.00 372	0.00 367	0.00 364	0.00 364	0.00 365

ESAPD		88.77 9	89.21 9	87.45 29	96.26 9	67.56 76	94.17 38	94.15 44	68.77 212	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	65.93 135	94.28 37	94.27 41	74.41 104	79.16 82	95.61 24	53.99 179	98.88 9	69.62 151	93.26 38	94.50 78
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 88	80.53 99	87.54 27	96.13 11	70.59 21	93.63 65	91.04 168	65.72 243	75.45 117	92.83 92	56.11 147	98.89 8	64.10 199	89.75 76	93.15 119

APDe-MVS		87.54 19	87.84 16	86.65 47	96.07 12	66.30 126	94.84 34	93.78 50	69.35 204	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 83	95.00 42	61.59 89	97.61 42	78.16 90	89.00 79	95.63 34

APD-MVS		85.93 41	85.99 35	85.76 79	95.98 14	65.21 148	93.59 67	92.58 110	66.54 235	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 18	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		69.90 259	66.48 266	80.14 213	95.36 16	62.93 202	89.56 200	76.11 331	50.27 325	57.69 280	85.23 195	39.68 276	95.73 117	33.35 334	71.05 211	81.78 292

114514_t		79.17 135	77.67 137	83.68 132	95.32 17	65.53 144	92.85 88	91.60 146	63.49 264	67.92 207	90.63 120	46.65 243	95.72 121	67.01 172	83.54 123	89.79 169

Regformer-1		87.24 23	87.60 20	86.15 67	95.14 18	65.83 138	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 82

Regformer-2		87.00 27	87.43 22	85.71 82	95.14 18	64.73 160	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 84

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	68.48 220	77.63 96	94.35 62	73.04 9	98.45 17	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	71.90 161	82.16 56	93.49 77	47.98 233	97.05 67	82.55 59	84.82 110	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	70.90 184	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 93	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	69.19 206	81.09 62	92.88 91	57.00 133	97.44 47	81.11 72	81.76 133	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	71.80 168	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	71.87 163	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	71.75 171	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	71.87 163	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	65.09 154	92.95 84	95.11 19	81.13 27	81.68 59	95.04 40	65.82 46	98.32 22	83.02 56	84.36 114	92.97 125

Regformer-4		85.45 46	85.69 42	84.73 109	94.17 33	63.23 195	92.95 84	94.83 25	80.66 29	81.29 61	95.04 40	65.12 52	98.08 28	82.74 57	84.36 114	92.88 129

agg_prior1		87.02 26	87.26 25	86.28 65	94.16 35	66.97 92	94.08 45	93.31 78	71.85 165	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	69.96 199	74.07 128	93.57 75	63.10 81	97.50 45	70.66 144	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	58.22 119	97.00 72	85.22 42	84.33 117	96.52 13

PVSNet_BlendedMVS		83.38 72	83.43 61	83.22 139	93.76 39	67.53 78	94.06 46	93.61 58	79.13 43	81.00 64	85.14 196	63.19 79	97.29 56	87.08 30	73.91 190	84.83 259

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 90

HFP-MVS		84.73 53	84.40 52	85.72 80	93.75 41	65.01 155	93.50 70	93.19 85	72.19 155	79.22 80	94.93 45	59.04 114	97.67 35	81.55 66	92.21 48	94.49 79

#test#		84.98 51	84.74 49	85.72 80	93.75 41	65.01 155	94.09 44	93.19 85	73.55 129	79.22 80	94.93 45	59.04 114	97.67 35	82.66 58	92.21 48	94.49 79

Anonymous202405211		77.96 160	75.33 180	85.87 72	93.73 43	64.52 162	94.85 33	85.36 295	62.52 273	76.11 110	90.18 127	29.43 325	97.29 56	68.51 161	77.24 169	95.81 30

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	64.37 171	93.50 70	93.15 88	72.19 155	78.85 86	94.86 49	56.69 140	97.45 46	81.55 66	92.20 50	94.02 98

region2R		84.36 57	84.03 55	85.36 92	93.54 46	64.31 173	93.43 73	92.95 96	72.16 158	78.86 85	94.84 50	56.97 134	97.53 44	81.38 69	92.11 52	94.24 83

TSAR-MVS + GP.		87.96 14	88.37 12	86.70 46	93.51 47	65.32 146	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	65.55 143	95.39 21	95.10 20	71.77 170	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	66.05 131	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
XVS		83.87 67	83.47 59	85.05 100	93.22 50	63.78 182	92.92 86	92.66 106	73.99 116	78.18 90	94.31 65	55.25 153	97.41 48	79.16 82	91.58 58	93.95 100

X-MVStestdata		76.86 181	74.13 196	85.05 100	93.22 50	63.78 182	92.92 86	92.66 106	73.99 116	78.18 90	10.19 363	55.25 153	97.41 48	79.16 82	91.58 58	93.95 100

SMA-MVS		88.14 11	88.29 14	87.67 22	93.21 52	68.72 50	93.85 58	94.03 46	74.18 114	91.74 2	96.67 5	65.61 49	98.42 20	89.24 14	96.08 3	95.88 29

原ACMM1				84.42 118	93.21 52	64.27 176		93.40 74	65.39 244	79.51 78	92.50 95	58.11 121	96.69 90	65.27 190	93.96 25	92.32 140

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 84	93.99 69	62.25 85	98.15 26	85.93 38	91.15 64	94.15 89

CP-MVS		83.71 71	83.40 63	84.65 112	93.14 55	63.84 180	94.59 35	92.28 117	71.03 182	77.41 99	94.92 47	55.21 156	96.19 100	81.32 70	90.70 68	93.91 103

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	56.76 136	99.02 4	92.68 3	93.76 30	96.37 15

DeepPCF-MVS	81.17 1	89.72 5	91.38 3	84.72 111	93.00 58	58.16 269	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	75.23 206	73.68 203	79.86 222	92.93 59	58.68 267	90.64 177	88.30 254	60.90 283	64.43 241	90.53 121	42.38 264	94.57 152	56.52 242	76.54 173	86.33 228
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 95	91.77 107	70.81 16	96.22 99	65.03 191	81.36 134	95.94 26

HSP-MVS		90.38 2	91.89 1	85.84 74	92.83 61	64.03 179	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	84.52 116	92.83 61	62.92 204	92.76 89	91.85 137	71.52 177	75.61 115	94.24 66	53.48 188	96.99 75	78.97 85	90.73 67	93.64 108

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 79	82.25 129	96.54 12

PGM-MVS		83.25 73	82.70 75	84.92 102	92.81 64	64.07 178	90.44 180	92.20 124	71.28 180	77.23 102	94.43 56	55.17 157	97.31 55	79.33 81	91.38 61	93.37 111

EI-MVSNet-Vis-set		83.77 69	83.67 56	84.06 123	92.79 65	63.56 191	91.76 135	94.81 27	79.65 36	77.87 92	94.09 67	63.35 77	97.90 31	79.35 80	79.36 144	90.74 160

MVSTER		82.47 85	82.05 79	83.74 128	92.68 66	69.01 44	91.90 127	93.21 82	79.83 32	72.14 150	85.71 193	74.72 7	94.72 149	75.72 103	72.49 200	87.50 203

MP-MVS		85.02 50	84.97 48	85.17 98	92.60 67	64.27 176	93.24 75	92.27 118	73.13 135	79.63 77	94.43 56	61.90 87	97.17 63	85.00 43	92.56 45	94.06 96
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
thres200		79.66 127	78.33 127	83.66 134	92.54 68	65.82 139	93.06 80	96.31 9	74.90 101	73.30 133	88.66 146	59.67 108	95.61 123	47.84 273	78.67 151	89.56 173

APD-MVS_3200maxsize		81.64 97	81.32 89	82.59 152	92.36 69	58.74 266	91.39 148	91.01 169	63.35 265	79.72 76	94.62 54	51.82 200	96.14 102	79.71 77	87.93 86	92.89 128

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	74.87 121	91.62 111	68.91 18	96.08 106	66.07 182	78.45 154	95.37 39

新几何1				84.73 109	92.32 71	64.28 175		91.46 152	59.56 293	79.77 75	92.90 89	56.95 135	96.57 93	63.40 204	92.91 41	93.34 112

1121		81.25 102	80.05 102	84.87 105	92.30 72	64.31 173	87.91 232	91.39 154	59.44 294	79.94 73	92.91 88	57.09 129	97.01 70	66.63 174	92.81 43	93.29 115

EI-MVSNet-UG-set		83.14 75	82.96 68	83.67 133	92.28 73	63.19 199	91.38 150	94.68 30	79.22 40	76.60 107	93.75 72	62.64 83	97.76 33	78.07 91	78.01 155	90.05 167

HPM-MVS		83.25 73	82.95 69	84.17 121	92.25 74	62.88 206	90.91 167	91.86 136	70.30 196	77.12 103	93.96 70	56.75 138	96.28 98	82.04 62	91.34 63	93.34 112
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	84.65 270	94.50 34	79.15 42	82.23 55	87.93 159	66.88 35	96.94 80	80.53 74	82.20 130	96.39 14

tfpn200view9		78.79 143	77.43 143	82.88 143	92.21 76	64.49 163	92.05 114	96.28 10	73.48 130	71.75 155	88.26 154	60.07 105	95.32 132	45.16 283	77.58 160	88.83 177

thres400		78.68 146	77.43 143	82.43 157	92.21 76	64.49 163	92.05 114	96.28 10	73.48 130	71.75 155	88.26 154	60.07 105	95.32 132	45.16 283	77.58 160	87.48 204

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	53.55 184	97.89 32	91.10 6	93.31 37	94.54 75

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	58.98 116	96.78 86	83.49 54	93.93 26	96.29 17

旧先验1					91.94 80	60.74 235		91.50 150			94.36 58	65.23 51			91.84 53	94.55 73

thres600view7		78.00 157	76.66 155	82.03 180	91.93 81	63.69 187	91.30 155	96.33 5	72.43 146	70.46 163	87.89 160	60.31 99	94.92 142	42.64 296	76.64 171	87.48 204

LS3D		69.17 267	66.40 267	77.50 269	91.92 82	56.12 291	85.12 267	80.37 324	46.96 332	56.50 286	87.51 168	37.25 293	93.71 200	32.52 339	79.40 143	82.68 286

GG-mvs-BLEND				86.53 54	91.91 83	69.67 36	75.02 324	94.75 28		78.67 88	90.85 116	77.91 2	94.56 153	72.25 126	93.74 31	95.36 40

tfpn111		78.00 157	76.62 156	82.13 174	91.89 84	63.21 196	91.19 161	96.33 5	72.28 150	70.45 164	87.89 160	60.31 99	94.91 143	42.61 297	76.64 171	88.27 189

conf200view11		78.32 154	77.01 150	82.27 167	91.89 84	63.21 196	91.19 161	96.33 5	72.28 150	70.45 164	87.89 160	60.31 99	95.32 132	45.16 283	77.58 160	88.27 189

thres100view900		78.37 152	77.01 150	82.46 153	91.89 84	63.21 196	91.19 161	96.33 5	72.28 150	70.45 164	87.89 160	60.31 99	95.32 132	45.16 283	77.58 160	88.83 177

zzz-MVS		84.73 53	84.47 50	85.50 84	91.89 84	65.16 149	91.55 143	92.23 119	75.32 95	80.53 67	95.21 37	56.06 148	97.16 64	84.86 45	92.55 46	94.18 85

MTAPA		83.91 66	83.38 64	85.50 84	91.89 84	65.16 149	81.75 291	92.23 119	75.32 95	80.53 67	95.21 37	56.06 148	97.16 64	84.86 45	92.55 46	94.18 85

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	84.34 116	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 99	80.67 96	83.93 125	91.71 91	62.90 205	92.13 108	92.22 123	71.79 169	71.68 157	93.49 77	50.32 210	96.96 78	78.47 87	84.22 121	91.93 146
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		79.46 132	77.65 138	84.89 103	91.68 92	65.66 141	93.55 68	88.09 258	72.93 139	73.37 132	91.12 114	46.20 248	96.12 103	56.28 244	85.61 107	92.91 127

ACMMP_Plus		86.05 40	85.80 39	86.80 44	91.58 93	67.53 78	91.79 132	93.49 64	74.93 100	84.61 38	95.30 31	59.42 110	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	86.57 182	63.93 69	96.09 104	74.91 113	89.18 78	95.25 49

HPM-MVS_fast		80.25 115	79.55 113	82.33 164	91.55 95	59.95 250	91.32 154	89.16 232	65.23 247	74.71 122	93.07 84	47.81 235	95.74 116	74.87 115	88.23 83	91.31 156

CPTT-MVS		79.59 129	79.16 121	80.89 206	91.54 96	59.80 252	92.10 110	88.54 251	60.42 286	72.96 135	93.28 79	48.27 229	92.80 221	78.89 86	86.50 100	90.06 166

CNLPA		74.31 221	72.30 224	80.32 210	91.49 97	61.66 223	90.85 168	80.72 323	56.67 308	63.85 245	90.64 118	46.75 241	90.84 267	53.79 252	75.99 176	88.47 185

view600		76.93 177	75.50 176	81.23 192	91.44 98	62.00 217	89.94 193	96.56 1	70.68 188	68.54 198	87.31 171	60.79 93	94.19 175	38.90 311	75.31 179	87.48 204

view800		76.93 177	75.50 176	81.23 192	91.44 98	62.00 217	89.94 193	96.56 1	70.68 188	68.54 198	87.31 171	60.79 93	94.19 175	38.90 311	75.31 179	87.48 204

conf0.05thres1000		76.93 177	75.50 176	81.23 192	91.44 98	62.00 217	89.94 193	96.56 1	70.68 188	68.54 198	87.31 171	60.79 93	94.19 175	38.90 311	75.31 179	87.48 204

tfpn		76.93 177	75.50 176	81.23 192	91.44 98	62.00 217	89.94 193	96.56 1	70.68 188	68.54 198	87.31 171	60.79 93	94.19 175	38.90 311	75.31 179	87.48 204

MP-MVS-pluss		85.24 47	85.13 47	85.56 83	91.42 102	65.59 142	91.54 144	92.51 113	74.56 103	80.62 66	95.64 23	59.15 113	97.00 72	86.94 32	93.80 28	94.07 95
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
gg-mvs-nofinetune		77.18 175	74.31 192	85.80 76	91.42 102	68.36 58	71.78 327	94.72 29	49.61 326	77.12 103	45.92 348	77.41 3	93.98 191	67.62 167	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	53.45 189	97.68 34	91.07 7	92.62 44	94.54 75

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	84.33 117	96.65 8

EPMVS		78.49 151	75.98 164	86.02 68	91.21 106	69.68 35	80.23 304	91.20 160	75.25 97	72.48 145	78.11 276	54.65 170	93.69 201	57.66 241	83.04 124	94.69 67

FMVSNet3		77.73 163	76.04 163	82.80 144	91.20 107	68.99 45	91.87 128	91.99 131	73.35 133	67.04 218	83.19 214	56.62 141	92.14 240	59.80 231	69.34 223	87.28 215

Anonymous20240529		76.84 183	74.15 195	84.88 104	91.02 108	64.95 158	93.84 60	91.09 165	53.57 315	73.00 134	87.42 169	35.91 303	97.32 54	69.14 156	72.41 202	92.36 138

tpmvs		72.88 233	69.76 241	82.22 171	90.98 109	67.05 90	78.22 318	88.30 254	63.10 269	64.35 242	74.98 298	55.09 160	94.27 172	43.25 290	69.57 222	85.34 255

tfpn_ndepth		76.45 189	75.22 182	80.14 213	90.97 110	58.92 263	90.11 188	93.24 81	65.96 240	67.37 216	90.52 122	66.67 37	92.29 238	37.71 317	74.44 185	89.21 175

MVS		84.66 55	82.86 71	90.06 1	90.93 111	74.56 5	87.91 232	95.54 14	68.55 217	72.35 149	94.71 53	59.78 107	98.90 7	81.29 71	94.69 19	96.74 7

PVSNet	73.49 8	80.05 119	78.63 125	84.31 119	90.92 112	64.97 157	92.47 102	91.05 167	79.18 41	72.43 147	90.51 123	37.05 298	94.06 185	68.06 162	86.00 104	93.90 104

3Dnovator+	73.60 7	82.10 93	80.60 98	86.60 49	90.89 113	66.80 104	95.20 24	93.44 72	74.05 115	67.42 213	92.49 96	49.46 219	97.65 39	70.80 142	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 90	81.78 58	92.34 101	40.09 275	97.13 66	86.85 33	82.04 131	95.60 35

BH-w/o		80.49 112	79.30 118	84.05 124	90.83 115	64.36 172	93.60 66	89.42 223	74.35 109	69.09 188	90.15 128	55.23 155	95.61 123	64.61 194	86.43 101	92.17 144

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		73.08 229	70.39 236	81.13 198	90.62 118	63.33 193	91.40 147	90.06 203	51.84 320	64.46 240	80.67 253	36.49 300	94.07 184	63.83 200	64.17 264	85.98 240

TR-MVS		78.77 144	77.37 146	82.95 142	90.49 119	60.88 230	93.67 64	90.07 201	70.08 198	74.51 123	91.37 112	45.69 249	95.70 122	60.12 229	80.32 139	92.29 141

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	74.94 213	73.53 210	79.17 242	90.40 121	52.07 308	89.19 208	89.61 218	62.69 271	70.07 171	92.67 94	48.89 227	94.32 169	38.26 316	79.97 140	91.12 157
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
mvs_anonymous		81.36 101	79.99 104	85.46 86	90.39 122	68.40 56	86.88 258	90.61 179	74.41 104	70.31 169	84.67 201	63.79 71	92.32 237	73.13 117	85.70 105	95.67 31

tfpn1000		75.25 205	74.00 199	79.03 246	90.30 123	57.56 277	88.55 219	93.36 76	64.14 260	65.17 232	89.76 141	67.06 34	91.46 264	34.54 332	73.09 195	88.06 195

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	47.71 236	96.98 76	77.90 93	89.78 75	93.65 107

Fast-Effi-MVS+		81.14 103	80.01 103	84.51 117	90.24 125	65.86 136	94.12 43	89.15 233	73.81 123	75.37 118	88.26 154	57.26 128	94.53 157	66.97 173	84.92 109	93.15 119

tpmrst		80.57 109	79.14 122	84.84 106	90.10 126	68.28 61	81.70 292	89.72 216	77.63 62	75.96 111	79.54 269	64.94 62	92.71 224	75.43 105	77.28 168	93.55 109

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	77.08 105	89.81 139	63.77 72	96.97 77	79.67 78	88.21 84	92.60 133

UGNet		79.87 123	78.68 124	83.45 138	89.96 128	61.51 225	92.13 108	90.79 172	76.83 73	78.85 86	86.33 185	38.16 284	96.17 101	67.93 164	87.17 91	92.67 131
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	75.68 112	88.27 153	60.18 104	98.60 14	80.46 75	90.27 73	94.96 61

abl_6		79.82 124	79.20 120	81.70 186	89.85 130	58.34 268	88.47 221	90.07 201	62.56 272	77.71 94	93.08 82	47.65 237	96.78 86	77.94 92	85.45 108	89.99 168

BH-untuned		78.68 146	77.08 148	83.48 137	89.84 131	63.74 184	92.70 92	88.59 249	71.57 175	66.83 221	88.65 147	51.75 202	95.39 130	59.03 234	84.77 111	91.32 155

test222					89.77 132	61.60 224	89.55 201	89.42 223	56.83 307	77.28 101	92.43 98	52.76 193			91.14 65	93.09 121

PMMVS		81.98 95	82.04 80	81.78 182	89.76 133	56.17 290	91.13 164	90.69 175	77.96 57	80.09 72	93.57 75	46.33 246	94.99 138	81.41 68	87.46 90	94.17 87

conf0.01		74.95 211	73.61 204	78.96 247	89.65 134	56.94 283	87.72 236	93.45 65	65.14 248	65.68 224	89.99 132	65.09 53	91.67 250	35.16 324	70.61 212	88.27 189

conf0.002		74.95 211	73.61 204	78.96 247	89.65 134	56.94 283	87.72 236	93.45 65	65.14 248	65.68 224	89.99 132	65.09 53	91.67 250	35.16 324	70.61 212	88.27 189

thresconf0.02		74.92 214	73.61 204	78.85 250	89.65 134	56.94 283	87.72 236	93.45 65	65.14 248	65.68 224	89.99 132	65.09 53	91.67 250	35.16 324	70.61 212	87.94 196

tfpn_n400		74.92 214	73.61 204	78.85 250	89.65 134	56.94 283	87.72 236	93.45 65	65.14 248	65.68 224	89.99 132	65.09 53	91.67 250	35.16 324	70.61 212	87.94 196

tfpnconf		74.92 214	73.61 204	78.85 250	89.65 134	56.94 283	87.72 236	93.45 65	65.14 248	65.68 224	89.99 132	65.09 53	91.67 250	35.16 324	70.61 212	87.94 196

tfpnview11		74.92 214	73.61 204	78.85 250	89.65 134	56.94 283	87.72 236	93.45 65	65.14 248	65.68 224	89.99 132	65.09 53	91.67 250	35.16 324	70.61 212	87.94 196

QAPM		79.95 122	77.39 145	87.64 23	89.63 140	71.41 12	93.30 74	93.70 55	65.34 246	67.39 215	91.75 109	47.83 234	98.96 5	57.71 240	89.81 74	92.54 135

3Dnovator	73.91 6	82.69 83	80.82 94	88.31 14	89.57 141	71.26 14	92.60 97	94.39 40	78.84 48	67.89 208	92.48 97	48.42 228	98.52 15	68.80 160	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	86.12 287	72.59 143	83.22 51	92.81 93	59.60 109	96.01 109	81.76 64	87.80 88	95.56 36

PatchmatchNet		77.46 165	74.63 186	85.96 70	89.55 143	70.35 23	79.97 308	89.55 219	72.23 153	70.94 160	76.91 288	57.03 131	92.79 222	54.27 250	81.17 135	94.74 66
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PatchMatch-RL		72.06 238	69.98 237	78.28 258	89.51 144	55.70 293	83.49 277	83.39 311	61.24 282	63.72 246	82.76 216	34.77 307	93.03 212	53.37 256	77.59 159	86.12 233

UA-Net		80.02 120	79.65 109	81.11 199	89.33 145	57.72 273	86.33 262	89.00 240	77.44 65	81.01 63	89.15 143	59.33 111	95.90 110	61.01 224	84.28 119	89.73 171

dp		75.01 209	72.09 226	83.76 127	89.28 146	66.22 129	79.96 309	89.75 211	71.16 181	67.80 210	77.19 284	51.81 201	92.54 229	50.39 263	71.44 209	92.51 136

tpmp4_e23		78.85 140	76.55 157	85.77 78	89.25 147	68.39 57	81.63 295	91.38 155	70.40 194	75.21 119	79.22 271	67.37 32	94.79 144	58.98 236	75.51 178	94.13 90

sss		82.71 82	82.38 77	83.73 130	89.25 147	59.58 255	92.24 106	94.89 23	77.96 57	79.86 74	92.38 99	56.70 139	97.05 67	77.26 97	80.86 138	94.55 73

MVSFormer		83.75 70	82.88 70	86.37 61	89.24 149	71.18 16	89.07 211	90.69 175	65.80 241	87.13 20	94.34 63	64.99 60	92.67 226	72.83 120	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 89	80.46 100	87.35 32	89.14 151	70.28 24	95.59 18	95.17 17	78.85 47	70.19 170	85.82 190	70.66 17	97.67 35	72.19 129	66.52 243	94.09 93
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			72.61 220		89.06 152	68.48 54	80.33 302	90.11 200	71.84 166	71.81 154	75.92 295	53.01 191	93.92 194	48.04 272	73.38 191

testdata				81.34 190	89.02 153	57.72 273		89.84 209	58.65 298	85.32 34	94.09 67	57.03 131	93.28 208	69.34 154	90.56 71	93.03 123

CostFormer		82.33 87	81.15 90	85.86 73	89.01 154	68.46 55	82.39 288	93.01 93	75.59 88	80.25 71	81.57 237	72.03 13	94.96 139	79.06 84	77.48 165	94.16 88

GBi-Net		75.65 199	73.83 201	81.10 200	88.85 155	65.11 151	90.01 189	90.32 187	70.84 185	67.04 218	80.25 260	48.03 230	91.54 259	59.80 231	69.34 223	86.64 224

test1		75.65 199	73.83 201	81.10 200	88.85 155	65.11 151	90.01 189	90.32 187	70.84 185	67.04 218	80.25 260	48.03 230	91.54 259	59.80 231	69.34 223	86.64 224

FMVSNet2		76.07 193	74.01 198	82.26 170	88.85 155	67.66 73	91.33 153	91.61 145	70.84 185	65.98 223	82.25 224	48.03 230	92.00 245	58.46 237	68.73 229	87.10 217

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	76.91 106	93.64 74	62.59 84	98.44 18	85.50 40	92.84 42	94.03 97
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 96	81.52 87	82.61 151	88.77 159	60.21 245	93.02 82	93.66 57	68.52 218	72.90 137	90.39 124	72.19 12	94.96 139	74.93 112	79.29 146	92.67 131

1112_ss		80.56 110	79.83 107	82.77 145	88.65 160	60.78 232	92.29 104	88.36 253	72.58 144	72.46 146	94.95 43	65.09 53	93.42 207	66.38 178	77.71 157	94.10 92

tpm cat1		75.30 204	72.21 225	84.58 114	88.52 161	67.77 70	78.16 319	88.02 259	61.88 279	68.45 203	76.37 289	60.65 97	94.03 189	53.77 253	74.11 187	91.93 146

LCM-MVSNet-Re		72.93 231	71.84 227	76.18 282	88.49 162	48.02 325	80.07 307	70.17 347	73.96 119	52.25 309	80.09 263	49.98 214	88.24 302	67.35 168	84.23 120	92.28 142

Vis-MVSNet		80.92 107	79.98 105	83.74 128	88.48 163	61.80 222	93.44 72	88.26 257	73.96 119	77.73 93	91.76 108	49.94 215	94.76 146	65.84 185	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)		79.24 134	79.57 110	78.24 261	88.46 164	52.29 307	90.41 182	89.12 234	74.24 110	69.13 187	91.91 105	65.77 47	90.09 281	59.00 235	88.09 85	92.33 139

ab-mvs		80.18 116	78.31 128	85.80 76	88.44 165	65.49 145	83.00 285	92.67 105	71.82 167	77.36 100	85.01 197	54.50 171	96.59 91	76.35 102	75.63 177	95.32 43

gm-plane-assit					88.42 166	67.04 91			78.62 52		91.83 106		97.37 50	76.57 100

MVS_111021_LR		82.02 94	81.52 87	83.51 136	88.42 166	62.88 206	89.77 199	88.93 241	76.78 74	75.55 116	93.10 80	50.31 211	95.38 131	83.82 53	87.02 92	92.26 143

tpm2		79.80 125	77.95 134	85.34 93	88.28 168	68.26 62	81.56 296	91.42 153	70.11 197	77.59 98	80.50 255	67.40 31	94.26 174	67.34 169	77.35 166	93.51 110

Test_1112_low_res		79.56 130	78.60 126	82.43 157	88.24 169	60.39 241	92.09 111	87.99 260	72.10 159	71.84 153	87.42 169	64.62 63	93.04 211	65.80 186	77.30 167	93.85 105

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 70	93.07 84	68.27 21	95.02 137	78.39 89	93.59 34	94.09 93

TESTMET0.1,1		82.41 86	81.98 81	83.72 131	88.08 171	63.74 184	92.70 92	93.77 52	79.30 38	77.61 97	87.57 167	58.19 120	94.08 183	73.91 116	86.68 96	93.33 114

diffmvs1		82.57 84	81.71 85	85.15 99	88.07 172	66.09 130	87.52 246	88.92 242	76.45 82	80.41 69	87.04 178	60.29 103	94.77 145	80.30 76	86.36 102	94.59 71

ADS-MVSNet2		66.90 283	63.44 286	77.26 275	88.06 173	60.70 236	68.01 337	75.56 336	57.57 300	64.48 238	69.87 325	38.68 278	84.10 317	40.87 302	67.89 235	86.97 218

ADS-MVSNet		68.54 271	64.38 282	81.03 203	88.06 173	66.90 95	68.01 337	84.02 304	57.57 300	64.48 238	69.87 325	38.68 278	89.21 295	40.87 302	67.89 235	86.97 218

EPNet_dtu		78.80 142	79.26 119	77.43 271	88.06 173	49.71 321	91.96 120	91.95 134	77.67 61	76.56 108	91.28 113	58.51 118	90.20 276	56.37 243	80.95 137	92.39 137
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
diffmvs		81.52 98	80.44 101	84.76 107	87.98 176	65.79 140	86.97 256	88.84 244	76.57 78	78.24 89	85.79 192	58.10 122	94.55 154	77.40 96	84.11 122	93.95 100

IS-MVSNet		80.14 117	79.41 115	82.33 164	87.91 177	60.08 249	91.97 119	88.27 256	72.90 140	71.44 159	91.73 110	61.44 90	93.66 202	62.47 217	86.53 99	93.24 116

CLD-MVS		82.73 80	82.35 78	83.86 126	87.90 178	67.65 74	95.45 19	92.18 127	85.06 8	72.58 142	92.27 102	52.46 197	95.78 114	84.18 48	79.06 147	88.16 193
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		81.03 105	79.56 111	85.43 89	87.81 179	68.11 65	90.18 187	90.01 205	70.65 192	72.95 136	86.06 188	63.61 74	94.50 158	75.01 111	79.75 142	93.67 106

1314		80.70 108	78.95 123	85.94 71	87.77 180	67.56 76	87.91 232	92.55 111	72.17 157	67.44 212	93.09 81	50.27 212	97.04 69	71.68 132	87.64 89	93.23 117

HQP-NCC					87.54 181		94.06 46		79.80 33	74.18 124

ACMP_Plane					87.54 181		94.06 46		79.80 33	74.18 124

HQP-MVS		81.14 103	80.64 97	82.64 150	87.54 181	63.66 189	94.06 46	91.70 143	79.80 33	74.18 124	90.30 125	51.63 204	95.61 123	77.63 94	78.90 148	88.63 181

NP-MVS					87.41 184	63.04 200					90.30 125

plane_prior6					87.23 185	62.32 213						50.66 208

plane_prior1					87.15 186

cascas		78.18 155	75.77 167	85.41 90	87.14 187	69.11 42	92.96 83	91.15 162	66.71 234	70.47 162	86.07 187	37.49 292	96.48 95	70.15 147	79.80 141	90.65 161

CHOSEN 280x420		77.35 170	76.95 153	78.55 255	87.07 188	62.68 210	69.71 333	82.95 315	68.80 211	71.48 158	87.27 176	66.03 43	84.00 321	76.47 101	82.81 127	88.95 176

HQP_MVS		80.34 114	79.75 108	82.12 175	86.94 189	62.42 211	93.13 78	91.31 157	78.81 49	72.53 143	89.14 144	50.66 208	95.55 127	76.74 98	78.53 152	88.39 186

plane_prior7					86.94 189	61.51 225

test-LLR		80.10 118	79.56 111	81.72 184	86.93 191	61.17 227	92.70 92	91.54 147	71.51 178	75.62 113	86.94 179	53.83 180	92.38 234	72.21 127	84.76 112	91.60 149

test-mter		79.96 121	79.38 117	81.72 184	86.93 191	61.17 227	92.70 92	91.54 147	73.85 121	75.62 113	86.94 179	49.84 217	92.38 234	72.21 127	84.76 112	91.60 149

Patchmatch-test1		75.00 210	71.80 229	84.58 114	86.63 193	70.08 26	81.06 298	89.19 230	71.60 174	70.01 172	77.16 286	45.53 250	88.63 296	51.79 259	73.27 192	95.02 60

xiu_mvs_v1_base_debu		82.16 90	81.12 91	85.26 95	86.42 194	68.72 50	92.59 99	90.44 181	73.12 136	84.20 44	94.36 58	38.04 286	95.73 117	84.12 49	86.81 93	91.33 152

xiu_mvs_v1_base		82.16 90	81.12 91	85.26 95	86.42 194	68.72 50	92.59 99	90.44 181	73.12 136	84.20 44	94.36 58	38.04 286	95.73 117	84.12 49	86.81 93	91.33 152

xiu_mvs_v1_base_debi		82.16 90	81.12 91	85.26 95	86.42 194	68.72 50	92.59 99	90.44 181	73.12 136	84.20 44	94.36 58	38.04 286	95.73 117	84.12 49	86.81 93	91.33 152

F-COLMAP		70.66 253	68.44 252	77.32 273	86.37 197	55.91 292	88.00 228	86.32 282	56.94 306	57.28 283	88.07 158	33.58 309	92.49 231	51.02 261	68.37 231	83.55 268

CDS-MVSNet		81.43 100	80.74 95	83.52 135	86.26 198	64.45 166	92.09 111	90.65 178	75.83 87	73.95 130	89.81 139	63.97 68	92.91 218	71.27 136	82.82 126	93.20 118
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
VDDNet		80.50 111	78.26 129	87.21 34	86.19 199	69.79 32	94.48 36	91.31 157	60.42 286	79.34 79	90.91 115	38.48 282	96.56 94	82.16 60	81.05 136	95.27 46

jason		86.40 34	86.17 34	87.11 38	86.16 200	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	79.29 133	77.63 139	84.29 120	86.06 201	65.96 134	87.03 252	91.10 164	69.86 200	69.79 177	90.64 118	57.54 127	96.59 91	64.37 198	82.29 128	90.32 164
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MS-PatchMatch		77.90 162	76.50 158	82.12 175	85.99 202	69.95 29	91.75 137	92.70 103	73.97 118	62.58 256	84.44 204	41.11 271	95.78 114	63.76 201	92.17 51	80.62 311

FIs		79.47 131	79.41 115	79.67 226	85.95 203	59.40 257	91.68 139	93.94 47	78.06 56	68.96 191	88.28 152	66.61 38	91.77 248	66.20 181	74.99 183	87.82 200

VPA-MVSNet		79.03 136	78.00 133	82.11 178	85.95 203	64.48 165	93.22 77	94.66 31	75.05 99	74.04 129	84.95 198	52.17 199	93.52 204	74.90 114	67.04 239	88.32 188

tpm		78.58 149	77.03 149	83.22 139	85.94 205	64.56 161	83.21 283	91.14 163	78.31 54	73.67 131	79.68 266	64.01 67	92.09 243	66.07 182	71.26 210	93.03 123

OpenMVS	70.45 11	78.54 150	75.92 165	86.41 60	85.93 206	71.68 11	92.74 90	92.51 113	66.49 236	64.56 237	91.96 104	43.88 259	98.10 27	54.61 248	90.65 69	89.44 174

OMC-MVS		78.67 148	77.91 136	80.95 205	85.76 207	57.40 278	88.49 220	88.67 247	73.85 121	72.43 147	92.10 103	49.29 221	94.55 154	72.73 122	77.89 156	90.91 159

EI-MVSNet		78.97 138	78.22 130	81.25 191	85.33 208	62.73 209	89.53 203	93.21 82	72.39 148	72.14 150	90.13 129	60.99 91	94.72 149	67.73 166	72.49 200	86.29 229

CVMVSNet		74.04 223	74.27 193	73.33 298	85.33 208	43.94 335	89.53 203	88.39 252	54.33 314	70.37 167	90.13 129	49.17 223	84.05 318	61.83 221	79.36 144	91.99 145

ACMH	63.93 17	68.62 269	64.81 275	80.03 217	85.22 210	63.25 194	87.72 236	84.66 299	60.83 284	51.57 312	79.43 270	27.29 331	94.96 139	41.76 298	64.84 258	81.88 291
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TAMVS		80.37 113	79.45 114	83.13 141	85.14 211	63.37 192	91.23 157	90.76 174	74.81 102	72.65 140	88.49 148	60.63 98	92.95 214	69.41 153	81.95 132	93.08 122

MSDG		69.54 265	65.73 269	80.96 204	85.11 212	63.71 186	84.19 272	83.28 312	56.95 305	54.50 293	84.03 205	31.50 318	96.03 107	42.87 294	69.13 226	83.14 279

ACMP	71.68 10	75.58 202	74.23 194	79.62 228	84.97 213	59.64 253	90.80 170	89.07 237	70.39 195	62.95 252	87.30 175	38.28 283	93.87 196	72.89 119	71.45 208	85.36 254
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
FC-MVSNet-test		77.99 159	78.08 132	77.70 266	84.89 214	55.51 294	90.27 185	93.75 54	76.87 71	66.80 222	87.59 166	65.71 48	90.23 275	62.89 212	73.94 189	87.37 211

PVSNet_0	68.08 15	71.81 240	68.32 254	82.27 167	84.68 215	62.31 214	88.68 216	90.31 190	75.84 86	57.93 277	80.65 254	37.85 289	94.19 175	69.94 148	29.05 350	90.31 165

WR-MVS		76.76 185	75.74 168	79.82 223	84.60 216	62.27 215	92.60 97	92.51 113	76.06 84	67.87 209	85.34 194	56.76 136	90.24 274	62.20 218	63.69 269	86.94 221

ACMH+	65.35 16	67.65 278	64.55 278	76.96 276	84.59 217	57.10 281	88.08 227	80.79 322	58.59 299	53.00 306	81.09 249	26.63 333	92.95 214	46.51 278	61.69 282	80.82 308

VPNet		78.82 141	77.53 141	82.70 147	84.52 218	66.44 122	93.93 54	92.23 119	80.46 30	72.60 141	88.38 151	49.18 222	93.13 210	72.47 125	63.97 267	88.55 183

IterMVS-LS		76.49 187	75.18 183	80.43 209	84.49 219	62.74 208	90.64 177	88.80 245	72.40 147	65.16 233	81.72 236	60.98 92	92.27 239	67.74 165	64.65 261	86.29 229
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
UniMVSNet_NR-MVSNet		78.15 156	77.55 140	79.98 218	84.46 220	60.26 243	92.25 105	93.20 84	77.50 64	68.88 192	86.61 181	66.10 42	92.13 241	66.38 178	62.55 271	87.54 202

FMVSNet5		68.04 275	65.66 270	75.18 286	84.43 221	57.89 270	83.54 276	86.26 284	61.83 280	53.64 303	73.30 302	37.15 296	85.08 314	48.99 268	61.77 278	82.56 288

MVS-HIRNet		60.25 307	55.55 313	74.35 291	84.37 222	56.57 289	71.64 328	74.11 340	34.44 349	45.54 331	42.24 351	31.11 321	89.81 288	40.36 305	76.10 175	76.67 333

LPG-MVS_test		75.82 198	74.58 188	79.56 230	84.31 223	59.37 258	90.44 180	89.73 214	69.49 202	64.86 234	88.42 149	38.65 280	94.30 170	72.56 123	72.76 197	85.01 257

LGP-MVS_train				79.56 230	84.31 223	59.37 258		89.73 214	69.49 202	64.86 234	88.42 149	38.65 280	94.30 170	72.56 123	72.76 197	85.01 257

ACMM	69.62 13	74.34 220	72.73 218	79.17 242	84.25 225	57.87 271	90.36 183	89.93 207	63.17 268	65.64 230	86.04 189	37.79 290	94.10 181	65.89 184	71.52 207	85.55 251
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
UniMVSNet (Re)		77.58 164	76.78 154	79.98 218	84.11 226	60.80 231	91.76 135	93.17 87	76.56 80	69.93 176	84.78 200	63.32 78	92.36 236	64.89 192	62.51 273	86.78 223

test_0402		64.54 293	61.09 298	74.92 287	84.10 227	60.75 234	87.95 229	79.71 326	52.03 319	52.41 308	77.20 283	32.21 315	91.64 256	23.14 349	61.03 285	72.36 339

LTVRE_ROB	59.60 19	66.27 286	63.54 285	74.45 290	84.00 228	51.55 310	67.08 340	83.53 308	58.78 297	54.94 291	80.31 258	34.54 308	93.23 209	40.64 304	68.03 233	78.58 327
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		65.86 288	60.94 299	80.62 207	83.75 229	58.83 264	58.91 350	75.26 338	44.50 341	50.95 316	77.09 287	58.81 117	87.90 304	35.13 330	64.03 265	95.12 54

nrg030		80.93 106	79.86 106	84.13 122	83.69 230	68.83 48	93.23 76	91.20 160	75.55 89	75.06 120	88.22 157	63.04 82	94.74 148	81.88 63	66.88 240	88.82 179

GA-MVS		78.33 153	76.23 161	84.65 112	83.65 231	66.30 126	91.44 145	90.14 199	76.01 85	70.32 168	84.02 206	42.50 263	94.72 149	70.98 140	77.00 170	92.94 126

FMVSNet1		72.71 235	69.91 239	81.10 200	83.60 232	65.11 151	90.01 189	90.32 187	63.92 261	63.56 247	80.25 260	36.35 301	91.54 259	54.46 249	66.75 241	86.64 224

OPM-MVS		79.00 137	78.09 131	81.73 183	83.52 233	63.83 181	91.64 142	90.30 191	76.36 83	71.97 152	89.93 138	46.30 247	95.17 136	75.10 108	77.70 158	86.19 231

tfpnnormal		70.10 257	67.36 261	78.32 257	83.45 234	60.97 229	88.85 213	92.77 101	64.85 255	60.83 261	78.53 274	43.52 261	93.48 205	31.73 340	61.70 281	80.52 312

Effi-MVS+-dtu		76.14 192	75.28 181	78.72 254	83.22 235	55.17 296	89.87 197	87.78 262	75.42 91	67.98 206	81.43 238	45.08 253	92.52 230	75.08 109	71.63 205	88.48 184

mvs-test1		78.74 145	77.95 134	81.14 197	83.22 235	57.13 280	93.96 51	87.78 262	75.42 91	72.68 139	90.80 117	45.08 253	94.54 156	75.08 109	77.49 164	91.74 148

CR-MVSNet		73.79 226	70.82 235	82.70 147	83.15 237	67.96 67	70.25 330	84.00 305	73.67 127	69.97 174	72.41 310	57.82 124	89.48 292	52.99 257	73.13 193	90.64 162

RPMNet		69.58 264	65.21 274	82.70 147	83.15 237	67.96 67	70.25 330	86.15 286	46.83 334	69.97 174	65.10 335	56.48 144	89.48 292	35.79 323	73.13 193	90.64 162

DU-MVS		76.86 181	75.84 166	79.91 220	82.96 239	60.26 243	91.26 156	91.54 147	76.46 81	68.88 192	86.35 183	56.16 145	92.13 241	66.38 178	62.55 271	87.35 213

NR-MVSNet		76.05 194	74.59 187	80.44 208	82.96 239	62.18 216	90.83 169	91.73 140	77.12 67	60.96 260	86.35 183	59.28 112	91.80 247	60.74 225	61.34 284	87.35 213

XXY-MVS		77.94 161	76.44 159	82.43 157	82.60 241	64.44 167	92.01 116	91.83 138	73.59 128	70.00 173	85.82 190	54.43 174	94.76 146	69.63 150	68.02 234	88.10 194

TranMVSNet+NR-MVSNet		75.86 197	74.52 190	79.89 221	82.44 242	60.64 238	91.37 151	91.37 156	76.63 76	67.65 211	86.21 186	52.37 198	91.55 258	61.84 220	60.81 287	87.48 204

IterMVS		72.65 237	70.83 234	78.09 264	82.17 243	62.96 201	87.64 244	86.28 283	71.56 176	60.44 262	78.85 273	45.42 252	86.66 310	63.30 205	61.83 277	84.65 261
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Patchmtry		67.53 280	63.93 283	78.34 256	82.12 244	64.38 170	68.72 334	84.00 305	48.23 331	59.24 267	72.41 310	57.82 124	89.27 294	46.10 280	56.68 303	81.36 299

PatchT		69.11 268	65.37 273	80.32 210	82.07 245	63.68 188	67.96 339	87.62 264	50.86 324	69.37 184	65.18 334	57.09 129	88.53 300	41.59 300	66.60 242	88.74 180

Anonymous20240521		69.68 263	68.15 257	74.28 293	82.04 246	49.91 319	85.92 265	90.52 180	63.87 262	57.61 281	81.33 241	41.82 265	89.57 291	46.86 277	63.36 270	83.37 275

MIMVSNet		71.64 243	68.44 252	81.23 192	81.97 247	64.44 167	73.05 326	88.80 245	69.67 201	64.59 236	74.79 299	32.79 311	87.82 305	53.99 251	76.35 174	91.42 151

MVP-Stereo		77.12 176	76.23 161	79.79 224	81.72 248	66.34 125	89.29 205	90.88 170	70.56 193	62.01 259	82.88 215	49.34 220	94.13 180	65.55 188	93.80 28	78.88 324
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
semantic-postprocess				76.32 280	81.48 249	60.67 237		85.99 289	66.17 238	59.50 266	78.88 272	45.51 251	83.65 323	62.58 216	61.93 276	84.63 262

pcd1.5k->3k		31.17 334	31.85 332	29.12 348	81.48 249	0.00 370	0.00 361	91.79 139	0.00 365	0.00 367	0.00 367	41.05 272	0.00 367	0.00 364	72.34 203	87.36 212

COLMAP_ROB	57.96 20	62.98 302	59.65 302	72.98 301	81.44 251	53.00 305	83.75 274	75.53 337	48.34 330	48.81 321	81.40 240	24.14 335	90.30 271	32.95 336	60.52 289	75.65 335
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
JIA-IIPM		66.06 287	62.45 293	76.88 277	81.42 252	54.45 300	57.49 351	88.67 247	49.36 327	63.86 244	46.86 347	56.06 148	90.25 272	49.53 267	68.83 227	85.95 241

WR-MVS_H		70.59 254	69.94 238	72.53 304	81.03 253	51.43 311	87.35 249	92.03 130	67.38 231	60.23 263	80.70 251	55.84 152	83.45 325	46.33 279	58.58 297	82.72 284

DI_MVS_plusplus_test		79.78 126	77.50 142	86.62 48	80.90 254	69.46 37	90.69 175	91.97 133	77.00 69	59.07 270	82.34 222	46.82 240	95.88 111	82.14 61	86.59 98	94.53 77

Fast-Effi-MVS+-dtu		75.04 208	73.37 213	80.07 216	80.86 255	59.52 256	91.20 160	85.38 294	71.90 161	65.20 231	84.84 199	41.46 270	92.97 213	66.50 177	72.96 196	87.73 201

Baseline_NR-MVSNet		73.99 224	72.83 217	77.48 270	80.78 256	59.29 260	91.79 132	84.55 300	68.85 210	68.99 190	80.70 251	56.16 145	92.04 244	62.67 215	60.98 286	81.11 305

v18		71.94 239	69.43 242	79.50 232	80.74 257	66.82 98	88.16 226	86.66 273	68.95 209	55.55 287	72.66 305	55.03 162	90.15 277	64.78 193	52.30 315	81.54 293

test_normal		79.66 127	77.36 147	86.54 52	80.72 258	69.21 41	90.68 176	92.16 128	76.99 70	58.63 274	82.03 231	46.70 242	95.86 112	81.74 65	86.63 97	94.56 72

CP-MVSNet		70.50 256	69.91 239	72.26 307	80.71 259	51.00 314	87.23 250	90.30 191	67.84 225	59.64 265	82.69 217	50.23 213	82.30 332	51.28 260	59.28 291	83.46 272

v1neww		77.39 167	75.71 169	82.44 154	80.69 260	66.83 96	91.94 124	90.18 196	74.19 111	69.60 178	82.51 218	54.99 164	94.44 159	71.68 132	65.60 246	86.05 236

v7new		77.39 167	75.71 169	82.44 154	80.69 260	66.83 96	91.94 124	90.18 196	74.19 111	69.60 178	82.51 218	54.99 164	94.44 159	71.68 132	65.60 246	86.05 236

v8		75.35 203	73.26 214	81.61 187	80.67 262	66.82 98	89.54 202	89.27 227	71.65 172	63.30 250	80.30 259	54.99 164	94.06 185	67.33 170	62.33 274	83.94 265

v6		77.39 167	75.71 169	82.44 154	80.67 262	66.82 98	91.94 124	90.18 196	74.19 111	69.60 178	82.50 221	55.00 163	94.44 159	71.68 132	65.60 246	86.05 236

v16		71.81 240	69.26 244	79.47 233	80.66 264	66.81 102	87.93 230	86.63 275	68.70 215	55.35 289	72.51 306	54.75 168	90.12 279	64.51 195	52.28 316	81.47 294

PS-MVSNAJss		77.26 174	76.31 160	80.13 215	80.64 265	59.16 261	90.63 179	91.06 166	72.80 141	68.58 197	84.57 203	53.55 184	93.96 192	72.97 118	71.96 204	87.27 216

v1141		77.28 172	75.57 173	82.42 160	80.63 266	66.73 106	91.96 120	90.42 184	74.41 104	69.46 181	82.12 228	55.09 160	94.40 164	70.99 139	65.05 253	86.12 233

v17		71.77 242	69.20 245	79.46 234	80.62 267	66.81 102	87.93 230	86.63 275	68.71 214	55.25 290	72.49 307	54.72 169	90.11 280	64.50 196	51.97 317	81.47 294

divwei89l23v2f112		77.28 172	75.57 173	82.42 160	80.62 267	66.72 108	91.96 120	90.42 184	74.41 104	69.46 181	82.12 228	55.11 159	94.40 164	71.00 137	65.04 254	86.12 233

TransMVSNet (Re)		70.07 258	67.66 260	77.31 274	80.62 267	59.13 262	91.78 134	84.94 298	65.97 239	60.08 264	80.44 256	50.78 207	91.87 246	48.84 269	45.46 335	80.94 307

v1		77.29 171	75.57 173	82.42 160	80.61 270	66.73 106	91.96 120	90.42 184	74.41 104	69.46 181	82.12 228	55.14 158	94.40 164	71.00 137	65.04 254	86.13 232

v15		71.40 244	68.75 247	79.35 235	80.39 271	66.70 110	87.57 245	86.64 274	68.66 216	54.68 292	72.00 314	54.50 171	89.98 282	63.69 202	50.66 322	81.38 298

v2v482		77.42 166	75.65 172	82.73 146	80.38 272	67.13 88	91.85 130	90.23 193	75.09 98	69.37 184	83.39 212	53.79 182	94.44 159	71.77 130	65.00 257	86.63 227

v7		76.83 184	75.01 184	82.29 166	80.35 273	66.70 110	91.68 139	89.97 206	73.47 132	69.22 186	82.22 225	52.52 195	94.43 163	69.73 149	65.96 245	85.74 248

PS-CasMVS		69.86 260	69.13 246	72.07 310	80.35 273	50.57 316	87.02 253	89.75 211	67.27 232	59.19 268	82.28 223	46.58 244	82.24 333	50.69 262	59.02 294	83.39 274

v11		71.05 250	68.32 254	79.23 239	80.34 275	66.57 117	87.01 254	86.55 279	68.11 223	54.40 295	71.66 319	52.94 192	89.91 285	62.71 214	51.12 320	81.21 302

V14		71.29 246	68.61 249	79.31 236	80.34 275	66.65 112	87.39 248	86.61 277	68.41 221	54.49 294	71.91 315	54.25 176	89.96 283	63.50 203	50.62 323	81.33 300

v10		74.77 218	72.54 222	81.46 188	80.33 277	66.71 109	89.15 209	89.08 236	70.94 183	63.08 251	79.86 264	52.52 195	94.04 188	65.70 187	62.17 275	83.64 267

V9		71.16 247	68.46 251	79.27 238	80.26 278	66.60 114	87.21 251	86.56 278	68.17 222	54.26 297	71.81 317	54.00 178	89.93 284	63.28 206	50.57 324	81.27 301

test0.0.03 1		72.76 234	72.71 219	72.88 302	80.25 279	47.99 326	91.22 158	89.45 221	71.51 178	62.51 257	87.66 165	53.83 180	85.06 315	50.16 264	67.84 237	85.58 249

v1144		76.73 186	74.88 185	82.27 167	80.23 280	66.60 114	91.68 139	90.21 195	73.69 125	69.06 189	81.89 233	52.73 194	94.40 164	69.21 155	65.23 250	85.80 244

v12		71.02 251	68.29 256	79.22 240	80.18 281	66.53 119	87.01 254	86.54 280	67.90 224	54.00 300	71.70 318	53.66 183	89.91 285	63.09 208	50.51 325	81.21 302

v13		70.90 252	68.15 257	79.15 244	80.08 282	66.45 121	86.83 259	86.50 281	67.62 230	53.78 302	71.61 320	53.51 187	89.87 287	62.89 212	50.50 326	81.14 304

LP		56.71 314	51.64 318	71.91 312	80.08 282	60.33 242	61.72 345	75.61 335	43.87 343	43.76 337	60.30 341	30.46 323	84.05 318	22.94 350	46.06 334	71.34 340

v148		76.19 191	74.47 191	81.36 189	80.05 284	64.44 167	91.75 137	90.23 193	73.68 126	67.13 217	80.84 250	55.92 151	93.86 198	68.95 158	61.73 280	85.76 247

v1192		75.98 196	73.92 200	82.15 173	79.73 285	66.24 128	91.22 158	89.75 211	72.67 142	68.49 202	81.42 239	49.86 216	94.27 172	67.08 171	65.02 256	85.95 241

AllTest		61.66 303	58.06 304	72.46 305	79.57 286	51.42 312	80.17 305	68.61 349	51.25 322	45.88 327	81.23 243	19.86 343	86.58 311	38.98 309	57.01 301	79.39 321

TestCases				72.46 305	79.57 286	51.42 312		68.61 349	51.25 322	45.88 327	81.23 243	19.86 343	86.58 311	38.98 309	57.01 301	79.39 321

MDA-MVSNet-bldmvs		61.54 305	57.70 306	73.05 300	79.53 288	57.00 282	83.08 284	81.23 319	57.57 300	34.91 347	72.45 309	32.79 311	86.26 313	35.81 322	41.95 339	75.89 334

v144192		76.05 194	74.03 197	82.12 175	79.50 289	66.55 118	91.39 148	89.71 217	72.30 149	68.17 204	81.33 241	51.75 202	94.03 189	67.94 163	64.19 263	85.77 245

v1921920		75.63 201	73.49 211	82.06 179	79.38 290	66.35 124	91.07 166	89.48 220	71.98 160	67.99 205	81.22 245	49.16 224	93.90 195	66.56 176	64.56 262	85.92 243

PEN-MVS		69.46 266	68.56 250	72.17 309	79.27 291	49.71 321	86.90 257	89.24 229	67.24 233	59.08 269	82.51 218	47.23 239	83.54 324	48.42 271	57.12 299	83.25 276

v1240		75.21 207	72.98 216	81.88 181	79.20 292	66.00 133	90.75 172	89.11 235	71.63 173	67.41 214	81.22 245	47.36 238	93.87 196	65.46 189	64.72 260	85.77 245

pmmvs4		73.92 225	71.81 228	80.25 212	79.17 293	65.24 147	87.43 247	87.26 270	67.64 229	63.46 248	83.91 207	48.96 226	91.53 262	62.94 211	65.49 249	83.96 264

V42		76.46 188	74.55 189	82.19 172	79.14 294	67.82 69	90.26 186	89.42 223	73.75 124	68.63 196	81.89 233	51.31 206	94.09 182	71.69 131	64.84 258	84.66 260

testpf		57.17 312	56.93 309	57.88 333	79.13 295	42.40 336	34.23 357	85.97 290	52.64 317	47.66 325	66.50 329	36.33 302	79.65 340	53.60 254	56.31 304	51.60 351

pm-mvs1		72.89 232	71.09 233	78.26 260	79.10 296	57.62 275	90.80 170	89.30 226	67.66 227	62.91 253	81.78 235	49.11 225	92.95 214	60.29 228	58.89 296	84.22 263

our_test_3		68.29 273	64.69 277	79.11 245	78.92 297	64.85 159	88.40 223	85.06 296	60.32 288	52.68 307	76.12 291	40.81 273	89.80 290	44.25 289	55.65 305	82.67 287

ppachtmachnet_test		67.72 277	63.70 284	79.77 225	78.92 297	66.04 132	88.68 216	82.90 316	60.11 290	55.45 288	75.96 294	39.19 277	90.55 268	39.53 307	52.55 314	82.71 285

TinyColmap		60.32 306	56.42 312	72.00 311	78.78 299	53.18 304	78.36 317	75.64 334	52.30 318	41.59 342	75.82 296	14.76 349	88.35 301	35.84 321	54.71 310	74.46 336

SixPastTwentyTwo		64.92 291	61.78 297	74.34 292	78.74 300	49.76 320	83.42 280	79.51 327	62.86 270	50.27 317	77.35 280	30.92 322	90.49 270	45.89 281	47.06 332	82.78 281

EG-PatchMatch MVS		68.55 270	65.41 272	77.96 265	78.69 301	62.93 202	89.86 198	89.17 231	60.55 285	50.27 317	77.73 279	22.60 339	94.06 185	47.18 276	72.65 199	76.88 332

pmmvs5		73.35 228	71.52 230	78.86 249	78.64 302	60.61 239	91.08 165	86.90 271	67.69 226	63.32 249	83.64 208	44.33 258	90.53 269	62.04 219	66.02 244	85.46 252

XVG-OURS		74.25 222	72.46 223	79.63 227	78.45 303	57.59 276	80.33 302	87.39 265	63.86 263	68.76 194	89.62 142	40.50 274	91.72 249	69.00 157	74.25 186	89.58 172

XVG-OURS-SEG-HR		74.70 219	73.08 215	79.57 229	78.25 304	57.33 279	80.49 300	87.32 268	63.22 267	68.76 194	90.12 131	44.89 256	91.59 257	70.55 145	74.09 188	89.79 169

MDA-MVSNet_test_wron		63.78 299	60.16 300	74.64 288	78.15 305	60.41 240	83.49 277	84.03 303	56.17 311	39.17 344	71.59 322	37.22 294	83.24 328	42.87 294	48.73 329	80.26 315

YYNet1		63.76 300	60.14 301	74.62 289	78.06 306	60.19 246	83.46 279	83.99 307	56.18 310	39.25 343	71.56 323	37.18 295	83.34 326	42.90 293	48.70 330	80.32 314

DTE-MVSNet		68.46 272	67.33 262	71.87 313	77.94 307	49.00 324	86.16 264	88.58 250	66.36 237	58.19 275	82.21 226	46.36 245	83.87 322	44.97 287	55.17 307	82.73 283

USDC		67.43 282	64.51 279	76.19 281	77.94 307	55.29 295	78.38 316	85.00 297	73.17 134	48.36 322	80.37 257	21.23 341	92.48 232	52.15 258	64.02 266	80.81 309

jajsoiax		73.05 230	71.51 231	77.67 267	77.46 309	54.83 297	88.81 214	90.04 204	69.13 207	62.85 254	83.51 210	31.16 320	92.75 223	70.83 141	69.80 219	85.43 253

mvs_tets		72.71 235	71.11 232	77.52 268	77.41 310	54.52 299	88.45 222	89.76 210	68.76 213	62.70 255	83.26 213	29.49 324	92.71 224	70.51 146	69.62 221	85.34 255

N_pmnet		50.55 320	49.11 323	54.88 337	77.17 311	4.02 367	84.36 271	2.00 368	48.59 328	45.86 329	68.82 327	32.22 314	82.80 329	31.58 341	51.38 319	77.81 330

test_djsdf		73.76 227	72.56 221	77.39 272	77.00 312	53.93 301	89.07 211	90.69 175	65.80 241	63.92 243	82.03 231	43.14 262	92.67 226	72.83 120	68.53 230	85.57 250

OpenMVS_ROB	61.12 18	66.39 285	62.92 290	76.80 278	76.51 313	57.77 272	89.22 206	83.41 310	55.48 312	53.86 301	77.84 278	26.28 334	93.95 193	34.90 331	68.76 228	78.68 326

v7n		71.31 245	68.65 248	79.28 237	76.40 314	60.77 233	86.71 260	89.45 221	64.17 259	58.77 273	78.24 275	44.59 257	93.54 203	57.76 239	61.75 279	83.52 270

K. test v3		63.09 301	59.61 303	73.53 297	76.26 315	49.38 323	83.27 281	77.15 330	64.35 258	47.77 323	72.32 312	28.73 326	87.79 306	49.93 266	36.69 345	83.41 273

RPSCF		64.24 295	61.98 296	71.01 314	76.10 316	45.00 332	75.83 323	75.94 333	46.94 333	58.96 271	84.59 202	31.40 319	82.00 334	47.76 274	60.33 290	86.04 239

OurMVSNet-221017-0		64.68 292	62.17 295	72.21 308	76.08 317	47.35 329	80.67 299	81.02 321	56.19 309	51.60 311	79.66 267	27.05 332	88.56 299	53.60 254	53.63 312	80.71 310

Test4		76.45 189	73.45 212	85.45 88	76.07 318	67.61 75	88.38 224	90.83 171	76.71 75	53.06 305	79.65 268	31.61 317	94.35 168	78.47 87	86.22 103	94.40 81

v748		70.55 255	67.97 259	78.27 259	75.75 319	58.78 265	86.29 263	89.25 228	65.12 254	56.66 285	77.17 285	45.05 255	92.95 214	58.13 238	58.33 298	83.10 280

Anonymous20231206		67.53 280	65.78 268	72.79 303	74.95 320	47.59 328	88.23 225	87.32 268	61.75 281	58.07 276	77.29 282	37.79 290	87.29 308	42.91 292	63.71 268	83.48 271

ITE_SJBPF				70.43 315	74.44 321	47.06 330		77.32 329	60.16 289	54.04 299	83.53 209	23.30 338	84.01 320	43.07 291	61.58 283	80.21 316

EU-MVSNet		64.01 297	63.01 289	67.02 323	74.40 322	38.86 346	83.27 281	86.19 285	45.11 338	54.27 296	81.15 248	36.91 299	80.01 338	48.79 270	57.02 300	82.19 290

XVG-ACMP-BASELINE		68.04 275	65.53 271	75.56 284	74.06 323	52.37 306	78.43 315	85.88 291	62.03 276	58.91 272	81.21 247	20.38 342	91.15 266	60.69 226	68.18 232	83.16 278

anonymousdsp		71.14 248	69.37 243	76.45 279	72.95 324	54.71 298	84.19 272	88.88 243	61.92 278	62.15 258	79.77 265	38.14 285	91.44 265	68.90 159	67.45 238	83.21 277

lessismore_v0				73.72 296	72.93 325	47.83 327		61.72 357		45.86 329	73.76 301	28.63 328	89.81 288	47.75 275	31.37 349	83.53 269

pmmvs6		67.57 279	64.76 276	76.00 283	72.82 326	53.37 303	88.71 215	86.78 272	53.19 316	57.58 282	78.03 277	35.33 305	92.41 233	55.56 246	54.88 309	82.21 289

V4		69.80 261	67.02 264	78.15 262	71.86 327	60.10 247	82.02 289	87.39 265	64.48 256	57.78 279	75.98 292	41.49 268	92.90 219	63.00 209	59.16 292	81.44 297

v52		69.80 261	67.01 265	78.15 262	71.84 328	60.10 247	82.02 289	87.39 265	64.48 256	57.80 278	75.97 293	41.47 269	92.90 219	63.00 209	59.13 293	81.45 296

testgi		64.48 294	62.87 291	69.31 317	71.24 329	40.62 341	85.49 266	79.92 325	65.36 245	54.18 298	83.49 211	23.74 337	84.55 316	41.60 299	60.79 288	82.77 282

Patchmatch-RL test		68.17 274	64.49 280	79.19 241	71.22 330	53.93 301	70.07 332	71.54 346	69.22 205	56.79 284	62.89 337	56.58 142	88.61 297	69.53 152	52.61 313	95.03 59

Gipuma		34.91 331	31.44 333	45.30 342	70.99 331	39.64 345	19.85 360	72.56 343	20.10 356	16.16 357	21.47 359	5.08 362	71.16 350	13.07 356	43.70 338	25.08 357
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
UnsupCasMVSNet_eth		65.79 289	63.10 288	73.88 294	70.71 332	50.29 318	81.09 297	89.88 208	72.58 144	49.25 320	74.77 300	32.57 313	87.43 307	55.96 245	41.04 341	83.90 266

CMPMVS	48.56 21	66.77 284	64.41 281	73.84 295	70.65 333	50.31 317	77.79 320	85.73 293	45.54 337	44.76 333	82.14 227	35.40 304	90.14 278	63.18 207	74.54 184	81.07 306
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
test20.03		63.83 298	62.65 292	67.38 322	70.58 334	39.94 342	86.57 261	84.17 302	63.29 266	51.86 310	77.30 281	37.09 297	82.47 330	38.87 315	54.13 311	79.73 319

testing_2		71.09 249	67.32 263	82.40 163	69.82 335	66.52 120	83.64 275	90.77 173	72.21 154	45.12 332	71.07 324	27.60 330	93.74 199	75.71 104	69.96 218	86.95 220

MIMVSNet1		60.16 308	57.33 308	68.67 318	69.71 336	44.13 334	78.92 313	84.21 301	55.05 313	44.63 334	71.85 316	23.91 336	81.54 336	32.63 338	55.03 308	80.35 313

pmmvs-eth3d		65.53 290	62.32 294	75.19 285	69.39 337	59.59 254	82.80 286	83.43 309	62.52 273	51.30 314	72.49 307	32.86 310	87.16 309	55.32 247	50.73 321	78.83 325

test2356		64.16 296	63.28 287	66.81 324	69.37 338	39.86 344	87.76 235	86.02 288	59.83 292	53.54 304	73.23 303	34.94 306	80.67 337	39.66 306	65.20 251	79.89 317

UnsupCasMVSNet_bld		61.60 304	57.71 305	73.29 299	68.73 339	51.64 309	78.61 314	89.05 238	57.20 304	46.11 326	61.96 339	28.70 327	88.60 298	50.08 265	38.90 343	79.63 320

testus		59.36 310	57.51 307	64.90 326	66.72 340	37.56 347	84.98 268	81.09 320	57.46 303	47.72 324	72.76 304	11.43 353	78.78 344	36.56 318	58.91 295	78.36 329

new-patchmatchnet		59.30 311	56.48 311	67.79 320	65.86 341	44.19 333	82.47 287	81.77 317	59.94 291	43.65 338	66.20 331	27.67 329	81.68 335	39.34 308	41.40 340	77.50 331

PM-MVS		59.40 309	56.59 310	67.84 319	63.63 342	41.86 338	76.76 321	63.22 355	59.01 296	51.07 315	72.27 313	11.72 351	83.25 327	61.34 222	50.28 327	78.39 328

DSMNet-mixed		56.78 313	54.44 315	63.79 328	63.21 343	29.44 355	64.43 343	64.10 354	42.12 346	51.32 313	71.60 321	31.76 316	75.04 347	36.23 320	65.20 251	86.87 222

new_pmnet		49.31 321	46.44 324	57.93 332	62.84 344	40.74 340	68.47 336	62.96 356	36.48 348	35.09 346	57.81 343	14.97 348	72.18 348	32.86 337	46.44 333	60.88 349

LF4IMVS		54.01 319	52.12 317	59.69 331	62.41 345	39.91 343	68.59 335	68.28 351	42.96 344	44.55 335	75.18 297	14.09 350	68.39 351	41.36 301	51.68 318	70.78 341

1111		56.66 315	54.98 314	61.69 329	61.99 346	31.38 351	79.81 310	83.17 313	45.66 335	41.94 340	65.44 332	41.50 266	79.56 341	27.64 344	47.68 331	74.14 337

.test1245		46.52 324	49.68 321	37.02 346	61.99 346	31.38 351	79.81 310	83.17 313	45.66 335	41.94 340	65.44 332	41.50 266	79.56 341	27.64 344	0.01 362	0.13 363

ambc				69.61 316	61.38 348	41.35 339	49.07 354	85.86 292		50.18 319	66.40 330	10.16 354	88.14 303	45.73 282	44.20 336	79.32 323

test1235678		55.73 316	52.74 316	64.68 327	60.16 349	35.56 349	81.65 293	81.46 318	51.27 321	38.93 345	62.82 338	17.44 345	78.58 345	30.87 342	50.09 328	79.89 317

TDRefinement		55.28 318	51.58 319	66.39 325	59.53 350	46.15 331	76.23 322	72.80 342	44.60 340	42.49 339	76.28 290	15.29 347	82.39 331	33.20 335	43.75 337	70.62 342

pmmvs3		55.51 317	51.50 320	67.53 321	57.90 351	50.93 315	80.37 301	73.66 341	40.63 347	44.15 336	64.75 336	16.30 346	78.97 343	44.77 288	40.98 342	72.69 338

test12356		47.51 322	44.82 325	55.56 335	52.53 352	21.09 362	71.45 329	76.03 332	44.14 342	30.69 348	58.18 342	9.01 357	76.14 346	26.95 346	34.43 348	69.46 344

DeepMVS_CX				34.71 347	51.45 353	24.73 361		28.48 367	31.46 350	17.49 356	52.75 345	5.80 361	42.60 362	18.18 354	19.42 351	36.81 355

FPMVS		45.64 325	43.10 327	53.23 339	51.42 354	36.46 348	64.97 342	71.91 344	29.13 351	27.53 350	61.55 340	9.83 355	65.01 355	16.00 355	55.58 306	58.22 350

PNet_i23d		32.77 332	29.98 334	41.11 344	48.05 355	29.17 356	65.82 341	50.02 360	21.42 354	14.74 358	37.19 355	1.11 367	55.11 358	19.75 353	11.77 355	39.06 353

wuyk23d		11.30 341	10.95 342	12.33 352	48.05 355	19.89 363	25.89 359	1.92 369	3.58 361	3.12 364	1.37 364	0.64 368	15.77 364	6.23 361	7.77 361	1.35 361

testmv		46.98 323	43.53 326	57.35 334	47.75 357	30.41 354	74.99 325	77.69 328	42.84 345	28.03 349	53.36 344	8.18 358	71.18 349	24.36 348	34.55 346	70.46 343

PMMVS2		37.93 329	33.61 331	50.92 340	46.31 358	24.76 360	60.55 349	50.05 359	28.94 352	20.93 352	47.59 346	4.41 364	65.13 354	25.14 347	18.55 352	62.87 347

no-one		44.13 326	38.39 328	61.34 330	45.91 359	41.94 337	61.67 346	75.07 339	45.05 339	20.07 353	40.68 354	11.58 352	79.82 339	30.18 343	15.30 353	62.26 348

E-PMN		24.61 336	24.00 337	26.45 349	43.74 360	18.44 364	60.86 347	39.66 362	15.11 357	9.53 361	22.10 358	6.52 360	46.94 360	8.31 359	10.14 356	13.98 359

EMVS		23.76 338	23.20 339	25.46 350	41.52 361	16.90 365	60.56 348	38.79 365	14.62 358	8.99 362	20.24 362	7.35 359	45.82 361	7.25 360	9.46 358	13.64 360

LCM-MVSNet		40.54 327	35.79 329	54.76 338	36.92 362	30.81 353	51.41 352	69.02 348	22.07 353	24.63 351	45.37 349	4.56 363	65.81 353	33.67 333	34.50 347	67.67 345

ANet_high		40.27 328	35.20 330	55.47 336	34.74 363	34.47 350	63.84 344	71.56 345	48.42 329	18.80 355	41.08 352	9.52 356	64.45 356	20.18 352	8.66 360	67.49 346

MVE	24.84 23	24.35 337	19.77 341	38.09 345	34.56 364	26.92 359	26.57 358	38.87 364	11.73 360	11.37 360	27.44 356	1.37 366	50.42 359	11.41 357	14.60 354	36.93 354
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuykxyi23d		29.03 335	23.09 340	46.84 341	31.67 365	28.82 357	43.46 355	57.72 358	14.39 359	7.52 363	20.84 360	0.64 368	60.29 357	21.57 351	10.04 357	51.40 352

PMVS	26.43 22	31.84 333	28.16 335	42.89 343	25.87 366	27.58 358	50.92 353	49.78 361	21.37 355	14.17 359	40.81 353	2.01 365	66.62 352	9.61 358	38.88 344	34.49 356
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tmp_tt		22.26 339	23.75 338	17.80 351	5.23 367	12.06 366	35.26 356	39.48 363	2.82 362	18.94 354	44.20 350	22.23 340	24.64 363	36.30 319	9.31 359	16.69 358

testmvs		7.23 343	9.62 344	0.06 354	0.04 368	0.02 369	84.98 268	0.02 370	0.03 363	0.18 365	1.21 365	0.01 371	0.02 365	0.14 362	0.01 362	0.13 363

test123		6.92 344	9.21 345	0.08 353	0.03 369	0.05 368	81.65 293	0.01 371	0.02 364	0.14 366	0.85 366	0.03 370	0.02 365	0.12 363	0.00 364	0.16 362

cdsmvs_eth3d_5k		19.86 340	26.47 336	0.00 355	0.00 370	0.00 370	0.00 361	93.45 65	0.00 365	0.00 367	95.27 33	49.56 218	0.00 367	0.00 364	0.00 364	0.00 365

pcd_1.5k_mvsjas		4.46 345	5.95 346	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	53.55 184	0.00 367	0.00 364	0.00 364	0.00 365

sosnet-low-res		0.00 346	0.00 347	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	0.00 372	0.00 367	0.00 364	0.00 364	0.00 365

sosnet		0.00 346	0.00 347	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	0.00 372	0.00 367	0.00 364	0.00 364	0.00 365

uncertanet		0.00 346	0.00 347	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	0.00 372	0.00 367	0.00 364	0.00 364	0.00 365

Regformer		0.00 346	0.00 347	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	0.00 372	0.00 367	0.00 364	0.00 364	0.00 365

ab-mvs-re		7.91 342	10.55 343	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	94.95 43	0.00 372	0.00 367	0.00 364	0.00 364	0.00 365

uanet		0.00 346	0.00 347	0.00 355	0.00 370	0.00 370	0.00 361	0.00 372	0.00 365	0.00 367	0.00 367	0.00 372	0.00 367	0.00 364	0.00 364	0.00 365

GSMVS																94.68 68

test_part1				0.00 355		0.00 370	0.00 361	94.26 42				0.00 372	0.00 367	0.00 364	0.00 364	0.00 365

sam_mvs1												57.85 123				94.68 68

sam_mvs												54.91 167

MTGPA								92.23 119

test_post1							78.95 312				20.70 361	53.05 190	91.50 263	60.43 227

test_post											23.01 357	56.49 143	92.67 226

patchmatchnet-post											67.62 328	57.62 126	90.25 272

MTMP							93.77 62	32.52 366

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 93	85.25 35	95.61 24	67.94 25		87.47 25	94.77 15

旧先验2							92.00 118		59.37 295	87.54 19			93.47 206	75.39 106

新几何2							91.41 146

无先验							92.71 91	92.61 109	62.03 276				97.01 70	66.63 174		93.97 99

原ACMM2							92.01 116

testdata2													96.09 104	61.26 223

segment_acmp												65.94 44

testdata1							89.21 207		77.55 63

plane_prior5								91.31 157					95.55 127	76.74 98	78.53 152	88.39 186

plane_prior4											89.14 144

plane_prior3						61.95 221			79.09 44	72.53 143

plane_prior2							93.13 78		78.81 49

plane_prior						62.42 211	93.85 58		79.38 37						78.80 150

n2								0.00 372

nn								0.00 372

door-mid								66.01 353

test11								93.01 93

door								66.57 352

HQP5-MVS						63.66 189

BP-MVS														77.63 94

HQP4-MVS										74.18 124			95.61 123			88.63 181

HQP3-MVS								91.70 143							78.90 148

HQP2-MVS												51.63 204

MDTV_nov1_ep13_2view						59.90 251	80.13 306		67.65 228	72.79 138		54.33 175		59.83 230		92.58 134

ACMMP++_ref															71.63 205

ACMMP++															69.72 220

Test By Simon												54.21 177

High-resolution multi-view benchmark