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.

ACMMP_Plus		78.77 7	78.78 7	78.74 20	85.44 30	61.04 31	83.84 28	85.16 12	62.88 42	78.10 9	91.26 3	52.51 49	88.39 13	79.34 3	90.52 1	86.78 39

HPM-MVS++		79.88 3	80.14 3	79.10 11	88.17 1	64.80 1	86.59 4	83.70 40	65.37 16	78.78 8	90.64 7	58.63 12	87.24 31	79.00 4	90.37 2	85.26 92

test_part1								86.64 4				65.59 1			90.06 3	86.78 39

CNVR-MVS		79.84 4	79.97 4	79.45 4	87.90 2	62.17 20	84.37 20	85.03 14	66.96 6	77.58 11	90.06 20	59.47 9	89.13 8	78.67 6	89.73 4	87.03 33

PHI-MVS		75.87 37	75.36 36	77.41 36	80.62 86	55.91 96	84.28 21	85.78 9	56.08 162	73.41 44	86.58 65	50.94 65	88.54 12	70.79 40	89.71 5	87.79 13

MP-MVS-pluss		78.35 11	78.46 8	78.03 30	84.96 38	59.52 45	82.93 39	85.39 10	62.15 53	76.41 15	91.51 2	52.47 51	86.78 43	80.66 2	89.64 6	87.80 12
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
DeepC-MVS	69.38 2	78.56 9	78.14 12	79.83 2	83.60 50	61.62 24	84.17 24	86.85 2	63.23 35	73.84 38	90.25 18	57.68 13	89.96 2	74.62 18	89.03 7	87.89 9
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
SteuartSystems-ACMMP		79.48 5	79.31 5	79.98 1	83.01 56	62.18 19	87.60 2	85.83 8	66.69 11	78.03 10	90.98 4	54.26 33	90.06 1	78.42 7	89.02 8	87.69 15
Skip Steuart: Steuart Systems R&D Blog.
test_prior3		76.89 27	76.96 21	76.69 44	84.20 47	57.27 72	81.75 59	84.88 16	60.37 78	75.01 21	89.06 33	56.22 18	86.43 54	72.19 32	88.96 9	86.38 42

test_prior2							81.75 59		60.37 78	75.01 21	89.06 33	56.22 18		72.19 32	88.96 9

DeepPCF-MVS	69.58 1	79.03 6	79.00 6	79.13 9	84.92 42	60.32 38	83.03 37	85.33 11	62.86 43	80.17 4	90.03 21	61.76 3	88.95 10	74.21 19	88.67 11	88.12 7

HSP-MVS		80.69 1	81.20 1	79.14 8	86.21 17	62.73 12	86.09 8	85.03 14	65.51 15	83.81 1	90.51 11	63.71 2	89.23 6	81.51 1	88.44 12	85.45 79

CDPH-MVS		76.31 32	75.67 35	78.22 27	85.35 33	59.14 50	81.31 69	84.02 29	56.32 156	74.05 32	88.98 36	53.34 44	87.92 24	69.23 44	88.42 13	87.59 18

train_agg		76.27 33	76.15 28	76.64 47	85.58 28	61.59 25	81.62 63	81.26 89	55.86 163	74.93 23	88.81 39	53.70 41	84.68 95	75.24 15	88.33 14	83.65 148

agg_prior3		76.13 34	75.89 34	76.85 42	85.76 24	62.02 21	81.65 61	81.01 97	55.51 172	73.73 39	88.60 43	53.23 45	84.90 88	75.24 15	88.33 14	83.65 148

APDe-MVS		80.16 2	80.59 2	78.86 18	86.64 10	60.02 40	88.12 1	86.42 6	62.94 40	82.40 3	92.12 1	59.64 7	89.76 3	78.70 5	88.32 16	86.79 38

test9_res														75.28 14	88.31 17	83.81 138

MPTG		77.61 19	77.36 18	78.35 24	86.08 21	63.57 2	83.37 33	80.97 98	65.13 18	75.77 17	90.88 5	48.63 101	86.66 45	77.23 8	88.17 18	84.81 105

MTAPA		76.90 26	76.42 27	78.35 24	86.08 21	63.57 2	74.92 184	80.97 98	65.13 18	75.77 17	90.88 5	48.63 101	86.66 45	77.23 8	88.17 18	84.81 105

test12				77.76 33	84.52 44	58.41 59		83.36 50		72.93 51		54.61 31	88.05 21		88.12 20	86.81 37

MP-MVS		78.35 11	78.26 11	78.64 21	86.54 12	63.47 5	86.02 9	83.55 43	63.89 31	73.60 42	90.60 8	54.85 29	86.72 44	77.20 10	88.06 21	85.74 67

DeepC-MVS_fast	68.24 3	77.25 22	76.63 25	79.12 10	86.15 19	60.86 33	84.71 18	84.85 18	61.98 59	73.06 49	88.88 38	53.72 40	89.06 9	68.27 47	88.04 22	87.42 24
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
原ACMM1				74.69 73	85.39 32	59.40 46		83.42 47	51.47 215	70.27 73	86.61 63	48.61 103	86.51 52	53.85 157	87.96 23	78.16 230

agg_prior2														73.09 29	87.93 24	84.33 116

agg_prior1		75.94 36	76.01 31	75.72 57	85.04 35	59.96 41	81.44 67	81.04 95	56.14 161	74.68 27	88.90 37	53.91 37	84.04 107	75.01 17	87.92 25	83.16 159

CSCG		76.92 25	76.75 23	77.41 36	83.96 49	59.60 44	82.95 38	86.50 5	60.78 71	75.27 20	84.83 91	60.76 4	86.56 50	67.86 51	87.87 26	86.06 56

MCST-MVS		77.48 20	77.45 16	77.54 34	86.67 9	58.36 60	83.22 35	86.93 1	56.91 141	74.91 25	88.19 44	59.15 10	87.68 27	73.67 25	87.45 27	86.57 41

NCCC		78.58 8	78.31 9	79.39 5	87.51 4	62.61 16	85.20 17	84.42 21	66.73 10	74.67 29	89.38 30	55.30 24	89.18 7	74.19 20	87.34 28	86.38 42

HFP-MVS		78.01 14	77.65 14	79.10 11	86.71 7	62.81 10	86.29 5	84.32 23	62.82 44	73.96 33	90.50 12	53.20 46	88.35 14	74.02 21	87.05 29	86.13 53

#test#		77.83 15	77.41 17	79.10 11	86.71 7	62.81 10	85.69 14	84.32 23	61.61 62	73.96 33	90.50 12	53.20 46	88.35 14	73.68 24	87.05 29	86.13 53

region2R		77.67 18	77.18 20	79.15 7	86.76 5	62.95 8	86.29 5	84.16 27	62.81 46	73.30 45	90.58 9	49.90 70	88.21 18	73.78 23	87.03 31	86.29 51

ACMMPR		77.71 16	77.23 19	79.16 6	86.75 6	62.93 9	86.29 5	84.24 25	62.82 44	73.55 43	90.56 10	49.80 72	88.24 17	74.02 21	87.03 31	86.32 49

APD-MVS		78.02 13	78.04 13	77.98 31	86.44 14	60.81 34	85.52 15	84.36 22	60.61 73	79.05 7	90.30 16	55.54 23	88.32 16	73.48 28	87.03 31	84.83 104
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
PGM-MVS		76.77 28	76.06 29	78.88 17	86.14 20	62.73 12	82.55 47	83.74 39	61.71 60	72.45 57	90.34 15	48.48 105	88.13 19	72.32 31	86.85 34	85.78 62

HPM-MVS		77.28 21	76.85 22	78.54 22	85.00 37	60.81 34	82.91 40	85.08 13	62.57 47	73.09 48	89.97 23	50.90 66	87.48 29	75.30 13	86.85 34	87.33 28

TSAR-MVS + MP.		78.44 10	78.28 10	78.90 16	84.96 38	61.41 27	84.03 26	83.82 38	59.34 113	79.37 6	89.76 26	59.84 5	87.62 28	76.69 11	86.74 36	87.68 16

XVS		77.17 23	76.56 26	79.00 14	86.32 15	62.62 14	85.83 10	83.92 32	64.55 22	72.17 58	90.01 22	47.95 110	88.01 22	71.55 36	86.74 36	86.37 45

X-MVStestdata		70.21 104	67.28 140	79.00 14	86.32 15	62.62 14	85.83 10	83.92 32	64.55 22	72.17 58	6.49 343	47.95 110	88.01 22	71.55 36	86.74 36	86.37 45

3Dnovator+	66.72 4	75.84 38	74.57 41	79.66 3	82.40 60	59.92 43	85.83 10	86.32 7	66.92 9	67.80 123	89.24 32	42.03 166	89.38 5	64.07 86	86.50 39	89.69 1

MVS_0304		76.73 29	76.04 30	78.78 19	81.32 73	58.89 54	82.50 49	84.07 28	67.73 5	72.08 60	87.28 54	49.49 74	89.57 4	73.52 27	86.40 40	87.87 11

EPNet		73.09 59	72.16 61	75.90 53	75.95 176	56.28 87	83.05 36	72.39 221	66.53 13	65.27 152	87.00 55	50.40 68	85.47 74	62.48 103	86.32 41	85.94 58
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DELS-MVS		74.76 43	74.46 42	75.65 60	77.84 138	52.25 140	75.59 168	84.17 26	63.76 32	73.15 47	82.79 121	59.58 8	86.80 41	67.24 56	86.04 42	87.89 9
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
CP-MVS		77.12 24	76.68 24	78.43 23	86.05 23	63.18 7	87.55 3	83.45 46	62.44 50	72.68 53	90.50 12	48.18 108	87.34 30	73.59 26	85.71 43	84.76 109

mPP-MVS		76.54 30	75.93 32	78.34 26	86.47 13	63.50 4	85.74 13	82.28 66	62.90 41	71.77 62	90.26 17	46.61 128	86.55 51	71.71 35	85.66 44	84.97 101

MSLP-MVS++		73.77 54	73.47 51	74.66 74	83.02 55	59.29 49	82.30 55	81.88 72	59.34 113	71.59 64	86.83 56	45.94 132	83.65 117	65.09 71	85.22 45	81.06 198

SD-MVS		77.70 17	77.62 15	77.93 32	84.47 45	61.88 23	84.55 19	83.87 36	60.37 78	79.89 5	89.38 30	54.97 26	85.58 70	76.12 12	84.94 46	86.33 48

3Dnovator	64.47 5	72.49 65	71.39 70	75.79 54	77.70 140	58.99 53	80.66 76	83.15 56	62.24 52	65.46 149	86.59 64	42.38 164	85.52 72	59.59 131	84.72 47	82.85 165

CANet		76.46 31	75.93 32	78.06 29	81.29 74	57.53 69	82.35 50	83.31 52	67.78 3	70.09 74	86.34 69	54.92 27	88.90 11	72.68 30	84.55 48	87.76 14

LFMVS		71.78 76	71.59 66	72.32 148	83.40 52	46.38 222	79.75 87	71.08 225	64.18 28	72.80 52	88.64 42	42.58 163	83.72 115	57.41 138	84.49 49	86.86 36

TSAR-MVS + GP.		74.90 42	74.15 45	77.17 39	82.00 63	58.77 56	81.80 58	78.57 154	58.58 121	74.32 31	84.51 100	55.94 20	87.22 32	67.11 57	84.48 50	85.52 74

MAR-MVS		71.51 79	70.15 87	75.60 62	81.84 65	59.39 47	81.38 68	82.90 61	54.90 181	68.08 116	78.70 215	47.73 112	85.51 73	51.68 173	84.17 51	81.88 179
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		72.17 71	71.41 69	74.45 80	81.95 64	57.22 74	84.03 26	80.38 115	59.89 92	68.40 108	82.33 132	49.64 73	87.83 25	51.87 169	84.16 52	78.30 228

IS-MVSNet		71.57 78	71.00 77	73.27 118	78.86 111	45.63 226	80.22 80	78.69 152	64.14 29	66.46 137	87.36 51	49.30 78	85.60 68	50.26 180	83.71 53	88.59 3

UA-Net		73.13 58	72.93 56	73.76 91	83.58 51	51.66 146	78.75 96	77.66 171	67.75 4	72.61 54	89.42 28	49.82 71	83.29 124	53.61 160	83.14 54	86.32 49

MG-MVS		73.96 51	73.89 47	74.16 82	85.65 26	49.69 193	81.59 65	81.29 88	61.45 63	71.05 66	88.11 45	51.77 56	87.73 26	61.05 121	83.09 55	85.05 98

OpenMVS	61.03 9	68.85 127	67.56 129	72.70 132	74.26 201	53.99 115	81.21 70	81.34 86	52.70 199	62.75 180	85.55 84	38.86 200	84.14 105	48.41 195	83.01 56	79.97 212

VDDNet		71.81 75	71.33 72	73.26 119	82.80 58	47.60 214	78.74 97	75.27 197	59.59 106	72.94 50	89.40 29	41.51 178	83.91 112	58.75 133	82.99 57	88.26 5

MVS_111021_HR		74.02 50	73.46 52	75.69 59	83.01 56	60.63 36	77.29 138	78.40 163	61.18 67	70.58 68	85.97 76	54.18 35	84.00 111	67.52 55	82.98 58	82.45 171

HPM-MVS_fast		74.30 48	73.46 52	76.80 43	84.45 46	59.04 51	83.65 30	81.05 94	60.15 84	70.43 69	89.84 25	41.09 184	85.59 69	67.61 54	82.90 59	85.77 64

ACMMP		76.02 35	75.33 37	78.07 28	85.20 34	61.91 22	85.49 16	84.44 20	63.04 38	69.80 84	89.74 27	45.43 139	87.16 35	72.01 34	82.87 60	85.14 94
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
APD-MVS_3200maxsize		74.96 41	74.39 43	76.67 46	82.20 61	58.24 62	83.67 29	83.29 53	58.41 125	73.71 40	90.14 19	45.62 134	85.99 62	69.64 42	82.85 61	85.78 62

VDD-MVS		72.50 64	72.09 62	73.75 93	81.58 67	49.69 193	77.76 125	77.63 172	63.21 36	73.21 46	89.02 35	42.14 165	83.32 123	61.72 118	82.50 62	88.25 6

CLD-MVS		73.33 56	72.68 58	75.29 67	78.82 112	53.33 124	78.23 109	84.79 19	61.30 66	70.41 70	81.04 168	52.41 52	87.12 36	64.61 76	82.49 63	85.41 86
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
canonicalmvs		74.67 45	74.98 39	73.71 95	78.94 110	50.56 165	80.23 79	83.87 36	60.30 82	77.15 12	86.56 66	59.65 6	82.00 157	66.01 64	82.12 64	88.58 4

MVS		67.37 159	66.33 165	70.51 178	75.46 182	50.94 151	73.95 195	81.85 74	41.57 297	62.54 185	78.57 220	47.98 109	85.47 74	52.97 164	82.05 65	75.14 260

alignmvs		73.86 53	73.99 46	73.45 107	78.20 127	50.50 167	78.57 101	82.43 65	59.40 111	76.57 13	86.71 59	56.42 17	81.23 170	65.84 66	81.79 66	88.62 2

1121		68.53 138	67.16 145	72.63 133	85.64 27	61.14 29	73.95 195	66.46 262	44.61 275	70.28 72	86.68 60	41.42 179	80.78 179	53.62 158	81.79 66	75.97 250

新几何1				70.76 173	85.66 25	61.13 30		66.43 263	44.68 274	70.29 71	86.64 61	41.29 181	75.23 249	49.72 185	81.75 68	75.93 253

Vis-MVSNet		72.18 70	71.37 71	74.61 77	81.29 74	55.41 105	80.90 72	78.28 165	60.73 72	69.23 99	88.09 46	44.36 152	82.65 148	57.68 136	81.75 68	85.77 64
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
VNet		69.68 112	70.19 86	68.16 204	79.73 100	41.63 257	70.53 241	77.38 177	60.37 78	70.69 67	86.63 62	51.08 62	77.09 233	53.61 160	81.69 70	85.75 66

abl_6		74.34 46	73.50 49	76.86 41	82.43 59	60.16 39	83.48 32	81.86 73	58.81 119	73.95 35	89.86 24	41.87 169	86.62 47	67.98 50	81.23 71	83.80 141

OPM-MVS		74.73 44	74.25 44	76.19 50	80.81 82	59.01 52	82.60 46	83.64 41	63.74 33	72.52 55	87.49 49	47.18 120	85.88 66	69.47 43	80.78 72	83.66 147

旧先验1					83.04 54	53.15 126		67.52 255			87.85 48	44.08 153			80.76 73	78.03 232

PAPM_NR		72.63 63	71.80 64	75.13 68	81.72 66	53.42 123	79.91 84	83.28 54	59.14 115	66.31 141	85.90 77	51.86 55	86.06 59	57.45 137	80.62 74	85.91 59

Vis-MVSNet (Re-imp)		63.69 204	63.88 188	63.14 254	74.75 191	31.04 321	71.16 235	63.64 279	56.32 156	59.80 228	84.99 89	44.51 148	75.46 246	39.12 257	80.62 74	82.92 162

HQP_MVS		74.31 47	73.73 48	76.06 51	81.41 71	56.31 85	84.22 22	84.01 30	64.52 24	69.27 96	86.10 73	45.26 143	87.21 33	68.16 48	80.58 76	84.65 110

plane_prior5								84.01 30					87.21 33	68.16 48	80.58 76	84.65 110

UGNet		68.81 128	67.39 135	73.06 122	78.33 124	54.47 112	79.77 86	75.40 196	60.45 76	63.22 174	84.40 101	32.71 264	80.91 176	51.71 172	80.56 78	83.81 138
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
plane_prior						56.31 85	83.58 31		63.19 37						80.48 79

Regformer-1		75.47 40	74.93 40	77.09 40	80.43 88	57.70 67	79.50 92	82.13 67	67.84 1	75.73 19	80.75 180	56.50 15	86.07 58	71.07 39	80.38 80	87.50 20

Regformer-2		75.63 39	74.99 38	77.54 34	80.43 88	58.32 61	79.50 92	82.92 59	67.84 1	75.94 16	80.75 180	55.73 21	86.80 41	71.44 38	80.38 80	87.50 20

HQP3-MVS								83.90 34							80.35 82

HQP-MVS		73.45 55	72.80 57	75.40 64	80.66 83	54.94 107	82.31 52	83.90 34	62.10 54	67.85 118	85.54 85	45.46 137	86.93 39	67.04 58	80.35 82	84.32 117

PCF-MVS	61.88 8	70.95 84	69.49 100	75.35 65	77.63 143	55.71 98	76.04 163	81.81 75	50.30 226	69.66 85	85.40 88	52.51 49	84.89 89	51.82 170	80.24 84	85.45 79
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
DP-MVS Recon		72.15 73	70.73 80	76.40 49	86.57 11	57.99 64	81.15 71	82.96 58	57.03 138	66.78 134	85.56 83	44.50 149	88.11 20	51.77 171	80.23 85	83.10 160

CPTT-MVS		72.78 61	72.08 63	74.87 71	84.88 43	61.41 27	84.15 25	77.86 167	55.27 174	67.51 127	88.08 47	41.93 168	81.85 159	69.04 46	80.01 86	81.35 192

Test4		67.77 156	65.97 168	73.19 121	68.64 279	50.58 162	74.80 187	80.48 113	54.13 190	59.11 236	79.07 213	33.89 250	83.12 129	63.61 94	79.98 87	85.87 60

test_normal		69.26 122	67.90 124	73.32 116	70.84 262	50.38 170	75.30 173	79.17 142	54.23 189	62.00 196	80.61 182	44.69 146	83.89 113	64.33 83	79.95 88	85.69 68

DI_MVS_plusplus_test		69.35 120	68.03 122	73.30 117	71.11 259	50.14 181	75.49 170	79.16 143	54.57 185	62.45 189	80.76 179	44.67 147	84.20 103	64.23 84	79.81 89	85.54 73

114514_t		70.83 85	69.56 95	74.64 76	86.21 17	54.63 111	82.34 51	81.81 75	48.22 243	63.01 177	85.83 79	40.92 187	87.10 37	57.91 135	79.79 90	82.18 174

MVS_Test		72.45 66	72.46 60	72.42 145	74.88 188	48.50 204	76.28 155	83.14 57	59.40 111	72.46 56	84.68 93	55.66 22	81.12 171	65.98 65	79.66 91	87.63 17

PS-MVSNAJ		70.51 94	69.70 91	72.93 124	81.52 68	55.79 97	74.92 184	79.00 146	55.04 179	69.88 80	78.66 216	47.05 121	82.19 154	61.61 119	79.58 92	80.83 202

PVSNet_Blended		68.59 133	67.72 126	71.19 166	77.03 162	50.57 163	72.51 216	81.52 78	51.91 207	64.22 170	77.77 230	49.13 94	82.87 137	55.82 144	79.58 92	80.14 211

EPP-MVSNet		72.16 72	71.31 73	74.71 72	78.68 117	49.70 191	82.10 56	81.65 77	60.40 77	65.94 144	85.84 78	51.74 57	86.37 56	55.93 143	79.55 94	88.07 8

xiu_mvs_v2_base		70.52 93	69.75 89	72.84 128	81.21 77	55.63 101	75.11 179	78.92 147	54.92 180	69.96 79	79.68 203	47.00 125	82.09 156	61.60 120	79.37 95	80.81 203

MVSFormer		71.50 80	70.38 84	74.88 70	78.76 114	57.15 79	82.79 41	78.48 158	51.26 218	69.49 91	83.22 117	43.99 155	83.24 125	66.06 62	79.37 95	84.23 124

lupinMVS		69.57 115	68.28 118	73.44 108	78.76 114	57.15 79	76.57 149	73.29 217	46.19 261	69.49 91	82.18 135	43.99 155	79.23 197	64.66 74	79.37 95	83.93 133

PAPM		67.92 155	66.69 157	71.63 157	78.09 131	49.02 200	77.09 141	81.24 91	51.04 221	60.91 216	83.98 108	47.71 113	84.99 80	40.81 250	79.32 98	80.90 201

FIs		70.82 86	71.43 68	68.98 196	78.33 124	38.14 280	76.96 144	83.59 42	61.02 68	67.33 129	86.73 57	55.07 25	81.64 162	54.61 154	79.22 99	87.14 31

jason		69.65 113	68.39 117	73.43 109	78.27 126	56.88 81	77.12 140	73.71 215	46.53 257	69.34 95	83.22 117	43.37 159	79.18 198	64.77 73	79.20 100	84.23 124
jason: jason.
PAPR		71.72 77	70.82 79	74.41 81	81.20 78	51.17 150	79.55 91	83.33 51	55.81 166	66.93 133	84.61 96	50.95 64	86.06 59	55.79 146	79.20 100	86.00 57

Effi-MVS+		73.31 57	72.54 59	75.62 61	77.87 137	53.64 118	79.62 90	79.61 124	61.63 61	72.02 61	82.61 126	56.44 16	85.97 64	63.99 89	79.07 102	87.25 29

gg-mvs-nofinetune		57.86 253	56.43 255	62.18 260	72.62 238	35.35 302	66.57 263	56.33 311	50.65 223	57.64 251	57.10 325	30.65 274	76.36 241	37.38 264	78.88 103	74.82 267

CDS-MVSNet		66.80 172	65.37 174	71.10 169	78.98 109	53.13 128	73.27 205	71.07 226	52.15 205	64.72 162	80.23 193	43.56 158	77.10 232	45.48 218	78.88 103	83.05 161
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
AdaColmap		69.99 108	68.66 112	73.97 85	84.94 40	57.83 65	82.63 45	78.71 151	56.28 158	64.34 166	84.14 104	41.57 174	87.06 38	46.45 205	78.88 103	77.02 243

CANet_DTU		68.18 151	67.71 128	69.59 189	74.83 189	46.24 223	78.66 99	76.85 183	59.60 103	63.45 173	82.09 141	35.25 236	77.41 229	59.88 128	78.76 106	85.14 94

test222					83.14 53	58.68 57	72.57 215	63.45 280	41.78 293	67.56 126	86.12 72	37.13 218			78.73 107	74.98 264

TAMVS		66.78 173	65.27 177	71.33 164	79.16 107	53.67 117	73.84 199	69.59 237	52.32 204	65.28 151	81.72 149	44.49 150	77.40 230	42.32 241	78.66 108	82.92 162

PVSNet_Blended_VisFu		71.45 81	70.39 83	74.65 75	82.01 62	58.82 55	79.93 83	80.35 117	55.09 177	65.82 148	82.16 138	49.17 93	82.64 149	60.34 125	78.62 109	82.50 170

testdata				64.66 246	81.52 68	52.93 129		65.29 268	46.09 262	73.88 37	87.46 50	38.08 209	66.26 282	53.31 163	78.48 110	74.78 268

QAPM		70.05 106	68.81 109	73.78 89	76.54 170	53.43 122	83.23 34	83.48 44	52.89 198	65.90 145	86.29 70	41.55 177	86.49 53	51.01 175	78.40 111	81.42 184

FC-MVSNet-test		69.80 110	70.58 82	67.46 209	77.61 148	34.73 305	76.05 162	83.19 55	60.84 69	65.88 146	86.46 67	54.52 32	80.76 181	52.52 166	78.12 112	86.91 34

LCM-MVSNet-Re		61.88 228	61.35 220	63.46 251	74.58 194	31.48 320	61.42 289	58.14 302	58.71 120	53.02 287	79.55 205	43.07 161	76.80 236	45.69 213	77.96 113	82.11 176

OMC-MVS		71.40 82	70.60 81	73.78 89	76.60 168	53.15 126	79.74 88	79.78 120	58.37 126	68.75 103	86.45 68	45.43 139	80.60 182	62.58 101	77.73 114	87.58 19

MVS_111021_LR		69.50 117	68.78 110	71.65 156	78.38 123	59.33 48	74.82 186	70.11 231	58.08 129	67.83 122	84.68 93	41.96 167	76.34 242	65.62 68	77.54 115	79.30 222

Fast-Effi-MVS+		70.28 103	69.12 106	73.73 94	78.50 120	51.50 149	75.01 181	79.46 137	56.16 160	68.59 104	79.55 205	53.97 36	84.05 106	53.34 162	77.53 116	85.65 71

xiu_mvs_v1_base_debu		68.58 134	67.28 140	72.48 139	78.19 128	57.19 76	75.28 174	75.09 201	51.61 210	70.04 75	81.41 162	32.79 260	79.02 206	63.81 91	77.31 117	81.22 194

xiu_mvs_v1_base		68.58 134	67.28 140	72.48 139	78.19 128	57.19 76	75.28 174	75.09 201	51.61 210	70.04 75	81.41 162	32.79 260	79.02 206	63.81 91	77.31 117	81.22 194

xiu_mvs_v1_base_debi		68.58 134	67.28 140	72.48 139	78.19 128	57.19 76	75.28 174	75.09 201	51.61 210	70.04 75	81.41 162	32.79 260	79.02 206	63.81 91	77.31 117	81.22 194

LPG-MVS_test		72.74 62	71.74 65	75.76 55	80.22 91	57.51 70	82.55 47	83.40 48	61.32 64	66.67 135	87.33 52	39.15 197	86.59 48	67.70 52	77.30 120	83.19 156

LGP-MVS_train				75.76 55	80.22 91	57.51 70		83.40 48	61.32 64	66.67 135	87.33 52	39.15 197	86.59 48	67.70 52	77.30 120	83.19 156

EPNet_dtu		61.90 226	61.97 211	61.68 262	72.89 234	39.78 265	75.85 166	65.62 265	55.09 177	54.56 274	79.36 208	37.59 212	67.02 278	39.80 256	76.95 122	78.25 229
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
TAPA-MVS	59.36 10	66.60 176	65.20 178	70.81 172	76.63 167	48.75 202	76.52 151	80.04 118	50.64 224	65.24 154	84.93 90	39.15 197	78.54 212	36.77 267	76.88 123	85.14 94
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
Regformer-3		73.89 52	73.28 54	75.71 58	79.75 97	55.48 104	78.54 103	79.93 119	66.58 12	73.62 41	80.30 190	54.87 28	84.54 98	69.09 45	76.84 124	87.10 32

Regformer-4		74.25 49	73.48 50	76.57 48	79.75 97	56.54 84	78.54 103	81.49 81	66.93 8	73.90 36	80.30 190	53.84 39	85.98 63	69.76 41	76.84 124	87.17 30

ACMP	63.53 6	72.30 68	71.20 75	75.59 63	80.28 90	57.54 68	82.74 43	82.84 63	60.58 74	65.24 154	86.18 71	39.25 196	86.03 61	66.95 60	76.79 126	83.22 154
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
cascas		65.98 184	63.42 194	73.64 99	77.26 158	52.58 134	72.26 220	77.21 179	48.56 238	61.21 212	74.60 270	32.57 268	85.82 67	50.38 179	76.75 127	82.52 169

BH-untuned		68.27 145	67.29 139	71.21 165	79.74 99	53.22 125	76.06 161	77.46 176	57.19 135	66.10 142	81.61 154	45.37 141	83.50 119	45.42 220	76.68 128	76.91 246

ACMM	61.98 7	70.80 87	69.73 90	74.02 83	80.59 87	58.59 58	82.68 44	82.02 71	55.46 173	67.18 130	84.39 102	38.51 202	83.17 127	60.65 122	76.10 129	80.30 208
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
BH-RMVSNet		68.81 128	67.42 134	72.97 123	80.11 94	52.53 135	74.26 192	76.29 186	58.48 124	68.38 109	84.20 103	42.59 162	83.83 114	46.53 204	75.91 130	82.56 167

XVG-OURS		68.76 131	67.37 136	72.90 125	74.32 200	57.22 74	70.09 247	78.81 149	55.24 175	67.79 124	85.81 81	36.54 230	78.28 219	62.04 113	75.74 131	83.19 156

mvs_anonymous		68.03 154	67.51 132	69.59 189	72.08 246	44.57 234	71.99 227	75.23 198	51.67 209	67.06 131	82.57 127	54.68 30	77.94 223	56.56 140	75.71 132	86.26 52

BH-w/o		66.85 171	65.83 170	69.90 186	79.29 102	52.46 137	74.66 188	76.65 184	54.51 186	64.85 161	78.12 222	45.59 136	82.95 133	43.26 234	75.54 133	74.27 272

LS3D		64.71 197	62.50 204	71.34 163	79.72 101	55.71 98	79.82 85	74.72 206	48.50 240	56.62 257	84.62 95	33.59 253	82.34 153	29.65 308	75.23 134	75.97 250

GG-mvs-BLEND				62.34 259	71.36 258	37.04 287	69.20 254	57.33 306		54.73 272	65.48 311	30.37 275	77.82 224	34.82 277	74.93 135	72.17 294

diffmvs		67.72 157	66.73 155	70.70 176	69.74 275	47.69 213	73.33 204	74.74 205	53.30 195	64.51 165	81.80 148	49.25 87	79.02 206	59.15 132	74.75 136	85.39 87

pcd1.5k->3k		30.06 314	30.56 315	28.55 329	78.81 113	0.00 352	0.00 343	82.07 70	0.00 347	0.00 349	0.00 349	39.61 193	0.00 348	0.00 347	74.56 137	85.66 70

nrg030		72.96 60	73.01 55	72.84 128	75.41 183	50.24 174	80.02 82	82.89 62	58.36 127	74.44 30	86.73 57	58.90 11	80.83 177	65.84 66	74.46 138	87.44 23

VPA-MVSNet		69.02 125	69.47 102	67.69 208	77.42 151	41.00 261	74.04 194	79.68 122	60.06 85	69.26 98	84.81 92	51.06 63	77.58 227	54.44 155	74.43 139	84.48 115

PS-MVSNAJss		72.24 69	71.21 74	75.31 66	78.50 120	55.93 95	81.63 62	82.12 68	56.24 159	70.02 78	85.68 82	47.05 121	84.34 102	65.27 70	74.41 140	85.67 69

EI-MVSNet-Vis-set		72.42 67	71.59 66	74.91 69	78.47 122	54.02 114	77.05 142	79.33 141	65.03 20	71.68 63	79.35 209	52.75 48	84.89 89	66.46 61	74.23 141	85.83 61

CHOSEN 1792x2688		65.08 195	62.84 200	71.82 153	81.49 70	56.26 88	66.32 266	74.20 211	40.53 303	63.16 176	78.65 217	41.30 180	77.80 225	45.80 212	74.09 142	81.40 185

testing_2		66.02 183	63.77 190	72.76 131	66.03 299	50.48 168	72.93 208	80.36 116	54.41 187	54.25 278	76.76 250	30.89 273	83.16 128	64.19 85	74.08 143	84.65 110

ACMMP++_ref															74.07 144

PVSNet_BlendedMVS		68.56 137	67.72 126	71.07 170	77.03 162	50.57 163	74.50 190	81.52 78	53.66 193	64.22 170	79.72 202	49.13 94	82.87 137	55.82 144	73.92 145	79.77 217

CMPMVS	42.80 21	57.81 254	55.97 258	63.32 252	60.98 319	47.38 216	64.66 277	69.50 238	32.06 324	46.83 306	77.80 229	29.50 282	71.36 261	48.68 192	73.75 146	71.21 299
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MS-PatchMatch		62.42 221	61.46 219	65.31 242	75.21 186	52.10 141	72.05 226	74.05 212	46.41 259	57.42 253	74.36 271	34.35 245	77.57 228	45.62 215	73.67 147	66.26 311

test-LLR		58.15 252	58.13 244	58.22 278	68.57 280	44.80 230	65.46 270	57.92 303	50.08 228	55.44 265	69.82 296	32.62 265	57.44 310	49.66 186	73.62 148	72.41 289

test-mter		56.42 260	55.82 259	58.22 278	68.57 280	44.80 230	65.46 270	57.92 303	39.94 307	55.44 265	69.82 296	21.92 316	57.44 310	49.66 186	73.62 148	72.41 289

EI-MVSNet-UG-set		71.92 74	71.06 76	74.52 79	77.98 135	53.56 120	76.62 148	79.16 143	64.40 26	71.18 65	78.95 214	52.19 54	84.66 97	65.47 69	73.57 150	85.32 89

TR-MVS		66.59 178	65.07 181	71.17 167	79.18 105	49.63 195	73.48 203	75.20 199	52.95 197	67.90 117	80.33 189	39.81 191	83.68 116	43.20 235	73.56 151	80.20 209

ab-mvs		66.65 175	66.42 162	67.37 210	76.17 172	41.73 255	70.41 244	76.14 188	53.99 191	65.98 143	83.51 114	49.48 75	76.24 243	48.60 193	73.46 152	84.14 131

EG-PatchMatch MVS		64.71 197	62.87 199	70.22 180	77.68 141	53.48 121	77.99 119	78.82 148	53.37 194	56.03 261	77.41 243	24.75 310	84.04 107	46.37 206	73.42 153	73.14 280

XVG-OURS-SEG-HR		68.81 128	67.47 133	72.82 130	74.40 199	56.87 82	70.59 240	79.04 145	54.77 182	66.99 132	86.01 75	39.57 194	78.21 220	62.54 102	73.33 154	83.37 151

thres200		62.20 223	61.16 223	65.34 241	75.38 184	39.99 263	69.60 250	69.29 242	55.64 170	61.87 199	76.99 245	37.07 219	78.96 211	31.28 297	73.28 155	77.06 242

conf200view11		63.38 206	62.41 205	66.29 222	77.31 152	38.66 275	72.65 211	69.11 244	57.07 136	62.45 189	81.03 169	37.01 220	79.17 199	31.84 288	73.25 156	81.03 199

thres100view900		63.28 209	62.41 205	65.89 231	77.31 152	38.66 275	72.65 211	69.11 244	57.07 136	62.45 189	81.03 169	37.01 220	79.17 199	31.84 288	73.25 156	79.83 214

tfpn200view9		63.18 211	62.18 209	66.21 224	76.85 165	39.62 266	71.96 228	69.44 240	56.63 148	62.61 183	79.83 198	37.18 215	79.17 199	31.84 288	73.25 156	79.83 214

thres400		63.31 207	62.18 209	66.72 215	76.85 165	39.62 266	71.96 228	69.44 240	56.63 148	62.61 183	79.83 198	37.18 215	79.17 199	31.84 288	73.25 156	81.36 186

TESTMET0.1,1		55.28 268	54.90 264	56.42 286	66.56 295	43.67 242	65.46 270	56.27 312	39.18 309	53.83 280	67.44 303	24.21 311	55.46 324	48.04 196	73.11 160	70.13 303

thres600view7		63.30 208	62.27 207	66.41 219	77.18 159	38.87 272	72.35 218	69.11 244	56.98 139	62.37 194	80.96 172	37.01 220	79.00 210	31.43 296	73.05 161	81.36 186

VPNet		67.52 158	68.11 121	65.74 233	79.18 105	36.80 292	72.17 221	72.83 219	62.04 57	67.79 124	85.83 79	48.88 100	76.60 239	51.30 174	72.97 162	83.81 138

mvs-test1		70.44 99	68.19 119	77.18 38	76.10 173	63.22 6	80.59 77	76.06 190	59.83 94	66.32 140	79.87 197	41.56 175	85.53 71	60.60 123	72.77 163	82.80 166

GBi-Net		67.21 162	66.55 158	69.19 193	77.63 143	43.33 244	77.31 135	77.83 168	56.62 150	65.04 157	82.70 122	41.85 170	80.33 185	47.18 199	72.76 164	83.92 134

test1		67.21 162	66.55 158	69.19 193	77.63 143	43.33 244	77.31 135	77.83 168	56.62 150	65.04 157	82.70 122	41.85 170	80.33 185	47.18 199	72.76 164	83.92 134

FMVSNet3		66.32 181	65.61 172	68.46 202	76.48 171	42.34 251	74.98 183	77.15 180	55.83 165	65.04 157	81.16 165	39.91 189	80.14 189	47.18 199	72.76 164	82.90 164

FMVSNet2		66.93 170	66.31 167	68.79 199	77.63 143	42.98 247	76.11 159	77.47 174	56.62 150	65.22 156	82.17 137	41.85 170	80.18 188	47.05 202	72.72 167	83.20 155

view600		62.77 215	61.84 212	65.55 235	77.28 154	36.87 288	72.15 222	67.78 251	56.79 142	61.46 207	81.92 142	36.88 223	78.42 213	29.86 303	72.46 168	81.36 186

view800		62.77 215	61.84 212	65.55 235	77.28 154	36.87 288	72.15 222	67.78 251	56.79 142	61.46 207	81.92 142	36.88 223	78.42 213	29.86 303	72.46 168	81.36 186

conf0.05thres1000		62.77 215	61.84 212	65.55 235	77.28 154	36.87 288	72.15 222	67.78 251	56.79 142	61.46 207	81.92 142	36.88 223	78.42 213	29.86 303	72.46 168	81.36 186

tfpn		62.77 215	61.84 212	65.55 235	77.28 154	36.87 288	72.15 222	67.78 251	56.79 142	61.46 207	81.92 142	36.88 223	78.42 213	29.86 303	72.46 168	81.36 186

PVSNet	50.76 19	58.40 249	57.39 247	61.42 264	75.53 181	44.04 239	61.43 288	63.45 280	47.04 255	56.91 255	73.61 276	27.00 298	64.76 287	39.12 257	72.40 172	75.47 258

MIMVSNet		57.35 255	57.07 249	58.22 278	74.21 202	37.18 285	62.46 284	60.88 294	48.88 236	55.29 268	75.99 260	31.68 271	62.04 296	31.87 287	72.35 173	75.43 259

1314		64.61 199	63.21 196	68.80 198	71.87 251	47.46 215	73.95 195	78.39 164	42.88 290	59.97 224	76.60 253	38.11 208	79.39 195	54.84 150	72.32 174	79.55 218

FMVSNet1		66.70 174	65.87 169	69.19 193	77.49 150	43.33 244	77.31 135	77.83 168	56.45 154	64.60 164	82.70 122	38.08 209	80.33 185	46.08 209	72.31 175	83.92 134

ACMMP++															72.16 176

MVP-Stereo		65.41 190	63.80 189	70.22 180	77.62 147	55.53 102	76.30 154	78.53 156	50.59 225	56.47 259	78.65 217	39.84 190	82.68 147	44.10 227	72.12 177	72.44 288
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
HyFIR lowres test		65.67 186	63.01 198	73.67 96	79.97 96	55.65 100	69.07 255	75.52 194	42.68 291	63.53 172	77.95 224	40.43 188	81.64 162	46.01 210	71.91 178	83.73 142

XVG-ACMP-BASELINE		64.36 201	62.23 208	70.74 174	72.35 242	52.45 138	70.80 239	78.45 160	53.84 192	59.87 226	81.10 167	16.24 323	79.32 196	55.64 148	71.76 179	80.47 205

HY-MVS	56.14 13	64.55 200	63.89 187	66.55 218	74.73 192	41.02 259	69.96 248	74.43 208	49.29 232	61.66 204	80.92 173	47.43 119	76.68 238	44.91 223	71.69 180	81.94 177

ACMH	55.70 15	65.20 193	63.57 193	70.07 183	78.07 132	52.01 145	79.48 94	79.69 121	55.75 167	56.59 258	80.98 171	27.12 296	80.94 174	42.90 239	71.58 181	77.25 241
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVSTER		67.16 164	65.58 173	71.88 152	70.37 267	49.70 191	70.25 246	78.45 160	51.52 213	69.16 100	80.37 186	38.45 203	82.50 150	60.19 126	71.46 182	83.44 150

EI-MVSNet		69.27 121	68.44 116	71.73 155	74.47 196	49.39 197	75.20 177	78.45 160	59.60 103	69.16 100	76.51 254	51.29 59	82.50 150	59.86 130	71.45 183	83.30 152

LTVRE_ROB	55.42 16	63.15 212	61.23 222	68.92 197	76.57 169	47.80 210	59.92 295	76.39 185	54.35 188	58.67 241	82.46 130	29.44 283	81.49 166	42.12 242	71.14 184	77.46 235
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
UniMVSNet (Re)		70.63 91	70.20 85	71.89 151	78.55 119	45.29 227	75.94 165	82.92 59	63.68 34	68.16 113	83.59 112	53.89 38	83.49 120	53.97 156	71.12 185	86.89 35

Effi-MVS+-dtu		69.64 114	67.53 131	75.95 52	76.10 173	62.29 18	80.20 81	76.06 190	59.83 94	65.26 153	77.09 244	41.56 175	84.02 110	60.60 123	71.09 186	81.53 182

NR-MVSNet		69.54 116	68.85 108	71.59 158	78.05 133	43.81 241	74.20 193	80.86 101	65.18 17	62.76 179	84.52 98	52.35 53	83.59 118	50.96 176	70.78 187	87.37 25

v1144		70.42 100	69.31 104	73.76 91	73.22 217	50.64 160	77.83 123	81.43 82	58.58 121	69.40 94	81.16 165	47.53 116	85.29 79	64.01 88	70.64 188	85.34 88

jajsoiax		68.25 147	66.45 160	73.66 97	75.62 179	55.49 103	80.82 73	78.51 157	52.33 203	64.33 167	84.11 105	28.28 288	81.81 161	63.48 96	70.62 189	83.67 146

v7		70.57 92	69.48 101	73.85 86	73.50 209	50.92 153	78.27 107	81.43 82	58.93 116	69.61 86	81.49 158	47.56 115	85.43 76	63.94 90	70.62 189	85.21 93

tfpn_ndepth		59.57 242	59.02 234	61.23 267	73.81 205	35.60 300	69.40 253	65.59 266	50.96 222	57.96 249	77.72 231	34.81 238	75.91 245	30.36 300	70.57 191	72.18 293

mvs_tets		68.18 151	66.36 164	73.63 100	75.61 180	55.35 106	80.77 74	78.56 155	52.48 202	64.27 169	84.10 106	27.45 294	81.84 160	63.45 97	70.56 192	83.69 143

UniMVSNet_NR-MVSNet		71.11 83	71.00 77	71.44 159	79.20 104	44.13 237	76.02 164	82.60 64	66.48 14	68.20 111	84.60 97	56.82 14	82.82 139	54.62 152	70.43 193	87.36 27

DU-MVS		70.01 107	69.53 96	71.44 159	78.05 133	44.13 237	75.01 181	81.51 80	64.37 27	68.20 111	84.52 98	49.12 96	82.82 139	54.62 152	70.43 193	87.37 25

v6		70.66 88	69.70 91	73.53 102	73.14 224	50.21 178	78.11 112	80.67 105	59.65 100	69.82 83	81.65 152	49.29 80	84.96 84	64.55 77	70.39 195	85.42 82

v1neww		70.66 88	69.70 91	73.53 102	73.15 221	50.22 175	78.11 112	80.68 103	59.65 100	69.83 81	81.67 150	49.29 80	84.96 84	64.55 77	70.38 196	85.42 82

v7new		70.66 88	69.70 91	73.53 102	73.15 221	50.22 175	78.11 112	80.68 103	59.65 100	69.83 81	81.67 150	49.29 80	84.96 84	64.55 77	70.38 196	85.42 82

v1192		69.97 109	68.68 111	73.85 86	73.19 220	50.94 151	77.68 129	81.36 85	57.51 133	68.95 102	80.85 176	45.28 142	85.33 78	62.97 99	70.37 198	85.27 91

PLC	56.13 14	65.09 194	63.21 196	70.72 175	81.04 80	54.87 110	78.57 101	77.47 174	48.51 239	55.71 262	81.89 146	33.71 251	79.71 190	41.66 246	70.37 198	77.58 234
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
GA-MVS		65.53 188	63.70 191	71.02 171	70.87 261	48.10 207	70.48 242	74.40 209	56.69 146	64.70 163	76.77 249	33.66 252	81.10 172	55.42 149	70.32 200	83.87 137

divwei89l23v2f112		70.50 95	69.53 96	73.41 111	72.91 232	50.00 185	77.69 126	80.59 108	59.50 108	69.60 87	81.43 159	49.26 85	84.77 92	64.48 81	70.31 201	85.47 76

v1141		70.50 95	69.53 96	73.41 111	72.92 231	50.00 185	77.69 126	80.60 107	59.50 108	69.60 87	81.43 159	49.24 90	84.77 92	64.48 81	70.30 202	85.46 78

v1		70.50 95	69.53 96	73.42 110	72.91 232	50.00 185	77.69 126	80.59 108	59.50 108	69.59 89	81.42 161	49.26 85	84.77 92	64.49 80	70.30 202	85.47 76

Fast-Effi-MVS+-dtu		67.37 159	65.33 176	73.48 106	72.94 230	57.78 66	77.47 133	76.88 182	57.60 132	61.97 197	76.85 248	39.31 195	80.49 183	54.72 151	70.28 204	82.17 175

v2v482		70.50 95	69.45 103	73.66 97	72.62 238	50.03 184	77.58 130	80.51 112	59.90 90	69.52 90	82.14 139	47.53 116	84.88 91	65.07 72	70.17 205	86.09 55

IB-MVS	56.42 12	65.40 191	62.73 202	73.40 113	74.89 187	52.78 131	73.09 207	75.13 200	55.69 168	58.48 245	73.73 275	32.86 259	86.32 57	50.63 177	70.11 206	81.10 197
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
CNLPA		65.43 189	64.02 186	69.68 187	78.73 116	58.07 63	77.82 124	70.71 228	51.49 214	61.57 206	83.58 113	38.23 207	70.82 263	43.90 228	70.10 207	80.16 210

tfpn1000		59.24 245	58.70 238	60.86 270	73.75 206	33.99 309	68.86 256	63.98 277	51.25 220	57.29 254	79.51 207	34.58 240	75.26 248	29.08 311	69.99 208	73.32 279

1112_ss		64.00 203	63.36 195	65.93 230	79.28 103	42.58 250	71.35 231	72.36 222	46.41 259	60.55 220	77.89 227	46.27 131	73.28 255	46.18 207	69.97 209	81.92 178

DP-MVS		65.68 185	63.66 192	71.75 154	84.93 41	56.87 82	80.74 75	73.16 218	53.06 196	59.09 237	82.35 131	36.79 228	85.94 65	32.82 284	69.96 210	72.45 287

IterMVS-LS		69.22 124	68.48 114	71.43 161	74.44 198	49.40 196	76.23 157	77.55 173	59.60 103	65.85 147	81.59 156	51.28 60	81.58 165	59.87 129	69.90 211	83.30 152
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v1921920		69.47 118	68.17 120	73.36 114	73.06 227	50.10 183	77.39 134	80.56 110	56.58 153	68.59 104	80.37 186	44.72 145	84.98 82	62.47 104	69.82 212	85.00 99

Baseline_NR-MVSNet		67.05 167	67.56 129	65.50 239	75.65 178	37.70 284	75.42 171	74.65 207	59.90 90	68.14 114	83.15 120	49.12 96	77.20 231	52.23 168	69.78 213	81.60 181

ACMH+	57.40 11	66.12 182	64.06 185	72.30 149	77.79 139	52.83 130	80.39 78	78.03 166	57.30 134	57.47 252	82.55 128	27.68 292	84.17 104	45.54 216	69.78 213	79.90 213

v1240		69.24 123	67.91 123	73.25 120	73.02 229	49.82 188	77.21 139	80.54 111	56.43 155	68.34 110	80.51 184	43.33 160	84.99 80	62.03 114	69.77 215	84.95 102

TranMVSNet+NR-MVSNet		70.36 101	70.10 88	71.17 167	78.64 118	42.97 248	76.53 150	81.16 93	66.95 7	68.53 107	85.42 87	51.61 58	83.07 130	52.32 167	69.70 216	87.46 22

v144192		69.71 111	68.51 113	73.33 115	73.10 226	50.13 182	77.54 132	80.64 106	56.65 147	68.57 106	80.55 183	46.87 126	84.96 84	62.98 98	69.66 217	84.89 103

WR-MVS		68.47 139	68.47 115	68.44 203	80.20 93	39.84 264	73.75 200	76.07 189	64.68 21	68.11 115	83.63 111	50.39 69	79.14 204	49.78 182	69.66 217	86.34 47

WTY-MVS		59.75 239	60.39 227	57.85 281	72.32 243	37.83 282	61.05 293	64.18 276	45.95 266	61.91 198	79.11 212	47.01 124	60.88 299	42.50 240	69.49 219	74.83 266

test_djsdf		69.45 119	67.74 125	74.58 78	74.57 195	54.92 109	82.79 41	78.48 158	51.26 218	65.41 150	83.49 115	38.37 204	83.24 125	66.06 62	69.25 220	85.56 72

CostFormer		64.04 202	62.51 203	68.61 201	71.88 250	45.77 225	71.30 232	70.60 229	47.55 250	64.31 168	76.61 252	41.63 173	79.62 192	49.74 184	69.00 221	80.42 206

tpm2		62.07 225	60.10 229	67.99 205	72.79 235	43.86 240	71.05 236	66.85 260	43.14 288	62.77 178	75.39 264	38.32 205	80.80 178	41.69 245	68.88 222	79.32 221

v10		70.21 104	69.02 107	73.81 88	73.51 208	50.92 153	78.74 97	81.39 84	60.05 86	66.39 139	81.83 147	47.58 114	85.41 77	62.80 100	68.86 223	85.09 97

v8		70.33 102	69.28 105	73.49 105	73.15 221	50.22 175	78.62 100	80.78 102	60.79 70	66.45 138	82.11 140	49.35 76	84.98 82	63.58 95	68.71 224	85.28 90

v7n		69.01 126	67.36 137	73.98 84	72.51 240	52.65 132	78.54 103	81.30 87	60.26 83	62.67 181	81.62 153	43.61 157	84.49 99	57.01 139	68.70 225	84.79 107

Test_1112_low_res		62.32 222	61.77 216	64.00 250	79.08 108	39.53 268	68.17 259	70.17 230	43.25 286	59.03 238	79.90 196	44.08 153	71.24 262	43.79 230	68.42 226	81.25 193

tfpnview11		59.40 243	58.81 235	61.17 268	74.15 203	33.83 311	68.32 258	64.22 275	51.79 208	58.04 248	79.57 204	35.41 234	75.41 247	29.57 309	68.26 227	74.25 273

PMMVS		53.96 272	53.26 276	56.04 287	62.60 312	50.92 153	61.17 292	56.09 313	32.81 322	53.51 285	66.84 305	34.04 247	59.93 303	44.14 226	68.18 228	57.27 326

tfpnnormal		62.47 220	61.63 218	64.99 244	74.81 190	39.01 271	71.22 233	73.72 214	55.22 176	60.21 222	80.09 195	41.26 183	76.98 235	30.02 302	68.09 229	78.97 226

DWT-MVSNet_test		61.90 226	59.93 230	67.83 206	71.98 249	46.09 224	71.03 237	69.71 233	50.09 227	58.51 244	70.62 290	30.21 278	77.63 226	49.28 188	67.91 230	79.78 216

Anonymous20231206		55.10 270	55.30 262	54.48 295	69.81 274	33.94 310	62.91 283	62.13 291	41.08 298	55.18 269	75.65 262	32.75 263	56.59 316	30.32 301	67.86 231	72.91 281

V42		68.65 132	67.35 138	72.56 136	68.93 278	50.18 179	72.90 209	79.47 136	56.92 140	69.45 93	80.26 192	46.29 130	82.99 131	64.07 86	67.82 232	84.53 113

MDTV_nov1_ep13			57.00 250		72.73 236	38.26 279	65.02 276	64.73 272	44.74 273	55.46 264	72.48 280	32.61 267	70.47 266	37.47 263	67.75 233

tpmp4_e23		62.71 219	60.13 228	70.45 179	73.40 213	48.39 205	72.82 210	69.49 239	44.88 271	59.91 225	74.99 266	37.79 211	81.47 167	40.22 252	67.71 234	81.48 183

anonymousdsp		67.00 169	64.82 183	73.57 101	70.09 269	56.13 90	76.35 153	77.35 178	48.43 241	64.99 160	80.84 177	33.01 257	80.34 184	64.66 74	67.64 235	84.23 124

OpenMVS_ROB	52.78 18	60.03 236	58.14 243	65.69 234	70.47 264	44.82 229	75.33 172	70.86 227	45.04 270	56.06 260	76.00 258	26.89 299	79.65 191	35.36 276	67.29 236	72.60 284

XXY-MVS		60.68 234	61.67 217	57.70 283	70.43 265	38.45 278	64.19 279	66.47 261	48.05 246	63.22 174	80.86 175	49.28 83	60.47 300	45.25 222	67.28 237	74.19 274

F-COLMAP		63.05 213	60.87 225	69.58 191	76.99 164	53.63 119	78.12 111	76.16 187	47.97 247	52.41 288	81.61 154	27.87 290	78.11 221	40.07 253	66.66 238	77.00 244

pm-mvs1		65.24 192	64.97 182	66.04 227	72.38 241	39.40 269	72.62 214	75.63 193	55.53 171	62.35 195	83.18 119	47.45 118	76.47 240	49.06 190	66.54 239	82.24 173

v148		68.24 149	67.19 144	71.40 162	70.43 265	47.77 212	75.76 167	77.03 181	58.91 117	67.36 128	80.10 194	48.60 104	81.89 158	60.01 127	66.52 240	84.53 113

sss		56.17 263	56.57 253	54.96 292	66.93 291	36.32 297	57.94 301	61.69 292	41.67 295	58.64 242	75.32 265	38.72 201	56.25 319	42.04 243	66.19 241	72.31 292

COLMAP_ROB	52.97 17	61.27 233	58.81 235	68.64 200	74.63 193	52.51 136	78.42 106	73.30 216	49.92 230	50.96 293	81.51 157	23.06 313	79.40 194	31.63 293	65.85 242	74.01 276
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
CVMVSNet		59.63 241	59.14 233	61.08 269	74.47 196	38.84 273	75.20 177	68.74 247	31.15 325	58.24 246	76.51 254	32.39 269	68.58 273	49.77 183	65.84 243	75.81 254

MSDG		61.81 229	59.23 232	69.55 192	72.64 237	52.63 133	70.45 243	75.81 192	51.38 216	53.70 281	76.11 257	29.52 281	81.08 173	37.70 262	65.79 244	74.93 265

PatchFormer-LS_test		62.20 223	60.59 226	67.04 213	72.18 245	46.82 220	70.36 245	68.62 248	51.92 206	59.19 235	70.23 293	36.86 227	75.07 250	50.23 181	65.68 245	79.23 223

FMVSNet5		55.86 265	54.93 263	58.66 277	71.05 260	36.35 295	64.18 280	62.48 288	46.76 256	50.66 296	74.73 269	25.80 304	64.04 289	33.11 283	65.57 246	75.59 257

pmmvs5		56.47 259	55.68 260	58.86 275	61.41 316	36.71 293	66.37 265	62.75 286	40.38 304	53.70 281	76.62 251	34.56 241	67.05 277	40.02 255	65.27 247	72.83 282

v748		67.26 161	65.67 171	72.02 150	69.90 273	49.77 190	76.24 156	79.57 133	58.58 121	60.49 221	80.38 185	44.47 151	82.17 155	56.16 142	65.26 248	84.12 132

tpm		57.34 256	58.16 242	54.86 293	71.80 252	34.77 304	67.47 262	56.04 314	48.20 244	60.10 223	76.92 246	37.17 217	53.41 327	40.76 251	65.01 249	76.40 249

pmmvs4		61.48 231	59.39 231	67.76 207	71.57 253	53.86 116	71.42 230	65.34 267	44.20 279	59.46 230	77.92 226	35.90 231	74.71 252	43.87 229	64.87 250	74.71 269

V4		67.09 165	65.16 179	72.87 126	66.76 294	51.60 147	73.69 201	79.45 138	57.88 130	62.45 189	78.58 219	40.96 185	83.34 121	61.99 115	64.71 251	83.68 144

test_0402		63.25 210	61.01 224	69.96 184	80.00 95	54.37 113	76.86 146	72.02 223	54.58 184	58.71 240	80.79 178	35.00 237	84.36 101	26.41 319	64.71 251	71.15 300

v52		67.09 165	65.16 179	72.87 126	66.77 293	51.60 147	73.69 201	79.45 138	57.88 130	62.46 188	78.57 220	40.95 186	83.34 121	61.99 115	64.70 253	83.68 144

CR-MVSNet		59.91 237	57.90 246	65.96 228	69.96 271	52.07 142	65.31 273	63.15 283	42.48 292	59.36 231	74.84 267	35.83 232	70.75 264	45.50 217	64.65 254	75.06 261

RPMNet		58.70 247	56.29 257	65.96 228	69.96 271	52.07 142	65.31 273	62.15 290	43.20 287	59.36 231	70.15 295	35.37 235	70.75 264	36.42 273	64.65 254	75.06 261

pmmvs6		63.69 204	62.82 201	66.27 223	70.63 263	39.27 270	73.13 206	75.47 195	52.69 200	59.75 229	82.30 133	39.71 192	77.03 234	47.40 198	64.35 256	82.53 168

WR-MVS_H		67.02 168	66.92 149	67.33 212	77.95 136	37.75 283	77.57 131	82.11 69	62.03 58	62.65 182	82.48 129	50.57 67	79.46 193	42.91 238	64.01 257	84.79 107

test0.0.03 1		53.32 277	53.59 274	52.50 303	62.81 311	29.45 324	59.51 296	54.11 322	50.08 228	54.40 276	74.31 272	32.62 265	55.92 321	30.50 299	63.95 258	72.15 295

PatchMatch-RL		56.25 262	54.55 266	61.32 266	77.06 161	56.07 92	65.57 269	54.10 323	44.13 281	53.49 286	71.27 288	25.20 307	66.78 279	36.52 272	63.66 259	61.12 320

PatchmatchNet		59.84 238	58.24 241	64.65 247	73.05 228	46.70 221	69.42 252	62.18 289	47.55 250	58.88 239	71.96 283	34.49 243	69.16 270	42.99 237	63.60 260	78.07 231
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
semantic-postprocess				65.40 240	71.99 248	50.80 157		69.63 236	45.71 268	60.61 219	77.93 225	36.56 229	65.99 284	55.67 147	63.50 261	79.42 220

CP-MVSNet		66.49 179	66.41 163	66.72 215	77.67 142	36.33 296	76.83 147	79.52 135	62.45 49	62.54 185	83.47 116	46.32 129	78.37 217	45.47 219	63.43 262	85.45 79

PS-CasMVS		66.42 180	66.32 166	66.70 217	77.60 149	36.30 298	76.94 145	79.61 124	62.36 51	62.43 193	83.66 110	45.69 133	78.37 217	45.35 221	63.26 263	85.42 82

IterMVS		62.79 214	61.27 221	67.35 211	69.37 276	52.04 144	71.17 234	68.24 250	52.63 201	59.82 227	76.91 247	37.32 214	72.36 258	52.80 165	63.19 264	77.66 233
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
PEN-MVS		66.60 176	66.45 160	67.04 213	77.11 160	36.56 294	77.03 143	80.42 114	62.95 39	62.51 187	84.03 107	46.69 127	79.07 205	44.22 224	63.08 265	85.51 75

tpmrst		58.24 250	58.70 238	56.84 285	66.97 290	34.32 307	69.57 251	61.14 293	47.17 254	58.58 243	71.60 284	41.28 182	60.41 301	49.20 189	62.84 266	75.78 255

testgi		51.90 281	52.37 278	50.51 308	60.39 322	23.55 338	58.42 299	58.15 301	49.03 235	51.83 290	79.21 211	22.39 314	55.59 322	29.24 310	62.64 267	72.40 291

Patchmatch-test1		59.75 239	58.00 245	64.98 245	74.14 204	48.06 208	63.35 281	63.23 282	49.13 234	59.33 234	71.46 285	37.45 213	69.59 268	41.39 249	62.57 268	77.30 237

EPMVS		53.96 272	53.69 272	54.79 294	66.12 298	31.96 319	62.34 286	49.05 330	44.42 278	55.54 263	71.33 287	30.22 277	56.70 314	41.65 247	62.54 269	75.71 256

ITE_SJBPF				62.09 261	66.16 297	44.55 235		64.32 274	47.36 252	55.31 267	80.34 188	19.27 319	62.68 294	36.29 274	62.39 270	79.04 224

MIMVSNet1		55.17 269	54.31 268	57.77 282	70.03 270	32.01 318	65.68 268	64.81 270	49.19 233	46.75 307	76.00 258	25.53 306	64.04 289	28.65 313	62.13 271	77.26 240

USDC		56.35 261	54.24 269	62.69 258	64.74 304	40.31 262	65.05 275	73.83 213	43.93 282	47.58 302	77.71 232	15.36 325	75.05 251	38.19 261	61.81 272	72.70 283

PatchT		53.17 278	53.44 275	52.33 304	68.29 284	25.34 335	58.21 300	54.41 320	44.46 277	54.56 274	69.05 298	33.32 255	60.94 298	36.93 266	61.76 273	70.73 302

v16		68.38 140	67.01 146	72.47 143	73.22 217	50.29 172	78.10 115	79.59 129	59.71 98	61.72 202	77.60 236	49.28 83	82.89 135	62.36 106	61.54 274	84.23 124

v18		68.33 142	66.96 148	72.42 145	73.13 225	50.16 180	77.97 120	79.57 133	59.57 107	61.80 200	77.50 241	49.30 78	82.90 134	62.31 107	61.50 275	84.20 130

tpm cat1		59.25 244	56.95 251	66.15 225	72.19 244	46.96 218	68.09 260	65.76 264	40.03 306	57.81 250	70.56 291	38.32 205	74.51 253	38.26 260	61.50 275	77.00 244

v17		68.37 141	67.00 147	72.48 139	73.22 217	50.31 171	78.10 115	79.58 131	59.71 98	61.67 203	77.60 236	49.31 77	82.89 135	62.37 105	61.48 277	84.23 124

tpmvs		58.47 248	56.95 251	63.03 256	70.20 268	41.21 258	67.90 261	67.23 258	49.62 231	54.73 272	70.84 289	34.14 246	76.24 243	36.64 270	61.29 278	71.64 296

Patchmtry		57.16 257	56.47 254	59.23 272	69.17 277	34.58 306	62.98 282	63.15 283	44.53 276	56.83 256	74.84 267	35.83 232	68.71 272	40.03 254	60.91 279	74.39 271

DTE-MVSNet		65.58 187	65.34 175	66.31 220	76.06 175	34.79 303	76.43 152	79.38 140	62.55 48	61.66 204	83.83 109	45.60 135	79.15 203	41.64 248	60.88 280	85.00 99

v11		68.15 153	66.73 155	72.42 145	73.43 211	50.28 173	77.94 121	79.65 123	59.88 93	61.11 214	77.55 239	48.25 107	82.75 146	61.88 117	60.85 281	84.23 124

CHOSEN 280x420		47.83 291	46.36 292	52.24 305	67.37 289	49.78 189	38.91 335	43.11 339	35.00 319	43.27 319	63.30 317	28.95 285	49.19 332	36.53 271	60.80 282	57.76 325

Patchmatch-test		49.08 288	48.28 288	51.50 306	64.40 306	30.85 322	45.68 327	48.46 333	35.60 318	46.10 310	72.10 282	34.47 244	46.37 333	27.08 317	60.65 283	77.27 239

v15		68.22 150	66.81 154	72.47 143	73.25 216	50.40 169	77.92 122	79.60 126	59.77 97	61.28 211	77.52 240	49.25 87	82.77 141	62.16 112	60.51 284	84.24 123

V14		68.25 147	66.82 153	72.52 138	73.33 215	50.53 166	78.02 118	79.60 126	59.83 94	61.16 213	77.57 238	49.19 91	82.77 141	62.18 108	60.50 285	84.26 122

V9		68.27 145	66.84 150	72.56 136	73.39 214	50.63 161	78.10 115	79.60 126	59.94 89	61.05 215	77.62 235	49.18 92	82.77 141	62.17 110	60.48 286	84.27 121

v12		68.28 144	66.83 152	72.60 135	73.43 211	50.74 158	78.18 110	79.59 129	60.01 88	60.89 217	77.66 234	49.12 96	82.77 141	62.18 108	60.46 287	84.29 120

v13		68.29 143	66.84 150	72.63 133	73.50 209	50.83 156	78.25 108	79.58 131	60.05 86	60.76 218	77.68 233	49.11 99	82.77 141	62.17 110	60.45 288	84.30 119

test20.03		53.87 274	54.02 271	53.41 299	61.47 315	28.11 327	61.30 290	59.21 298	51.34 217	52.09 289	77.43 242	33.29 256	58.55 307	29.76 307	60.27 289	73.58 278

MVS-HIRNet		45.52 296	44.48 298	48.65 311	68.49 282	34.05 308	59.41 298	44.50 338	27.03 329	37.96 328	50.47 332	26.16 303	64.10 288	26.74 318	59.52 290	47.82 330

Patchmatch-RL test		58.16 251	55.49 261	66.15 225	67.92 286	48.89 201	60.66 294	51.07 327	47.86 248	59.36 231	62.71 318	34.02 248	72.27 259	56.41 141	59.40 291	77.30 237

AllTest		57.08 258	54.65 265	64.39 248	71.44 254	49.03 198	69.92 249	67.30 256	45.97 264	47.16 304	79.77 200	17.47 320	67.56 275	33.65 281	59.16 292	76.57 247

TestCases				64.39 248	71.44 254	49.03 198		67.30 256	45.97 264	47.16 304	79.77 200	17.47 320	67.56 275	33.65 281	59.16 292	76.57 247

RPSCF		55.80 266	54.22 270	60.53 271	65.13 303	42.91 249	64.30 278	57.62 305	36.84 316	58.05 247	82.28 134	28.01 289	56.24 320	37.14 265	58.61 294	82.44 172

EU-MVSNet		55.61 267	54.41 267	59.19 273	65.41 302	33.42 313	72.44 217	71.91 224	28.81 327	51.27 291	73.87 274	24.76 309	69.08 271	43.04 236	58.20 295	75.06 261

pmmvs-eth3d		58.81 246	56.31 256	66.30 221	67.61 287	52.42 139	72.30 219	64.76 271	43.55 284	54.94 270	74.19 273	28.95 285	72.60 257	43.31 232	57.21 296	73.88 277

TinyColmap		54.14 271	51.72 279	61.40 265	66.84 292	41.97 252	66.52 264	68.51 249	44.81 272	42.69 321	75.77 261	11.66 333	72.94 256	31.96 286	56.77 297	69.27 307

OurMVSNet-221017-0		61.37 232	58.63 240	69.61 188	72.05 247	48.06 208	73.93 198	72.51 220	47.23 253	54.74 271	80.92 173	21.49 317	81.24 169	48.57 194	56.22 298	79.53 219

TransMVSNet (Re)		64.72 196	64.33 184	65.87 232	75.22 185	38.56 277	74.66 188	75.08 204	58.90 118	61.79 201	82.63 125	51.18 61	78.07 222	43.63 231	55.87 299	80.99 200

test2356		45.61 295	44.66 297	48.47 312	60.15 323	28.08 328	52.44 315	52.83 326	38.01 312	46.13 309	60.98 320	15.08 326	55.54 323	20.43 331	55.85 300	61.78 318

FPMVS		42.18 303	41.11 303	45.39 315	58.03 328	41.01 260	49.50 321	53.81 324	30.07 326	33.71 329	64.03 312	11.69 332	52.08 330	14.01 337	55.11 301	43.09 333

dp		51.89 282	51.60 280	52.77 302	68.44 283	32.45 316	62.36 285	54.57 319	44.16 280	49.31 299	67.91 300	28.87 287	56.61 315	33.89 280	54.89 302	69.24 308

ADS-MVSNet2		51.33 284	48.76 287	59.07 274	66.02 300	44.60 233	50.90 319	59.76 297	36.90 314	50.74 294	66.18 309	26.38 300	63.11 291	27.17 315	54.76 303	69.50 305

ADS-MVSNet		48.48 290	47.77 289	50.63 307	66.02 300	29.92 323	50.90 319	50.87 329	36.90 314	50.74 294	66.18 309	26.38 300	52.47 329	27.17 315	54.76 303	69.50 305

PM-MVS		52.33 280	50.19 283	58.75 276	62.10 313	45.14 228	65.75 267	40.38 340	43.60 283	53.52 284	72.65 279	9.16 339	65.87 285	50.41 178	54.18 305	65.24 313

JIA-IIPM		51.56 283	47.68 291	63.21 253	64.61 305	50.73 159	47.71 324	58.77 300	42.90 289	48.46 301	51.72 329	24.97 308	70.24 267	36.06 275	53.89 306	68.64 309

ambc				65.13 243	63.72 309	37.07 286	47.66 325	78.78 150		54.37 277	71.42 286	11.24 335	80.94 174	45.64 214	53.85 307	77.38 236

DSMNet-mixed		39.30 308	38.72 307	41.03 321	51.22 334	19.66 340	45.53 328	31.35 345	15.83 339	39.80 327	67.42 304	22.19 315	45.13 336	22.43 323	52.69 308	58.31 324

testus		44.59 298	43.87 300	46.76 314	59.85 325	24.65 336	53.86 311	55.82 315	36.26 317	43.97 317	63.42 315	8.39 340	53.14 328	20.70 330	52.52 309	62.51 316

N_pmnet		39.35 307	40.28 304	36.54 324	63.76 308	1.62 350	49.37 322	0.76 352	34.62 320	43.61 318	66.38 308	26.25 302	42.57 339	26.02 321	51.77 310	65.44 312

TDRefinement		53.44 276	50.72 282	61.60 263	64.31 307	46.96 218	70.89 238	65.27 269	41.78 293	44.61 313	77.98 223	11.52 334	66.36 281	28.57 314	51.59 311	71.49 297

Gipuma		34.77 312	31.91 314	43.33 319	62.05 314	37.87 281	20.39 340	67.03 259	23.23 333	18.41 338	25.84 338	4.24 345	62.73 293	14.71 336	51.32 312	29.38 338
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
Anonymous20231211		55.92 264	53.63 273	62.77 257	68.22 285	35.56 301	74.48 191	69.89 232	46.42 258	49.07 300	73.45 277	21.13 318	76.77 237	28.74 312	51.30 313	75.97 250

YYNet1		50.73 285	48.96 284	56.03 288	61.10 318	41.78 254	51.94 317	56.44 310	40.94 300	44.84 311	67.80 302	30.08 279	55.08 325	36.77 267	50.71 314	71.22 298

MDA-MVSNet_test_wron		50.71 286	48.95 285	56.00 289	61.17 317	41.84 253	51.90 318	56.45 309	40.96 299	44.79 312	67.84 301	30.04 280	55.07 326	36.71 269	50.69 315	71.11 301

testpf		44.11 300	45.40 295	40.26 322	60.52 321	27.34 329	33.26 337	54.33 321	45.87 267	41.08 323	60.26 321	16.46 322	59.14 305	46.09 208	50.68 316	34.31 336

SixPastTwentyTwo		61.65 230	58.80 237	70.20 182	75.80 177	47.22 217	75.59 168	69.68 235	54.61 183	54.11 279	79.26 210	27.07 297	82.96 132	43.27 233	49.79 317	80.41 207

1111		44.40 299	45.00 296	42.61 320	57.55 329	17.33 343	53.82 313	57.05 307	40.78 301	44.11 315	66.57 306	13.37 328	45.77 334	22.15 324	49.58 318	64.73 315

test1235678		45.66 294	44.46 299	49.26 309	59.88 324	28.68 326	56.36 306	55.54 317	39.12 310	40.89 324	63.40 316	14.41 327	57.32 312	21.05 328	49.47 319	61.78 318

new-patchmatchnet		47.56 292	47.73 290	47.06 313	58.81 327	9.37 346	48.78 323	59.21 298	43.28 285	44.22 314	68.66 299	25.67 305	57.20 313	31.57 295	49.35 320	74.62 270

LF4IMVS		42.95 301	42.26 301	45.04 316	48.30 337	32.50 315	54.80 308	48.49 332	28.03 328	40.51 326	70.16 294	9.24 338	43.89 337	31.63 293	49.18 321	58.72 323

PMVS	28.69 22	36.22 309	33.29 313	45.02 317	36.82 345	35.98 299	54.68 309	48.74 331	26.31 330	21.02 336	51.61 330	2.88 349	60.10 302	9.99 341	47.58 322	38.99 335
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
pmmvs3		44.92 297	41.95 302	53.86 296	52.58 333	43.55 243	62.11 287	46.90 337	26.05 331	40.63 325	60.19 322	11.08 336	57.91 309	31.83 292	46.15 323	60.11 322

MDA-MVSNet-bldmvs		53.87 274	50.81 281	63.05 255	66.25 296	48.58 203	56.93 304	63.82 278	48.09 245	41.22 322	70.48 292	30.34 276	68.00 274	34.24 279	45.92 324	72.57 285

LP		48.51 289	45.51 294	57.52 284	62.86 310	44.53 236	52.38 316	59.84 296	38.11 311	42.81 320	61.02 319	23.23 312	63.02 292	24.10 322	45.24 325	65.02 314

UnsupCasMVSNet_eth		53.16 279	52.47 277	55.23 290	59.45 326	33.39 314	59.43 297	69.13 243	45.98 263	50.35 298	72.32 281	29.30 284	58.26 308	42.02 244	44.30 326	74.05 275

UnsupCasMVSNet_bld		50.07 287	48.87 286	53.66 297	60.97 320	33.67 312	57.62 302	64.56 273	39.47 308	47.38 303	64.02 314	27.47 293	59.32 304	34.69 278	43.68 327	67.98 310

new_pmnet		34.13 313	34.29 312	33.64 325	52.63 332	18.23 342	44.43 331	33.90 343	22.81 334	30.89 331	53.18 327	10.48 337	35.72 343	20.77 329	39.51 328	46.98 331

K. test v3		60.47 235	57.11 248	70.56 177	73.74 207	48.22 206	75.10 180	62.55 287	58.27 128	53.62 283	76.31 256	27.81 291	81.59 164	47.42 197	39.18 329	81.88 179

LCM-MVSNet		40.30 306	35.88 311	53.57 298	42.24 340	29.15 325	45.21 329	60.53 295	22.23 335	28.02 333	50.98 331	3.72 347	61.78 297	31.22 298	38.76 330	69.78 304

testmv		42.25 302	40.11 305	48.66 310	53.23 331	27.02 330	56.62 305	55.74 316	37.25 313	33.10 330	59.52 323	7.78 341	56.58 317	19.61 332	38.13 331	62.40 317

lessismore_v0				69.91 185	71.42 256	47.80 210		50.90 328		50.39 297	75.56 263	27.43 295	81.33 168	45.91 211	34.10 332	80.59 204

test12356		36.16 310	35.94 310	36.83 323	50.82 335	8.52 347	44.84 330	53.49 325	32.72 323	30.11 332	55.08 326	7.11 343	49.47 331	16.60 334	32.68 333	52.50 328

no-one		40.85 305	36.09 309	55.14 291	48.55 336	38.72 274	42.15 333	62.92 285	34.60 321	23.55 335	49.74 333	12.21 331	66.16 283	26.27 320	24.84 334	60.54 321

PVSNet_0	43.31 20	47.46 293	45.64 293	52.92 301	67.60 288	44.65 232	54.06 310	54.64 318	41.59 296	46.15 308	58.75 324	30.99 272	58.66 306	32.18 285	24.81 335	55.46 327

PMMVS2		27.40 317	25.91 317	31.87 328	39.46 344	6.57 348	31.17 338	28.52 346	23.96 332	20.45 337	48.94 334	4.20 346	37.94 342	16.51 335	19.97 336	51.09 329

MVE	17.77 23	21.41 320	17.77 322	32.34 327	34.34 347	25.44 334	16.11 341	24.11 347	11.19 341	13.22 341	31.92 336	1.58 350	30.95 344	10.47 339	17.03 337	40.62 334
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN		23.77 318	22.73 319	26.90 330	42.02 341	20.67 339	42.66 332	35.70 341	17.43 337	10.28 343	25.05 339	6.42 344	42.39 340	10.28 340	14.71 338	17.63 339

wuykxyi23d		28.12 315	22.54 320	44.87 318	34.97 346	32.11 317	37.96 336	47.31 335	13.32 340	9.29 345	23.72 340	0.45 352	56.58 317	21.85 326	13.98 339	45.93 332

EMVS		22.97 319	21.84 321	26.36 331	40.20 342	19.53 341	41.95 334	34.64 342	17.09 338	9.73 344	22.83 341	7.29 342	42.22 341	9.18 342	13.66 340	17.32 340

PNet_i23d		27.88 316	25.99 316	33.55 326	47.54 338	25.89 332	47.24 326	32.91 344	21.44 336	15.90 339	38.09 335	0.85 351	42.76 338	16.90 333	13.03 341	32.00 337

wuyk23d		13.32 322	12.52 323	15.71 333	47.54 338	26.27 331	31.06 339	1.98 351	4.93 343	5.18 346	1.94 346	0.45 352	18.54 345	6.81 344	12.83 342	2.33 343

ANet_high		41.38 304	37.47 308	53.11 300	39.73 343	24.45 337	56.94 303	69.69 234	47.65 249	26.04 334	52.32 328	12.44 330	62.38 295	21.80 327	10.61 343	72.49 286

tmp_tt		9.43 323	11.14 324	4.30 335	2.38 349	4.40 349	13.62 342	16.08 349	0.39 344	15.89 340	13.06 342	15.80 324	5.54 347	12.63 338	10.46 344	2.95 342

DeepMVS_CX				12.03 334	17.97 348	10.91 345		10.60 350	7.46 342	11.07 342	28.36 337	3.28 348	11.29 346	8.01 343	9.74 345	13.89 341

cdsmvs_eth3d_5k		17.50 321	23.34 318	0.00 338	0.00 352	0.00 352	0.00 343	78.63 153	0.00 347	0.00 349	82.18 135	49.25 87	0.00 348	0.00 347	0.00 346	0.00 347

pcd_1.5k_mvsjas		3.92 327	5.23 328	0.00 338	0.00 352	0.00 352	0.00 343	0.00 353	0.00 347	0.00 349	0.00 349	47.05 121	0.00 348	0.00 347	0.00 346	0.00 347

sosnet-low-res		0.00 328	0.00 329	0.00 338	0.00 352	0.00 352	0.00 343	0.00 353	0.00 347	0.00 349	0.00 349	0.00 355	0.00 348	0.00 347	0.00 346	0.00 347

sosnet		0.00 328	0.00 329	0.00 338	0.00 352	0.00 352	0.00 343	0.00 353	0.00 347	0.00 349	0.00 349	0.00 355	0.00 348	0.00 347	0.00 346	0.00 347

uncertanet		0.00 328	0.00 329	0.00 338	0.00 352	0.00 352	0.00 343	0.00 353	0.00 347	0.00 349	0.00 349	0.00 355	0.00 348	0.00 347	0.00 346	0.00 347

Regformer		0.00 328	0.00 329	0.00 338	0.00 352	0.00 352	0.00 343	0.00 353	0.00 347	0.00 349	0.00 349	0.00 355	0.00 348	0.00 347	0.00 346	0.00 347

.test1245		34.88 311	39.49 306	21.04 332	57.55 329	17.33 343	53.82 313	57.05 307	40.78 301	44.11 315	66.57 306	13.37 328	45.77 334	22.15 324	0.00 346	0.03 345

testmvs		4.52 326	6.03 327	0.01 337	0.01 350	0.00 352	53.86 311	0.00 353	0.01 345	0.04 347	0.27 347	0.00 355	0.00 348	0.04 345	0.00 346	0.03 345

test123		4.73 325	6.30 326	0.02 336	0.01 350	0.01 351	56.36 306	0.00 353	0.01 345	0.04 347	0.21 348	0.01 354	0.00 348	0.03 346	0.00 346	0.04 344

ab-mvs-re		6.49 324	8.65 325	0.00 338	0.00 352	0.00 352	0.00 343	0.00 353	0.00 347	0.00 349	77.89 227	0.00 355	0.00 348	0.00 347	0.00 346	0.00 347

uanet		0.00 328	0.00 329	0.00 338	0.00 352	0.00 352	0.00 343	0.00 353	0.00 347	0.00 349	0.00 349	0.00 355	0.00 348	0.00 347	0.00 346	0.00 347

test_part2					87.58 3	60.47 37				83.42 2

test_full								86.76 3

sam_mvs1												34.74 239

sam_mvs												33.43 254

MTGPA								80.97 98

test_post1							68.67 257				3.64 344	32.39 269	69.49 269	44.17 225

test_post											3.55 345	33.90 249	66.52 280

patchmatchnet-post											64.03 312	34.50 242	74.27 254

MTMP								17.08 348

gm-plane-assit					71.40 257	41.72 256			48.85 237		73.31 278		82.48 152	48.90 191

TEST9					85.58 28	61.59 25	81.62 63	81.26 89	55.65 169	74.93 23	88.81 39	53.70 41	84.68 95

test_8					85.40 31	60.96 32	81.54 66	81.18 92	55.86 163	74.81 26	88.80 41	53.70 41	84.45 100

agg_prior					85.04 35	59.96 41		81.04 95		74.68 27			84.04 107

test_prior4						62.51 17	82.08 57

test_prior				76.69 44	84.20 47	57.27 72		84.88 16					86.43 54			86.38 42

旧先验2							76.08 160		45.32 269	76.55 14			65.56 286	58.75 133

新几何2							76.12 158

无先验							79.66 89	74.30 210	48.40 242				80.78 179	53.62 158		79.03 225

原ACMM2							79.02 95

testdata2													72.18 260	46.95 203

segment_acmp												54.23 34

testdata1							72.65 211		60.50 75

plane_prior7					81.41 71	55.96 94

plane_prior6					81.20 78	56.24 89						45.26 143

plane_prior4											86.10 73

plane_prior3						56.09 91			63.92 30	69.27 96

plane_prior2							84.22 22		64.52 24

plane_prior1					81.27 76

n2								0.00 353

nn								0.00 353

door-mid								47.19 336

test11								83.47 45

door								47.60 334

HQP5-MVS						54.94 107

HQP-NCC					80.66 83		82.31 52		62.10 54	67.85 118

ACMP_Plane					80.66 83		82.31 52		62.10 54	67.85 118

BP-MVS														67.04 58

HQP4-MVS										67.85 118			86.93 39			84.32 117

HQP2-MVS												45.46 137

NP-MVS					80.98 81	56.05 93					85.54 85

MDTV_nov1_ep13_2view						25.89 332	61.22 291		40.10 305	51.10 292		32.97 258		38.49 259		78.61 227

Test By Simon												48.33 106

High-resolution multi-view benchmark