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.

DVP-MVS++		81.67 1	82.40 1	79.47 9	87.24 14	59.15 68	88.18 1	87.15 6	65.04 20	84.26 5	91.86 6	67.01 1	90.84 3	79.48 4	91.38 2	88.42 9

SED-MVS		81.56 2	82.30 2	79.32 12	87.77 4	58.90 77	87.82 7	86.78 14	64.18 35	85.97 1	91.84 8	66.87 3	90.83 5	78.63 15	90.87 5	88.23 14

MSP-MVS		81.06 3	81.40 4	80.02 1	86.21 34	62.73 12	86.09 17	86.83 12	65.51 14	83.81 10	90.51 23	63.71 12	89.23 20	81.51 1	88.44 32	88.09 19
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
DVP-MVS		80.84 4	81.64 3	78.42 36	87.75 7	59.07 72	87.85 5	85.03 38	64.26 32	83.82 8	92.00 3	64.82 8	90.75 8	78.66 13	90.61 11	85.45 115
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
DPE-MVS		80.56 5	80.98 5	79.29 14	87.27 13	60.56 48	85.71 26	86.42 18	63.28 48	83.27 13	91.83 10	64.96 7	90.47 10	76.41 27	89.67 22	86.84 63
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
SMA-MVS		80.28 6	80.39 7	79.95 3	86.60 25	61.95 22	86.33 13	85.75 26	62.49 66	82.20 15	92.28 1	56.53 36	89.70 15	79.85 3	91.48 1	88.19 16
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
APDe-MVS		80.16 7	80.59 6	78.86 28	86.64 23	60.02 53	88.12 3	86.42 18	62.94 55	82.40 14	92.12 2	59.64 19	89.76 14	78.70 11	88.32 36	86.79 66

HPM-MVS++		79.88 8	80.14 8	79.10 20	88.17 1	64.80 1	86.59 12	83.70 66	65.37 15	78.78 25	90.64 19	58.63 24	87.24 53	79.00 10	90.37 14	85.26 124

CNVR-MVS		79.84 9	79.97 9	79.45 10	87.90 2	62.17 20	84.37 37	85.03 38	66.96 5	77.58 32	90.06 40	59.47 21	89.13 22	78.67 12	89.73 20	87.03 58

SteuartSystems-ACMMP		79.48 10	79.31 11	79.98 2	83.01 82	62.18 19	87.60 9	85.83 24	66.69 10	78.03 31	90.98 14	54.26 59	90.06 12	78.42 17	89.02 27	87.69 34
Skip Steuart: Steuart Systems R&D Blog.
ETH3 D test6400		79.14 11	79.32 10	78.61 32	86.34 31	58.11 89	84.65 34	87.66 4	58.56 141	78.87 24	89.54 53	63.67 13	89.57 16	74.60 36	89.98 17	88.14 17

DeepPCF-MVS	69.58 1	79.03 12	79.00 13	79.13 18	84.92 64	60.32 51	83.03 63	85.33 33	62.86 58	80.17 17	90.03 43	61.76 15	88.95 24	74.21 38	88.67 31	88.12 18

SF-MVS		78.82 13	79.22 12	77.60 49	82.88 84	57.83 93	84.99 32	88.13 3	61.86 79	79.16 20	90.75 17	57.96 26	87.09 60	77.08 23	90.18 15	87.87 25

ZNCC-MVS		78.82 13	78.67 17	79.30 13	86.43 30	62.05 21	86.62 11	86.01 23	63.32 47	75.08 44	90.47 27	53.96 63	88.68 27	76.48 26	89.63 24	87.16 55

ACMMP_NAP		78.77 15	78.78 15	78.74 30	85.44 52	61.04 36	83.84 53	85.16 35	62.88 57	78.10 28	91.26 13	52.51 79	88.39 30	79.34 6	90.52 13	86.78 67

ETH3D-3000-0.1		78.58 16	78.91 14	77.61 48	83.06 79	57.86 92	84.14 46	88.31 1	60.37 101	79.14 22	90.35 29	57.76 29	87.00 63	77.16 22	89.90 18	87.97 22

NCCC		78.58 16	78.31 20	79.39 11	87.51 12	62.61 16	85.20 31	84.42 47	66.73 9	74.67 55	89.38 56	55.30 48	89.18 21	74.19 39	87.34 48	86.38 73

DeepC-MVS	69.38 2	78.56 18	78.14 24	79.83 6	83.60 72	61.62 26	84.17 43	86.85 10	63.23 50	73.84 68	90.25 35	57.68 30	89.96 13	74.62 35	89.03 26	87.89 23
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
testtj		78.47 19	78.43 19	78.61 32	86.82 17	60.67 46	86.07 18	85.38 32	62.12 72	78.65 26	90.29 33	55.76 44	89.31 19	73.55 47	87.22 49	85.84 96

TSAR-MVS + MP.		78.44 20	78.28 21	78.90 26	84.96 60	61.41 29	84.03 47	83.82 64	59.34 126	79.37 19	89.76 51	59.84 17	87.62 50	76.69 25	86.74 58	87.68 35
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
xxxxxxxxxxxxxcwj		78.37 21	78.25 23	78.76 29	86.17 36	61.30 31	83.98 49	79.95 148	59.00 129	79.16 20	90.75 17	57.96 26	87.09 60	77.08 23	90.18 15	87.87 25

MP-MVS-pluss		78.35 22	78.46 18	78.03 43	84.96 60	59.52 61	82.93 66	85.39 31	62.15 71	76.41 36	91.51 11	52.47 81	86.78 69	80.66 2	89.64 23	87.80 30
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MP-MVS		78.35 22	78.26 22	78.64 31	86.54 27	63.47 5	86.02 20	83.55 70	63.89 40	73.60 71	90.60 20	54.85 55	86.72 70	77.20 21	88.06 41	85.74 104
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
GST-MVS		78.14 24	77.85 27	78.99 25	86.05 43	61.82 25	85.84 21	85.21 34	63.56 44	74.29 60	90.03 43	52.56 78	88.53 29	74.79 34	88.34 34	86.63 70

ETH3D cwj APD-0.16		78.02 25	78.13 25	77.71 47	82.10 90	58.65 82	82.72 71	87.55 5	58.33 146	78.05 30	90.06 40	58.35 25	87.65 49	76.15 28	89.86 19	86.82 64

APD-MVS		78.02 25	78.04 26	77.98 44	86.44 29	60.81 43	85.52 28	84.36 48	60.61 94	79.05 23	90.30 32	55.54 47	88.32 33	73.48 48	87.03 52	84.83 135
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
HFP-MVS		78.01 27	77.65 28	79.10 20	86.71 20	62.81 10	86.29 14	84.32 49	62.82 59	73.96 63	90.50 24	53.20 74	88.35 31	74.02 41	87.05 50	86.13 87

#test#		77.83 28	77.41 31	79.10 20	86.71 20	62.81 10	85.69 27	84.32 49	61.61 82	73.96 63	90.50 24	53.20 74	88.35 31	73.68 44	87.05 50	86.13 87

ACMMPR		77.71 29	77.23 33	79.16 16	86.75 19	62.93 9	86.29 14	84.24 51	62.82 59	73.55 72	90.56 22	49.80 108	88.24 34	74.02 41	87.03 52	86.32 82

SD-MVS		77.70 30	77.62 29	77.93 45	84.47 67	61.88 24	84.55 35	83.87 62	60.37 101	79.89 18	89.38 56	54.97 52	85.58 103	76.12 29	84.94 68	86.33 80
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
region2R		77.67 31	77.18 34	79.15 17	86.76 18	62.95 8	86.29 14	84.16 53	62.81 61	73.30 75	90.58 21	49.90 106	88.21 35	73.78 43	87.03 52	86.29 85

zzz-MVS		77.61 32	77.36 32	78.35 37	86.08 41	63.57 2	83.37 59	80.97 133	65.13 18	75.77 38	90.88 15	48.63 121	86.66 72	77.23 19	88.17 38	84.81 136

MCST-MVS		77.48 33	77.45 30	77.54 50	86.67 22	58.36 86	83.22 61	86.93 9	56.91 166	74.91 49	88.19 69	59.15 22	87.68 48	73.67 45	87.45 47	86.57 71

HPM-MVS		77.28 34	76.85 36	78.54 34	85.00 59	60.81 43	82.91 67	85.08 36	62.57 64	73.09 82	89.97 46	50.90 102	87.48 51	75.30 30	86.85 56	87.33 52
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
DeepC-MVS_fast	68.24 3	77.25 35	76.63 39	79.12 19	86.15 38	60.86 41	84.71 33	84.85 43	61.98 78	73.06 83	88.88 64	53.72 68	89.06 23	68.27 79	88.04 42	87.42 46
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
XVS		77.17 36	76.56 40	79.00 23	86.32 32	62.62 14	85.83 22	83.92 58	64.55 26	72.17 95	90.01 45	47.95 129	88.01 40	71.55 61	86.74 58	86.37 76

CP-MVS		77.12 37	76.68 38	78.43 35	86.05 43	63.18 7	87.55 10	83.45 73	62.44 68	72.68 88	90.50 24	48.18 127	87.34 52	73.59 46	85.71 64	84.76 140

CSCG		76.92 38	76.75 37	77.41 52	83.96 71	59.60 59	82.95 64	86.50 17	60.78 92	75.27 42	84.83 129	60.76 16	86.56 77	67.86 85	87.87 46	86.06 90

MTAPA		76.90 39	76.42 41	78.35 37	86.08 41	63.57 2	74.92 206	80.97 133	65.13 18	75.77 38	90.88 15	48.63 121	86.66 72	77.23 19	88.17 38	84.81 136

test_prior3		76.89 40	76.96 35	76.69 63	84.20 69	57.27 101	81.75 86	84.88 41	60.37 101	75.01 45	89.06 59	56.22 40	86.43 83	72.19 53	88.96 28	86.38 73

PGM-MVS		76.77 41	76.06 43	78.88 27	86.14 39	62.73 12	82.55 75	83.74 65	61.71 80	72.45 94	90.34 31	48.48 125	88.13 36	72.32 52	86.85 56	85.78 98

mPP-MVS		76.54 42	75.93 46	78.34 39	86.47 28	63.50 4	85.74 25	82.28 96	62.90 56	71.77 98	90.26 34	46.61 152	86.55 78	71.71 59	85.66 65	84.97 132

CANet		76.46 43	75.93 46	78.06 42	81.29 105	57.53 98	82.35 77	83.31 79	67.78 3	70.09 112	86.34 104	54.92 53	88.90 25	72.68 51	84.55 72	87.76 33

CDPH-MVS		76.31 44	75.67 51	78.22 40	85.35 55	59.14 70	81.31 95	84.02 54	56.32 179	74.05 61	88.98 62	53.34 73	87.92 43	69.23 76	88.42 33	87.59 39

train_agg		76.27 45	76.15 42	76.64 66	85.58 49	61.59 27	81.62 89	81.26 124	55.86 189	74.93 47	88.81 65	53.70 69	84.68 124	75.24 32	88.33 35	83.65 178

CS-MVS		76.16 46	76.00 45	76.62 67	80.18 129	54.35 149	84.52 36	83.98 57	63.24 49	73.29 76	87.26 84	55.11 50	86.25 87	71.80 58	84.65 70	89.26 4

SR-MVS		76.13 47	75.70 50	77.40 54	85.87 45	61.20 33	85.52 28	82.19 97	59.99 112	75.10 43	90.35 29	47.66 133	86.52 79	71.64 60	82.99 84	84.47 146

CS-MVS-test		76.07 48	75.85 49	76.73 62	80.33 121	54.44 147	82.95 64	86.18 21	63.54 45	73.32 74	84.50 139	55.21 49	86.44 82	71.92 57	84.65 70	89.32 3

ACMMP		76.02 49	75.33 53	78.07 41	85.20 56	61.91 23	85.49 30	84.44 46	63.04 53	69.80 122	89.74 52	45.43 165	87.16 57	72.01 55	82.87 89	85.14 125
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
agg_prior1		75.94 50	76.01 44	75.72 81	85.04 57	59.96 54	81.44 93	81.04 130	56.14 185	74.68 53	88.90 63	53.91 65	84.04 136	75.01 33	87.92 45	83.16 193

PHI-MVS		75.87 51	75.36 52	77.41 52	80.62 117	55.91 127	84.28 40	85.78 25	56.08 187	73.41 73	86.58 99	50.94 101	88.54 28	70.79 66	89.71 21	87.79 31

DROMVSNet		75.84 52	75.87 48	75.74 80	78.86 156	52.65 170	83.73 54	86.08 22	63.47 46	72.77 87	87.25 85	53.13 76	87.93 42	71.97 56	85.57 66	86.66 69

3Dnovator+	66.72 4	75.84 52	74.57 62	79.66 8	82.40 87	59.92 56	85.83 22	86.32 20	66.92 8	67.80 159	89.24 58	42.03 196	89.38 18	64.07 117	86.50 61	89.69 1

Regformer-2		75.63 54	74.99 56	77.54 50	80.43 119	58.32 87	79.50 121	82.92 87	67.84 1	75.94 37	80.75 218	55.73 45	86.80 67	71.44 63	80.38 116	87.50 42

DPM-MVS		75.47 55	75.00 55	76.88 59	81.38 104	59.16 67	79.94 111	85.71 27	56.59 174	72.46 92	86.76 89	56.89 34	87.86 45	66.36 97	88.91 30	83.64 179

Regformer-1		75.47 55	74.93 58	77.09 57	80.43 119	57.70 96	79.50 121	82.13 98	67.84 1	75.73 40	80.75 218	56.50 37	86.07 88	71.07 65	80.38 116	87.50 42

test1172		75.36 57	74.81 60	77.02 58	85.47 51	60.79 45	83.94 52	81.63 109	59.52 123	74.66 56	90.18 36	44.74 172	85.84 97	70.63 68	82.52 93	84.42 147

APD-MVS_3200maxsize		74.96 58	74.39 65	76.67 65	82.20 89	58.24 88	83.67 55	83.29 80	58.41 143	73.71 69	90.14 37	45.62 158	85.99 92	69.64 72	82.85 90	85.78 98

TSAR-MVS + GP.		74.90 59	74.15 67	77.17 56	82.00 92	58.77 80	81.80 85	78.57 173	58.58 139	74.32 59	84.51 138	55.94 43	87.22 54	67.11 92	84.48 74	85.52 111

casdiffmvs		74.80 60	74.89 59	74.53 109	75.59 231	50.37 204	78.17 139	85.06 37	62.80 62	74.40 58	87.86 76	57.88 28	83.61 147	69.46 75	82.79 91	89.59 2

DELS-MVS		74.76 61	74.46 63	75.65 85	77.84 185	52.25 179	75.59 191	84.17 52	63.76 41	73.15 78	82.79 168	59.58 20	86.80 67	67.24 91	86.04 63	87.89 23
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
test_part1		74.74 62	74.42 64	75.70 83	81.69 97	51.26 189	83.98 49	87.05 8	65.31 16	73.10 81	86.20 106	53.94 64	88.06 38	65.32 108	73.17 199	87.77 32

OPM-MVS		74.73 63	74.25 66	76.19 73	80.81 113	59.01 75	82.60 74	83.64 67	63.74 42	72.52 91	87.49 79	47.18 143	85.88 96	69.47 74	80.78 108	83.66 177
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
canonicalmvs		74.67 64	74.98 57	73.71 128	78.94 155	50.56 202	80.23 106	83.87 62	60.30 107	77.15 33	86.56 100	59.65 18	82.00 183	66.01 101	82.12 96	88.58 8

baseline		74.61 65	74.70 61	74.34 113	75.70 227	49.99 211	77.54 151	84.63 45	62.73 63	73.98 62	87.79 78	57.67 31	83.82 143	69.49 73	82.74 92	89.20 5

SR-MVS-dyc-post		74.57 66	73.90 69	76.58 68	83.49 74	59.87 57	84.29 38	81.36 117	58.07 149	73.14 79	90.07 38	44.74 172	85.84 97	68.20 80	81.76 102	84.03 157

dcpmvs_2		74.55 67	75.23 54	72.48 159	82.34 88	53.34 161	77.87 142	81.46 114	57.80 156	75.49 41	86.81 88	62.22 14	77.75 259	71.09 64	82.02 98	86.34 78

ETV-MVS		74.46 68	73.84 71	76.33 72	79.27 146	55.24 139	79.22 124	85.00 40	64.97 24	72.65 89	79.46 245	53.65 72	87.87 44	67.45 90	82.91 87	85.89 95

abl_6		74.34 69	73.50 74	76.86 60	82.43 86	60.16 52	83.48 58	81.86 103	58.81 133	73.95 65	89.86 48	41.87 199	86.62 74	67.98 84	81.23 107	83.80 170

HQP_MVS		74.31 70	73.73 72	76.06 74	81.41 102	56.31 116	84.22 41	84.01 55	64.52 28	69.27 130	86.10 109	45.26 169	87.21 55	68.16 82	80.58 112	84.65 141

HPM-MVS_fast		74.30 71	73.46 77	76.80 61	84.45 68	59.04 74	83.65 56	81.05 129	60.15 109	70.43 107	89.84 49	41.09 214	85.59 102	67.61 88	82.90 88	85.77 101

Regformer-4		74.25 72	73.48 75	76.57 69	79.75 134	56.54 115	78.54 134	81.49 113	66.93 7	73.90 66	80.30 226	53.84 67	85.98 93	69.76 71	76.84 163	87.17 54

MVS_111021_HR		74.02 73	73.46 77	75.69 84	83.01 82	60.63 47	77.29 158	78.40 184	61.18 87	70.58 106	85.97 113	54.18 61	84.00 140	67.52 89	82.98 86	82.45 205

MG-MVS		73.96 74	73.89 70	74.16 116	85.65 47	49.69 216	81.59 91	81.29 123	61.45 83	71.05 103	88.11 70	51.77 90	87.73 47	61.05 145	83.09 82	85.05 129

Regformer-3		73.89 75	73.28 79	75.71 82	79.75 134	55.48 136	78.54 134	79.93 149	66.58 11	73.62 70	80.30 226	54.87 54	84.54 127	69.09 77	76.84 163	87.10 57

alignmvs		73.86 76	73.99 68	73.45 138	78.20 174	50.50 203	78.57 132	82.43 94	59.40 124	76.57 34	86.71 93	56.42 39	81.23 200	65.84 103	81.79 100	88.62 6

MSLP-MVS++		73.77 77	73.47 76	74.66 102	83.02 81	59.29 66	82.30 82	81.88 102	59.34 126	71.59 101	86.83 87	45.94 156	83.65 146	65.09 111	85.22 67	81.06 229

HQP-MVS		73.45 78	72.80 82	75.40 89	80.66 114	54.94 140	82.31 79	83.90 60	62.10 73	67.85 154	85.54 123	45.46 163	86.93 64	67.04 93	80.35 118	84.32 149

CLD-MVS		73.33 79	72.68 83	75.29 93	78.82 158	53.33 162	78.23 138	84.79 44	61.30 86	70.41 108	81.04 208	52.41 82	87.12 58	64.61 116	82.49 95	85.41 119
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
Effi-MVS+		73.31 80	72.54 84	75.62 86	77.87 184	53.64 154	79.62 119	79.61 154	61.63 81	72.02 97	82.61 173	56.44 38	85.97 94	63.99 120	79.07 138	87.25 53

UA-Net		73.13 81	72.93 81	73.76 124	83.58 73	51.66 187	78.75 127	77.66 194	67.75 4	72.61 90	89.42 54	49.82 107	83.29 152	53.61 196	83.14 81	86.32 82

EPNet		73.09 82	72.16 86	75.90 76	75.95 223	56.28 118	83.05 62	72.39 260	66.53 12	65.27 203	87.00 86	50.40 104	85.47 109	62.48 133	86.32 62	85.94 92
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
nrg030		72.96 83	73.01 80	72.84 151	75.41 234	50.24 205	80.02 109	82.89 90	58.36 145	74.44 57	86.73 91	58.90 23	80.83 210	65.84 103	74.46 178	87.44 45

CPTT-MVS		72.78 84	72.08 88	74.87 98	84.88 65	61.41 29	84.15 44	77.86 190	55.27 202	67.51 164	88.08 72	41.93 198	81.85 185	69.04 78	80.01 122	81.35 222

LPG-MVS_test		72.74 85	71.74 90	75.76 78	80.22 124	57.51 99	82.55 75	83.40 75	61.32 84	66.67 178	87.33 82	39.15 227	86.59 75	67.70 86	77.30 158	83.19 190

h-mvs33		72.71 86	71.49 93	76.40 70	81.99 93	59.58 60	76.92 167	76.74 210	60.40 98	74.81 50	85.95 114	45.54 161	85.76 100	70.41 69	70.61 229	83.86 165

PAPM_NR		72.63 87	71.80 89	75.13 94	81.72 96	53.42 160	79.91 113	83.28 81	59.14 128	66.31 186	85.90 115	51.86 89	86.06 89	57.45 165	80.62 110	85.91 94

VDD-MVS		72.50 88	72.09 87	73.75 126	81.58 98	49.69 216	77.76 146	77.63 195	63.21 51	73.21 77	89.02 61	42.14 195	83.32 151	61.72 140	82.50 94	88.25 13

3Dnovator	64.47 5	72.49 89	71.39 96	75.79 77	77.70 187	58.99 76	80.66 102	83.15 84	62.24 70	65.46 200	86.59 98	42.38 194	85.52 105	59.59 157	84.72 69	82.85 199

MVS_Test		72.45 90	72.46 85	72.42 163	74.88 239	48.50 231	76.28 179	83.14 85	59.40 124	72.46 92	84.68 131	55.66 46	81.12 201	65.98 102	79.66 126	87.63 37

EI-MVSNet-Vis-set		72.42 91	71.59 91	74.91 96	78.47 167	54.02 150	77.05 163	79.33 160	65.03 22	71.68 100	79.35 248	52.75 77	84.89 120	66.46 96	74.23 181	85.83 97

ACMP	63.53 6	72.30 92	71.20 101	75.59 88	80.28 122	57.54 97	82.74 70	82.84 91	60.58 95	65.24 207	86.18 107	39.25 225	86.03 91	66.95 95	76.79 165	83.22 188
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PS-MVSNAJss		72.24 93	71.21 100	75.31 91	78.50 165	55.93 126	81.63 88	82.12 99	56.24 182	70.02 116	85.68 120	47.05 145	84.34 131	65.27 109	74.41 180	85.67 105

Vis-MVSNet		72.18 94	71.37 97	74.61 105	81.29 105	55.41 137	80.90 98	78.28 186	60.73 93	69.23 133	88.09 71	44.36 178	82.65 172	57.68 164	81.75 104	85.77 101
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
API-MVS		72.17 95	71.41 95	74.45 111	81.95 94	57.22 103	84.03 47	80.38 143	59.89 116	68.40 142	82.33 180	49.64 109	87.83 46	51.87 210	84.16 78	78.30 263

EPP-MVSNet		72.16 96	71.31 99	74.71 99	78.68 162	49.70 214	82.10 83	81.65 108	60.40 98	65.94 191	85.84 116	51.74 91	86.37 85	55.93 173	79.55 129	88.07 21

DP-MVS Recon		72.15 97	70.73 107	76.40 70	86.57 26	57.99 91	81.15 97	82.96 86	57.03 163	66.78 174	85.56 121	44.50 176	88.11 37	51.77 212	80.23 121	83.10 194

EI-MVSNet-UG-set		71.92 98	71.06 103	74.52 110	77.98 182	53.56 156	76.62 171	79.16 161	64.40 30	71.18 102	78.95 252	52.19 85	84.66 126	65.47 107	73.57 189	85.32 121

VDDNet		71.81 99	71.33 98	73.26 145	82.80 85	47.60 243	78.74 128	75.27 227	59.59 122	72.94 84	89.40 55	41.51 208	83.91 141	58.75 161	82.99 84	88.26 12

EIA-MVS		71.78 100	70.60 108	75.30 92	79.85 133	53.54 157	77.27 159	83.26 82	57.92 153	66.49 181	79.39 246	52.07 87	86.69 71	60.05 152	79.14 137	85.66 106

LFMVS		71.78 100	71.59 91	72.32 164	83.40 76	46.38 252	79.75 116	71.08 267	64.18 35	72.80 86	88.64 68	42.58 191	83.72 144	57.41 166	84.49 73	86.86 62

PAPR		71.72 102	70.82 106	74.41 112	81.20 109	51.17 190	79.55 120	83.33 78	55.81 192	66.93 173	84.61 134	50.95 100	86.06 89	55.79 176	79.20 135	86.00 91

IS-MVSNet		71.57 103	71.00 104	73.27 144	78.86 156	45.63 265	80.22 107	78.69 170	64.14 38	66.46 182	87.36 81	49.30 112	85.60 101	50.26 221	83.71 80	88.59 7

MAR-MVS		71.51 104	70.15 116	75.60 87	81.84 95	59.39 63	81.38 94	82.90 89	54.90 214	68.08 151	78.70 253	47.73 131	85.51 106	51.68 214	84.17 77	81.88 214
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
MVSFormer		71.50 105	70.38 113	74.88 97	78.76 159	57.15 108	82.79 68	78.48 177	51.26 253	69.49 125	83.22 163	43.99 181	83.24 153	66.06 99	79.37 130	84.23 152

PVSNet_Blended_VisFu		71.45 106	70.39 112	74.65 103	82.01 91	58.82 79	79.93 112	80.35 144	55.09 207	65.82 196	82.16 186	49.17 115	82.64 173	60.34 150	78.62 146	82.50 204

OMC-MVS		71.40 107	70.60 108	73.78 122	76.60 213	53.15 164	79.74 117	79.78 150	58.37 144	68.75 137	86.45 102	45.43 165	80.60 215	62.58 131	77.73 152	87.58 40

UniMVSNet_NR-MVSNet		71.11 108	71.00 104	71.44 178	79.20 148	44.13 276	76.02 187	82.60 93	66.48 13	68.20 145	84.60 135	56.82 35	82.82 168	54.62 186	70.43 231	87.36 51

hse-mvs2		71.04 109	69.86 119	74.60 106	79.58 139	57.12 110	73.96 222	75.25 228	60.40 98	74.81 50	81.95 190	45.54 161	82.90 161	70.41 69	66.83 279	83.77 171

GeoE		71.01 110	70.15 116	73.60 134	79.57 140	52.17 180	78.93 126	78.12 187	58.02 151	67.76 162	83.87 151	52.36 83	82.72 170	56.90 168	75.79 171	85.92 93

PCF-MVS	61.88 8	70.95 111	69.49 125	75.35 90	77.63 190	55.71 129	76.04 186	81.81 105	50.30 261	69.66 123	85.40 126	52.51 79	84.89 120	51.82 211	80.24 120	85.45 115
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
114514_t		70.83 112	69.56 123	74.64 104	86.21 34	54.63 145	82.34 78	81.81 105	48.22 280	63.01 233	85.83 117	40.92 215	87.10 59	57.91 163	79.79 123	82.18 208

FIs		70.82 113	71.43 94	68.98 226	78.33 171	38.14 321	76.96 165	83.59 69	61.02 88	67.33 166	86.73 91	55.07 51	81.64 189	54.61 188	79.22 134	87.14 56

ACMM	61.98 7	70.80 114	69.73 121	74.02 117	80.59 118	58.59 83	82.68 72	82.02 101	55.46 200	67.18 169	84.39 141	38.51 232	83.17 155	60.65 147	76.10 169	80.30 240
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
diffmvs		70.69 115	70.43 111	71.46 177	69.45 315	48.95 226	72.93 239	78.46 179	57.27 160	71.69 99	83.97 150	51.48 93	77.92 256	70.70 67	77.95 151	87.53 41

UniMVSNet (Re)		70.63 116	70.20 114	71.89 167	78.55 164	45.29 267	75.94 188	82.92 87	63.68 43	68.16 148	83.59 158	53.89 66	83.49 150	53.97 191	71.12 224	86.89 61

xiu_mvs_v2_base		70.52 117	69.75 120	72.84 151	81.21 108	55.63 132	75.11 200	78.92 164	54.92 213	69.96 119	79.68 240	47.00 149	82.09 182	61.60 142	79.37 130	80.81 233

PS-MVSNAJ		70.51 118	69.70 122	72.93 149	81.52 99	55.79 128	74.92 206	79.00 163	55.04 212	69.88 120	78.66 254	47.05 145	82.19 180	61.61 141	79.58 127	80.83 232

v2v482		70.50 119	69.45 127	73.66 130	72.62 271	50.03 210	77.58 148	80.51 141	59.90 113	69.52 124	82.14 187	47.53 136	84.88 122	65.07 112	70.17 237	86.09 89

mvs-test1		70.44 120	68.19 147	77.18 55	76.10 220	63.22 6	80.59 103	76.06 217	59.83 117	66.32 185	79.87 234	41.56 205	85.53 104	60.60 148	72.77 204	82.80 200

v1144		70.42 121	69.31 128	73.76 124	73.22 259	50.64 199	77.83 144	81.43 115	58.58 139	69.40 128	81.16 205	47.53 136	85.29 114	64.01 119	70.64 227	85.34 120

TranMVSNet+NR-MVSNet		70.36 122	70.10 118	71.17 189	78.64 163	42.97 287	76.53 173	81.16 128	66.95 6	68.53 141	85.42 125	51.61 92	83.07 156	52.32 204	69.70 248	87.46 44

v8		70.33 123	69.28 129	73.49 136	73.15 261	50.22 206	78.62 131	80.78 137	60.79 91	66.45 183	82.11 188	49.35 111	84.98 117	63.58 125	68.71 263	85.28 122

Fast-Effi-MVS+		70.28 124	69.12 132	73.73 127	78.50 165	51.50 188	75.01 203	79.46 158	56.16 184	68.59 138	79.55 243	53.97 62	84.05 135	53.34 198	77.53 154	85.65 107

X-MVStestdata		70.21 125	67.28 168	79.00 23	86.32 32	62.62 14	85.83 22	83.92 58	64.55 26	72.17 95	6.49 373	47.95 129	88.01 40	71.55 61	86.74 58	86.37 76

v10		70.21 125	69.02 133	73.81 121	73.51 258	50.92 194	78.74 128	81.39 116	60.05 111	66.39 184	81.83 193	47.58 135	85.41 112	62.80 130	68.86 262	85.09 128

QAPM		70.05 127	68.81 136	73.78 122	76.54 215	53.43 159	83.23 60	83.48 71	52.89 234	65.90 193	86.29 105	41.55 207	86.49 81	51.01 216	78.40 148	81.42 218

DU-MVS		70.01 128	69.53 124	71.44 178	78.05 180	44.13 276	75.01 203	81.51 112	64.37 31	68.20 145	84.52 136	49.12 118	82.82 168	54.62 186	70.43 231	87.37 49

AdaColmap		69.99 129	68.66 139	73.97 119	84.94 62	57.83 93	82.63 73	78.71 169	56.28 181	64.34 220	84.14 144	41.57 204	87.06 62	46.45 248	78.88 139	77.02 280

v1192		69.97 130	68.68 138	73.85 120	73.19 260	50.94 192	77.68 147	81.36 117	57.51 158	68.95 136	80.85 215	45.28 168	85.33 113	62.97 129	70.37 233	85.27 123

Anonymous20240529		69.91 131	69.02 133	72.56 157	80.19 127	47.65 241	77.56 150	80.99 132	55.45 201	69.88 120	86.76 89	39.24 226	82.18 181	54.04 190	77.10 160	87.85 27

patch_mono-2		69.85 132	71.09 102	66.16 258	79.11 152	54.80 144	71.97 254	74.31 243	53.50 228	70.90 104	84.17 143	57.63 32	63.31 329	66.17 98	82.02 98	80.38 239

FC-MVSNet-test		69.80 133	70.58 110	67.46 242	77.61 195	34.73 346	76.05 185	83.19 83	60.84 90	65.88 194	86.46 101	54.52 58	80.76 214	52.52 203	78.12 149	86.91 60

v144192		69.71 134	68.51 140	73.33 143	73.10 262	50.13 208	77.54 151	80.64 138	56.65 168	68.57 140	80.55 220	46.87 150	84.96 119	62.98 128	69.66 249	84.89 134

test_yl		69.69 135	69.13 130	71.36 182	78.37 169	45.74 261	74.71 210	80.20 145	57.91 154	70.01 117	83.83 152	42.44 192	82.87 164	54.97 182	79.72 124	85.48 113

DCV-MVSNet		69.69 135	69.13 130	71.36 182	78.37 169	45.74 261	74.71 210	80.20 145	57.91 154	70.01 117	83.83 152	42.44 192	82.87 164	54.97 182	79.72 124	85.48 113

VNet		69.68 137	70.19 115	68.16 236	79.73 137	41.63 300	70.53 275	77.38 200	60.37 101	70.69 105	86.63 96	51.08 98	77.09 268	53.61 196	81.69 106	85.75 103

jason		69.65 138	68.39 145	73.43 140	78.27 173	56.88 112	77.12 161	73.71 251	46.53 298	69.34 129	83.22 163	43.37 185	79.18 235	64.77 113	79.20 135	84.23 152
jason: jason.
Effi-MVS+-dtu		69.64 139	67.53 158	75.95 75	76.10 220	62.29 18	80.20 108	76.06 217	59.83 117	65.26 206	77.09 274	41.56 205	84.02 139	60.60 148	71.09 225	81.53 217

lupinMVS		69.57 140	68.28 146	73.44 139	78.76 159	57.15 108	76.57 172	73.29 254	46.19 301	69.49 125	82.18 183	43.99 181	79.23 234	64.66 114	79.37 130	83.93 160

NR-MVSNet		69.54 141	68.85 135	71.59 176	78.05 180	43.81 280	74.20 218	80.86 136	65.18 17	62.76 235	84.52 136	52.35 84	83.59 148	50.96 217	70.78 226	87.37 49

MVS_111021_LR		69.50 142	68.78 137	71.65 174	78.38 168	59.33 64	74.82 208	70.11 275	58.08 148	67.83 158	84.68 131	41.96 197	76.34 276	65.62 106	77.54 153	79.30 257

v1921920		69.47 143	68.17 148	73.36 142	73.06 263	50.10 209	77.39 154	80.56 139	56.58 175	68.59 138	80.37 222	44.72 174	84.98 117	62.47 134	69.82 244	85.00 130

test_djsdf		69.45 144	67.74 151	74.58 107	74.57 246	54.92 142	82.79 68	78.48 177	51.26 253	65.41 201	83.49 161	38.37 234	83.24 153	66.06 99	69.25 255	85.56 110

Anonymous20231211		69.28 145	68.47 142	71.73 171	80.28 122	47.18 247	79.98 110	82.37 95	54.61 216	67.24 167	84.01 148	39.43 223	82.41 178	55.45 180	72.83 203	85.62 109

EI-MVSNet		69.27 146	68.44 144	71.73 171	74.47 247	49.39 221	75.20 198	78.45 180	59.60 119	69.16 134	76.51 284	51.29 94	82.50 175	59.86 156	71.45 222	83.30 185

v1240		69.24 147	67.91 150	73.25 146	73.02 265	49.82 212	77.21 160	80.54 140	56.43 177	68.34 144	80.51 221	43.33 186	84.99 115	62.03 138	69.77 247	84.95 133

IterMVS-LS		69.22 148	68.48 141	71.43 180	74.44 249	49.40 220	76.23 180	77.55 196	59.60 119	65.85 195	81.59 199	51.28 95	81.58 192	59.87 155	69.90 243	83.30 185
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
VPA-MVSNet		69.02 149	69.47 126	67.69 240	77.42 198	41.00 304	74.04 220	79.68 152	60.06 110	69.26 132	84.81 130	51.06 99	77.58 262	54.44 189	74.43 179	84.48 145

v7n		69.01 150	67.36 165	73.98 118	72.51 274	52.65 170	78.54 134	81.30 122	60.26 108	62.67 237	81.62 196	43.61 183	84.49 128	57.01 167	68.70 264	84.79 138

OpenMVS	61.03 9	68.85 151	67.56 155	72.70 155	74.26 253	53.99 151	81.21 96	81.34 121	52.70 235	62.75 236	85.55 122	38.86 230	84.14 134	48.41 236	83.01 83	79.97 246

XVG-OURS-SEG-HR		68.81 152	67.47 161	72.82 153	74.40 250	56.87 113	70.59 274	79.04 162	54.77 215	66.99 171	86.01 112	39.57 222	78.21 252	62.54 132	73.33 194	83.37 183

BH-RMVSNet		68.81 152	67.42 162	72.97 148	80.11 130	52.53 174	74.26 217	76.29 213	58.48 142	68.38 143	84.20 142	42.59 190	83.83 142	46.53 247	75.91 170	82.56 201

UGNet		68.81 152	67.39 163	73.06 147	78.33 171	54.47 146	79.77 115	75.40 226	60.45 97	63.22 230	84.40 140	32.71 292	80.91 209	51.71 213	80.56 114	83.81 166
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
RRT_MVS		68.77 155	66.71 179	74.95 95	75.93 224	58.55 84	80.50 104	75.84 219	56.09 186	68.17 147	83.74 155	28.50 320	82.98 158	65.67 105	65.91 285	83.33 184

XVG-OURS		68.76 156	67.37 164	72.90 150	74.32 252	57.22 103	70.09 281	78.81 166	55.24 203	67.79 160	85.81 119	36.54 255	78.28 251	62.04 137	75.74 172	83.19 190

V42		68.65 157	67.35 166	72.56 157	68.93 320	50.18 207	72.90 240	79.47 157	56.92 165	69.45 127	80.26 228	46.29 154	82.99 157	64.07 117	67.82 272	84.53 143

PVSNet_Blended		68.59 158	67.72 152	71.19 187	77.03 205	50.57 200	72.51 246	81.52 110	51.91 242	64.22 225	77.77 270	49.13 116	82.87 164	55.82 174	79.58 127	80.14 243

xiu_mvs_v1_base_debu		68.58 159	67.28 168	72.48 159	78.19 175	57.19 105	75.28 195	75.09 233	51.61 244	70.04 113	81.41 201	32.79 288	79.02 242	63.81 121	77.31 155	81.22 224

xiu_mvs_v1_base		68.58 159	67.28 168	72.48 159	78.19 175	57.19 105	75.28 195	75.09 233	51.61 244	70.04 113	81.41 201	32.79 288	79.02 242	63.81 121	77.31 155	81.22 224

xiu_mvs_v1_base_debi		68.58 159	67.28 168	72.48 159	78.19 175	57.19 105	75.28 195	75.09 233	51.61 244	70.04 113	81.41 201	32.79 288	79.02 242	63.81 121	77.31 155	81.22 224

PVSNet_BlendedMVS		68.56 162	67.72 152	71.07 192	77.03 205	50.57 200	74.50 214	81.52 110	53.66 227	64.22 225	79.72 239	49.13 116	82.87 164	55.82 174	73.92 184	79.77 252

1121		68.53 163	67.16 174	72.63 156	85.64 48	61.14 34	73.95 223	66.46 301	44.61 313	70.28 110	86.68 94	41.42 209	80.78 212	53.62 194	81.79 100	75.97 288

WR-MVS		68.47 164	68.47 142	68.44 233	80.20 126	39.84 307	73.75 231	76.07 216	64.68 25	68.11 150	83.63 157	50.39 105	79.14 240	49.78 222	69.66 249	86.34 78

AUN-MVS		68.45 165	66.41 187	74.57 108	79.53 141	57.08 111	73.93 226	75.23 229	54.44 221	66.69 177	81.85 192	37.10 250	82.89 162	62.07 136	66.84 278	83.75 172

c3_l		68.33 166	67.56 155	70.62 199	70.87 294	46.21 256	74.47 215	78.80 167	56.22 183	66.19 187	78.53 259	51.88 88	81.40 194	62.08 135	69.04 258	84.25 151

BH-untuned		68.27 167	67.29 167	71.21 186	79.74 136	53.22 163	76.06 184	77.46 199	57.19 161	66.10 188	81.61 197	45.37 167	83.50 149	45.42 262	76.68 167	76.91 284

jajsoiax		68.25 168	66.45 183	73.66 130	75.62 229	55.49 135	80.82 99	78.51 176	52.33 239	64.33 221	84.11 145	28.28 322	81.81 187	63.48 126	70.62 228	83.67 175

v148		68.24 169	67.19 173	71.40 181	70.43 300	47.77 240	75.76 190	77.03 205	58.91 131	67.36 165	80.10 231	48.60 124	81.89 184	60.01 153	66.52 282	84.53 143

CANet_DTU		68.18 170	67.71 154	69.59 217	74.83 240	46.24 255	78.66 130	76.85 207	59.60 119	63.45 229	82.09 189	35.25 262	77.41 264	59.88 154	78.76 143	85.14 125

mvs_tets		68.18 170	66.36 189	73.63 133	75.61 230	55.35 138	80.77 100	78.56 174	52.48 238	64.27 223	84.10 146	27.45 328	81.84 186	63.45 127	70.56 230	83.69 174

RRT_test8_iter05		68.17 172	66.86 178	72.07 166	75.81 225	46.33 253	76.41 176	81.81 105	56.43 177	66.52 180	81.30 204	31.90 300	84.25 132	63.77 124	67.83 271	85.64 108

miper_ehance_all_eth		68.03 173	67.24 172	70.40 203	70.54 298	46.21 256	73.98 221	78.68 171	55.07 210	66.05 189	77.80 268	52.16 86	81.31 197	61.53 144	69.32 252	83.67 175

mvs_anonymous		68.03 173	67.51 159	69.59 217	72.08 279	44.57 274	71.99 253	75.23 229	51.67 243	67.06 170	82.57 174	54.68 56	77.94 255	56.56 169	75.71 173	86.26 86

ET-MVSNet_ETH3D		67.96 175	65.72 201	74.68 101	76.67 211	55.62 133	75.11 200	74.74 237	52.91 233	60.03 262	80.12 230	33.68 278	82.64 173	61.86 139	76.34 168	85.78 98

thisisatest0530		67.92 176	65.78 200	74.33 114	76.29 217	51.03 191	76.89 168	74.25 245	53.67 226	65.59 198	81.76 194	35.15 263	85.50 107	55.94 172	72.47 209	86.47 72

PAPM		67.92 176	66.69 180	71.63 175	78.09 178	49.02 224	77.09 162	81.24 126	51.04 255	60.91 257	83.98 149	47.71 132	84.99 115	40.81 294	79.32 133	80.90 231

tttt0517		67.83 178	65.66 202	74.33 114	76.69 210	50.82 196	77.86 143	73.99 248	54.54 219	64.64 218	82.53 176	35.06 264	85.50 107	55.71 177	69.91 242	86.67 68

ECVR-MVS		67.72 179	67.51 159	68.35 234	79.46 142	36.29 340	74.79 209	66.93 298	58.72 135	67.19 168	88.05 73	36.10 256	81.38 195	52.07 207	84.25 75	87.39 47

eth_miper_zixun_eth		67.63 180	66.28 193	71.67 173	71.60 286	48.33 233	73.68 232	77.88 189	55.80 193	65.91 192	78.62 257	47.35 142	82.88 163	59.45 158	66.25 283	83.81 166

UniMVSNet_ETH3D		67.60 181	67.07 176	69.18 225	77.39 199	42.29 291	74.18 219	75.59 223	60.37 101	66.77 175	86.06 111	37.64 241	78.93 247	52.16 206	73.49 191	86.32 82

VPNet		67.52 182	68.11 149	65.74 267	79.18 149	36.80 332	72.17 251	72.83 257	62.04 76	67.79 160	85.83 117	48.88 120	76.60 273	51.30 215	72.97 202	83.81 166

cl22		67.47 183	66.45 183	70.54 201	69.85 311	46.49 251	73.85 229	77.35 201	55.07 210	65.51 199	77.92 264	47.64 134	81.10 202	61.58 143	69.32 252	84.01 159

Fast-Effi-MVS+-dtu		67.37 184	65.33 207	73.48 137	72.94 266	57.78 95	77.47 153	76.88 206	57.60 157	61.97 248	76.85 278	39.31 224	80.49 219	54.72 185	70.28 236	82.17 210

MVS		67.37 184	66.33 190	70.51 202	75.46 233	50.94 192	73.95 223	81.85 104	41.57 337	62.54 241	78.57 258	47.98 128	85.47 109	52.97 201	82.05 97	75.14 297

test1111		67.21 186	67.14 175	67.42 243	79.24 147	34.76 345	73.89 228	65.65 305	58.71 137	66.96 172	87.95 75	36.09 257	80.53 216	52.03 208	83.79 79	86.97 59

GBi-Net		67.21 186	66.55 181	69.19 222	77.63 190	43.33 283	77.31 155	77.83 191	56.62 171	65.04 211	82.70 169	41.85 200	80.33 221	47.18 242	72.76 205	83.92 161

test1		67.21 186	66.55 181	69.19 222	77.63 190	43.33 283	77.31 155	77.83 191	56.62 171	65.04 211	82.70 169	41.85 200	80.33 221	47.18 242	72.76 205	83.92 161

cl____		67.18 189	66.26 194	69.94 210	70.20 303	45.74 261	73.30 234	76.83 208	55.10 205	65.27 203	79.57 242	47.39 140	80.53 216	59.41 160	69.22 256	83.53 181

DIV-MVS_self_test		67.18 189	66.26 194	69.94 210	70.20 303	45.74 261	73.29 235	76.83 208	55.10 205	65.27 203	79.58 241	47.38 141	80.53 216	59.43 159	69.22 256	83.54 180

MVSTER		67.16 191	65.58 204	71.88 168	70.37 302	49.70 214	70.25 280	78.45 180	51.52 247	69.16 134	80.37 222	38.45 233	82.50 175	60.19 151	71.46 221	83.44 182

miper_enhance_ethall		67.11 192	66.09 196	70.17 207	69.21 317	45.98 259	72.85 241	78.41 183	51.38 250	65.65 197	75.98 293	51.17 97	81.25 198	60.82 146	69.32 252	83.29 187

Baseline_NR-MVSNet		67.05 193	67.56 155	65.50 269	75.65 228	37.70 325	75.42 193	74.65 239	59.90 113	68.14 149	83.15 166	49.12 118	77.20 266	52.23 205	69.78 245	81.60 216

WR-MVS_H		67.02 194	66.92 177	67.33 246	77.95 183	37.75 324	77.57 149	82.11 100	62.03 77	62.65 238	82.48 177	50.57 103	79.46 230	42.91 281	64.01 298	84.79 138

anonymousdsp		67.00 195	64.82 212	73.57 135	70.09 306	56.13 121	76.35 177	77.35 201	48.43 278	64.99 214	80.84 216	33.01 285	80.34 220	64.66 114	67.64 274	84.23 152

FMVSNet2		66.93 196	66.31 192	68.79 229	77.63 190	42.98 286	76.11 182	77.47 197	56.62 171	65.22 209	82.17 185	41.85 200	80.18 224	47.05 245	72.72 208	83.20 189

BH-w/o		66.85 197	65.83 199	69.90 213	79.29 144	52.46 176	74.66 212	76.65 211	54.51 220	64.85 215	78.12 260	45.59 160	82.95 160	43.26 277	75.54 174	74.27 310

Anonymous202405211		66.84 198	65.99 197	69.40 221	80.19 127	42.21 292	71.11 268	71.31 266	58.80 134	67.90 152	86.39 103	29.83 312	79.65 227	49.60 228	78.78 142	86.33 80

CDS-MVSNet		66.80 199	65.37 205	71.10 191	78.98 154	53.13 166	73.27 236	71.07 268	52.15 241	64.72 216	80.23 229	43.56 184	77.10 267	45.48 260	78.88 139	83.05 195
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		66.78 200	65.27 208	71.33 185	79.16 151	53.67 153	73.84 230	69.59 280	52.32 240	65.28 202	81.72 195	44.49 177	77.40 265	42.32 285	78.66 145	82.92 196

FMVSNet1		66.70 201	65.87 198	69.19 222	77.49 197	43.33 283	77.31 155	77.83 191	56.45 176	64.60 219	82.70 169	38.08 239	80.33 221	46.08 251	72.31 213	83.92 161

ab-mvs		66.65 202	66.42 186	67.37 244	76.17 219	41.73 297	70.41 278	76.14 215	53.99 223	65.98 190	83.51 160	49.48 110	76.24 277	48.60 234	73.46 192	84.14 155

PEN-MVS		66.60 203	66.45 183	67.04 247	77.11 203	36.56 334	77.03 164	80.42 142	62.95 54	62.51 243	84.03 147	46.69 151	79.07 241	44.22 266	63.08 307	85.51 112

TAPA-MVS	59.36 10	66.60 203	65.20 209	70.81 195	76.63 212	48.75 228	76.52 174	80.04 147	50.64 259	65.24 207	84.93 128	39.15 227	78.54 248	36.77 313	76.88 162	85.14 125
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TR-MVS		66.59 205	65.07 210	71.17 189	79.18 149	49.63 218	73.48 233	75.20 231	52.95 232	67.90 152	80.33 225	39.81 220	83.68 145	43.20 278	73.56 190	80.20 241

CP-MVSNet		66.49 206	66.41 187	66.72 249	77.67 189	36.33 337	76.83 170	79.52 156	62.45 67	62.54 241	83.47 162	46.32 153	78.37 249	45.47 261	63.43 304	85.45 115

PS-CasMVS		66.42 207	66.32 191	66.70 251	77.60 196	36.30 339	76.94 166	79.61 154	62.36 69	62.43 245	83.66 156	45.69 157	78.37 249	45.35 263	63.26 305	85.42 118

FMVSNet3		66.32 208	65.61 203	68.46 232	76.48 216	42.34 290	74.98 205	77.15 204	55.83 191	65.04 211	81.16 205	39.91 218	80.14 225	47.18 242	72.76 205	82.90 198

ACMH+	57.40 11	66.12 209	64.06 215	72.30 165	77.79 186	52.83 168	80.39 105	78.03 188	57.30 159	57.47 288	82.55 175	27.68 326	84.17 133	45.54 258	69.78 245	79.90 247

cascas		65.98 210	63.42 226	73.64 132	77.26 201	52.58 173	72.26 250	77.21 203	48.56 275	61.21 256	74.60 305	32.57 296	85.82 99	50.38 220	76.75 166	82.52 203

thisisatest0515		65.83 211	63.50 225	72.82 153	73.75 256	49.50 219	71.32 262	73.12 256	49.39 268	63.82 227	76.50 286	34.95 266	84.84 123	53.20 200	75.49 175	84.13 156

DP-MVS		65.68 212	63.66 223	71.75 170	84.93 63	56.87 113	80.74 101	73.16 255	53.06 231	59.09 274	82.35 179	36.79 254	85.94 95	32.82 333	69.96 241	72.45 325

HyFIR lowres test		65.67 213	63.01 230	73.67 129	79.97 132	55.65 131	69.07 289	75.52 224	42.68 331	63.53 228	77.95 262	40.43 216	81.64 189	46.01 252	71.91 216	83.73 173

DTE-MVSNet		65.58 214	65.34 206	66.31 254	76.06 222	34.79 343	76.43 175	79.38 159	62.55 65	61.66 252	83.83 152	45.60 159	79.15 239	41.64 293	60.88 321	85.00 130

bset_n11_16_dypcd		65.57 215	63.69 222	71.19 187	70.84 296	51.79 186	71.37 260	70.48 273	53.33 230	65.19 210	76.41 287	31.46 302	81.76 188	65.12 110	69.04 258	80.01 245

GA-MVS		65.53 216	63.70 221	71.02 193	70.87 294	48.10 235	70.48 276	74.40 241	56.69 167	64.70 217	76.77 279	33.66 279	81.10 202	55.42 181	70.32 235	83.87 164

CNLPA		65.43 217	64.02 216	69.68 215	78.73 161	58.07 90	77.82 145	70.71 271	51.49 248	61.57 254	83.58 159	38.23 237	70.82 297	43.90 271	70.10 239	80.16 242

MVP-Stereo		65.41 218	63.80 220	70.22 204	77.62 194	55.53 134	76.30 178	78.53 175	50.59 260	56.47 294	78.65 255	39.84 219	82.68 171	44.10 270	72.12 215	72.44 326
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
IB-MVS	56.42 12	65.40 219	62.73 234	73.40 141	74.89 238	52.78 169	73.09 238	75.13 232	55.69 195	58.48 282	73.73 311	32.86 287	86.32 86	50.63 218	70.11 238	81.10 228
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
test2506		65.33 220	64.61 213	67.50 241	79.46 142	34.19 349	74.43 216	51.92 356	58.72 135	66.75 176	88.05 73	25.99 338	80.92 208	51.94 209	84.25 75	87.39 47

pm-mvs1		65.24 221	64.97 211	66.04 262	72.38 275	39.40 312	72.62 244	75.63 222	55.53 199	62.35 247	83.18 165	47.45 138	76.47 274	49.06 231	66.54 281	82.24 207

ACMH	55.70 15	65.20 222	63.57 224	70.07 208	78.07 179	52.01 185	79.48 123	79.69 151	55.75 194	56.59 293	80.98 210	27.12 330	80.94 206	42.90 282	71.58 220	77.25 278
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PLC	56.13 14	65.09 223	63.21 228	70.72 198	81.04 111	54.87 143	78.57 132	77.47 197	48.51 276	55.71 297	81.89 191	33.71 277	79.71 226	41.66 291	70.37 233	77.58 272
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CHOSEN 1792x2688		65.08 224	62.84 232	71.82 169	81.49 101	56.26 119	66.32 300	74.20 246	40.53 342	63.16 232	78.65 255	41.30 210	77.80 258	45.80 254	74.09 182	81.40 219

TransMVSNet (Re)		64.72 225	64.33 214	65.87 266	75.22 236	38.56 318	74.66 212	75.08 236	58.90 132	61.79 251	82.63 172	51.18 96	78.07 254	43.63 274	55.87 337	80.99 230

EG-PatchMatch MVS		64.71 226	62.87 231	70.22 204	77.68 188	53.48 158	77.99 141	78.82 165	53.37 229	56.03 296	77.41 273	24.75 345	84.04 136	46.37 249	73.42 193	73.14 317

LS3D		64.71 226	62.50 236	71.34 184	79.72 138	55.71 129	79.82 114	74.72 238	48.50 277	56.62 292	84.62 133	33.59 280	82.34 179	29.65 351	75.23 176	75.97 288

1314		64.61 228	63.21 228	68.80 228	71.87 284	47.46 244	73.95 223	78.39 185	42.88 330	59.97 263	76.60 283	38.11 238	79.39 232	54.84 184	72.32 212	79.55 253

HY-MVS	56.14 13	64.55 229	63.89 217	66.55 252	74.73 243	41.02 302	69.96 282	74.43 240	49.29 269	61.66 252	80.92 212	47.43 139	76.68 272	44.91 265	71.69 218	81.94 212

XVG-ACMP-BASELINE		64.36 230	62.23 239	70.74 197	72.35 276	52.45 177	70.80 273	78.45 180	53.84 225	59.87 265	81.10 207	16.24 359	79.32 233	55.64 179	71.76 217	80.47 236

CostFormer		64.04 231	62.51 235	68.61 231	71.88 283	45.77 260	71.30 263	70.60 272	47.55 288	64.31 222	76.61 282	41.63 203	79.62 229	49.74 224	69.00 260	80.42 237

1112_ss		64.00 232	63.36 227	65.93 264	79.28 145	42.58 289	71.35 261	72.36 261	46.41 299	60.55 259	77.89 266	46.27 155	73.28 287	46.18 250	69.97 240	81.92 213

baseline1		63.81 233	63.87 219	63.62 281	76.29 217	36.36 335	71.78 257	67.29 295	56.05 188	64.23 224	82.95 167	47.11 144	74.41 284	47.30 241	61.85 315	80.10 244

pmmvs6		63.69 234	62.82 233	66.27 256	70.63 297	39.27 313	73.13 237	75.47 225	52.69 236	59.75 268	82.30 181	39.71 221	77.03 269	47.40 240	64.35 297	82.53 202

Vis-MVSNet (Re-imp)		63.69 234	63.88 218	63.14 286	74.75 242	31.04 360	71.16 266	63.64 318	56.32 179	59.80 267	84.99 127	44.51 175	75.46 279	39.12 302	80.62 110	82.92 196

baseline2		63.42 236	61.26 250	69.89 214	72.55 273	47.62 242	71.54 258	68.38 290	50.11 262	54.82 308	75.55 297	43.06 188	80.96 205	48.13 237	67.16 277	81.11 227

thres400		63.31 237	62.18 240	66.72 249	76.85 208	39.62 309	71.96 255	69.44 282	56.63 169	62.61 239	79.83 235	37.18 246	79.17 236	31.84 337	73.25 196	81.36 220

thres600view7		63.30 238	62.27 238	66.41 253	77.18 202	38.87 315	72.35 248	69.11 286	56.98 164	62.37 246	80.96 211	37.01 252	79.00 245	31.43 344	73.05 201	81.36 220

thres100view900		63.28 239	62.41 237	65.89 265	77.31 200	38.66 317	72.65 242	69.11 286	57.07 162	62.45 244	81.03 209	37.01 252	79.17 236	31.84 337	73.25 196	79.83 249

test_0402		63.25 240	61.01 253	69.96 209	80.00 131	54.37 148	76.86 169	72.02 262	54.58 218	58.71 277	80.79 217	35.00 265	84.36 130	26.41 359	64.71 294	71.15 337

tfpn200view9		63.18 241	62.18 240	66.21 257	76.85 208	39.62 309	71.96 255	69.44 282	56.63 169	62.61 239	79.83 235	37.18 246	79.17 236	31.84 337	73.25 196	79.83 249

LTVRE_ROB	55.42 16	63.15 242	61.23 251	68.92 227	76.57 214	47.80 238	59.92 331	76.39 212	54.35 222	58.67 278	82.46 178	29.44 315	81.49 193	42.12 287	71.14 223	77.46 273
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
F-COLMAP		63.05 243	60.87 256	69.58 219	76.99 207	53.63 155	78.12 140	76.16 214	47.97 284	52.41 327	81.61 197	27.87 324	78.11 253	40.07 297	66.66 280	77.00 281

IterMVS		62.79 244	61.27 249	67.35 245	69.37 316	52.04 184	71.17 265	68.24 291	52.63 237	59.82 266	76.91 277	37.32 245	72.36 290	52.80 202	63.19 306	77.66 271
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IterMVS-SCA-FT		62.49 245	61.52 246	65.40 271	71.99 281	50.80 197	71.15 267	69.63 279	45.71 307	60.61 258	77.93 263	37.45 243	65.99 322	55.67 178	63.50 303	79.42 255

tfpnnormal		62.47 246	61.63 245	64.99 275	74.81 241	39.01 314	71.22 264	73.72 250	55.22 204	60.21 260	80.09 232	41.26 213	76.98 270	30.02 349	68.09 268	78.97 260

MS-PatchMatch		62.42 247	61.46 247	65.31 273	75.21 237	52.10 181	72.05 252	74.05 247	46.41 299	57.42 289	74.36 306	34.35 272	77.57 263	45.62 257	73.67 186	66.26 350

Test_1112_low_res		62.32 248	61.77 243	64.00 280	79.08 153	39.53 311	68.17 291	70.17 274	43.25 326	59.03 275	79.90 233	44.08 179	71.24 296	43.79 273	68.42 266	81.25 223

D2MVS		62.30 249	60.29 258	68.34 235	66.46 335	48.42 232	65.70 303	73.42 252	47.71 286	58.16 284	75.02 301	30.51 305	77.71 260	53.96 192	71.68 219	78.90 261

thres200		62.20 250	61.16 252	65.34 272	75.38 235	39.99 306	69.60 284	69.29 284	55.64 198	61.87 250	76.99 275	37.07 251	78.96 246	31.28 345	73.28 195	77.06 279

tpm2		62.07 251	60.10 259	67.99 237	72.79 268	43.86 279	71.05 270	66.85 299	43.14 328	62.77 234	75.39 299	38.32 235	80.80 211	41.69 290	68.88 261	79.32 256

miper_lstm_enhance		62.03 252	60.88 255	65.49 270	66.71 333	46.25 254	56.29 343	75.70 221	50.68 257	61.27 255	75.48 298	40.21 217	68.03 311	56.31 171	65.25 291	82.18 208

DWT-MVSNet_test		61.90 253	59.93 260	67.83 238	71.98 282	46.09 258	71.03 271	69.71 276	50.09 263	58.51 281	70.62 327	30.21 309	77.63 261	49.28 229	67.91 269	79.78 251

EPNet_dtu		61.90 253	61.97 242	61.68 295	72.89 267	39.78 308	75.85 189	65.62 306	55.09 207	54.56 312	79.36 247	37.59 242	67.02 316	39.80 300	76.95 161	78.25 264
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
LCM-MVSNet-Re		61.88 255	61.35 248	63.46 282	74.58 245	31.48 359	61.42 325	58.14 339	58.71 137	53.02 326	79.55 243	43.07 187	76.80 271	45.69 255	77.96 150	82.11 211

MSDG		61.81 256	59.23 262	69.55 220	72.64 270	52.63 172	70.45 277	75.81 220	51.38 250	53.70 319	76.11 289	29.52 313	81.08 204	37.70 308	65.79 288	74.93 302

SixPastTwentyTwo		61.65 257	58.80 265	70.20 206	75.80 226	47.22 246	75.59 191	69.68 278	54.61 216	54.11 316	79.26 249	27.07 331	82.96 159	43.27 276	49.79 352	80.41 238

CL-MVSNet_self_test		61.53 258	60.94 254	63.30 284	68.95 319	36.93 331	67.60 295	72.80 258	55.67 196	59.95 264	76.63 280	45.01 171	72.22 293	39.74 301	62.09 314	80.74 234

RPMNet		61.53 258	58.42 268	70.86 194	69.96 309	52.07 182	65.31 309	81.36 117	43.20 327	59.36 270	70.15 333	35.37 261	85.47 109	36.42 320	64.65 295	75.06 298

pmmvs4		61.48 260	59.39 261	67.76 239	71.57 287	53.86 152	71.42 259	65.34 308	44.20 318	59.46 269	77.92 264	35.90 258	74.71 282	43.87 272	64.87 293	74.71 306

OurMVSNet-221017-0		61.37 261	58.63 267	69.61 216	72.05 280	48.06 236	73.93 226	72.51 259	47.23 294	54.74 309	80.92 212	21.49 354	81.24 199	48.57 235	56.22 336	79.53 254

COLMAP_ROB	52.97 17	61.27 262	58.81 264	68.64 230	74.63 244	52.51 175	78.42 137	73.30 253	49.92 266	50.96 332	81.51 200	23.06 347	79.40 231	31.63 341	65.85 286	74.01 313
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
XXY-MVS		60.68 263	61.67 244	57.70 317	70.43 300	38.45 319	64.19 315	66.47 300	48.05 283	63.22 230	80.86 214	49.28 113	60.47 338	45.25 264	67.28 276	74.19 311

SCA		60.49 264	58.38 269	66.80 248	74.14 255	48.06 236	63.35 317	63.23 321	49.13 271	59.33 273	72.10 318	37.45 243	74.27 285	44.17 267	62.57 310	78.05 267

K. test v3		60.47 265	57.11 277	70.56 200	73.74 257	48.22 234	75.10 202	62.55 325	58.27 147	53.62 321	76.31 288	27.81 325	81.59 191	47.42 239	39.18 363	81.88 214

OpenMVS_ROB	52.78 18	60.03 266	58.14 272	65.69 268	70.47 299	44.82 269	75.33 194	70.86 270	45.04 309	56.06 295	76.00 290	26.89 333	79.65 227	35.36 325	67.29 275	72.60 322

CR-MVSNet		59.91 267	57.90 274	65.96 263	69.96 309	52.07 182	65.31 309	63.15 322	42.48 332	59.36 270	74.84 302	35.83 259	70.75 298	45.50 259	64.65 295	75.06 298

PatchmatchNet		59.84 268	58.24 270	64.65 277	73.05 264	46.70 250	69.42 286	62.18 327	47.55 288	58.88 276	71.96 320	34.49 270	69.16 306	42.99 280	63.60 302	78.07 266
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
WTY-MVS		59.75 269	60.39 257	57.85 315	72.32 277	37.83 323	61.05 329	64.18 316	45.95 306	61.91 249	79.11 251	47.01 148	60.88 337	42.50 284	69.49 251	74.83 303

CVMVSNet		59.63 270	59.14 263	61.08 300	74.47 247	38.84 316	75.20 198	68.74 288	31.15 357	58.24 283	76.51 284	32.39 297	68.58 309	49.77 223	65.84 287	75.81 291

tpm cat1		59.25 271	56.95 280	66.15 259	72.19 278	46.96 248	68.09 292	65.76 304	40.03 345	57.81 286	70.56 328	38.32 235	74.51 283	38.26 306	61.50 318	77.00 281

pmmvs-eth3d		58.81 272	56.31 285	66.30 255	67.61 327	52.42 178	72.30 249	64.76 312	43.55 324	54.94 307	74.19 308	28.95 317	72.60 289	43.31 275	57.21 332	73.88 314

MVS_0304		58.51 273	57.36 276	61.96 294	70.04 307	41.83 295	69.40 287	65.46 307	50.73 256	53.30 325	74.06 309	22.65 348	70.18 304	42.16 286	68.44 265	73.86 315

tpmvs		58.47 274	56.95 280	63.03 288	70.20 303	41.21 301	67.90 294	67.23 296	49.62 267	54.73 310	70.84 325	34.14 273	76.24 277	36.64 317	61.29 319	71.64 333

PVSNet	50.76 19	58.40 275	57.39 275	61.42 297	75.53 232	44.04 278	61.43 324	63.45 319	47.04 296	56.91 290	73.61 312	27.00 332	64.76 325	39.12 302	72.40 210	75.47 295

tpmrst		58.24 276	58.70 266	56.84 318	66.97 330	34.32 348	69.57 285	61.14 331	47.17 295	58.58 280	71.60 321	41.28 212	60.41 339	49.20 230	62.84 308	75.78 292

Patchmatch-RL test		58.16 277	55.49 289	66.15 259	67.92 326	48.89 227	60.66 330	51.07 358	47.86 285	59.36 270	62.71 355	34.02 275	72.27 292	56.41 170	59.40 326	77.30 275

test-LLR		58.15 278	58.13 273	58.22 311	68.57 321	44.80 270	65.46 306	57.92 340	50.08 264	55.44 300	69.82 335	32.62 293	57.44 348	49.66 226	73.62 187	72.41 327

ppachtmachnet_test		58.06 279	55.38 290	66.10 261	69.51 313	48.99 225	68.01 293	66.13 303	44.50 315	54.05 317	70.74 326	32.09 299	72.34 291	36.68 316	56.71 335	76.99 283

gg-mvs-nofinetune		57.86 280	56.43 284	62.18 292	72.62 271	35.35 342	66.57 297	56.33 346	50.65 258	57.64 287	57.10 358	30.65 304	76.36 275	37.38 310	78.88 139	74.82 304

CMPMVS	42.80 21	57.81 281	55.97 286	63.32 283	60.98 359	47.38 245	64.66 313	69.50 281	32.06 356	46.83 347	77.80 268	29.50 314	71.36 295	48.68 233	73.75 185	71.21 336
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MIMVSNet		57.35 282	57.07 278	58.22 311	74.21 254	37.18 326	62.46 320	60.88 332	48.88 273	55.29 303	75.99 292	31.68 301	62.04 334	31.87 336	72.35 211	75.43 296

tpm		57.34 283	58.16 271	54.86 325	71.80 285	34.77 344	67.47 296	56.04 349	48.20 281	60.10 261	76.92 276	37.17 248	53.41 361	40.76 295	65.01 292	76.40 287

Patchmtry		57.16 284	56.47 283	59.23 304	69.17 318	34.58 347	62.98 318	63.15 322	44.53 314	56.83 291	74.84 302	35.83 259	68.71 308	40.03 298	60.91 320	74.39 309

AllTest		57.08 285	54.65 294	64.39 278	71.44 288	49.03 222	69.92 283	67.30 293	45.97 304	47.16 345	79.77 237	17.47 356	67.56 313	33.65 330	59.16 327	76.57 285

our_test_3		56.49 286	54.42 296	62.68 290	69.51 313	45.48 266	66.08 301	61.49 330	44.11 321	50.73 336	69.60 337	33.05 284	68.15 310	38.38 305	56.86 333	74.40 308

pmmvs5		56.47 287	55.68 288	58.86 308	61.41 356	36.71 333	66.37 299	62.75 324	40.38 343	53.70 319	76.62 281	34.56 268	67.05 315	40.02 299	65.27 290	72.83 320

test-mter		56.42 288	55.82 287	58.22 311	68.57 321	44.80 270	65.46 306	57.92 340	39.94 346	55.44 300	69.82 335	21.92 351	57.44 348	49.66 226	73.62 187	72.41 327

USDC		56.35 289	54.24 300	62.69 289	64.74 343	40.31 305	65.05 311	73.83 249	43.93 322	47.58 343	77.71 271	15.36 361	75.05 281	38.19 307	61.81 316	72.70 321

PatchMatch-RL		56.25 290	54.55 295	61.32 299	77.06 204	56.07 123	65.57 305	54.10 354	44.13 320	53.49 324	71.27 324	25.20 342	66.78 317	36.52 319	63.66 301	61.12 353

sss		56.17 291	56.57 282	54.96 324	66.93 331	36.32 338	57.94 337	61.69 329	41.67 335	58.64 279	75.32 300	38.72 231	56.25 354	42.04 288	66.19 284	72.31 330

FMVSNet5		55.86 292	54.93 292	58.66 310	71.05 293	36.35 336	64.18 316	62.48 326	46.76 297	50.66 337	74.73 304	25.80 339	64.04 327	33.11 332	65.57 289	75.59 294

RPSCF		55.80 293	54.22 301	60.53 301	65.13 342	42.91 288	64.30 314	57.62 342	36.84 351	58.05 285	82.28 182	28.01 323	56.24 355	37.14 311	58.61 329	82.44 206

EU-MVSNet		55.61 294	54.41 297	59.19 306	65.41 341	33.42 353	72.44 247	71.91 263	28.81 359	51.27 330	73.87 310	24.76 344	69.08 307	43.04 279	58.20 330	75.06 298

Anonymous20240521		55.30 295	54.41 297	57.96 314	60.92 361	41.73 297	71.09 269	71.06 269	41.18 338	48.65 341	73.31 313	16.93 358	59.25 343	42.54 283	64.01 298	72.90 319

TESTMET0.1,1		55.28 296	54.90 293	56.42 319	66.56 334	43.67 281	65.46 306	56.27 347	39.18 348	53.83 318	67.44 344	24.21 346	55.46 358	48.04 238	73.11 200	70.13 342

KD-MVS_self_test		55.22 297	53.89 303	59.21 305	57.80 366	27.47 366	57.75 338	74.32 242	47.38 290	50.90 333	70.00 334	28.45 321	70.30 302	40.44 296	57.92 331	79.87 248

MIMVSNet1		55.17 298	54.31 299	57.77 316	70.03 308	32.01 357	65.68 304	64.81 311	49.19 270	46.75 348	76.00 290	25.53 341	64.04 327	28.65 353	62.13 313	77.26 277

Anonymous20231206		55.10 299	55.30 291	54.48 327	69.81 312	33.94 351	62.91 319	62.13 328	41.08 339	55.18 304	75.65 295	32.75 291	56.59 353	30.32 348	67.86 270	72.91 318

TinyColmap		54.14 300	51.72 310	61.40 298	66.84 332	41.97 293	66.52 298	68.51 289	44.81 310	42.69 357	75.77 294	11.66 365	72.94 288	31.96 335	56.77 334	69.27 346

EPMVS		53.96 301	53.69 304	54.79 326	66.12 338	31.96 358	62.34 322	49.05 361	44.42 317	55.54 298	71.33 323	30.22 308	56.70 351	41.65 292	62.54 311	75.71 293

PMMVS		53.96 301	53.26 307	56.04 320	62.60 352	50.92 194	61.17 328	56.09 348	32.81 355	53.51 323	66.84 346	34.04 274	59.93 341	44.14 269	68.18 267	57.27 358

test20.03		53.87 303	54.02 302	53.41 332	61.47 355	28.11 365	61.30 326	59.21 335	51.34 252	52.09 328	77.43 272	33.29 283	58.55 345	29.76 350	60.27 324	73.58 316

MDA-MVSNet-bldmvs		53.87 303	50.81 314	63.05 287	66.25 336	48.58 230	56.93 341	63.82 317	48.09 282	41.22 358	70.48 331	30.34 307	68.00 312	34.24 328	45.92 357	72.57 323

KD-MVS_2432*1600		53.45 305	51.50 312	59.30 302	62.82 349	37.14 327	55.33 344	71.79 264	47.34 292	55.09 305	70.52 329	21.91 352	70.45 300	35.72 323	42.97 360	70.31 340

miper_refine_blended		53.45 305	51.50 312	59.30 302	62.82 349	37.14 327	55.33 344	71.79 264	47.34 292	55.09 305	70.52 329	21.91 352	70.45 300	35.72 323	42.97 360	70.31 340

TDRefinement		53.44 307	50.72 315	61.60 296	64.31 346	46.96 248	70.89 272	65.27 310	41.78 333	44.61 353	77.98 261	11.52 366	66.36 320	28.57 354	51.59 347	71.49 334

test0.0.03 1		53.32 308	53.59 305	52.50 336	62.81 351	29.45 363	59.51 332	54.11 353	50.08 264	54.40 314	74.31 307	32.62 293	55.92 356	30.50 347	63.95 300	72.15 332

PatchT		53.17 309	53.44 306	52.33 337	68.29 325	25.34 370	58.21 336	54.41 352	44.46 316	54.56 312	69.05 338	33.32 282	60.94 336	36.93 312	61.76 317	70.73 339

UnsupCasMVSNet_eth		53.16 310	52.47 308	55.23 323	59.45 363	33.39 354	59.43 333	69.13 285	45.98 303	50.35 339	72.32 317	29.30 316	58.26 346	42.02 289	44.30 358	74.05 312

PM-MVS		52.33 311	50.19 316	58.75 309	62.10 353	45.14 268	65.75 302	40.38 371	43.60 323	53.52 322	72.65 315	9.16 371	65.87 323	50.41 219	54.18 342	65.24 352

testgi		51.90 312	52.37 309	50.51 341	60.39 362	23.55 372	58.42 335	58.15 338	49.03 272	51.83 329	79.21 250	22.39 349	55.59 357	29.24 352	62.64 309	72.40 329

dp		51.89 313	51.60 311	52.77 335	68.44 324	32.45 356	62.36 321	54.57 351	44.16 319	49.31 340	67.91 340	28.87 319	56.61 352	33.89 329	54.89 339	69.24 347

JIA-IIPM		51.56 314	47.68 324	63.21 285	64.61 344	50.73 198	47.71 357	58.77 337	42.90 329	48.46 342	51.72 361	24.97 343	70.24 303	36.06 322	53.89 343	68.64 348

ADS-MVSNet2		51.33 315	48.76 320	59.07 307	66.02 339	44.60 273	50.90 352	59.76 334	36.90 349	50.74 334	66.18 348	26.38 334	63.11 330	27.17 355	54.76 340	69.50 344

YYNet1		50.73 316	48.96 317	56.03 321	61.10 358	41.78 296	51.94 350	56.44 345	40.94 341	44.84 351	67.80 342	30.08 310	55.08 359	36.77 313	50.71 349	71.22 335

MDA-MVSNet_test_wron		50.71 317	48.95 318	56.00 322	61.17 357	41.84 294	51.90 351	56.45 344	40.96 340	44.79 352	67.84 341	30.04 311	55.07 360	36.71 315	50.69 350	71.11 338

UnsupCasMVSNet_bld		50.07 318	48.87 319	53.66 330	60.97 360	33.67 352	57.62 339	64.56 314	39.47 347	47.38 344	64.02 353	27.47 327	59.32 342	34.69 327	43.68 359	67.98 349

Patchmatch-test		49.08 319	48.28 321	51.50 339	64.40 345	30.85 361	45.68 359	48.46 364	35.60 352	46.10 350	72.10 318	34.47 271	46.37 365	27.08 357	60.65 323	77.27 276

ADS-MVSNet		48.48 320	47.77 322	50.63 340	66.02 339	29.92 362	50.90 352	50.87 360	36.90 349	50.74 334	66.18 348	26.38 334	52.47 362	27.17 355	54.76 340	69.50 344

CHOSEN 280x420		47.83 321	46.36 325	52.24 338	67.37 329	49.78 213	38.91 365	43.11 369	35.00 353	43.27 356	63.30 354	28.95 317	49.19 364	36.53 318	60.80 322	57.76 357

new-patchmatchnet		47.56 322	47.73 323	47.06 343	58.81 364	9.37 378	48.78 356	59.21 335	43.28 325	44.22 354	68.66 339	25.67 340	57.20 350	31.57 343	49.35 353	74.62 307

PVSNet_0	43.31 20	47.46 323	45.64 326	52.92 334	67.60 328	44.65 272	54.06 348	54.64 350	41.59 336	46.15 349	58.75 357	30.99 303	58.66 344	32.18 334	24.81 366	55.46 359

MVS-HIRNet		45.52 324	44.48 327	48.65 342	68.49 323	34.05 350	59.41 334	44.50 368	27.03 361	37.96 362	50.47 364	26.16 337	64.10 326	26.74 358	59.52 325	47.82 362

pmmvs3		44.92 325	41.95 329	53.86 329	52.58 368	43.55 282	62.11 323	46.90 367	26.05 363	40.63 359	60.19 356	11.08 368	57.91 347	31.83 340	46.15 356	60.11 354

LF4IMVS		42.95 326	42.26 328	45.04 345	48.30 370	32.50 355	54.80 346	48.49 363	28.03 360	40.51 360	70.16 332	9.24 370	43.89 367	31.63 341	49.18 354	58.72 355

EGC-MVSNET		42.47 327	38.48 333	54.46 328	74.33 251	48.73 229	70.33 279	51.10 357	0.03 376	0.18 377	67.78 343	13.28 362	66.49 319	18.91 364	50.36 351	48.15 361

FPMVS		42.18 328	41.11 330	45.39 344	58.03 365	41.01 303	49.50 354	53.81 355	30.07 358	33.71 363	64.03 351	11.69 364	52.08 363	14.01 368	55.11 338	43.09 364

ANet_high		41.38 329	37.47 334	53.11 333	39.73 375	24.45 371	56.94 340	69.69 277	47.65 287	26.04 366	52.32 360	12.44 363	62.38 333	21.80 362	10.61 373	72.49 324

LCM-MVSNet		40.30 330	35.88 335	53.57 331	42.24 372	29.15 364	45.21 361	60.53 333	22.23 367	28.02 365	50.98 363	3.72 377	61.78 335	31.22 346	38.76 364	69.78 343

N_pmnet		39.35 331	40.28 331	36.54 349	63.76 347	1.62 382	49.37 355	0.76 382	34.62 354	43.61 355	66.38 347	26.25 336	42.57 368	26.02 360	51.77 346	65.44 351

DSMNet-mixed		39.30 332	38.72 332	41.03 348	51.22 369	19.66 374	45.53 360	31.35 375	15.83 370	39.80 361	67.42 345	22.19 350	45.13 366	22.43 361	52.69 345	58.31 356

PMVS	28.69 22	36.22 333	33.29 337	45.02 346	36.82 377	35.98 341	54.68 347	48.74 362	26.31 362	21.02 367	51.61 362	2.88 379	60.10 340	9.99 372	47.58 355	38.99 367
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
Gipuma		34.77 334	31.91 338	43.33 347	62.05 354	37.87 322	20.39 368	67.03 297	23.23 365	18.41 369	25.84 369	4.24 375	62.73 331	14.71 367	51.32 348	29.38 368
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
new_pmnet		34.13 335	34.29 336	33.64 350	52.63 367	18.23 376	44.43 362	33.90 374	22.81 366	30.89 364	53.18 359	10.48 369	35.72 372	20.77 363	39.51 362	46.98 363

PMMVS2		27.40 336	25.91 339	31.87 352	39.46 376	6.57 379	31.17 366	28.52 376	23.96 364	20.45 368	48.94 365	4.20 376	37.94 371	16.51 365	19.97 368	51.09 360

E-PMN		23.77 337	22.73 341	26.90 353	42.02 373	20.67 373	42.66 363	35.70 372	17.43 368	10.28 374	25.05 370	6.42 373	42.39 369	10.28 371	14.71 370	17.63 369

EMVS		22.97 338	21.84 342	26.36 354	40.20 374	19.53 375	41.95 364	34.64 373	17.09 369	9.73 375	22.83 371	7.29 372	42.22 370	9.18 373	13.66 371	17.32 370

MVE	17.77 23	21.41 339	17.77 344	32.34 351	34.34 378	25.44 369	16.11 369	24.11 377	11.19 371	13.22 371	31.92 367	1.58 380	30.95 373	10.47 370	17.03 369	40.62 366
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
test_method		19.68 340	18.10 343	24.41 355	13.68 380	3.11 381	12.06 371	42.37 370	2.00 374	11.97 372	36.38 366	5.77 374	29.35 374	15.06 366	23.65 367	40.76 365

cdsmvs_eth3d_5k		17.50 341	23.34 340	0.00 361	0.00 384	0.00 384	0.00 372	78.63 172	0.00 379	0.00 380	82.18 183	49.25 114	0.00 378	0.00 378	0.00 376	0.00 376

wuyk23d		13.32 342	12.52 345	15.71 356	47.54 371	26.27 367	31.06 367	1.98 381	4.93 373	5.18 376	1.94 376	0.45 381	18.54 375	6.81 375	12.83 372	2.33 373

tmp_tt		9.43 343	11.14 346	4.30 358	2.38 381	4.40 380	13.62 370	16.08 379	0.39 375	15.89 370	13.06 372	15.80 360	5.54 377	12.63 369	10.46 374	2.95 372

ab-mvs-re		6.49 344	8.65 347	0.00 361	0.00 384	0.00 384	0.00 372	0.00 383	0.00 379	0.00 380	77.89 266	0.00 383	0.00 378	0.00 378	0.00 376	0.00 376

test123		4.73 345	6.30 348	0.02 359	0.01 382	0.01 383	56.36 342	0.00 383	0.01 377	0.04 378	0.21 378	0.01 382	0.00 378	0.03 377	0.00 376	0.04 374

testmvs		4.52 346	6.03 349	0.01 360	0.01 382	0.00 384	53.86 349	0.00 383	0.01 377	0.04 378	0.27 377	0.00 383	0.00 378	0.04 376	0.00 376	0.03 375

pcd_1.5k_mvsjas		3.92 347	5.23 350	0.00 361	0.00 384	0.00 384	0.00 372	0.00 383	0.00 379	0.00 380	0.00 379	47.05 145	0.00 378	0.00 378	0.00 376	0.00 376

test_blank		0.00 348	0.00 351	0.00 361	0.00 384	0.00 384	0.00 372	0.00 383	0.00 379	0.00 380	0.00 379	0.00 383	0.00 378	0.00 378	0.00 376	0.00 376

uanet_test		0.00 348	0.00 351	0.00 361	0.00 384	0.00 384	0.00 372	0.00 383	0.00 379	0.00 380	0.00 379	0.00 383	0.00 378	0.00 378	0.00 376	0.00 376

DCPMVS		0.00 348	0.00 351	0.00 361	0.00 384	0.00 384	0.00 372	0.00 383	0.00 379	0.00 380	0.00 379	0.00 383	0.00 378	0.00 378	0.00 376	0.00 376

sosnet-low-res		0.00 348	0.00 351	0.00 361	0.00 384	0.00 384	0.00 372	0.00 383	0.00 379	0.00 380	0.00 379	0.00 383	0.00 378	0.00 378	0.00 376	0.00 376

sosnet		0.00 348	0.00 351	0.00 361	0.00 384	0.00 384	0.00 372	0.00 383	0.00 379	0.00 380	0.00 379	0.00 383	0.00 378	0.00 378	0.00 376	0.00 376

uncertanet		0.00 348	0.00 351	0.00 361	0.00 384	0.00 384	0.00 372	0.00 383	0.00 379	0.00 380	0.00 379	0.00 383	0.00 378	0.00 378	0.00 376	0.00 376

Regformer		0.00 348	0.00 351	0.00 361	0.00 384	0.00 384	0.00 372	0.00 383	0.00 379	0.00 380	0.00 379	0.00 383	0.00 378	0.00 378	0.00 376	0.00 376

uanet		0.00 348	0.00 351	0.00 361	0.00 384	0.00 384	0.00 372	0.00 383	0.00 379	0.00 380	0.00 379	0.00 383	0.00 378	0.00 378	0.00 376	0.00 376

FOURS1					86.12 40	60.82 42	88.18 1	83.61 68	60.87 89	81.50 16

MSC_two_6792asdad				79.95 3	87.24 14	61.04 36		85.62 28					90.96 1	79.31 7	90.65 8	87.85 27

PC_three_1452									55.09 207	84.46 4	89.84 49	66.68 5	89.41 17	74.24 37	91.38 2	88.42 9

No_MVS				79.95 3	87.24 14	61.04 36		85.62 28					90.96 1	79.31 7	90.65 8	87.85 27

test_one_0601					87.58 9	59.30 65		86.84 11	65.01 23	83.80 11	91.86 6	64.03 11

eth-test2					0.00 384

eth-test					0.00 384

ZD-MVS					86.64 23	60.38 50		82.70 92	57.95 152	78.10 28	90.06 40	56.12 42	88.84 26	74.05 40	87.00 55

RE-MVS-def			73.71 73		83.49 74	59.87 57	84.29 38	81.36 117	58.07 149	73.14 79	90.07 38	43.06 188		68.20 80	81.76 102	84.03 157

IU-MVS					87.77 4	59.15 68		85.53 30	53.93 224	84.64 3				79.07 9	90.87 5	88.37 11

OPU-MVS				79.83 6	87.54 11	60.93 40	87.82 7				89.89 47	67.01 1	90.33 11	73.16 49	91.15 4	88.23 14

test_241102_TWO								86.73 16	64.18 35	84.26 5	91.84 8	65.19 6	90.83 5	78.63 15	90.70 7	87.65 36

test_241102_ONE					87.77 4	58.90 77		86.78 14	64.20 34	85.97 1	91.34 12	66.87 3	90.78 7

9.14			78.75 16		83.10 78		84.15 44	88.26 2	59.90 113	78.57 27	90.36 28	57.51 33	86.86 66	77.39 18	89.52 25

save fliter					86.17 36	61.30 31	83.98 49	79.66 153	59.00 129

test_0728_THIRD									65.04 20	83.82 8	92.00 3	64.69 10	90.75 8	79.48 4	90.63 10	88.09 19

test_0728_SECOND				79.19 15	87.82 3	59.11 71	87.85 5	87.15 6					90.84 3	78.66 13	90.61 11	87.62 38

test0726					87.75 7	59.07 72	87.86 4	86.83 12	64.26 32	84.19 7	91.92 5	64.82 8

GSMVS																78.05 267

test_part2					87.58 9	60.47 49				83.42 12

sam_mvs1												34.74 267				78.05 267

sam_mvs												33.43 281

ambc				65.13 274	63.72 348	37.07 329	47.66 358	78.78 168		54.37 315	71.42 322	11.24 367	80.94 206	45.64 256	53.85 344	77.38 274

MTGPA								80.97 133

test_post1							68.67 290				3.64 374	32.39 297	69.49 305	44.17 267

test_post											3.55 375	33.90 276	66.52 318

patchmatchnet-post											64.03 351	34.50 269	74.27 285

GG-mvs-BLEND				62.34 291	71.36 292	37.04 330	69.20 288	57.33 343		54.73 310	65.48 350	30.37 306	77.82 257	34.82 326	74.93 177	72.17 331

MTMP							86.03 19	17.08 378

gm-plane-assit					71.40 291	41.72 299			48.85 274		73.31 313		82.48 177	48.90 232

test9_res														75.28 31	88.31 37	83.81 166

TEST9					85.58 49	61.59 27	81.62 89	81.26 124	55.65 197	74.93 47	88.81 65	53.70 69	84.68 124

test_8					85.40 53	60.96 39	81.54 92	81.18 127	55.86 189	74.81 50	88.80 67	53.70 69	84.45 129

agg_prior2														73.09 50	87.93 44	84.33 148

agg_prior					85.04 57	59.96 54		81.04 130		74.68 53			84.04 136

TestCases				64.39 278	71.44 288	49.03 222		67.30 293	45.97 304	47.16 345	79.77 237	17.47 356	67.56 313	33.65 330	59.16 327	76.57 285

test_prior4						62.51 17	82.08 84

test_prior2							81.75 86		60.37 101	75.01 45	89.06 59	56.22 40		72.19 53	88.96 28

test_prior				76.69 63	84.20 69	57.27 101		84.88 41					86.43 83			86.38 73

旧先验2							76.08 183		45.32 308	76.55 35			65.56 324	58.75 161

新几何2							76.12 181

新几何1				70.76 196	85.66 46	61.13 35		66.43 302	44.68 312	70.29 109	86.64 95	41.29 211	75.23 280	49.72 225	81.75 104	75.93 290

旧先验1					83.04 80	53.15 164		67.52 292			87.85 77	44.08 179			80.76 109	78.03 270

无先验							79.66 118	74.30 244	48.40 279				80.78 212	53.62 194		79.03 259

原ACMM2							79.02 125

原ACMM1				74.69 100	85.39 54	59.40 62		83.42 74	51.47 249	70.27 111	86.61 97	48.61 123	86.51 80	53.85 193	87.96 43	78.16 265

test222					83.14 77	58.68 81	72.57 245	63.45 319	41.78 333	67.56 163	86.12 108	37.13 249			78.73 144	74.98 301

testdata2													72.18 294	46.95 246

segment_acmp												54.23 60

testdata				64.66 276	81.52 99	52.93 167		65.29 309	46.09 302	73.88 67	87.46 80	38.08 239	66.26 321	53.31 199	78.48 147	74.78 305

testdata1							72.65 242		60.50 96

test12				77.76 46	84.52 66	58.41 85		83.36 77		72.93 85		54.61 57	88.05 39		88.12 40	86.81 65

plane_prior7					81.41 102	55.96 125

plane_prior6					81.20 109	56.24 120						45.26 169

plane_prior5								84.01 55					87.21 55	68.16 82	80.58 112	84.65 141

plane_prior4											86.10 109

plane_prior3						56.09 122			63.92 39	69.27 130

plane_prior2							84.22 41		64.52 28

plane_prior1					81.27 107

plane_prior						56.31 116	83.58 57		63.19 52						80.48 115

n2								0.00 383

nn								0.00 383

door-mid								47.19 366

lessismore_v0				69.91 212	71.42 290	47.80 238		50.90 359		50.39 338	75.56 296	27.43 329	81.33 196	45.91 253	34.10 365	80.59 235

LGP-MVS_train				75.76 78	80.22 124	57.51 99		83.40 75	61.32 84	66.67 178	87.33 82	39.15 227	86.59 75	67.70 86	77.30 158	83.19 190

test11								83.47 72

door								47.60 365

HQP5-MVS						54.94 140

HQP-NCC					80.66 114		82.31 79		62.10 73	67.85 154

ACMP_Plane					80.66 114		82.31 79		62.10 73	67.85 154

BP-MVS														67.04 93

HQP4-MVS										67.85 154			86.93 64			84.32 149

HQP3-MVS								83.90 60							80.35 118

HQP2-MVS												45.46 163

NP-MVS					80.98 112	56.05 124					85.54 123

MDTV_nov1_ep13_2view						25.89 368	61.22 327		40.10 344	51.10 331		32.97 286		38.49 304		78.61 262

MDTV_nov1_ep13			57.00 279		72.73 269	38.26 320	65.02 312	64.73 313	44.74 311	55.46 299	72.48 316	32.61 295	70.47 299	37.47 309	67.75 273

ACMMP++_ref															74.07 183

ACMMP++															72.16 214

Test By Simon												48.33 126

ITE_SJBPF				62.09 293	66.16 337	44.55 275		64.32 315	47.36 291	55.31 302	80.34 224	19.27 355	62.68 332	36.29 321	62.39 312	79.04 258

DeepMVS_CX				12.03 357	17.97 379	10.91 377		10.60 380	7.46 372	11.07 373	28.36 368	3.28 378	11.29 376	8.01 374	9.74 375	13.89 371

High-resolution multi-view benchmark