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 10	87.24 14	59.15 67	88.18 1	87.15 3	65.04 16	84.26 5	91.86 6	67.01 1	90.84 3	79.48 7	91.38 2	88.42 21

FOURS1					86.12 37	60.82 37	88.18 1	83.61 72	60.87 96	81.50 19

APDe-MVS		80.16 8	80.59 6	78.86 31	86.64 21	60.02 48	88.12 3	86.42 15	62.94 55	82.40 16	92.12 2	59.64 21	89.76 19	78.70 15	88.32 34	86.79 86
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
test0726					87.75 7	59.07 71	87.86 4	86.83 8	64.26 31	84.19 7	91.92 5	64.82 8

DVP-MVS		80.84 4	81.64 3	78.42 37	87.75 7	59.07 71	87.85 5	85.03 40	64.26 31	83.82 8	92.00 3	64.82 8	90.75 8	78.66 18	90.61 11	85.45 149
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
test_0728_SECOND				79.19 16	87.82 3	59.11 70	87.85 5	87.15 3					90.84 3	78.66 18	90.61 11	87.62 54

SED-MVS		81.56 2	82.30 2	79.32 13	87.77 4	58.90 76	87.82 7	86.78 10	64.18 34	85.97 1	91.84 8	66.87 3	90.83 5	78.63 20	90.87 5	88.23 29

OPU-MVS				79.83 7	87.54 11	60.93 35	87.82 7				89.89 50	67.01 1	90.33 12	73.16 69	91.15 4	88.23 29

SteuartSystems-ACMMP		79.48 13	79.31 13	79.98 3	83.01 79	62.18 16	87.60 9	85.83 23	66.69 9	78.03 34	90.98 19	54.26 64	90.06 14	78.42 23	89.02 26	87.69 50
Skip Steuart: Steuart Systems R&D Blog.
CP-MVS		77.12 35	76.68 35	78.43 36	86.05 39	63.18 5	87.55 10	83.45 77	62.44 68	72.68 111	90.50 30	48.18 159	87.34 57	73.59 67	85.71 65	84.76 180

MED-MVS test				79.09 23	85.30 50	59.25 64	86.84 11	85.86 21	60.95 94	83.65 12	90.57 25		89.91 16	77.02 34	89.43 22	88.10 34

TestfortrainingZip a		79.97 10	80.40 7	78.69 33	85.30 50	58.20 85	86.84 11	85.86 21	60.95 94	83.65 12	90.57 25	64.70 10	89.91 16	76.25 42	89.43 22	87.96 39

TestfortrainingZip							86.84 11

ZNCC-MVS		78.82 15	78.67 18	79.30 14	86.43 29	62.05 18	86.62 14	86.01 20	63.32 46	75.08 59	90.47 32	53.96 70	88.68 30	76.48 38	89.63 20	87.16 75

HPM-MVS++		79.88 11	80.14 11	79.10 21	88.17 1	64.80 1	86.59 15	83.70 69	65.37 13	78.78 27	90.64 22	58.63 27	87.24 58	79.00 14	90.37 14	85.26 161

SMA-MVS		80.28 6	80.39 8	79.95 4	86.60 24	61.95 19	86.33 16	85.75 25	62.49 66	82.20 18	92.28 1	56.53 40	89.70 20	79.85 6	91.48 1	88.19 31
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
HFP-MVS		78.01 26	77.65 28	79.10 21	86.71 19	62.81 8	86.29 17	84.32 51	62.82 59	73.96 83	90.50 30	53.20 84	88.35 34	74.02 63	87.05 50	86.13 117

region2R		77.67 30	77.18 32	79.15 18	86.76 17	62.95 6	86.29 17	84.16 54	62.81 61	73.30 91	90.58 24	49.90 135	88.21 37	73.78 65	87.03 51	86.29 114

ACMMPR		77.71 28	77.23 31	79.16 17	86.75 18	62.93 7	86.29 17	84.24 52	62.82 59	73.55 89	90.56 28	49.80 138	88.24 36	74.02 63	87.03 51	86.32 110

MM		80.20 7	80.28 10	79.99 2	82.19 88	60.01 49	86.19 20	83.93 58	73.19 1	77.08 43	91.21 18	57.23 35	90.73 10	83.35 1	88.12 37	89.22 7

MSP-MVS		81.06 3	81.40 4	80.02 1	86.21 32	62.73 9	86.09 21	86.83 8	65.51 12	83.81 10	90.51 29	63.71 13	89.23 23	81.51 2	88.44 30	88.09 36
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
MTMP							86.03 22	17.08 477

MP-MVS		78.35 22	78.26 23	78.64 34	86.54 26	63.47 4	86.02 23	83.55 74	63.89 39	73.60 88	90.60 23	54.85 59	86.72 75	77.20 31	88.06 39	85.74 135
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
lecture		77.75 27	77.84 27	77.50 52	82.75 83	57.62 92	85.92 24	86.20 18	60.53 105	78.99 26	91.45 12	51.51 115	87.78 50	75.65 47	87.55 46	87.10 77

GST-MVS		78.14 24	77.85 26	78.99 27	86.05 39	61.82 22	85.84 25	85.21 34	63.56 43	74.29 78	90.03 46	52.56 93	88.53 32	74.79 57	88.34 32	86.63 95

XVS		77.17 34	76.56 39	79.00 25	86.32 30	62.62 11	85.83 26	83.92 59	64.55 25	72.17 119	90.01 48	47.95 161	88.01 43	71.55 86	86.74 58	86.37 104

X-MVStestdata		70.21 152	67.28 211	79.00 25	86.32 30	62.62 11	85.83 26	83.92 59	64.55 25	72.17 119	6.49 472	47.95 161	88.01 43	71.55 86	86.74 58	86.37 104

3Dnovator+	66.72 4	75.84 53	74.57 65	79.66 9	82.40 85	59.92 51	85.83 26	86.32 17	66.92 7	67.80 201	89.24 59	42.03 239	89.38 22	64.07 145	86.50 62	89.69 3

mPP-MVS		76.54 42	75.93 47	78.34 39	86.47 27	63.50 3	85.74 29	82.28 109	62.90 56	71.77 124	90.26 38	46.61 186	86.55 83	71.71 84	85.66 66	84.97 172

DPE-MVS		80.56 5	80.98 5	79.29 15	87.27 13	60.56 41	85.71 30	86.42 15	63.28 47	83.27 15	91.83 10	64.96 7	90.47 11	76.41 39	89.67 18	86.84 84
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
ME-MVS		80.04 9	80.36 9	79.08 24	86.63 23	59.25 64	85.62 31	86.73 12	63.10 52	82.27 17	90.57 25	61.90 15	89.88 18	77.02 34	89.43 22	88.10 34

SR-MVS		76.13 50	75.70 51	77.40 56	85.87 41	61.20 29	85.52 32	82.19 110	59.99 125	75.10 58	90.35 35	47.66 166	86.52 84	71.64 85	82.99 89	84.47 189

APD-MVS		78.02 25	78.04 25	77.98 44	86.44 28	60.81 38	85.52 32	84.36 50	60.61 103	79.05 25	90.30 37	55.54 52	88.32 35	73.48 68	87.03 51	84.83 176
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ACMMP		76.02 51	75.33 55	78.07 41	85.20 52	61.91 20	85.49 34	84.44 48	63.04 53	69.80 155	89.74 54	45.43 200	87.16 64	72.01 79	82.87 94	85.14 163
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
NCCC		78.58 18	78.31 20	79.39 12	87.51 12	62.61 13	85.20 35	84.42 49	66.73 8	74.67 72	89.38 57	55.30 53	89.18 24	74.19 61	87.34 49	86.38 102

SF-MVS		78.82 15	79.22 14	77.60 50	82.88 81	57.83 89	84.99 36	88.13 2	61.86 79	79.16 24	90.75 21	57.96 28	87.09 67	77.08 33	90.18 15	87.87 42

reproduce-ours		76.90 37	76.58 37	77.87 46	83.99 65	60.46 43	84.75 37	83.34 82	60.22 119	77.85 35	91.42 14	50.67 127	87.69 52	72.46 74	84.53 73	85.46 147

our_new_method		76.90 37	76.58 37	77.87 46	83.99 65	60.46 43	84.75 37	83.34 82	60.22 119	77.85 35	91.42 14	50.67 127	87.69 52	72.46 74	84.53 73	85.46 147

DeepC-MVS_fast	68.24 3	77.25 33	76.63 36	79.12 20	86.15 35	60.86 36	84.71 39	84.85 44	61.98 78	73.06 103	88.88 65	53.72 76	89.06 26	68.27 101	88.04 40	87.42 62
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MGCNet		78.45 20	78.28 21	78.98 28	80.73 113	57.91 88	84.68 40	81.64 119	68.35 2	75.77 49	90.38 33	53.98 68	90.26 13	81.30 3	87.68 45	88.77 13

reproduce_model		76.43 44	76.08 44	77.49 53	83.47 73	60.09 47	84.60 41	82.90 100	59.65 132	77.31 38	91.43 13	49.62 140	87.24 58	71.99 80	83.75 84	85.14 163

SD-MVS		77.70 29	77.62 29	77.93 45	84.47 62	61.88 21	84.55 42	83.87 64	60.37 112	79.89 21	89.38 57	54.97 57	85.58 112	76.12 43	84.94 69	86.33 108
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
CS-MVS		76.25 48	75.98 46	77.06 59	80.15 127	55.63 129	84.51 43	83.90 61	63.24 48	73.30 91	87.27 100	55.06 55	86.30 92	71.78 83	84.58 71	89.25 6

CNVR-MVS		79.84 12	79.97 12	79.45 11	87.90 2	62.17 17	84.37 44	85.03 40	66.96 5	77.58 37	90.06 44	59.47 23	89.13 25	78.67 17	89.73 16	87.03 78

NormalMVS		76.26 47	75.74 50	77.83 48	82.75 83	59.89 52	84.36 45	83.21 89	64.69 22	74.21 79	87.40 93	49.48 141	86.17 95	68.04 106	87.55 46	87.42 62

SymmetryMVS		75.28 58	74.60 64	77.30 57	83.85 68	59.89 52	84.36 45	75.51 256	64.69 22	74.21 79	87.40 93	49.48 141	86.17 95	68.04 106	83.88 82	85.85 126

SR-MVS-dyc-post		74.57 68	73.90 74	76.58 69	83.49 71	59.87 54	84.29 47	81.36 127	58.07 165	73.14 98	90.07 42	44.74 210	85.84 106	68.20 102	81.76 107	84.03 201

RE-MVS-def			73.71 78		83.49 71	59.87 54	84.29 47	81.36 127	58.07 165	73.14 98	90.07 42	43.06 229		68.20 102	81.76 107	84.03 201

PHI-MVS		75.87 52	75.36 54	77.41 54	80.62 118	55.91 122	84.28 49	85.78 24	56.08 215	73.41 90	86.58 121	50.94 125	88.54 31	70.79 91	89.71 17	87.79 47

HQP_MVS		74.31 71	73.73 77	76.06 76	81.41 100	56.31 111	84.22 50	84.01 56	64.52 27	69.27 164	86.10 138	45.26 204	87.21 62	68.16 104	80.58 122	84.65 181

plane_prior2							84.22 50		64.52 27

DeepC-MVS	69.38 2	78.56 19	78.14 24	79.83 7	83.60 69	61.62 23	84.17 52	86.85 6	63.23 49	73.84 86	90.25 39	57.68 31	89.96 15	74.62 58	89.03 25	87.89 40
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
9.14			78.75 17		83.10 76		84.15 53	88.26 1	59.90 126	78.57 29	90.36 34	57.51 34	86.86 72	77.39 29	89.52 21

CPTT-MVS		72.78 95	72.08 102	74.87 101	84.88 60	61.41 26	84.15 53	77.86 214	55.27 235	67.51 207	88.08 78	41.93 242	81.85 200	69.04 100	80.01 131	81.35 278

TSAR-MVS + MP.		78.44 21	78.28 21	78.90 29	84.96 55	61.41 26	84.03 55	83.82 67	59.34 142	79.37 23	89.76 53	59.84 18	87.62 55	76.69 36	86.74 58	87.68 51
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
API-MVS		72.17 111	71.41 113	74.45 118	81.95 92	57.22 98	84.03 55	80.38 156	59.89 130	68.40 178	82.33 234	49.64 139	87.83 49	51.87 266	84.16 80	78.30 328

save fliter					86.17 34	61.30 28	83.98 57	79.66 166	59.00 146

SPE-MVS-test		75.62 56	75.31 56	76.56 70	80.63 117	55.13 140	83.88 58	85.22 33	62.05 75	71.49 131	86.03 141	53.83 72	86.36 90	67.74 109	86.91 55	88.19 31

ACMMP_NAP		78.77 17	78.78 16	78.74 32	85.44 46	61.04 31	83.84 59	85.16 35	62.88 57	78.10 32	91.26 17	52.51 94	88.39 33	79.34 9	90.52 13	86.78 87

EC-MVSNet		75.84 53	75.87 49	75.74 84	78.86 156	52.65 195	83.73 60	86.08 19	63.47 45	72.77 110	87.25 101	53.13 85	87.93 45	71.97 81	85.57 67	86.66 93

APD-MVS_3200maxsize		74.96 60	74.39 67	76.67 66	82.20 87	58.24 84	83.67 61	83.29 86	58.41 159	73.71 87	90.14 40	45.62 193	85.99 102	69.64 95	82.85 95	85.78 129

HPM-MVS_fast		74.30 72	73.46 81	76.80 62	84.45 63	59.04 73	83.65 62	81.05 142	60.15 121	70.43 141	89.84 51	41.09 260	85.59 111	67.61 112	82.90 93	85.77 132

plane_prior						56.31 111	83.58 63		63.19 51						80.48 125

QAPM		70.05 156	68.81 168	73.78 137	76.54 243	53.43 173	83.23 64	83.48 75	52.89 285	65.90 241	86.29 132	41.55 252	86.49 86	51.01 273	78.40 169	81.42 272

MCST-MVS		77.48 31	77.45 30	77.54 51	86.67 20	58.36 83	83.22 65	86.93 5	56.91 193	74.91 64	88.19 74	59.15 25	87.68 54	73.67 66	87.45 48	86.57 96

EPNet		73.09 90	72.16 100	75.90 78	75.95 251	56.28 113	83.05 66	72.39 307	66.53 10	65.27 253	87.00 104	50.40 130	85.47 117	62.48 171	86.32 63	85.94 122
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DeepPCF-MVS	69.58 1	79.03 14	79.00 15	79.13 19	84.92 59	60.32 46	83.03 67	85.33 32	62.86 58	80.17 20	90.03 46	61.76 16	88.95 27	74.21 60	88.67 29	88.12 33

CSCG		76.92 36	76.75 34	77.41 54	83.96 67	59.60 56	82.95 68	86.50 14	60.78 99	75.27 54	84.83 166	60.76 17	86.56 80	67.86 108	87.87 44	86.06 119

MP-MVS-pluss		78.35 22	78.46 19	78.03 43	84.96 55	59.52 58	82.93 69	85.39 31	62.15 71	76.41 47	91.51 11	52.47 96	86.78 74	80.66 4	89.64 19	87.80 46
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HPM-MVS		77.28 32	76.85 33	78.54 35	85.00 54	60.81 38	82.91 70	85.08 37	62.57 64	73.09 102	89.97 49	50.90 126	87.48 56	75.30 51	86.85 56	87.33 70
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
MVSFormer		71.50 125	70.38 136	74.88 100	78.76 159	57.15 103	82.79 71	78.48 199	51.26 311	69.49 158	83.22 211	43.99 220	83.24 163	66.06 127	79.37 139	84.23 195

test_djsdf		69.45 179	67.74 194	74.58 112	74.57 288	54.92 144	82.79 71	78.48 199	51.26 311	65.41 250	83.49 207	38.37 287	83.24 163	66.06 127	69.25 320	85.56 142

ACMP	63.53 6	72.30 108	71.20 120	75.59 90	80.28 120	57.54 93	82.74 73	82.84 103	60.58 104	65.24 257	86.18 135	39.25 277	86.03 101	66.95 122	76.79 197	83.22 233
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMM	61.98 7	70.80 140	69.73 147	74.02 129	80.59 119	58.59 81	82.68 74	82.02 113	55.46 230	67.18 214	84.39 184	38.51 285	83.17 165	60.65 188	76.10 207	80.30 300
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
AdaColmap		69.99 158	68.66 172	73.97 133	84.94 57	57.83 89	82.63 75	78.71 187	56.28 211	64.34 272	84.14 187	41.57 250	87.06 68	46.45 311	78.88 154	77.02 349

OPM-MVS		74.73 64	74.25 70	76.19 75	80.81 112	59.01 74	82.60 76	83.64 71	63.74 41	72.52 114	87.49 90	47.18 177	85.88 105	69.47 97	80.78 116	83.66 222
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
PGM-MVS		76.77 40	76.06 45	78.88 30	86.14 36	62.73 9	82.55 77	83.74 68	61.71 80	72.45 117	90.34 36	48.48 157	88.13 40	72.32 76	86.85 56	85.78 129

LPG-MVS_test		72.74 96	71.74 107	75.76 82	80.22 122	57.51 95	82.55 77	83.40 79	61.32 85	66.67 225	87.33 98	39.15 279	86.59 78	67.70 110	77.30 189	83.19 235

CANet		76.46 43	75.93 47	78.06 42	81.29 103	57.53 94	82.35 79	83.31 85	67.78 3	70.09 145	86.34 130	54.92 58	88.90 28	72.68 73	84.55 72	87.76 48

114514_t		70.83 138	69.56 150	74.64 109	86.21 32	54.63 147	82.34 80	81.81 116	48.22 352	63.01 293	85.83 148	40.92 262	87.10 66	57.91 214	79.79 132	82.18 262

HQP-NCC					80.66 114		82.31 81		62.10 72	67.85 195

ACMP_Plane					80.66 114		82.31 81		62.10 72	67.85 195

HQP-MVS		73.45 81	72.80 91	75.40 91	80.66 114	54.94 142	82.31 81	83.90 61	62.10 72	67.85 195	85.54 158	45.46 198	86.93 70	67.04 118	80.35 126	84.32 191

MSLP-MVS++		73.77 78	73.47 80	74.66 107	83.02 78	59.29 63	82.30 84	81.88 114	59.34 142	71.59 128	86.83 108	45.94 191	83.65 154	65.09 138	85.22 68	81.06 286

EPP-MVSNet		72.16 113	71.31 117	74.71 104	78.68 162	49.70 253	82.10 85	81.65 118	60.40 109	65.94 239	85.84 147	51.74 111	86.37 89	55.93 228	79.55 138	88.07 38

test_prior4						62.51 14	82.08 86

TSAR-MVS + GP.		74.90 61	74.15 71	77.17 58	82.00 90	58.77 79	81.80 87	78.57 195	58.58 156	74.32 77	84.51 181	55.94 49	87.22 61	67.11 117	84.48 76	85.52 143

test_prior2							81.75 88		60.37 112	75.01 60	89.06 60	56.22 45		72.19 77	88.96 27

PS-MVSNAJss		72.24 109	71.21 119	75.31 93	78.50 168	55.93 121	81.63 89	82.12 111	56.24 212	70.02 149	85.68 154	47.05 179	84.34 141	65.27 137	74.41 229	85.67 138

TEST9					85.58 44	61.59 24	81.62 90	81.26 134	55.65 225	74.93 62	88.81 66	53.70 77	84.68 135

train_agg		76.27 46	76.15 43	76.64 68	85.58 44	61.59 24	81.62 90	81.26 134	55.86 217	74.93 62	88.81 66	53.70 77	84.68 135	75.24 53	88.33 33	83.65 223

MG-MVS		73.96 76	73.89 75	74.16 127	85.65 43	49.69 255	81.59 92	81.29 133	61.45 83	71.05 134	88.11 76	51.77 110	87.73 51	61.05 184	83.09 87	85.05 168

test_8					85.40 47	60.96 34	81.54 93	81.18 138	55.86 217	74.81 67	88.80 68	53.70 77	84.45 139

MAR-MVS		71.51 124	70.15 142	75.60 89	81.84 93	59.39 60	81.38 94	82.90 100	54.90 252	68.08 191	78.70 309	47.73 164	85.51 114	51.68 270	84.17 79	81.88 268
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
CDPH-MVS		76.31 45	75.67 52	78.22 40	85.35 49	59.14 69	81.31 95	84.02 55	56.32 209	74.05 81	88.98 62	53.34 82	87.92 46	69.23 99	88.42 31	87.59 56

OpenMVS	61.03 9	68.85 193	67.56 198	72.70 177	74.26 297	53.99 157	81.21 96	81.34 131	52.70 287	62.75 298	85.55 157	38.86 283	84.14 143	48.41 295	83.01 88	79.97 306

DP-MVS Recon		72.15 114	70.73 129	76.40 71	86.57 25	57.99 87	81.15 97	82.96 98	57.03 190	66.78 220	85.56 155	44.50 214	88.11 41	51.77 268	80.23 129	83.10 240

balanced_conf03		76.58 41	76.55 40	76.68 65	81.73 94	52.90 186	80.94 98	85.70 27	61.12 92	74.90 65	87.17 102	56.46 41	88.14 39	72.87 71	88.03 41	89.00 9

Vis-MVSNet		72.18 110	71.37 115	74.61 110	81.29 103	55.41 135	80.90 99	78.28 209	60.73 100	69.23 167	88.09 77	44.36 216	82.65 183	57.68 215	81.75 109	85.77 132
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
jajsoiax		68.25 209	66.45 229	73.66 147	75.62 257	55.49 134	80.82 100	78.51 198	52.33 295	64.33 273	84.11 188	28.28 396	81.81 202	63.48 159	70.62 289	83.67 220

mvs_tets		68.18 212	66.36 235	73.63 150	75.61 258	55.35 138	80.77 101	78.56 196	52.48 294	64.27 275	84.10 189	27.45 404	81.84 201	63.45 160	70.56 291	83.69 219

DP-MVS		65.68 261	63.66 274	71.75 201	84.93 58	56.87 108	80.74 102	73.16 300	53.06 282	59.09 346	82.35 233	36.79 309	85.94 104	32.82 413	69.96 305	72.45 398

3Dnovator	64.47 5	72.49 103	71.39 114	75.79 81	77.70 201	58.99 75	80.66 103	83.15 94	62.24 70	65.46 249	86.59 120	42.38 237	85.52 113	59.59 198	84.72 70	82.85 245

ACMH+	57.40 11	66.12 257	64.06 266	72.30 189	77.79 197	52.83 191	80.39 104	78.03 212	57.30 183	57.47 363	82.55 227	27.68 402	84.17 142	45.54 321	69.78 309	79.90 308

viewdifsd2359ckpt09		73.42 82	72.45 97	76.30 74	77.25 221	53.27 177	80.36 105	82.48 106	57.96 170	72.24 118	85.73 152	53.22 83	86.27 93	63.79 155	79.06 152	89.36 5

sasdasda		74.67 65	74.98 60	73.71 144	78.94 154	50.56 234	80.23 106	83.87 64	60.30 116	77.15 40	86.56 122	59.65 19	82.00 197	66.01 129	82.12 100	88.58 18

canonicalmvs		74.67 65	74.98 60	73.71 144	78.94 154	50.56 234	80.23 106	83.87 64	60.30 116	77.15 40	86.56 122	59.65 19	82.00 197	66.01 129	82.12 100	88.58 18

IS-MVSNet		71.57 123	71.00 124	73.27 164	78.86 156	45.63 315	80.22 108	78.69 188	64.14 37	66.46 228	87.36 96	49.30 145	85.60 110	50.26 279	83.71 85	88.59 17

Effi-MVS+-dtu		69.64 170	67.53 201	75.95 77	76.10 249	62.29 15	80.20 109	76.06 245	59.83 131	65.26 256	77.09 341	41.56 251	84.02 147	60.60 189	71.09 286	81.53 271

nrg030		72.96 92	73.01 87	72.84 173	75.41 263	50.24 239	80.02 110	82.89 102	58.36 161	74.44 74	86.73 112	58.90 26	80.83 229	65.84 132	74.46 226	87.44 61

Anonymous20231211		69.28 182	68.47 177	71.73 202	80.28 120	47.18 299	79.98 111	82.37 108	54.61 256	67.24 212	84.01 191	39.43 274	82.41 191	55.45 236	72.83 259	85.62 141

DPM-MVS		75.47 57	75.00 59	76.88 60	81.38 102	59.16 66	79.94 112	85.71 26	56.59 203	72.46 115	86.76 110	56.89 38	87.86 48	66.36 125	88.91 28	83.64 224

PVSNet_Blended_VisFu		71.45 127	70.39 135	74.65 108	82.01 89	58.82 78	79.93 113	80.35 157	55.09 240	65.82 245	82.16 242	49.17 148	82.64 184	60.34 190	78.62 163	82.50 256

PAPM_NR		72.63 100	71.80 105	75.13 96	81.72 95	53.42 174	79.91 114	83.28 87	59.14 144	66.31 232	85.90 145	51.86 107	86.06 99	57.45 217	80.62 120	85.91 124

LS3D		64.71 275	62.50 291	71.34 223	79.72 134	55.71 126	79.82 115	74.72 273	48.50 348	56.62 369	84.62 174	33.59 341	82.34 192	29.65 435	75.23 221	75.97 359

UGNet		68.81 194	67.39 206	73.06 168	78.33 178	54.47 148	79.77 116	75.40 259	60.45 107	63.22 286	84.40 183	32.71 354	80.91 228	51.71 269	80.56 124	83.81 212
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
LFMVS		71.78 119	71.59 108	72.32 188	83.40 74	46.38 304	79.75 117	71.08 316	64.18 34	72.80 109	88.64 71	42.58 234	83.72 152	57.41 218	84.49 75	86.86 83

OMC-MVS		71.40 128	70.60 131	73.78 137	76.60 241	53.15 180	79.74 118	79.78 163	58.37 160	68.75 172	86.45 127	45.43 200	80.60 233	62.58 169	77.73 178	87.58 57

casdiffmvs_mvg		76.14 49	76.30 42	75.66 86	76.46 245	51.83 215	79.67 119	85.08 37	65.02 19	75.84 48	88.58 72	59.42 24	85.08 123	72.75 72	83.93 81	90.08 1
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
无先验							79.66 120	74.30 280	48.40 350				80.78 231	53.62 251		79.03 323

Effi-MVS+		73.31 85	72.54 95	75.62 88	77.87 194	53.64 164	79.62 121	79.61 167	61.63 82	72.02 122	82.61 221	56.44 42	85.97 103	63.99 148	79.07 151	87.25 72

GDP-MVS		72.64 99	71.28 118	76.70 63	77.72 200	54.22 154	79.57 122	84.45 47	55.30 234	71.38 132	86.97 105	39.94 267	87.00 69	67.02 120	79.20 147	88.89 11

PAPR		71.72 122	70.82 127	74.41 119	81.20 107	51.17 220	79.55 123	83.33 84	55.81 220	66.93 219	84.61 175	50.95 124	86.06 99	55.79 231	79.20 147	86.00 120

ACMH	55.70 15	65.20 270	63.57 275	70.07 251	78.07 188	52.01 211	79.48 124	79.69 164	55.75 222	56.59 370	80.98 267	27.12 407	80.94 225	42.90 349	71.58 278	77.25 347
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ETV-MVS		74.46 70	73.84 76	76.33 73	79.27 144	55.24 139	79.22 125	85.00 42	64.97 21	72.65 112	79.46 299	53.65 80	87.87 47	67.45 114	82.91 92	85.89 125

BP-MVS1		73.41 83	72.25 99	76.88 60	76.68 238	53.70 162	79.15 126	81.07 141	60.66 102	71.81 123	87.39 95	40.93 261	87.24 58	71.23 88	81.29 113	89.71 2

原ACMM2							79.02 127

fmvsm_l_conf0.5_n_3		73.23 87	73.13 86	73.55 154	74.40 292	55.13 140	78.97 128	74.96 271	56.64 196	74.76 70	88.75 70	55.02 56	78.77 275	76.33 40	78.31 171	86.74 88

GeoE		71.01 133	70.15 142	73.60 152	79.57 137	52.17 206	78.93 129	78.12 211	58.02 167	67.76 204	83.87 194	52.36 98	82.72 181	56.90 220	75.79 211	85.92 123

UA-Net		73.13 89	72.93 88	73.76 139	83.58 70	51.66 217	78.75 130	77.66 218	67.75 4	72.61 113	89.42 55	49.82 137	83.29 162	53.61 252	83.14 86	86.32 110

VDDNet		71.81 118	71.33 116	73.26 165	82.80 82	47.60 295	78.74 131	75.27 261	59.59 137	72.94 105	89.40 56	41.51 253	83.91 149	58.75 210	82.99 89	88.26 26

v10		70.21 152	69.02 162	73.81 136	73.51 310	50.92 226	78.74 131	81.39 125	60.05 123	66.39 230	81.83 250	47.58 168	85.41 120	62.80 168	68.86 327	85.09 167

viewdifsd2359ckpt13		72.40 107	71.79 106	74.22 125	75.63 256	51.77 216	78.67 133	83.13 96	57.08 187	71.59 128	85.36 162	53.10 86	82.64 184	63.07 165	78.51 165	88.24 28

CANet_DTU		68.18 212	67.71 197	69.59 261	74.83 277	46.24 306	78.66 134	76.85 234	59.60 134	63.45 284	82.09 246	35.25 319	77.41 298	59.88 195	78.76 158	85.14 163

MVSMamba_PlusPlus		75.75 55	75.44 53	76.67 66	80.84 111	53.06 183	78.62 135	85.13 36	59.65 132	71.53 130	87.47 91	56.92 37	88.17 38	72.18 78	86.63 61	88.80 12

v8		70.33 150	69.28 157	73.49 156	73.15 316	50.22 240	78.62 135	80.78 148	60.79 98	66.45 229	82.11 245	49.35 144	84.98 126	63.58 158	68.71 328	85.28 159

alignmvs		73.86 77	73.99 72	73.45 158	78.20 181	50.50 236	78.57 137	82.43 107	59.40 140	76.57 45	86.71 114	56.42 43	81.23 216	65.84 132	81.79 106	88.62 16

PLC	56.13 14	65.09 271	63.21 283	70.72 240	81.04 109	54.87 145	78.57 137	77.47 221	48.51 347	55.71 378	81.89 248	33.71 338	79.71 249	41.66 358	70.37 294	77.58 340
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
v7n		69.01 190	67.36 208	73.98 132	72.51 330	52.65 195	78.54 139	81.30 132	60.26 118	62.67 299	81.62 254	43.61 222	84.49 138	57.01 219	68.70 329	84.79 178

COLMAP_ROB	52.97 17	61.27 320	58.81 330	68.64 277	74.63 284	52.51 200	78.42 140	73.30 296	49.92 328	50.96 415	81.51 258	23.06 427	79.40 254	31.63 423	65.85 351	74.01 386
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
Elysia		70.19 154	68.29 184	75.88 79	74.15 299	54.33 152	78.26 141	83.21 89	55.04 246	67.28 210	83.59 202	30.16 377	86.11 97	63.67 156	79.26 144	87.20 73

StellarMVS		70.19 154	68.29 184	75.88 79	74.15 299	54.33 152	78.26 141	83.21 89	55.04 246	67.28 210	83.59 202	30.16 377	86.11 97	63.67 156	79.26 144	87.20 73

fmvsm_s_conf0.5_n_a		69.54 174	68.74 170	71.93 194	72.47 331	53.82 160	78.25 143	62.26 397	49.78 329	73.12 101	86.21 134	52.66 92	76.79 315	75.02 54	68.88 325	85.18 162

fmvsm_s_conf0.5_n_8		74.30 72	74.39 67	74.01 130	75.33 265	52.89 188	78.24 144	77.32 227	61.65 81	78.13 31	88.90 64	52.82 90	81.54 207	78.46 22	78.67 161	87.60 55

CLD-MVS		73.33 84	72.68 93	75.29 95	78.82 158	53.33 176	78.23 145	84.79 45	61.30 87	70.41 142	81.04 265	52.41 97	87.12 65	64.61 144	82.49 99	85.41 153
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
test_fmvsmconf0.1_n		72.81 94	72.33 98	74.24 124	69.89 380	55.81 124	78.22 146	75.40 259	54.17 265	75.00 61	88.03 82	53.82 73	80.23 243	78.08 25	78.34 170	86.69 90

test_fmvsmconf_n		73.01 91	72.59 94	74.27 123	71.28 357	55.88 123	78.21 147	75.56 254	54.31 263	74.86 66	87.80 86	54.72 60	80.23 243	78.07 26	78.48 166	86.70 89

casdiffmvs		74.80 62	74.89 62	74.53 115	75.59 259	50.37 237	78.17 148	85.06 39	62.80 62	74.40 75	87.86 84	57.88 29	83.61 155	69.46 98	82.79 96	89.59 4
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
fmvsm_s_conf0.5_n_5		72.69 98	72.80 91	72.37 187	74.11 302	53.21 179	78.12 149	73.31 295	53.98 268	76.81 44	88.05 79	53.38 81	77.37 300	76.64 37	80.78 116	86.53 98

fmvsm_s_conf0.1_n_a		69.32 181	68.44 179	71.96 192	70.91 361	53.78 161	78.12 149	62.30 396	49.35 335	73.20 95	86.55 124	51.99 105	76.79 315	74.83 56	68.68 330	85.32 157

F-COLMAP		63.05 298	60.87 317	69.58 263	76.99 234	53.63 165	78.12 149	76.16 241	47.97 357	52.41 410	81.61 255	27.87 399	78.11 282	40.07 365	66.66 346	77.00 350

fmvsm_s_conf0.5_n_10		74.11 74	73.98 73	74.48 117	74.61 285	52.86 190	78.10 152	77.06 231	57.14 186	78.24 30	88.79 69	52.83 89	82.26 193	77.79 28	81.30 112	88.32 24

test_fmvsmconf0.01_n		72.17 111	71.50 110	74.16 127	67.96 399	55.58 132	78.06 153	74.67 274	54.19 264	74.54 73	88.23 73	50.35 132	80.24 242	78.07 26	77.46 184	86.65 94

EG-PatchMatch MVS		64.71 275	62.87 286	70.22 247	77.68 202	53.48 169	77.99 154	78.82 183	53.37 280	56.03 377	77.41 337	24.75 424	84.04 145	46.37 312	73.42 249	73.14 389

fmvsm_s_conf0.5_n		69.58 172	68.84 167	71.79 200	72.31 336	52.90 186	77.90 155	62.43 395	49.97 327	72.85 108	85.90 145	52.21 100	76.49 321	75.75 45	70.26 299	85.97 121

SSM_0404		70.84 136	69.41 155	75.12 97	79.20 146	53.86 158	77.89 156	80.00 161	53.88 270	69.40 161	84.61 175	43.21 226	86.56 80	58.80 208	77.68 180	84.95 173

dcpmvs_2		74.55 69	75.23 57	72.48 182	82.34 86	53.34 175	77.87 157	81.46 123	57.80 176	75.49 51	86.81 109	62.22 14	77.75 292	71.09 89	82.02 103	86.34 106

tttt0517		67.83 222	65.66 248	74.33 121	76.69 237	50.82 228	77.86 158	73.99 287	54.54 259	64.64 270	82.53 230	35.06 321	85.50 115	55.71 232	69.91 306	86.67 92

fmvsm_s_conf0.1_n		69.41 180	68.60 173	71.83 197	71.07 359	52.88 189	77.85 159	62.44 394	49.58 332	72.97 104	86.22 133	51.68 112	76.48 322	75.53 49	70.10 302	86.14 116

v1144		70.42 147	69.31 156	73.76 139	73.22 314	50.64 231	77.83 160	81.43 124	58.58 156	69.40 161	81.16 262	47.53 170	85.29 122	64.01 147	70.64 288	85.34 156

CNLPA		65.43 265	64.02 267	69.68 259	78.73 161	58.07 86	77.82 161	70.71 320	51.49 306	61.57 318	83.58 205	38.23 291	70.82 357	43.90 336	70.10 302	80.16 303

fmvsm_s_conf0.5_n_3		73.55 80	74.39 67	71.03 233	74.09 303	51.86 214	77.77 162	75.60 252	61.18 90	78.67 28	88.98 62	55.88 50	77.73 293	78.69 16	78.68 160	83.50 227

VDD-MVS		72.50 102	72.09 101	73.75 141	81.58 96	49.69 255	77.76 163	77.63 219	63.21 50	73.21 94	89.02 61	42.14 238	83.32 161	61.72 178	82.50 98	88.25 27

v1192		69.97 159	68.68 171	73.85 134	73.19 315	50.94 224	77.68 164	81.36 127	57.51 182	68.95 171	80.85 272	45.28 203	85.33 121	62.97 167	70.37 294	85.27 160

v2v482		70.50 145	69.45 154	73.66 147	72.62 326	50.03 245	77.58 165	80.51 152	59.90 126	69.52 157	82.14 243	47.53 170	84.88 132	65.07 139	70.17 300	86.09 118

WR-MVS_H		67.02 240	66.92 221	67.33 293	77.95 193	37.75 390	77.57 166	82.11 112	62.03 77	62.65 300	82.48 231	50.57 129	79.46 253	42.91 348	64.01 366	84.79 178

Anonymous20240529		69.91 160	69.02 162	72.56 179	80.19 125	47.65 293	77.56 167	80.99 144	55.45 231	69.88 153	86.76 110	39.24 278	82.18 195	54.04 247	77.10 193	87.85 43

v144192		69.71 165	68.51 174	73.33 163	73.10 317	50.13 242	77.54 168	80.64 149	56.65 195	68.57 175	80.55 275	46.87 184	84.96 128	62.98 166	69.66 313	84.89 175

baseline		74.61 67	74.70 63	74.34 120	75.70 254	49.99 246	77.54 168	84.63 46	62.73 63	73.98 82	87.79 87	57.67 32	83.82 151	69.49 96	82.74 97	89.20 8

viewmacassd2359aftdt		73.15 88	73.16 85	73.11 167	75.15 271	49.31 262	77.53 170	83.21 89	60.42 108	73.20 95	87.34 97	53.82 73	81.05 222	67.02 120	80.79 115	88.96 10

Fast-Effi-MVS+-dtu		67.37 230	65.33 256	73.48 157	72.94 321	57.78 91	77.47 171	76.88 233	57.60 181	61.97 311	76.85 345	39.31 275	80.49 237	54.72 241	70.28 298	82.17 264

fmvsm_l_conf0.5_n_9		73.27 86	73.66 79	72.09 191	73.82 304	52.72 194	77.45 172	74.28 281	56.61 202	77.10 42	88.16 75	56.17 46	77.09 305	78.27 24	81.13 114	86.48 100

v1921920		69.47 178	68.17 188	73.36 162	73.06 318	50.10 243	77.39 173	80.56 150	56.58 204	68.59 173	80.37 277	44.72 211	84.98 126	62.47 172	69.82 308	85.00 169

tt0805		67.77 224	67.24 215	69.34 266	74.87 275	40.08 367	77.36 174	81.37 126	55.31 233	66.33 231	84.65 173	37.35 299	82.55 187	55.65 234	72.28 270	85.39 154

GBi-Net		67.21 232	66.55 227	69.19 267	77.63 205	43.33 336	77.31 175	77.83 215	56.62 199	65.04 262	82.70 217	41.85 243	80.33 239	47.18 305	72.76 260	83.92 207

test1		67.21 232	66.55 227	69.19 267	77.63 205	43.33 336	77.31 175	77.83 215	56.62 199	65.04 262	82.70 217	41.85 243	80.33 239	47.18 305	72.76 260	83.92 207

FMVSNet1		66.70 247	65.87 244	69.19 267	77.49 213	43.33 336	77.31 175	77.83 215	56.45 205	64.60 271	82.70 217	38.08 293	80.33 239	46.08 314	72.31 269	83.92 207

fmvsm_s_conf0.5_n_9		75.16 59	75.22 58	75.01 98	78.34 177	55.37 137	77.30 178	73.95 288	61.40 84	79.46 22	90.14 40	57.07 36	81.15 217	80.00 5	79.31 143	88.51 20

MVS_111021_HR		74.02 75	73.46 81	75.69 85	83.01 79	60.63 40	77.29 179	78.40 206	61.18 90	70.58 140	85.97 143	54.18 66	84.00 148	67.52 113	82.98 91	82.45 257

SSM_0407		70.41 148	68.96 165	74.75 103	78.65 163	53.46 170	77.28 180	80.00 161	53.88 270	68.14 185	84.61 175	43.21 226	86.26 94	58.80 208	76.11 204	84.54 183

EIA-MVS		71.78 119	70.60 131	75.30 94	79.85 131	53.54 168	77.27 181	83.26 88	57.92 172	66.49 227	79.39 301	52.07 104	86.69 76	60.05 192	79.14 150	85.66 139

viewmanbaseed2359cas		72.92 93	72.89 89	73.00 169	75.16 269	49.25 265	77.25 182	83.11 97	59.52 139	72.93 106	86.63 117	54.11 67	80.98 223	66.63 123	80.67 119	88.76 14

v1240		69.24 184	67.91 193	73.25 166	73.02 320	49.82 247	77.21 183	80.54 151	56.43 206	68.34 180	80.51 276	43.33 225	84.99 124	62.03 176	69.77 311	84.95 173

fmvsm_l_conf0.5_n		70.99 134	70.82 127	71.48 211	71.45 350	54.40 150	77.18 184	70.46 322	48.67 344	75.17 56	86.86 107	53.77 75	76.86 313	76.33 40	77.51 183	83.17 239

jason		69.65 169	68.39 181	73.43 160	78.27 180	56.88 107	77.12 185	73.71 291	46.53 376	69.34 163	83.22 211	43.37 224	79.18 259	64.77 141	79.20 147	84.23 195
jason: jason.
PAPM		67.92 219	66.69 225	71.63 208	78.09 187	49.02 268	77.09 186	81.24 136	51.04 314	60.91 324	83.98 192	47.71 165	84.99 124	40.81 362	79.32 142	80.90 289

EI-MVSNet-Vis-set		72.42 106	71.59 108	74.91 99	78.47 170	54.02 156	77.05 187	79.33 173	65.03 18	71.68 126	79.35 303	52.75 91	84.89 130	66.46 124	74.23 230	85.83 128

PEN-MVS		66.60 249	66.45 229	67.04 294	77.11 226	36.56 403	77.03 188	80.42 155	62.95 54	62.51 305	84.03 190	46.69 185	79.07 266	44.22 330	63.08 376	85.51 144

FIs		70.82 139	71.43 112	68.98 273	78.33 178	38.14 386	76.96 189	83.59 73	61.02 93	67.33 209	86.73 112	55.07 54	81.64 203	54.61 244	79.22 146	87.14 76

PS-CasMVS		66.42 253	66.32 237	66.70 298	77.60 211	36.30 408	76.94 190	79.61 167	62.36 69	62.43 308	83.66 200	45.69 192	78.37 278	45.35 327	63.26 374	85.42 152

h-mvs33		72.71 97	71.49 111	76.40 71	81.99 91	59.58 57	76.92 191	76.74 237	60.40 109	74.81 67	85.95 144	45.54 196	85.76 108	70.41 93	70.61 290	83.86 211

fmvsm_l_conf0.5_n_a		70.50 145	70.27 138	71.18 227	71.30 356	54.09 155	76.89 192	69.87 326	47.90 358	74.37 76	86.49 125	53.07 88	76.69 318	75.41 50	77.11 192	82.76 246

thisisatest0530		67.92 219	65.78 246	74.33 121	76.29 246	51.03 223	76.89 192	74.25 282	53.67 277	65.59 247	81.76 252	35.15 320	85.50 115	55.94 227	72.47 265	86.47 101

viewcassd2359sk11		73.56 79	73.41 83	74.00 131	77.13 223	50.35 238	76.86 194	83.69 70	61.23 89	73.14 98	86.38 129	56.09 48	82.96 169	67.15 116	79.01 153	88.70 15

test_0402		63.25 294	61.01 314	69.96 252	80.00 129	54.37 151	76.86 194	72.02 311	54.58 258	58.71 349	80.79 274	35.00 322	84.36 140	26.41 447	64.71 360	71.15 417

CP-MVSNet		66.49 252	66.41 233	66.72 296	77.67 203	36.33 406	76.83 196	79.52 169	62.45 67	62.54 303	83.47 208	46.32 188	78.37 278	45.47 325	63.43 373	85.45 149

fmvsm_s_conf0.5_n_4		72.04 115	71.85 104	72.58 178	73.74 307	52.49 201	76.69 197	72.42 306	56.42 207	75.32 53	87.04 103	52.13 103	78.01 284	79.29 12	73.65 240	87.26 71

EI-MVSNet-UG-set		71.92 116	71.06 123	74.52 116	77.98 192	53.56 167	76.62 198	79.16 174	64.40 29	71.18 133	78.95 308	52.19 101	84.66 137	65.47 135	73.57 243	85.32 157

RRT-MVS		71.46 126	70.70 130	73.74 142	77.76 199	49.30 263	76.60 199	80.45 154	61.25 88	68.17 183	84.78 168	44.64 212	84.90 129	64.79 140	77.88 177	87.03 78

lupinMVS		69.57 173	68.28 186	73.44 159	78.76 159	57.15 103	76.57 200	73.29 297	46.19 379	69.49 158	82.18 239	43.99 220	79.23 258	64.66 142	79.37 139	83.93 206

TranMVSNet+NR-MVSNet		70.36 149	70.10 144	71.17 228	78.64 166	42.97 342	76.53 201	81.16 140	66.95 6	68.53 176	85.42 160	51.61 113	83.07 166	52.32 260	69.70 312	87.46 60

TAPA-MVS	59.36 10	66.60 249	65.20 258	70.81 237	76.63 240	48.75 274	76.52 202	80.04 160	50.64 319	65.24 257	84.93 165	39.15 279	78.54 277	36.77 389	76.88 195	85.14 163
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
DTE-MVSNet		65.58 263	65.34 255	66.31 305	76.06 250	34.79 416	76.43 203	79.38 172	62.55 65	61.66 316	83.83 195	45.60 194	79.15 263	41.64 360	60.88 391	85.00 169

anonymousdsp		67.00 241	64.82 261	73.57 153	70.09 376	56.13 116	76.35 204	77.35 225	48.43 349	64.99 265	80.84 273	33.01 347	80.34 238	64.66 142	67.64 338	84.23 195

MVP-Stereo		65.41 266	63.80 271	70.22 247	77.62 209	55.53 133	76.30 205	78.53 197	50.59 320	56.47 373	78.65 312	39.84 270	82.68 182	44.10 334	72.12 272	72.44 399
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
fmvsm_s_conf0.5_n_6		72.59 101	72.87 90	71.73 202	75.14 272	51.96 212	76.28 206	77.12 230	57.63 180	73.85 85	86.91 106	51.54 114	77.87 289	77.18 32	80.18 130	85.37 155

MVS_Test		72.45 104	72.46 96	72.42 186	74.88 274	48.50 280	76.28 206	83.14 95	59.40 140	72.46 115	84.68 171	55.66 51	81.12 218	65.98 131	79.66 135	87.63 53

LuminaMVS		68.24 210	66.82 223	72.51 181	73.46 313	53.60 166	76.23 208	78.88 182	52.78 286	68.08 191	80.13 283	32.70 355	81.41 209	63.16 164	75.97 208	82.53 253

IterMVS-LS		69.22 185	68.48 175	71.43 217	74.44 291	49.40 259	76.23 208	77.55 220	59.60 134	65.85 244	81.59 257	51.28 119	81.58 206	59.87 196	69.90 307	83.30 230
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
新几何2							76.12 210

FMVSNet2		66.93 242	66.31 238	68.79 276	77.63 205	42.98 341	76.11 211	77.47 221	56.62 199	65.22 259	82.17 241	41.85 243	80.18 245	47.05 308	72.72 263	83.20 234

旧先验2							76.08 212		45.32 387	76.55 46			65.56 393	58.75 210

BH-untuned		68.27 208	67.29 210	71.21 225	79.74 132	53.22 178	76.06 213	77.46 223	57.19 185	66.10 236	81.61 255	45.37 202	83.50 158	45.42 326	76.68 199	76.91 353

FC-MVSNet-test		69.80 164	70.58 133	67.46 289	77.61 210	34.73 419	76.05 214	83.19 93	60.84 97	65.88 243	86.46 126	54.52 63	80.76 232	52.52 259	78.12 173	86.91 81

PCF-MVS	61.88 8	70.95 135	69.49 152	75.35 92	77.63 205	55.71 126	76.04 215	81.81 116	50.30 322	69.66 156	85.40 161	52.51 94	84.89 130	51.82 267	80.24 128	85.45 149
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
UniMVSNet_NR-MVSNet		71.11 130	71.00 124	71.44 215	79.20 146	44.13 328	76.02 216	82.60 105	66.48 11	68.20 181	84.60 178	56.82 39	82.82 179	54.62 242	70.43 292	87.36 69

UniMVSNet (Re)		70.63 142	70.20 139	71.89 195	78.55 167	45.29 318	75.94 217	82.92 99	63.68 42	68.16 184	83.59 202	53.89 71	83.49 159	53.97 248	71.12 283	86.89 82

KinetiMVS		71.26 129	70.16 141	74.57 113	74.59 286	52.77 193	75.91 218	81.20 137	60.72 101	69.10 170	85.71 153	41.67 248	83.53 157	63.91 151	78.62 163	87.42 62

test_fmvsmvis_n_1920		70.84 136	70.38 136	72.22 190	71.16 358	55.39 136	75.86 219	72.21 309	49.03 339	73.28 93	86.17 136	51.83 109	77.29 302	75.80 44	78.05 174	83.98 204

EPNet_dtu		61.90 312	61.97 298	61.68 356	72.89 322	39.78 371	75.85 220	65.62 364	55.09 240	54.56 393	79.36 302	37.59 296	67.02 384	39.80 370	76.95 194	78.25 329
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MGCFI-Net		72.45 104	73.34 84	69.81 258	77.77 198	43.21 339	75.84 221	81.18 138	59.59 137	75.45 52	86.64 115	57.74 30	77.94 285	63.92 149	81.90 105	88.30 25

v148		68.24 210	67.19 218	71.40 218	70.43 369	47.77 292	75.76 222	77.03 232	58.91 148	67.36 208	80.10 285	48.60 156	81.89 199	60.01 193	66.52 348	84.53 186

test_fmvsm_n_1920		71.73 121	71.14 121	73.50 155	72.52 329	56.53 110	75.60 223	76.16 241	48.11 354	77.22 39	85.56 155	53.10 86	77.43 297	74.86 55	77.14 191	86.55 97

SixPastTwentyTwo		61.65 315	58.80 332	70.20 249	75.80 252	47.22 298	75.59 224	69.68 328	54.61 256	54.11 397	79.26 304	27.07 408	82.96 169	43.27 343	49.79 436	80.41 298

DELS-MVS		74.76 63	74.46 66	75.65 87	77.84 196	52.25 205	75.59 224	84.17 53	63.76 40	73.15 97	82.79 216	59.58 22	86.80 73	67.24 115	86.04 64	87.89 40
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
FA-MVS(test-final)		69.82 162	68.48 175	73.84 135	78.44 171	50.04 244	75.58 226	78.99 180	58.16 163	67.59 205	82.14 243	42.66 232	85.63 109	56.60 221	76.19 203	85.84 127

Baseline_NR-MVSNet		67.05 239	67.56 198	65.50 323	75.65 255	37.70 392	75.42 227	74.65 275	59.90 126	68.14 185	83.15 214	49.12 151	77.20 303	52.23 261	69.78 309	81.60 270

OpenMVS_ROB	52.78 18	60.03 329	58.14 339	65.69 320	70.47 368	44.82 320	75.33 228	70.86 319	45.04 388	56.06 376	76.00 360	26.89 411	79.65 250	35.36 402	67.29 341	72.60 394

viewdifsd2359ckpt07		71.90 117	71.97 103	71.69 205	74.81 278	48.08 286	75.30 229	80.49 153	60.00 124	71.63 127	86.33 131	56.34 44	79.25 257	65.40 136	77.41 185	87.76 48

xiu_mvs_v1_base_debu		68.58 200	67.28 211	72.48 182	78.19 182	57.19 100	75.28 230	75.09 267	51.61 302	70.04 146	81.41 259	32.79 350	79.02 268	63.81 152	77.31 186	81.22 281

xiu_mvs_v1_base		68.58 200	67.28 211	72.48 182	78.19 182	57.19 100	75.28 230	75.09 267	51.61 302	70.04 146	81.41 259	32.79 350	79.02 268	63.81 152	77.31 186	81.22 281

xiu_mvs_v1_base_debi		68.58 200	67.28 211	72.48 182	78.19 182	57.19 100	75.28 230	75.09 267	51.61 302	70.04 146	81.41 259	32.79 350	79.02 268	63.81 152	77.31 186	81.22 281

EI-MVSNet		69.27 183	68.44 179	71.73 202	74.47 289	49.39 260	75.20 233	78.45 202	59.60 134	69.16 168	76.51 353	51.29 118	82.50 188	59.86 197	71.45 280	83.30 230

CVMVSNet		59.63 335	59.14 327	61.08 365	74.47 289	38.84 380	75.20 233	68.74 339	31.15 442	58.24 356	76.51 353	32.39 363	68.58 371	49.77 281	65.84 352	75.81 361

ET-MVSNet_ETH3D		67.96 218	65.72 247	74.68 106	76.67 239	55.62 131	75.11 235	74.74 272	52.91 284	60.03 332	80.12 284	33.68 339	82.64 184	61.86 177	76.34 201	85.78 129

xiu_mvs_v2_base		70.52 143	69.75 146	72.84 173	81.21 106	55.63 129	75.11 235	78.92 181	54.92 251	69.96 152	79.68 294	47.00 183	82.09 196	61.60 180	79.37 139	80.81 291

K. test v3		60.47 326	57.11 345	70.56 243	73.74 307	48.22 283	75.10 237	62.55 392	58.27 162	53.62 403	76.31 357	27.81 400	81.59 205	47.42 301	39.18 451	81.88 268

Fast-Effi-MVS+		70.28 151	69.12 161	73.73 143	78.50 168	51.50 218	75.01 238	79.46 171	56.16 214	68.59 173	79.55 297	53.97 69	84.05 144	53.34 254	77.53 182	85.65 140

DU-MVS		70.01 157	69.53 151	71.44 215	78.05 189	44.13 328	75.01 238	81.51 122	64.37 30	68.20 181	84.52 179	49.12 151	82.82 179	54.62 242	70.43 292	87.37 67

FMVSNet3		66.32 256	65.61 249	68.46 279	76.48 244	42.34 346	74.98 240	77.15 229	55.83 219	65.04 262	81.16 262	39.91 268	80.14 246	47.18 305	72.76 260	82.90 244

mvsmamba		68.47 204	66.56 226	74.21 126	79.60 135	52.95 184	74.94 241	75.48 257	52.09 298	60.10 330	83.27 210	36.54 310	84.70 134	59.32 202	77.69 179	84.99 171

MTAPA		76.90 37	76.42 41	78.35 38	86.08 38	63.57 2	74.92 242	80.97 145	65.13 15	75.77 49	90.88 20	48.63 154	86.66 77	77.23 30	88.17 36	84.81 177

PS-MVSNAJ		70.51 144	69.70 148	72.93 171	81.52 97	55.79 125	74.92 242	79.00 179	55.04 246	69.88 153	78.66 311	47.05 179	82.19 194	61.61 179	79.58 136	80.83 290

MVS_111021_LR		69.50 177	68.78 169	71.65 207	78.38 173	59.33 61	74.82 244	70.11 324	58.08 164	67.83 200	84.68 171	41.96 240	76.34 325	65.62 134	77.54 181	79.30 319

ECVR-MVS		67.72 225	67.51 202	68.35 281	79.46 139	36.29 409	74.79 245	66.93 353	58.72 151	67.19 213	88.05 79	36.10 312	81.38 211	52.07 263	84.25 77	87.39 65

test_yl		69.69 166	69.13 159	71.36 221	78.37 175	45.74 311	74.71 246	80.20 158	57.91 173	70.01 150	83.83 195	42.44 235	82.87 175	54.97 238	79.72 133	85.48 145

DCV-MVSNet		69.69 166	69.13 159	71.36 221	78.37 175	45.74 311	74.71 246	80.20 158	57.91 173	70.01 150	83.83 195	42.44 235	82.87 175	54.97 238	79.72 133	85.48 145

TransMVSNet (Re)		64.72 274	64.33 264	65.87 318	75.22 266	38.56 382	74.66 248	75.08 270	58.90 149	61.79 314	82.63 220	51.18 120	78.07 283	43.63 341	55.87 414	80.99 288

BH-w/o		66.85 243	65.83 245	69.90 256	79.29 141	52.46 202	74.66 248	76.65 238	54.51 260	64.85 267	78.12 319	45.59 195	82.95 171	43.26 344	75.54 215	74.27 383

IMVS_0403		69.09 188	68.14 189	71.95 193	77.06 227	49.73 249	74.51 250	78.60 191	52.70 287	66.69 223	82.58 222	46.43 187	83.38 160	59.20 203	75.46 217	82.74 247

PVSNet_BlendedMVS		68.56 203	67.72 195	71.07 232	77.03 232	50.57 232	74.50 251	81.52 120	53.66 278	64.22 278	79.72 293	49.13 149	82.87 175	55.82 229	73.92 234	79.77 314

MonoMVSNet		64.15 283	63.31 281	66.69 299	70.51 367	44.12 330	74.47 252	74.21 283	57.81 175	63.03 291	76.62 349	38.33 288	77.31 301	54.22 246	60.59 396	78.64 326

c3_l		68.33 207	67.56 198	70.62 242	70.87 362	46.21 307	74.47 252	78.80 185	56.22 213	66.19 233	78.53 316	51.88 106	81.40 210	62.08 173	69.04 323	84.25 194

test2506		65.33 268	64.61 262	67.50 288	79.46 139	34.19 424	74.43 254	51.92 435	58.72 151	66.75 222	88.05 79	25.99 416	80.92 227	51.94 265	84.25 77	87.39 65

IMVS_0407		68.90 192	67.93 192	71.82 198	77.06 227	49.73 249	74.40 255	78.60 191	52.70 287	66.19 233	82.58 222	45.17 206	83.00 167	59.20 203	75.46 217	82.74 247

BH-RMVSNet		68.81 194	67.42 205	72.97 170	80.11 128	52.53 199	74.26 256	76.29 240	58.48 158	68.38 179	84.20 185	42.59 233	83.83 150	46.53 310	75.91 209	82.56 251

NR-MVSNet		69.54 174	68.85 166	71.59 209	78.05 189	43.81 333	74.20 257	80.86 147	65.18 14	62.76 297	84.52 179	52.35 99	83.59 156	50.96 275	70.78 287	87.37 67

UniMVSNet_ETH3D		67.60 227	67.07 220	69.18 270	77.39 216	42.29 347	74.18 258	75.59 253	60.37 112	66.77 221	86.06 140	37.64 295	78.93 273	52.16 262	73.49 245	86.32 110

VPA-MVSNet		69.02 189	69.47 153	67.69 287	77.42 215	41.00 363	74.04 259	79.68 165	60.06 122	69.26 166	84.81 167	51.06 123	77.58 295	54.44 245	74.43 228	84.48 188

miper_ehance_all_eth		68.03 215	67.24 215	70.40 246	70.54 366	46.21 307	73.98 260	78.68 189	55.07 243	66.05 237	77.80 329	52.16 102	81.31 213	61.53 183	69.32 317	83.67 220

hse-mvs2		71.04 131	69.86 145	74.60 111	79.58 136	57.12 105	73.96 261	75.25 262	60.40 109	74.81 67	81.95 247	45.54 196	82.90 172	70.41 93	66.83 345	83.77 216

1314		64.61 278	63.21 283	68.80 275	71.87 343	47.46 296	73.95 262	78.39 207	42.88 409	59.97 333	76.60 352	38.11 292	79.39 255	54.84 240	72.32 268	79.55 315

MVS		67.37 230	66.33 236	70.51 245	75.46 261	50.94 224	73.95 262	81.85 115	41.57 416	62.54 303	78.57 315	47.98 160	85.47 117	52.97 257	82.05 102	75.14 369

AUN-MVS		68.45 206	66.41 233	74.57 113	79.53 138	57.08 106	73.93 264	75.23 263	54.44 261	66.69 223	81.85 249	37.10 305	82.89 173	62.07 174	66.84 344	83.75 217

OurMVSNet-221017-0		61.37 319	58.63 334	69.61 260	72.05 339	48.06 287	73.93 264	72.51 305	47.23 369	54.74 390	80.92 269	21.49 434	81.24 215	48.57 294	56.22 413	79.53 316

test1111		67.21 232	67.14 219	67.42 290	79.24 145	34.76 418	73.89 266	65.65 363	58.71 153	66.96 218	87.95 83	36.09 313	80.53 234	52.03 264	83.79 83	86.97 80

cl22		67.47 229	66.45 229	70.54 244	69.85 382	46.49 303	73.85 267	77.35 225	55.07 243	65.51 248	77.92 325	47.64 167	81.10 219	61.58 181	69.32 317	84.01 203

TAMVS		66.78 246	65.27 257	71.33 224	79.16 150	53.67 163	73.84 268	69.59 330	52.32 296	65.28 252	81.72 253	44.49 215	77.40 299	42.32 352	78.66 162	82.92 242

WR-MVS		68.47 204	68.47 177	68.44 280	80.20 124	39.84 370	73.75 269	76.07 244	64.68 24	68.11 189	83.63 201	50.39 131	79.14 264	49.78 280	69.66 313	86.34 106

eth_miper_zixun_eth		67.63 226	66.28 239	71.67 206	71.60 346	48.33 282	73.68 270	77.88 213	55.80 221	65.91 240	78.62 314	47.35 176	82.88 174	59.45 199	66.25 349	83.81 212

guyue		68.10 214	67.23 217	70.71 241	73.67 309	49.27 264	73.65 271	76.04 246	55.62 227	67.84 199	82.26 237	41.24 258	78.91 274	61.01 185	73.72 238	83.94 205

TR-MVS		66.59 251	65.07 259	71.17 228	79.18 148	49.63 257	73.48 272	75.20 265	52.95 283	67.90 193	80.33 280	39.81 271	83.68 153	43.20 345	73.56 244	80.20 302

VortexMVS		66.41 254	65.50 251	69.16 271	73.75 305	48.14 284	73.41 273	78.28 209	53.73 275	64.98 266	78.33 317	40.62 263	79.07 266	58.88 207	67.50 339	80.26 301

fmvsm_s_conf0.1_n_2		69.64 170	69.01 164	71.52 210	71.66 345	51.04 222	73.39 274	67.14 351	55.02 249	75.11 57	87.64 88	42.94 231	77.01 308	75.55 48	72.63 264	86.52 99

fmvsm_s_conf0.5_n_2		69.82 162	69.27 158	71.46 212	72.00 340	51.08 221	73.30 275	67.79 345	55.06 245	75.24 55	87.51 89	44.02 219	77.00 309	75.67 46	72.86 258	86.31 113

cl____		67.18 235	66.26 240	69.94 253	70.20 373	45.74 311	73.30 275	76.83 235	55.10 238	65.27 253	79.57 296	47.39 174	80.53 234	59.41 201	69.22 321	83.53 226

DIV-MVS_self_test		67.18 235	66.26 240	69.94 253	70.20 373	45.74 311	73.29 277	76.83 235	55.10 238	65.27 253	79.58 295	47.38 175	80.53 234	59.43 200	69.22 321	83.54 225

AstraMVS		67.86 221	66.83 222	70.93 235	73.50 311	49.34 261	73.28 278	74.01 286	55.45 231	68.10 190	83.28 209	38.93 282	79.14 264	63.22 163	71.74 275	84.30 193

CDS-MVSNet		66.80 245	65.37 254	71.10 231	78.98 153	53.13 182	73.27 279	71.07 317	52.15 297	64.72 268	80.23 282	43.56 223	77.10 304	45.48 324	78.88 154	83.05 241
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
viewdifsd2359ckpt11		69.13 186	68.38 182	71.38 219	71.57 347	48.61 277	73.22 280	73.18 298	57.65 178	70.67 138	84.73 169	50.03 133	79.80 247	63.25 161	71.10 284	85.74 135

viewmsd2359difaftdt		69.13 186	68.38 182	71.38 219	71.57 347	48.61 277	73.22 280	73.18 298	57.65 178	70.67 138	84.73 169	50.03 133	79.80 247	63.25 161	71.10 284	85.74 135

diffmvs_AUTHOR		71.02 132	70.87 126	71.45 214	69.89 380	48.97 271	73.16 282	78.33 208	57.79 177	72.11 121	85.26 163	51.84 108	77.89 288	71.00 90	78.47 168	87.49 59

pmmvs6		63.69 288	62.82 288	66.27 307	70.63 364	39.27 377	73.13 283	75.47 258	52.69 292	59.75 339	82.30 235	39.71 272	77.03 307	47.40 302	64.35 365	82.53 253

IB-MVS	56.42 12	65.40 267	62.73 289	73.40 161	74.89 273	52.78 192	73.09 284	75.13 266	55.69 223	58.48 355	73.73 386	32.86 349	86.32 91	50.63 276	70.11 301	81.10 285
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
diffmvs		70.69 141	70.43 134	71.46 212	69.45 387	48.95 272	72.93 285	78.46 201	57.27 184	71.69 125	83.97 193	51.48 116	77.92 287	70.70 92	77.95 176	87.53 58
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
V42		68.65 198	67.35 209	72.56 179	68.93 393	50.18 241	72.90 286	79.47 170	56.92 192	69.45 160	80.26 281	46.29 189	82.99 168	64.07 145	67.82 336	84.53 186

miper_enhance_ethall		67.11 238	66.09 242	70.17 250	69.21 390	45.98 309	72.85 287	78.41 205	51.38 308	65.65 246	75.98 363	51.17 121	81.25 214	60.82 187	69.32 317	83.29 232

thres100view900		63.28 293	62.41 292	65.89 316	77.31 219	38.66 381	72.65 288	69.11 337	57.07 188	62.45 306	81.03 266	37.01 307	79.17 260	31.84 419	73.25 252	79.83 311

testdata1							72.65 288		60.50 106

FE-MVS		65.91 259	63.33 280	73.63 150	77.36 217	51.95 213	72.62 290	75.81 248	53.70 276	65.31 251	78.96 307	28.81 392	86.39 88	43.93 335	73.48 246	82.55 252

pm-mvs1		65.24 269	64.97 260	66.04 313	72.38 333	39.40 376	72.62 290	75.63 251	55.53 228	62.35 310	83.18 213	47.45 172	76.47 323	49.06 290	66.54 347	82.24 261

test222					83.14 75	58.68 80	72.57 292	63.45 385	41.78 412	67.56 206	86.12 137	37.13 304			78.73 159	74.98 373

PVSNet_Blended		68.59 199	67.72 195	71.19 226	77.03 232	50.57 232	72.51 293	81.52 120	51.91 300	64.22 278	77.77 332	49.13 149	82.87 175	55.82 229	79.58 136	80.14 304

EU-MVSNet		55.61 369	54.41 372	59.19 376	65.41 417	33.42 429	72.44 294	71.91 312	28.81 444	51.27 413	73.87 385	24.76 423	69.08 368	43.04 346	58.20 404	75.06 370

thres600view7		63.30 292	62.27 294	66.41 303	77.18 222	38.87 379	72.35 295	69.11 337	56.98 191	62.37 309	80.96 268	37.01 307	79.00 271	31.43 426	73.05 256	81.36 276

pmmvs-eth3d		58.81 340	56.31 357	66.30 306	67.61 401	52.42 204	72.30 296	64.76 371	43.55 402	54.94 388	74.19 381	28.95 389	72.60 343	43.31 342	57.21 408	73.88 387

viewmambaseed2359dif		68.91 191	68.18 187	71.11 230	70.21 372	48.05 289	72.28 297	75.90 247	51.96 299	70.93 135	84.47 182	51.37 117	78.59 276	61.55 182	74.97 222	86.68 91

cascas		65.98 258	63.42 278	73.64 149	77.26 220	52.58 198	72.26 298	77.21 228	48.56 345	61.21 321	74.60 378	32.57 361	85.82 107	50.38 278	76.75 198	82.52 255

VPNet		67.52 228	68.11 190	65.74 319	79.18 148	36.80 401	72.17 299	72.83 303	62.04 76	67.79 202	85.83 148	48.88 153	76.60 320	51.30 271	72.97 257	83.81 212

MS-PatchMatch		62.42 304	61.46 304	65.31 328	75.21 267	52.10 207	72.05 300	74.05 285	46.41 377	57.42 365	74.36 379	34.35 330	77.57 296	45.62 320	73.67 239	66.26 436

mvs_anonymous		68.03 215	67.51 202	69.59 261	72.08 338	44.57 325	71.99 301	75.23 263	51.67 301	67.06 216	82.57 226	54.68 61	77.94 285	56.56 224	75.71 213	86.26 115

patch_mono-2		69.85 161	71.09 122	66.16 309	79.11 151	54.80 146	71.97 302	74.31 279	53.50 279	70.90 136	84.17 186	57.63 33	63.31 402	66.17 126	82.02 103	80.38 299

tfpn200view9		63.18 295	62.18 296	66.21 308	76.85 235	39.62 373	71.96 303	69.44 333	56.63 197	62.61 301	79.83 288	37.18 301	79.17 260	31.84 419	73.25 252	79.83 311

thres400		63.31 291	62.18 296	66.72 296	76.85 235	39.62 373	71.96 303	69.44 333	56.63 197	62.61 301	79.83 288	37.18 301	79.17 260	31.84 419	73.25 252	81.36 276

SD_0403		63.07 297	63.49 277	61.82 355	75.16 269	31.14 441	71.89 305	73.47 292	53.34 281	58.22 357	81.81 251	45.17 206	73.86 338	37.43 383	74.87 224	80.45 296

baseline1		63.81 287	63.87 270	63.62 342	76.29 246	36.36 404	71.78 306	67.29 349	56.05 216	64.23 277	82.95 215	47.11 178	74.41 335	47.30 304	61.85 385	80.10 305

baseline2		63.42 290	61.26 309	69.89 257	72.55 328	47.62 294	71.54 307	68.38 341	50.11 324	54.82 389	75.55 368	43.06 229	80.96 224	48.13 298	67.16 343	81.11 284

pmmvs4		61.48 318	59.39 325	67.76 286	71.57 347	53.86 158	71.42 308	65.34 366	44.20 396	59.46 341	77.92 325	35.90 314	74.71 333	43.87 337	64.87 359	74.71 379

1112_ss		64.00 286	63.36 279	65.93 315	79.28 143	42.58 345	71.35 309	72.36 308	46.41 377	60.55 327	77.89 327	46.27 190	73.28 340	46.18 313	69.97 304	81.92 267

thisisatest0515		65.83 260	63.50 276	72.82 175	73.75 305	49.50 258	71.32 310	73.12 302	49.39 334	63.82 280	76.50 355	34.95 323	84.84 133	53.20 256	75.49 216	84.13 200

CostFormer		64.04 285	62.51 290	68.61 278	71.88 342	45.77 310	71.30 311	70.60 321	47.55 363	64.31 274	76.61 351	41.63 249	79.62 252	49.74 282	69.00 324	80.42 297

tfpnnormal		62.47 303	61.63 302	64.99 331	74.81 278	39.01 378	71.22 312	73.72 290	55.22 237	60.21 328	80.09 286	41.26 257	76.98 311	30.02 433	68.09 334	78.97 324

IterMVS		62.79 300	61.27 308	67.35 292	69.37 388	52.04 210	71.17 313	68.24 343	52.63 293	59.82 336	76.91 344	37.32 300	72.36 345	52.80 258	63.19 375	77.66 339
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Vis-MVSNet (Re-imp)		63.69 288	63.88 269	63.14 347	74.75 280	31.04 442	71.16 314	63.64 383	56.32 209	59.80 337	84.99 164	44.51 213	75.46 330	39.12 374	80.62 120	82.92 242

IterMVS-SCA-FT		62.49 302	61.52 303	65.40 325	71.99 341	50.80 229	71.15 315	69.63 329	45.71 385	60.61 326	77.93 324	37.45 297	65.99 391	55.67 233	63.50 372	79.42 317

Anonymous202405211		66.84 244	65.99 243	69.40 265	80.19 125	42.21 349	71.11 316	71.31 315	58.80 150	67.90 193	86.39 128	29.83 382	79.65 250	49.60 286	78.78 157	86.33 108

Anonymous20240521		55.30 370	54.41 372	57.96 387	60.92 442	41.73 353	71.09 317	71.06 318	41.18 417	48.65 427	73.31 389	16.93 440	59.25 418	42.54 350	64.01 366	72.90 391

tpm2		62.07 309	60.10 321	67.99 284	72.79 323	43.86 332	71.05 318	66.85 354	43.14 407	62.77 296	75.39 372	38.32 289	80.80 230	41.69 357	68.88 325	79.32 318

TDRefinement		53.44 384	50.72 394	61.60 357	64.31 423	46.96 300	70.89 319	65.27 368	41.78 412	44.61 440	77.98 322	11.52 455	66.36 388	28.57 439	51.59 430	71.49 412

XVG-ACMP-BASELINE		64.36 282	62.23 295	70.74 239	72.35 334	52.45 203	70.80 320	78.45 202	53.84 272	59.87 335	81.10 264	16.24 443	79.32 256	55.64 235	71.76 274	80.47 295

mmtdpeth		60.40 327	59.12 328	64.27 337	69.59 384	48.99 269	70.67 321	70.06 325	54.96 250	62.78 295	73.26 391	27.00 409	67.66 377	58.44 213	45.29 443	76.16 358

XVG-OURS-SEG-HR		68.81 194	67.47 204	72.82 175	74.40 292	56.87 108	70.59 322	79.04 178	54.77 254	66.99 217	86.01 142	39.57 273	78.21 281	62.54 170	73.33 250	83.37 229

VNet		69.68 168	70.19 140	68.16 283	79.73 133	41.63 356	70.53 323	77.38 224	60.37 112	70.69 137	86.63 117	51.08 122	77.09 305	53.61 252	81.69 111	85.75 134

GA-MVS		65.53 264	63.70 273	71.02 234	70.87 362	48.10 285	70.48 324	74.40 277	56.69 194	64.70 269	76.77 346	33.66 340	81.10 219	55.42 237	70.32 297	83.87 210

MSDG		61.81 314	59.23 326	69.55 264	72.64 325	52.63 197	70.45 325	75.81 248	51.38 308	53.70 400	76.11 358	29.52 384	81.08 221	37.70 381	65.79 353	74.93 374

ab-mvs		66.65 248	66.42 232	67.37 291	76.17 248	41.73 353	70.41 326	76.14 243	53.99 267	65.98 238	83.51 206	49.48 141	76.24 326	48.60 293	73.46 247	84.14 199

fmvsm_s_conf0.5_n_7		69.54 174	69.67 149	69.15 272	73.47 312	51.41 219	70.35 327	73.34 294	57.05 189	68.41 177	85.83 148	49.86 136	72.84 342	71.86 82	76.83 196	83.19 235

EGC-MVSNET		42.47 414	38.48 422	54.46 405	74.33 294	48.73 275	70.33 328	51.10 438	0.03 475	0.18 476	67.78 427	13.28 449	66.49 387	18.91 458	50.36 434	48.15 455

MVSTER		67.16 237	65.58 250	71.88 196	70.37 371	49.70 253	70.25 329	78.45 202	51.52 305	69.16 168	80.37 277	38.45 286	82.50 188	60.19 191	71.46 279	83.44 228

reproduce_monomvs		62.56 301	61.20 311	66.62 300	70.62 365	44.30 327	70.13 330	73.13 301	54.78 253	61.13 322	76.37 356	25.63 419	75.63 329	58.75 210	60.29 397	79.93 307

XVG-OURS		68.76 197	67.37 207	72.90 172	74.32 295	57.22 98	70.09 331	78.81 184	55.24 236	67.79 202	85.81 151	36.54 310	78.28 280	62.04 175	75.74 212	83.19 235

HY-MVS	56.14 13	64.55 279	63.89 268	66.55 301	74.73 281	41.02 360	69.96 332	74.43 276	49.29 336	61.66 316	80.92 269	47.43 173	76.68 319	44.91 329	71.69 276	81.94 266

AllTest		57.08 354	54.65 368	64.39 335	71.44 351	49.03 266	69.92 333	67.30 347	45.97 382	47.16 431	79.77 290	17.47 437	67.56 380	33.65 407	59.16 401	76.57 354

testing3		56.54 358	55.92 360	58.41 381	77.52 212	27.93 452	69.72 334	56.36 422	54.75 255	58.63 353	77.80 329	20.88 435	71.75 352	25.31 449	62.25 382	75.53 365

sc_t1		59.76 332	57.84 343	65.54 321	74.87 275	42.95 343	69.61 335	64.16 378	48.90 341	58.68 350	77.12 339	28.19 397	72.35 346	43.75 340	55.28 416	81.31 279

thres200		62.20 308	61.16 312	65.34 327	75.38 264	39.99 369	69.60 336	69.29 335	55.64 226	61.87 313	76.99 342	37.07 306	78.96 272	31.28 427	73.28 251	77.06 348

tpmrst		58.24 345	58.70 333	56.84 392	66.97 405	34.32 422	69.57 337	61.14 403	47.17 370	58.58 354	71.60 402	41.28 256	60.41 412	49.20 288	62.84 377	75.78 362

PatchmatchNet		59.84 331	58.24 337	64.65 333	73.05 319	46.70 302	69.42 338	62.18 398	47.55 363	58.88 348	71.96 399	34.49 328	69.16 367	42.99 347	63.60 370	78.07 331
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
WB-MVSnew		59.66 334	59.69 323	59.56 369	75.19 268	35.78 413	69.34 339	64.28 375	46.88 373	61.76 315	75.79 364	40.61 264	65.20 394	32.16 415	71.21 281	77.70 338

GG-mvs-BLEND				62.34 352	71.36 355	37.04 399	69.20 340	57.33 419		54.73 391	65.48 438	30.37 373	77.82 290	34.82 403	74.93 223	72.17 404

HyFIR lowres test		65.67 262	63.01 285	73.67 146	79.97 130	55.65 128	69.07 341	75.52 255	42.68 410	63.53 283	77.95 323	40.43 265	81.64 203	46.01 315	71.91 273	83.73 218

UWE-MVS		60.18 328	59.78 322	61.39 361	77.67 203	33.92 427	69.04 342	63.82 381	48.56 345	64.27 275	77.64 334	27.20 406	70.40 362	33.56 410	76.24 202	79.83 311

test_post1							68.67 343				3.64 473	32.39 363	69.49 366	44.17 331

tt0320		58.59 341	56.81 351	63.92 340	75.46 261	41.32 358	68.63 344	64.06 379	47.05 371	56.19 375	74.19 381	30.34 374	71.36 353	39.92 369	55.45 415	79.09 320

testing222		62.29 307	61.31 307	65.25 329	77.87 194	38.53 383	68.34 345	66.31 359	56.37 208	63.15 290	77.58 335	28.47 394	76.18 328	37.04 387	76.65 200	81.05 287

tt0320-xc		58.33 344	56.41 356	64.08 338	75.79 253	41.34 357	68.30 346	62.72 391	47.90 358	56.29 374	74.16 383	28.53 393	71.04 356	41.50 361	52.50 428	79.88 309

Test_1112_low_res		62.32 305	61.77 300	64.00 339	79.08 152	39.53 375	68.17 347	70.17 323	43.25 405	59.03 347	79.90 287	44.08 217	71.24 355	43.79 338	68.42 331	81.25 280

tpm cat1		59.25 338	56.95 348	66.15 310	72.19 337	46.96 300	68.09 348	65.76 362	40.03 426	57.81 361	70.56 409	38.32 289	74.51 334	38.26 379	61.50 388	77.00 350

ppachtmachnet_test		58.06 348	55.38 364	66.10 312	69.51 385	48.99 269	68.01 349	66.13 361	44.50 393	54.05 398	70.74 408	32.09 366	72.34 347	36.68 392	56.71 412	76.99 352

tpmvs		58.47 342	56.95 348	63.03 349	70.20 373	41.21 359	67.90 350	67.23 350	49.62 331	54.73 391	70.84 407	34.14 331	76.24 326	36.64 393	61.29 389	71.64 409

testing91		64.46 280	63.80 271	66.47 302	78.43 172	40.06 368	67.63 351	69.59 330	59.06 145	63.18 288	78.05 321	34.05 332	76.99 310	48.30 296	75.87 210	82.37 259

CL-MVSNet_self_test		61.53 316	60.94 315	63.30 345	68.95 392	36.93 400	67.60 352	72.80 304	55.67 224	59.95 334	76.63 348	45.01 209	72.22 349	39.74 371	62.09 384	80.74 293

testing11		62.81 299	61.90 299	65.54 321	78.38 173	40.76 365	67.59 353	66.78 355	55.48 229	60.13 329	77.11 340	31.67 368	76.79 315	45.53 322	74.45 227	79.06 321

test_vis1_n_1920		58.86 339	59.06 329	58.25 382	63.76 424	43.14 340	67.49 354	66.36 358	40.22 424	65.89 242	71.95 400	31.04 369	59.75 416	59.94 194	64.90 358	71.85 407

tpm		57.34 352	58.16 338	54.86 402	71.80 344	34.77 417	67.47 355	56.04 426	48.20 353	60.10 330	76.92 343	37.17 303	53.41 445	40.76 363	65.01 357	76.40 356

testing99		64.05 284	63.29 282	66.34 304	78.17 185	39.76 372	67.33 356	68.00 344	58.60 155	63.03 291	78.10 320	32.57 361	76.94 312	48.22 297	75.58 214	82.34 260

FE-MVSNET		55.16 374	53.75 380	59.41 371	65.29 418	33.20 431	67.21 357	66.21 360	48.39 351	49.56 425	73.53 388	29.03 388	72.51 344	30.38 431	54.10 422	72.52 396

gg-mvs-nofinetune		57.86 349	56.43 355	62.18 353	72.62 326	35.35 414	66.57 358	56.33 423	50.65 318	57.64 362	57.10 450	30.65 371	76.36 324	37.38 384	78.88 154	74.82 376

TinyColmap		54.14 377	51.72 389	61.40 360	66.84 407	41.97 350	66.52 359	68.51 340	44.81 389	42.69 445	75.77 365	11.66 453	72.94 341	31.96 417	56.77 411	69.27 430

pmmvs5		56.47 360	55.68 362	58.86 378	61.41 436	36.71 402	66.37 360	62.75 390	40.38 423	53.70 400	76.62 349	34.56 326	67.05 383	40.02 367	65.27 355	72.83 392

CHOSEN 1792x2688		65.08 272	62.84 287	71.82 198	81.49 99	56.26 114	66.32 361	74.20 284	40.53 422	63.16 289	78.65 312	41.30 254	77.80 291	45.80 317	74.09 231	81.40 275

our_test_3		56.49 359	54.42 371	62.68 351	69.51 385	45.48 316	66.08 362	61.49 401	44.11 399	50.73 419	69.60 419	33.05 345	68.15 372	38.38 378	56.86 409	74.40 381

mvs5depth		55.64 368	53.81 379	61.11 364	59.39 445	40.98 364	65.89 363	68.28 342	50.21 323	58.11 359	75.42 371	17.03 439	67.63 379	43.79 338	46.21 440	74.73 378

PM-MVS		52.33 388	50.19 397	58.75 379	62.10 433	45.14 319	65.75 364	40.38 461	43.60 401	53.52 404	72.65 392	9.16 461	65.87 392	50.41 277	54.18 421	65.24 438

D2MVS		62.30 306	60.29 320	68.34 282	66.46 411	48.42 281	65.70 365	73.42 293	47.71 361	58.16 358	75.02 374	30.51 372	77.71 294	53.96 249	71.68 277	78.90 325

MIMVSNet1		55.17 373	54.31 374	57.77 389	70.03 377	32.01 437	65.68 366	64.81 370	49.19 337	46.75 434	76.00 360	25.53 420	64.04 398	28.65 438	62.13 383	77.26 346

PatchMatch-RL		56.25 363	54.55 370	61.32 362	77.06 227	56.07 118	65.57 367	54.10 432	44.13 398	53.49 406	71.27 406	25.20 421	66.78 385	36.52 395	63.66 369	61.12 440

Syy-MVS		56.00 365	56.23 358	55.32 399	74.69 282	26.44 458	65.52 368	57.49 417	50.97 315	56.52 371	72.18 395	39.89 269	68.09 373	24.20 450	64.59 363	71.44 413

myMVS_eth3d		54.86 376	54.61 369	55.61 398	74.69 282	27.31 455	65.52 368	57.49 417	50.97 315	56.52 371	72.18 395	21.87 433	68.09 373	27.70 441	64.59 363	71.44 413

test-LLR		58.15 347	58.13 340	58.22 383	68.57 394	44.80 321	65.46 370	57.92 414	50.08 325	55.44 381	69.82 416	32.62 358	57.44 428	49.66 284	73.62 241	72.41 400

TESTMET0.1,1		55.28 371	54.90 367	56.42 394	66.56 409	43.67 334	65.46 370	56.27 424	39.18 429	53.83 399	67.44 428	24.21 425	55.46 439	48.04 299	73.11 255	70.13 424

test-mter		56.42 361	55.82 361	58.22 383	68.57 394	44.80 321	65.46 370	57.92 414	39.94 427	55.44 381	69.82 416	21.92 430	57.44 428	49.66 284	73.62 241	72.41 400

SDMVSNet		68.03 215	68.10 191	67.84 285	77.13 223	48.72 276	65.32 373	79.10 175	58.02 167	65.08 260	82.55 227	47.83 163	73.40 339	63.92 149	73.92 234	81.41 273

CR-MVSNet		59.91 330	57.90 342	65.96 314	69.96 378	52.07 208	65.31 374	63.15 388	42.48 411	59.36 342	74.84 375	35.83 315	70.75 358	45.50 323	64.65 361	75.06 370

RPMNet		61.53 316	58.42 335	70.86 236	69.96 378	52.07 208	65.31 374	81.36 127	43.20 406	59.36 342	70.15 414	35.37 318	85.47 117	36.42 396	64.65 361	75.06 370

USDC		56.35 362	54.24 375	62.69 350	64.74 420	40.31 366	65.05 376	73.83 289	43.93 400	47.58 429	77.71 333	15.36 446	75.05 332	38.19 380	61.81 386	72.70 393

MDTV_nov1_ep13			57.00 347		72.73 324	38.26 385	65.02 377	64.73 372	44.74 390	55.46 380	72.48 393	32.61 360	70.47 359	37.47 382	67.75 337

ETVMVS		59.51 337	58.81 330	61.58 358	77.46 214	34.87 415	64.94 378	59.35 408	54.06 266	61.08 323	76.67 347	29.54 383	71.87 351	32.16 415	74.07 232	78.01 336

CMPMVS	42.80 21	57.81 350	55.97 359	63.32 344	60.98 440	47.38 297	64.66 379	69.50 332	32.06 440	46.83 433	77.80 329	29.50 385	71.36 353	48.68 292	73.75 237	71.21 416
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
WBMVS		60.54 324	60.61 318	60.34 367	78.00 191	35.95 411	64.55 380	64.89 369	49.63 330	63.39 285	78.70 309	33.85 337	67.65 378	42.10 354	70.35 296	77.43 342

IMVS_0404		64.63 277	64.22 265	65.88 317	77.06 227	49.73 249	64.40 381	78.60 191	52.70 287	53.16 407	82.58 222	34.82 324	65.16 395	59.20 203	75.46 217	82.74 247

RPSCF		55.80 367	54.22 376	60.53 366	65.13 419	42.91 344	64.30 382	57.62 416	36.84 433	58.05 360	82.28 236	28.01 398	56.24 436	37.14 386	58.61 403	82.44 258

XXY-MVS		60.68 321	61.67 301	57.70 390	70.43 369	38.45 384	64.19 383	66.47 356	48.05 356	63.22 286	80.86 271	49.28 146	60.47 411	45.25 328	67.28 342	74.19 384

FMVSNet5		55.86 366	54.93 366	58.66 380	71.05 360	36.35 405	64.18 384	62.48 393	46.76 375	50.66 420	74.73 377	25.80 417	64.04 398	33.11 411	65.57 354	75.59 364

UBG		59.62 336	59.53 324	59.89 368	78.12 186	35.92 412	64.11 385	60.81 405	49.45 333	61.34 319	75.55 368	33.05 345	67.39 382	38.68 376	74.62 225	76.35 357

testing3-2		62.06 310	62.36 293	61.17 363	79.29 141	30.31 444	64.09 386	63.49 384	63.50 44	62.84 294	82.22 238	32.35 365	69.02 369	40.01 368	73.43 248	84.17 198

icg_test_0407_2		66.41 254	66.75 224	65.37 326	77.06 227	49.73 249	63.79 387	78.60 191	52.70 287	66.19 233	82.58 222	45.17 206	63.65 401	59.20 203	75.46 217	82.74 247

test_cas_vis1_n_1920		56.91 355	56.71 352	57.51 391	59.13 446	45.40 317	63.58 388	61.29 402	36.24 434	67.14 215	71.85 401	29.89 381	56.69 432	57.65 216	63.58 371	70.46 421

UWE-MVS-28		52.25 389	52.35 387	51.93 423	66.99 404	22.79 466	63.48 389	48.31 447	46.78 374	52.73 409	76.11 358	27.78 401	57.82 427	20.58 456	68.41 332	75.17 368

SCA		60.49 325	58.38 336	66.80 295	74.14 301	48.06 287	63.35 390	63.23 387	49.13 338	59.33 345	72.10 397	37.45 297	74.27 336	44.17 331	62.57 379	78.05 332

myMVS_eth3d28		60.66 322	61.04 313	59.51 370	77.32 218	31.58 439	63.11 391	63.87 380	59.00 146	60.90 325	78.26 318	32.69 356	66.15 390	36.10 398	78.13 172	80.81 291

Patchmtry		57.16 353	56.47 354	59.23 374	69.17 391	34.58 420	62.98 392	63.15 388	44.53 392	56.83 368	74.84 375	35.83 315	68.71 370	40.03 366	60.91 390	74.39 382

Anonymous20231206		55.10 375	55.30 365	54.48 404	69.81 383	33.94 426	62.91 393	62.13 399	41.08 418	55.18 385	75.65 366	32.75 353	56.59 434	30.32 432	67.86 335	72.91 390

sd_testset		64.46 280	64.45 263	64.51 334	77.13 223	42.25 348	62.67 394	72.11 310	58.02 167	65.08 260	82.55 227	41.22 259	69.88 365	47.32 303	73.92 234	81.41 273

MIMVSNet		57.35 351	57.07 346	58.22 383	74.21 298	37.18 395	62.46 395	60.88 404	48.88 342	55.29 384	75.99 362	31.68 367	62.04 407	31.87 418	72.35 267	75.43 367

dp		51.89 391	51.60 390	52.77 417	68.44 397	32.45 436	62.36 396	54.57 429	44.16 397	49.31 426	67.91 424	28.87 391	56.61 433	33.89 406	54.89 418	69.24 431

EPMVS		53.96 378	53.69 381	54.79 403	66.12 414	31.96 438	62.34 397	49.05 443	44.42 395	55.54 379	71.33 405	30.22 376	56.70 431	41.65 359	62.54 380	75.71 363

pmmvs3		44.92 409	41.95 416	53.86 407	52.58 455	43.55 335	62.11 398	46.90 453	26.05 451	40.63 447	60.19 446	11.08 458	57.91 426	31.83 422	46.15 441	60.11 441

test_vis1_n		49.89 400	48.69 402	53.50 411	53.97 450	37.38 394	61.53 399	47.33 451	28.54 445	59.62 340	67.10 432	13.52 448	52.27 449	49.07 289	57.52 406	70.84 419

PVSNet	50.76 19	58.40 343	57.39 344	61.42 359	75.53 260	44.04 331	61.43 400	63.45 385	47.04 372	56.91 367	73.61 387	27.00 409	64.76 396	39.12 374	72.40 266	75.47 366

LCM-MVSNet-Re		61.88 313	61.35 306	63.46 343	74.58 287	31.48 440	61.42 401	58.14 413	58.71 153	53.02 408	79.55 297	43.07 228	76.80 314	45.69 318	77.96 175	82.11 265

test20.03		53.87 380	54.02 377	53.41 413	61.47 435	28.11 451	61.30 402	59.21 409	51.34 310	52.09 411	77.43 336	33.29 344	58.55 423	29.76 434	60.27 398	73.58 388

MDTV_nov1_ep13_2view						25.89 460	61.22 403		40.10 425	51.10 414		32.97 348		38.49 377		78.61 327

PMMVS		53.96 378	53.26 384	56.04 395	62.60 431	50.92 226	61.17 404	56.09 425	32.81 439	53.51 405	66.84 433	34.04 333	59.93 415	44.14 333	68.18 333	57.27 448

test_fmvs1_n		51.37 393	50.35 396	54.42 406	52.85 453	37.71 391	61.16 405	51.93 434	28.15 446	63.81 281	69.73 418	13.72 447	53.95 443	51.16 272	60.65 394	71.59 410

WTY-MVS		59.75 333	60.39 319	57.85 388	72.32 335	37.83 389	61.05 406	64.18 376	45.95 384	61.91 312	79.11 306	47.01 182	60.88 410	42.50 351	69.49 316	74.83 375

dmvs_testset		50.16 398	51.90 388	44.94 434	66.49 410	11.78 474	61.01 407	51.50 436	51.17 313	50.30 423	67.44 428	39.28 276	60.29 413	22.38 453	57.49 407	62.76 439

Patchmatch-RL test		58.16 346	55.49 363	66.15 310	67.92 400	48.89 273	60.66 408	51.07 439	47.86 360	59.36 342	62.71 444	34.02 334	72.27 348	56.41 225	59.40 400	77.30 344

test_fmvs1		51.32 395	50.48 395	53.81 408	53.57 451	37.51 393	60.63 409	51.16 437	28.02 448	63.62 282	69.23 421	16.41 442	53.93 444	51.01 273	60.70 393	69.99 425

LTVRE_ROB	55.42 16	63.15 296	61.23 310	68.92 274	76.57 242	47.80 290	59.92 410	76.39 239	54.35 262	58.67 351	82.46 232	29.44 386	81.49 208	42.12 353	71.14 282	77.46 341
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
SSC-MVS3.2		60.57 323	61.39 305	58.12 386	74.29 296	32.63 434	59.52 411	65.53 365	59.90 126	62.45 306	79.75 292	41.96 240	63.90 400	39.47 372	69.65 315	77.84 337

test0.0.03 1		53.32 385	53.59 382	52.50 419	62.81 430	29.45 446	59.51 412	54.11 431	50.08 325	54.40 395	74.31 380	32.62 358	55.92 437	30.50 430	63.95 368	72.15 405

UnsupCasMVSNet_eth		53.16 387	52.47 385	55.23 400	59.45 444	33.39 430	59.43 413	69.13 336	45.98 381	50.35 422	72.32 394	29.30 387	58.26 425	42.02 356	44.30 444	74.05 385

MVS-HIRNet		45.52 408	44.48 410	48.65 428	68.49 396	34.05 425	59.41 414	44.50 456	27.03 449	37.96 456	50.47 458	26.16 415	64.10 397	26.74 446	59.52 399	47.82 457

testgi		51.90 390	52.37 386	50.51 426	60.39 443	23.55 465	58.42 415	58.15 412	49.03 339	51.83 412	79.21 305	22.39 428	55.59 438	29.24 437	62.64 378	72.40 402

dmvs_re		56.77 357	56.83 350	56.61 393	69.23 389	41.02 360	58.37 416	64.18 376	50.59 320	57.45 364	71.42 403	35.54 317	58.94 421	37.23 385	67.45 340	69.87 426

PatchT		53.17 386	53.44 383	52.33 420	68.29 398	25.34 462	58.21 417	54.41 430	44.46 394	54.56 393	69.05 422	33.32 343	60.94 409	36.93 388	61.76 387	70.73 420

WB-MVS		43.26 411	43.41 411	42.83 438	63.32 427	10.32 476	58.17 418	45.20 454	45.42 386	40.44 449	67.26 431	34.01 335	58.98 420	11.96 467	24.88 461	59.20 442

sss		56.17 364	56.57 353	54.96 401	66.93 406	36.32 407	57.94 419	61.69 400	41.67 414	58.64 352	75.32 373	38.72 284	56.25 435	42.04 355	66.19 350	72.31 403

ttmdpeth		45.56 407	42.95 412	53.39 414	52.33 456	29.15 447	57.77 420	48.20 448	31.81 441	49.86 424	77.21 338	8.69 462	59.16 419	27.31 442	33.40 458	71.84 408

test_fmvs2		48.69 402	47.49 407	52.29 421	48.63 460	33.06 433	57.76 421	48.05 449	25.71 452	59.76 338	69.60 419	11.57 454	52.23 450	49.45 287	56.86 409	71.58 411

KD-MVS_self_test		55.22 372	53.89 378	59.21 375	57.80 449	27.47 454	57.75 422	74.32 278	47.38 365	50.90 416	70.00 415	28.45 395	70.30 363	40.44 364	57.92 405	79.87 310

UnsupCasMVSNet_bld		50.07 399	48.87 400	53.66 409	60.97 441	33.67 428	57.62 423	64.56 373	39.47 428	47.38 430	64.02 442	27.47 403	59.32 417	34.69 404	43.68 445	67.98 434

mamv4		56.85 356	58.00 341	53.43 412	72.46 332	54.47 148	57.56 424	54.74 427	38.81 430	57.42 365	79.45 300	47.57 169	38.70 465	60.88 186	53.07 425	67.11 435

SSC-MVS		41.96 416	41.99 415	41.90 439	62.46 432	9.28 478	57.41 425	44.32 457	43.38 403	38.30 455	66.45 434	32.67 357	58.42 424	10.98 468	21.91 464	57.99 446

ANet_high		41.38 417	37.47 424	53.11 415	39.73 471	24.45 463	56.94 426	69.69 327	47.65 362	26.04 463	52.32 453	12.44 451	62.38 406	21.80 454	10.61 472	72.49 397

MDA-MVSNet-bldmvs		53.87 380	50.81 393	63.05 348	66.25 412	48.58 279	56.93 427	63.82 381	48.09 355	41.22 446	70.48 412	30.34 374	68.00 376	34.24 405	45.92 442	72.57 395

test123		4.73 443	6.30 446	0.02 458	0.01 481	0.01 483	56.36 428	0.00 482	0.01 476	0.04 477	0.21 477	0.01 480	0.00 477	0.03 477	0.00 475	0.04 473

miper_lstm_enhance		62.03 311	60.88 316	65.49 324	66.71 408	46.25 305	56.29 429	75.70 250	50.68 317	61.27 320	75.48 370	40.21 266	68.03 375	56.31 226	65.25 356	82.18 262

KD-MVS_2432*1600		53.45 382	51.50 391	59.30 372	62.82 428	37.14 396	55.33 430	71.79 313	47.34 367	55.09 386	70.52 410	21.91 431	70.45 360	35.72 400	42.97 446	70.31 422

miper_refine_blended		53.45 382	51.50 391	59.30 372	62.82 428	37.14 396	55.33 430	71.79 313	47.34 367	55.09 386	70.52 410	21.91 431	70.45 360	35.72 400	42.97 446	70.31 422

LF4IMVS		42.95 412	42.26 414	45.04 432	48.30 461	32.50 435	54.80 432	48.49 445	28.03 447	40.51 448	70.16 413	9.24 460	43.89 460	31.63 423	49.18 438	58.72 444

PMVS	28.69 22	36.22 424	33.29 429	45.02 433	36.82 473	35.98 410	54.68 433	48.74 444	26.31 450	21.02 466	51.61 455	2.88 474	60.10 414	9.99 471	47.58 439	38.99 464
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVStest1		42.65 413	39.29 420	52.71 418	47.26 463	34.58 420	54.41 434	50.84 442	23.35 454	39.31 454	74.08 384	12.57 450	55.09 440	23.32 451	28.47 460	68.47 433

PVSNet_0	43.31 20	47.46 406	45.64 409	52.92 416	67.60 402	44.65 323	54.06 435	54.64 428	41.59 415	46.15 436	58.75 447	30.99 370	58.66 422	32.18 414	24.81 462	55.46 450

testmvs		4.52 444	6.03 447	0.01 459	0.01 481	0.00 484	53.86 436	0.00 482	0.01 476	0.04 477	0.27 476	0.00 481	0.00 477	0.04 476	0.00 475	0.03 474

test_fmvs3		44.30 410	42.55 413	49.55 427	42.83 465	27.15 457	53.03 437	44.93 455	22.03 460	53.69 402	64.94 439	4.21 469	49.63 452	47.47 300	49.82 435	71.88 406

APD_test1		37.39 423	34.94 426	44.72 435	48.88 459	33.19 432	52.95 438	44.00 458	19.49 461	27.28 462	58.59 448	3.18 473	52.84 447	18.92 457	41.17 449	48.14 456

dongtai		34.52 426	34.94 426	33.26 448	61.06 439	16.00 473	52.79 439	23.78 474	40.71 421	39.33 453	48.65 462	16.91 441	48.34 454	12.18 466	19.05 466	35.44 465

YYNet1		50.73 396	48.96 398	56.03 396	61.10 438	41.78 352	51.94 440	56.44 421	40.94 420	44.84 438	67.80 426	30.08 379	55.08 441	36.77 389	50.71 432	71.22 415

MDA-MVSNet_test_wron		50.71 397	48.95 399	56.00 397	61.17 437	41.84 351	51.90 441	56.45 420	40.96 419	44.79 439	67.84 425	30.04 380	55.07 442	36.71 391	50.69 433	71.11 418

kuosan		29.62 433	30.82 432	26.02 453	52.99 452	16.22 472	51.09 442	22.71 475	33.91 438	33.99 457	40.85 463	15.89 444	33.11 470	7.59 474	18.37 467	28.72 467

ADS-MVSNet2		51.33 394	48.76 401	59.07 377	66.02 415	44.60 324	50.90 443	59.76 407	36.90 431	50.74 417	66.18 436	26.38 412	63.11 403	27.17 443	54.76 419	69.50 428

ADS-MVSNet		48.48 403	47.77 404	50.63 425	66.02 415	29.92 445	50.90 443	50.87 441	36.90 431	50.74 417	66.18 436	26.38 412	52.47 448	27.17 443	54.76 419	69.50 428

mamba_0408		67.78 223	65.42 252	74.85 102	78.65 163	53.46 170	50.83 445	79.09 176	53.75 273	68.14 185	83.83 195	41.79 246	86.56 80	56.58 222	76.11 204	84.54 183

SSM_04072		64.98 273	65.42 252	63.68 341	78.65 163	53.46 170	50.83 445	79.09 176	53.75 273	68.14 185	83.83 195	41.79 246	53.03 446	56.58 222	76.11 204	84.54 183

FPMVS		42.18 415	41.11 417	45.39 431	58.03 448	41.01 362	49.50 447	53.81 433	30.07 443	33.71 458	64.03 440	11.69 452	52.08 451	14.01 462	55.11 417	43.09 459

N_pmnet		39.35 421	40.28 418	36.54 445	63.76 424	1.62 482	49.37 448	0.76 481	34.62 437	43.61 443	66.38 435	26.25 414	42.57 461	26.02 448	51.77 429	65.44 437

new-patchmatchnet		47.56 405	47.73 405	47.06 429	58.81 447	9.37 477	48.78 449	59.21 409	43.28 404	44.22 441	68.66 423	25.67 418	57.20 430	31.57 425	49.35 437	74.62 380

test_vis1_rt		41.35 418	39.45 419	47.03 430	46.65 464	37.86 388	47.76 450	38.65 462	23.10 456	44.21 442	51.22 456	11.20 457	44.08 459	39.27 373	53.02 426	59.14 443

JIA-IIPM		51.56 392	47.68 406	63.21 346	64.61 421	50.73 230	47.71 451	58.77 411	42.90 408	48.46 428	51.72 454	24.97 422	70.24 364	36.06 399	53.89 423	68.64 432

ambc				65.13 330	63.72 426	37.07 398	47.66 452	78.78 186		54.37 396	71.42 403	11.24 456	80.94 225	45.64 319	53.85 424	77.38 343

testf1		31.46 431	28.89 435	39.16 441	41.99 468	28.78 449	46.45 453	37.56 463	14.28 468	21.10 464	48.96 459	1.48 477	47.11 455	13.63 463	34.56 455	41.60 460

APD_test2		31.46 431	28.89 435	39.16 441	41.99 468	28.78 449	46.45 453	37.56 463	14.28 468	21.10 464	48.96 459	1.48 477	47.11 455	13.63 463	34.56 455	41.60 460

Patchmatch-test		49.08 401	48.28 403	51.50 424	64.40 422	30.85 443	45.68 455	48.46 446	35.60 435	46.10 437	72.10 397	34.47 329	46.37 457	27.08 445	60.65 394	77.27 345

DSMNet-mixed		39.30 422	38.72 421	41.03 440	51.22 457	19.66 469	45.53 456	31.35 468	15.83 467	39.80 451	67.42 430	22.19 429	45.13 458	22.43 452	52.69 427	58.31 445

LCM-MVSNet		40.30 419	35.88 425	53.57 410	42.24 466	29.15 447	45.21 457	60.53 406	22.23 459	28.02 461	50.98 457	3.72 471	61.78 408	31.22 428	38.76 452	69.78 427

new_pmnet		34.13 427	34.29 428	33.64 447	52.63 454	18.23 471	44.43 458	33.90 467	22.81 457	30.89 460	53.18 452	10.48 459	35.72 469	20.77 455	39.51 450	46.98 458

mvsany_test1		39.38 420	38.16 423	43.02 437	49.05 458	34.28 423	44.16 459	25.94 472	22.74 458	46.57 435	62.21 445	23.85 426	41.16 464	33.01 412	35.91 454	53.63 451

E-PMN		23.77 435	22.73 439	26.90 451	42.02 467	20.67 468	42.66 460	35.70 465	17.43 463	10.28 473	25.05 469	6.42 464	42.39 462	10.28 470	14.71 469	17.63 468

EMVS		22.97 436	21.84 440	26.36 452	40.20 470	19.53 470	41.95 461	34.64 466	17.09 464	9.73 474	22.83 470	7.29 463	42.22 463	9.18 472	13.66 470	17.32 469

test_vis3_rt		32.09 429	30.20 434	37.76 444	35.36 475	27.48 453	40.60 462	28.29 471	16.69 465	32.52 459	40.53 464	1.96 475	37.40 467	33.64 409	42.21 448	48.39 454

CHOSEN 280x420		47.83 404	46.36 408	52.24 422	67.37 403	49.78 248	38.91 463	43.11 459	35.00 436	43.27 444	63.30 443	28.95 389	49.19 453	36.53 394	60.80 392	57.76 447

mvsany_test3		32.62 428	30.57 433	38.77 443	36.16 474	24.20 464	38.10 464	20.63 476	19.14 462	40.36 450	57.43 449	5.06 466	36.63 468	29.59 436	28.66 459	55.49 449

test_f		31.86 430	31.05 431	34.28 446	32.33 477	21.86 467	32.34 465	30.46 469	16.02 466	39.78 452	55.45 451	4.80 467	32.36 471	30.61 429	37.66 453	48.64 453

PMMVS2		27.40 434	25.91 437	31.87 450	39.46 472	6.57 479	31.17 466	28.52 470	23.96 453	20.45 467	48.94 461	4.20 470	37.94 466	16.51 459	19.97 465	51.09 452

wuyk23d		13.32 440	12.52 443	15.71 455	47.54 462	26.27 459	31.06 467	1.98 480	4.93 472	5.18 475	1.94 475	0.45 479	18.54 474	6.81 475	12.83 471	2.33 472

Gipuma		34.77 425	31.91 430	43.33 436	62.05 434	37.87 387	20.39 468	67.03 352	23.23 455	18.41 468	25.84 468	4.24 468	62.73 404	14.71 461	51.32 431	29.38 466
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVE	17.77 23	21.41 437	17.77 442	32.34 449	34.34 476	25.44 461	16.11 469	24.11 473	11.19 470	13.22 470	31.92 466	1.58 476	30.95 472	10.47 469	17.03 468	40.62 463
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
tmp_tt		9.43 441	11.14 444	4.30 457	2.38 480	4.40 480	13.62 470	16.08 478	0.39 474	15.89 469	13.06 471	15.80 445	5.54 476	12.63 465	10.46 473	2.95 471

test_method		19.68 438	18.10 441	24.41 454	13.68 479	3.11 481	12.06 471	42.37 460	2.00 473	11.97 471	36.38 465	5.77 465	29.35 473	15.06 460	23.65 463	40.76 462

mmdepth		0.00 446	0.00 449	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	0.00 478	0.00 481	0.00 477	0.00 478	0.00 475	0.00 475

monomultidepth		0.00 446	0.00 449	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	0.00 478	0.00 481	0.00 477	0.00 478	0.00 475	0.00 475

test_blank		0.00 446	0.00 449	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	0.00 478	0.00 481	0.00 477	0.00 478	0.00 475	0.00 475

uanet_test		0.00 446	0.00 449	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	0.00 478	0.00 481	0.00 477	0.00 478	0.00 475	0.00 475

DCPMVS		0.00 446	0.00 449	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	0.00 478	0.00 481	0.00 477	0.00 478	0.00 475	0.00 475

cdsmvs_eth3d_5k		17.50 439	23.34 438	0.00 460	0.00 483	0.00 484	0.00 472	78.63 190	0.00 478	0.00 479	82.18 239	49.25 147	0.00 477	0.00 478	0.00 475	0.00 475

pcd_1.5k_mvsjas		3.92 445	5.23 448	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	0.00 478	47.05 179	0.00 477	0.00 478	0.00 475	0.00 475

sosnet-low-res		0.00 446	0.00 449	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	0.00 478	0.00 481	0.00 477	0.00 478	0.00 475	0.00 475

sosnet		0.00 446	0.00 449	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	0.00 478	0.00 481	0.00 477	0.00 478	0.00 475	0.00 475

uncertanet		0.00 446	0.00 449	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	0.00 478	0.00 481	0.00 477	0.00 478	0.00 475	0.00 475

Regformer		0.00 446	0.00 449	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	0.00 478	0.00 481	0.00 477	0.00 478	0.00 475	0.00 475

ab-mvs-re		6.49 442	8.65 445	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	77.89 327	0.00 481	0.00 477	0.00 478	0.00 475	0.00 475

uanet		0.00 446	0.00 449	0.00 460	0.00 483	0.00 484	0.00 472	0.00 482	0.00 478	0.00 479	0.00 478	0.00 481	0.00 477	0.00 478	0.00 475	0.00 475

WAC-MVS						27.31 455								27.77 440

MSC_two_6792asdad				79.95 4	87.24 14	61.04 31		85.62 28					90.96 1	79.31 10	90.65 8	87.85 43

PC_three_1452									55.09 240	84.46 4	89.84 51	66.68 5	89.41 21	74.24 59	91.38 2	88.42 21

No_MVS				79.95 4	87.24 14	61.04 31		85.62 28					90.96 1	79.31 10	90.65 8	87.85 43

test_one_0601					87.58 9	59.30 62		86.84 7	65.01 20	83.80 11	91.86 6	64.03 12

eth-test2					0.00 483

eth-test					0.00 483

ZD-MVS					86.64 21	60.38 45		82.70 104	57.95 171	78.10 32	90.06 44	56.12 47	88.84 29	74.05 62	87.00 54

IU-MVS					87.77 4	59.15 67		85.53 30	53.93 269	84.64 3				79.07 13	90.87 5	88.37 23

test_241102_TWO								86.73 12	64.18 34	84.26 5	91.84 8	65.19 6	90.83 5	78.63 20	90.70 7	87.65 52

test_241102_ONE					87.77 4	58.90 76		86.78 10	64.20 33	85.97 1	91.34 16	66.87 3	90.78 7

test_0728_THIRD									65.04 16	83.82 8	92.00 3	64.69 11	90.75 8	79.48 7	90.63 10	88.09 36

GSMVS																78.05 332

test_part2					87.58 9	60.47 42				83.42 14

sam_mvs1												34.74 325				78.05 332

sam_mvs												33.43 342

MTGPA								80.97 145

test_post											3.55 474	33.90 336	66.52 386

patchmatchnet-post											64.03 440	34.50 327	74.27 336

gm-plane-assit					71.40 354	41.72 355			48.85 343		73.31 389		82.48 190	48.90 291

test9_res														75.28 52	88.31 35	83.81 212

agg_prior2														73.09 70	87.93 43	84.33 190

agg_prior					85.04 53	59.96 50		81.04 143		74.68 71			84.04 145

TestCases				64.39 335	71.44 351	49.03 266		67.30 347	45.97 382	47.16 431	79.77 290	17.47 437	67.56 380	33.65 407	59.16 401	76.57 354

test_prior				76.69 64	84.20 64	57.27 97		84.88 43					86.43 87			86.38 102

新几何1				70.76 238	85.66 42	61.13 30		66.43 357	44.68 391	70.29 143	86.64 115	41.29 255	75.23 331	49.72 283	81.75 109	75.93 360

旧先验1					83.04 77	53.15 180		67.52 346			87.85 85	44.08 217			80.76 118	78.03 335

原ACMM1				74.69 105	85.39 48	59.40 59		83.42 78	51.47 307	70.27 144	86.61 119	48.61 155	86.51 85	53.85 250	87.96 42	78.16 330

testdata2													72.18 350	46.95 309

segment_acmp												54.23 65

testdata				64.66 332	81.52 97	52.93 185		65.29 367	46.09 380	73.88 84	87.46 92	38.08 293	66.26 389	53.31 255	78.48 166	74.78 377

test12				77.76 49	84.52 61	58.41 82		83.36 81		72.93 106		54.61 62	88.05 42		88.12 37	86.81 85

plane_prior7					81.41 100	55.96 120

plane_prior6					81.20 107	56.24 115						45.26 204

plane_prior5								84.01 56					87.21 62	68.16 104	80.58 122	84.65 181

plane_prior4											86.10 138

plane_prior3						56.09 117			63.92 38	69.27 164

plane_prior1					81.27 105

n2								0.00 482

nn								0.00 482

door-mid								47.19 452

lessismore_v0				69.91 255	71.42 353	47.80 290		50.90 440		50.39 421	75.56 367	27.43 405	81.33 212	45.91 316	34.10 457	80.59 294

LGP-MVS_train				75.76 82	80.22 122	57.51 95		83.40 79	61.32 85	66.67 225	87.33 98	39.15 279	86.59 78	67.70 110	77.30 189	83.19 235

test11								83.47 76

door								47.60 450

HQP5-MVS						54.94 142

BP-MVS														67.04 118

HQP4-MVS										67.85 195			86.93 70			84.32 191

HQP3-MVS								83.90 61							80.35 126

HQP2-MVS												45.46 198

NP-MVS					80.98 110	56.05 119					85.54 158

ACMMP++_ref															74.07 232

ACMMP++															72.16 271

Test By Simon												48.33 158

ITE_SJBPF				62.09 354	66.16 413	44.55 326		64.32 374	47.36 366	55.31 383	80.34 279	19.27 436	62.68 405	36.29 397	62.39 381	79.04 322

DeepMVS_CX				12.03 456	17.97 478	10.91 475		10.60 479	7.46 471	11.07 472	28.36 467	3.28 472	11.29 475	8.01 473	9.74 474	13.89 470

High-resolution multi-view benchmark