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 68	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 27

FOURS1					86.12 37	60.82 37	88.18 1	83.61 79	60.87 103	81.50 20

APDe-MVS		80.16 9	80.59 7	78.86 32	86.64 21	60.02 48	88.12 3	86.42 15	62.94 56	82.40 17	92.12 2	59.64 22	89.76 20	78.70 15	88.32 35	86.79 93
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
test0726					87.75 7	59.07 72	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 38	87.75 7	59.07 72	87.85 5	85.03 41	64.26 31	83.82 8	92.00 3	64.82 8	90.75 8	78.66 18	90.61 11	85.45 157
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 71	87.85 5	87.15 3					90.84 3	78.66 18	90.61 11	87.62 61

SED-MVS		81.56 2	82.30 2	79.32 13	87.77 4	58.90 77	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 35

OPU-MVS				79.83 7	87.54 11	60.93 35	87.82 7				89.89 51	67.01 1	90.33 12	73.16 71	91.15 4	88.23 35

SteuartSystems-ACMMP		79.48 14	79.31 14	79.98 3	83.01 80	62.18 16	87.60 9	85.83 24	66.69 9	78.03 35	90.98 19	54.26 71	90.06 14	78.42 23	89.02 27	87.69 57
Skip Steuart: Steuart Systems R&D Blog.
CP-MVS		77.12 36	76.68 36	78.43 37	86.05 39	63.18 5	87.55 10	83.45 84	62.44 69	72.68 119	90.50 31	48.18 167	87.34 58	73.59 69	85.71 66	84.76 188

MED-MVS test				79.09 23	85.30 50	59.25 64	86.84 11	85.86 21	60.95 100	83.65 12	90.57 25		89.91 16	77.02 34	89.43 22	88.10 40

MED-MVS		80.31 6	80.72 6	79.09 23	85.30 50	59.25 64	86.84 11	85.86 21	63.10 52	83.65 12	90.57 25	64.70 10	89.91 16	77.02 34	89.43 22	88.10 40

TestfortrainingZip a		79.97 11	80.40 8	78.69 34	85.30 50	58.20 86	86.84 11	85.86 21	60.95 100	83.65 12	90.57 25	64.70 10	89.91 16	76.25 43	89.43 22	87.96 46

TestfortrainingZip							86.84 11

ZNCC-MVS		78.82 16	78.67 19	79.30 14	86.43 29	62.05 18	86.62 15	86.01 20	63.32 46	75.08 60	90.47 33	53.96 78	88.68 31	76.48 39	89.63 20	87.16 82

HPM-MVS++		79.88 12	80.14 12	79.10 21	88.17 1	64.80 1	86.59 16	83.70 75	65.37 13	78.78 28	90.64 22	58.63 28	87.24 59	79.00 14	90.37 14	85.26 169

SMA-MVS		80.28 7	80.39 9	79.95 4	86.60 24	61.95 19	86.33 17	85.75 26	62.49 67	82.20 19	92.28 1	56.53 41	89.70 21	79.85 6	91.48 1	88.19 37
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 27	77.65 29	79.10 21	86.71 19	62.81 8	86.29 18	84.32 52	62.82 60	73.96 84	90.50 31	53.20 92	88.35 35	74.02 65	87.05 51	86.13 124

region2R		77.67 31	77.18 33	79.15 18	86.76 17	62.95 6	86.29 18	84.16 55	62.81 62	73.30 98	90.58 24	49.90 143	88.21 38	73.78 67	87.03 52	86.29 121

ACMMPR		77.71 29	77.23 32	79.16 17	86.75 18	62.93 7	86.29 18	84.24 53	62.82 60	73.55 94	90.56 29	49.80 146	88.24 37	74.02 65	87.03 52	86.32 117

MM		80.20 8	80.28 11	79.99 2	82.19 89	60.01 49	86.19 21	83.93 59	73.19 1	77.08 44	91.21 18	57.23 36	90.73 10	83.35 1	88.12 38	89.22 7

MSP-MVS		81.06 3	81.40 4	80.02 1	86.21 32	62.73 9	86.09 22	86.83 8	65.51 12	83.81 10	90.51 30	63.71 14	89.23 24	81.51 2	88.44 31	88.09 43
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 23	17.08 488

MP-MVS		78.35 23	78.26 24	78.64 35	86.54 26	63.47 4	86.02 24	83.55 81	63.89 39	73.60 92	90.60 23	54.85 66	86.72 76	77.20 31	88.06 40	85.74 143
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
lecture		77.75 28	77.84 28	77.50 53	82.75 84	57.62 93	85.92 25	86.20 18	60.53 112	78.99 27	91.45 12	51.51 123	87.78 51	75.65 49	87.55 47	87.10 84

GST-MVS		78.14 25	77.85 27	78.99 28	86.05 39	61.82 22	85.84 26	85.21 35	63.56 43	74.29 79	90.03 47	52.56 101	88.53 33	74.79 59	88.34 33	86.63 102

XVS		77.17 35	76.56 40	79.00 26	86.32 30	62.62 11	85.83 27	83.92 60	64.55 25	72.17 127	90.01 49	47.95 169	88.01 44	71.55 88	86.74 59	86.37 111

X-MVStestdata		70.21 160	67.28 219	79.00 26	86.32 30	62.62 11	85.83 27	83.92 60	64.55 25	72.17 127	6.49 483	47.95 169	88.01 44	71.55 88	86.74 59	86.37 111

3Dnovator+	66.72 4	75.84 54	74.57 66	79.66 9	82.40 86	59.92 51	85.83 27	86.32 17	66.92 7	67.80 209	89.24 60	42.03 247	89.38 23	64.07 153	86.50 63	89.69 3

mPP-MVS		76.54 43	75.93 48	78.34 40	86.47 27	63.50 3	85.74 30	82.28 116	62.90 57	71.77 132	90.26 39	46.61 194	86.55 84	71.71 86	85.66 67	84.97 180

DPE-MVS		80.56 5	80.98 5	79.29 15	87.27 13	60.56 41	85.71 31	86.42 15	63.28 47	83.27 16	91.83 10	64.96 7	90.47 11	76.41 40	89.67 18	86.84 91
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
ME-MVS		80.04 10	80.36 10	79.08 25	86.63 23	59.25 64	85.62 32	86.73 12	63.10 52	82.27 18	90.57 25	61.90 16	89.88 19	77.02 34	89.43 22	88.10 40

SR-MVS		76.13 51	75.70 52	77.40 57	85.87 41	61.20 29	85.52 33	82.19 117	59.99 132	75.10 59	90.35 36	47.66 174	86.52 85	71.64 87	82.99 90	84.47 197

APD-MVS		78.02 26	78.04 26	77.98 45	86.44 28	60.81 38	85.52 33	84.36 51	60.61 110	79.05 26	90.30 38	55.54 59	88.32 36	73.48 70	87.03 52	84.83 184
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ACMMP		76.02 52	75.33 56	78.07 42	85.20 53	61.91 20	85.49 35	84.44 49	63.04 54	69.80 163	89.74 55	45.43 208	87.16 65	72.01 81	82.87 95	85.14 171
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 19	78.31 21	79.39 12	87.51 12	62.61 13	85.20 36	84.42 50	66.73 8	74.67 73	89.38 58	55.30 60	89.18 25	74.19 63	87.34 50	86.38 109

SF-MVS		78.82 16	79.22 15	77.60 51	82.88 82	57.83 90	84.99 37	88.13 2	61.86 83	79.16 25	90.75 21	57.96 29	87.09 68	77.08 33	90.18 15	87.87 49

reproduce-ours		76.90 38	76.58 38	77.87 47	83.99 66	60.46 43	84.75 38	83.34 89	60.22 126	77.85 36	91.42 14	50.67 135	87.69 53	72.46 76	84.53 74	85.46 155

our_new_method		76.90 38	76.58 38	77.87 47	83.99 66	60.46 43	84.75 38	83.34 89	60.22 126	77.85 36	91.42 14	50.67 135	87.69 53	72.46 76	84.53 74	85.46 155

DeepC-MVS_fast	68.24 3	77.25 34	76.63 37	79.12 20	86.15 35	60.86 36	84.71 40	84.85 45	61.98 82	73.06 110	88.88 66	53.72 84	89.06 27	68.27 103	88.04 41	87.42 69
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 21	78.28 22	78.98 29	80.73 114	57.91 89	84.68 41	81.64 126	68.35 2	75.77 50	90.38 34	53.98 76	90.26 13	81.30 3	87.68 46	88.77 16

reproduce_model		76.43 45	76.08 45	77.49 54	83.47 74	60.09 47	84.60 42	82.90 107	59.65 139	77.31 39	91.43 13	49.62 148	87.24 59	71.99 82	83.75 85	85.14 171

SD-MVS		77.70 30	77.62 30	77.93 46	84.47 63	61.88 21	84.55 43	83.87 65	60.37 119	79.89 22	89.38 58	54.97 64	85.58 113	76.12 45	84.94 70	86.33 115
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 49	75.98 47	77.06 60	80.15 128	55.63 130	84.51 44	83.90 62	63.24 48	73.30 98	87.27 101	55.06 62	86.30 93	71.78 85	84.58 72	89.25 6

CNVR-MVS		79.84 13	79.97 13	79.45 11	87.90 2	62.17 17	84.37 45	85.03 41	66.96 5	77.58 38	90.06 45	59.47 24	89.13 26	78.67 17	89.73 16	87.03 85

NormalMVS		76.26 48	75.74 51	77.83 49	82.75 84	59.89 52	84.36 46	83.21 96	64.69 22	74.21 80	87.40 94	49.48 149	86.17 96	68.04 110	87.55 47	87.42 69

SymmetryMVS		75.28 59	74.60 65	77.30 58	83.85 69	59.89 52	84.36 46	75.51 267	64.69 22	74.21 80	87.40 94	49.48 149	86.17 96	68.04 110	83.88 83	85.85 134

SR-MVS-dyc-post		74.57 69	73.90 77	76.58 70	83.49 72	59.87 54	84.29 48	81.36 134	58.07 173	73.14 105	90.07 43	44.74 218	85.84 107	68.20 104	81.76 108	84.03 209

RE-MVS-def			73.71 82		83.49 72	59.87 54	84.29 48	81.36 134	58.07 173	73.14 105	90.07 43	43.06 237		68.20 104	81.76 108	84.03 209

PHI-MVS		75.87 53	75.36 55	77.41 55	80.62 119	55.91 123	84.28 50	85.78 25	56.08 223	73.41 95	86.58 128	50.94 133	88.54 32	70.79 93	89.71 17	87.79 54

HQP_MVS		74.31 72	73.73 81	76.06 77	81.41 101	56.31 112	84.22 51	84.01 57	64.52 27	69.27 172	86.10 145	45.26 212	87.21 63	68.16 107	80.58 123	84.65 189

plane_prior2							84.22 51		64.52 27

DeepC-MVS	69.38 2	78.56 20	78.14 25	79.83 7	83.60 70	61.62 23	84.17 53	86.85 6	63.23 49	73.84 89	90.25 40	57.68 32	89.96 15	74.62 60	89.03 26	87.89 47
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 18		83.10 77		84.15 54	88.26 1	59.90 133	78.57 30	90.36 35	57.51 35	86.86 73	77.39 29	89.52 21

CPTT-MVS		72.78 103	72.08 110	74.87 102	84.88 61	61.41 26	84.15 54	77.86 221	55.27 243	67.51 215	88.08 79	41.93 250	81.85 207	69.04 102	80.01 132	81.35 287

TSAR-MVS + MP.		78.44 22	78.28 22	78.90 30	84.96 56	61.41 26	84.03 56	83.82 70	59.34 149	79.37 24	89.76 54	59.84 19	87.62 56	76.69 37	86.74 59	87.68 58
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
API-MVS		72.17 119	71.41 121	74.45 119	81.95 93	57.22 99	84.03 56	80.38 163	59.89 137	68.40 186	82.33 242	49.64 147	87.83 50	51.87 274	84.16 81	78.30 339

save fliter					86.17 34	61.30 28	83.98 58	79.66 173	59.00 153

SPE-MVS-test		75.62 57	75.31 57	76.56 71	80.63 118	55.13 141	83.88 59	85.22 34	62.05 79	71.49 139	86.03 148	53.83 80	86.36 91	67.74 114	86.91 56	88.19 37

ACMMP_NAP		78.77 18	78.78 17	78.74 33	85.44 46	61.04 31	83.84 60	85.16 36	62.88 58	78.10 33	91.26 17	52.51 102	88.39 34	79.34 9	90.52 13	86.78 94

EC-MVSNet		75.84 54	75.87 50	75.74 85	78.86 157	52.65 196	83.73 61	86.08 19	63.47 45	72.77 118	87.25 104	53.13 93	87.93 46	71.97 83	85.57 68	86.66 100

APD-MVS_3200maxsize		74.96 61	74.39 68	76.67 67	82.20 88	58.24 85	83.67 62	83.29 93	58.41 167	73.71 90	90.14 41	45.62 201	85.99 103	69.64 97	82.85 96	85.78 137

HPM-MVS_fast		74.30 73	73.46 87	76.80 63	84.45 64	59.04 74	83.65 63	81.05 149	60.15 128	70.43 149	89.84 52	41.09 269	85.59 112	67.61 117	82.90 94	85.77 140

plane_prior						56.31 112	83.58 64		63.19 51						80.48 126

QAPM		70.05 164	68.81 176	73.78 144	76.54 250	53.43 174	83.23 65	83.48 82	52.89 295	65.90 249	86.29 139	41.55 261	86.49 87	51.01 281	78.40 177	81.42 281

MCST-MVS		77.48 32	77.45 31	77.54 52	86.67 20	58.36 84	83.22 66	86.93 5	56.91 201	74.91 65	88.19 75	59.15 26	87.68 55	73.67 68	87.45 49	86.57 103

EPNet		73.09 98	72.16 108	75.90 79	75.95 258	56.28 114	83.05 67	72.39 318	66.53 10	65.27 261	87.00 109	50.40 138	85.47 118	62.48 179	86.32 64	85.94 129
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DeepPCF-MVS	69.58 1	79.03 15	79.00 16	79.13 19	84.92 60	60.32 46	83.03 68	85.33 33	62.86 59	80.17 21	90.03 47	61.76 17	88.95 28	74.21 62	88.67 30	88.12 39

CSCG		76.92 37	76.75 35	77.41 55	83.96 68	59.60 56	82.95 69	86.50 14	60.78 106	75.27 55	84.83 174	60.76 18	86.56 81	67.86 113	87.87 45	86.06 126

MP-MVS-pluss		78.35 23	78.46 20	78.03 44	84.96 56	59.52 58	82.93 70	85.39 32	62.15 75	76.41 48	91.51 11	52.47 104	86.78 75	80.66 4	89.64 19	87.80 53
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HPM-MVS		77.28 33	76.85 34	78.54 36	85.00 55	60.81 38	82.91 71	85.08 38	62.57 65	73.09 109	89.97 50	50.90 134	87.48 57	75.30 53	86.85 57	87.33 77
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
MVSFormer		71.50 133	70.38 144	74.88 101	78.76 160	57.15 104	82.79 72	78.48 206	51.26 322	69.49 166	83.22 219	43.99 228	83.24 164	66.06 135	79.37 142	84.23 203

test_djsdf		69.45 187	67.74 202	74.58 113	74.57 296	54.92 145	82.79 72	78.48 206	51.26 322	65.41 258	83.49 215	38.37 296	83.24 164	66.06 135	69.25 329	85.56 150

ACMP	63.53 6	72.30 116	71.20 128	75.59 91	80.28 121	57.54 94	82.74 74	82.84 110	60.58 111	65.24 265	86.18 142	39.25 286	86.03 102	66.95 129	76.79 205	83.22 241
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMM	61.98 7	70.80 148	69.73 155	74.02 135	80.59 120	58.59 82	82.68 75	82.02 120	55.46 238	67.18 222	84.39 192	38.51 294	83.17 166	60.65 196	76.10 215	80.30 311
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
AdaColmap		69.99 166	68.66 180	73.97 139	84.94 58	57.83 90	82.63 76	78.71 194	56.28 219	64.34 280	84.14 195	41.57 259	87.06 69	46.45 320	78.88 161	77.02 360

OPM-MVS		74.73 65	74.25 71	76.19 76	80.81 113	59.01 75	82.60 77	83.64 78	63.74 41	72.52 122	87.49 91	47.18 185	85.88 106	69.47 99	80.78 117	83.66 230
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
PGM-MVS		76.77 41	76.06 46	78.88 31	86.14 36	62.73 9	82.55 78	83.74 72	61.71 84	72.45 125	90.34 37	48.48 165	88.13 41	72.32 78	86.85 57	85.78 137

LPG-MVS_test		72.74 104	71.74 115	75.76 83	80.22 123	57.51 96	82.55 78	83.40 86	61.32 91	66.67 233	87.33 99	39.15 288	86.59 79	67.70 115	77.30 197	83.19 243

CANet		76.46 44	75.93 48	78.06 43	81.29 104	57.53 95	82.35 80	83.31 92	67.78 3	70.09 153	86.34 137	54.92 65	88.90 29	72.68 75	84.55 73	87.76 55

114514_t		70.83 146	69.56 158	74.64 110	86.21 32	54.63 148	82.34 81	81.81 123	48.22 363	63.01 301	85.83 156	40.92 271	87.10 67	57.91 222	79.79 135	82.18 270

HQP-NCC					80.66 115		82.31 82		62.10 76	67.85 203

ACMP_Plane					80.66 115		82.31 82		62.10 76	67.85 203

HQP-MVS		73.45 87	72.80 99	75.40 92	80.66 115	54.94 143	82.31 82	83.90 62	62.10 76	67.85 203	85.54 166	45.46 206	86.93 71	67.04 125	80.35 127	84.32 199

MSLP-MVS++		73.77 82	73.47 86	74.66 108	83.02 79	59.29 63	82.30 85	81.88 121	59.34 149	71.59 136	86.83 113	45.94 199	83.65 155	65.09 146	85.22 69	81.06 296

EPP-MVSNet		72.16 121	71.31 125	74.71 105	78.68 163	49.70 261	82.10 86	81.65 125	60.40 116	65.94 247	85.84 155	51.74 119	86.37 90	55.93 236	79.55 141	88.07 45

test_prior4						62.51 14	82.08 87

TSAR-MVS + GP.		74.90 62	74.15 72	77.17 59	82.00 91	58.77 80	81.80 88	78.57 202	58.58 164	74.32 78	84.51 189	55.94 56	87.22 62	67.11 124	84.48 77	85.52 151

test_prior2							81.75 89		60.37 119	75.01 61	89.06 61	56.22 46		72.19 79	88.96 28

PS-MVSNAJss		72.24 117	71.21 127	75.31 94	78.50 169	55.93 122	81.63 90	82.12 118	56.24 220	70.02 157	85.68 162	47.05 187	84.34 142	65.27 145	74.41 237	85.67 146

TEST9					85.58 44	61.59 24	81.62 91	81.26 141	55.65 233	74.93 63	88.81 67	53.70 85	84.68 136

train_agg		76.27 47	76.15 44	76.64 69	85.58 44	61.59 24	81.62 91	81.26 141	55.86 225	74.93 63	88.81 67	53.70 85	84.68 136	75.24 55	88.33 34	83.65 231

MG-MVS		73.96 79	73.89 78	74.16 128	85.65 43	49.69 263	81.59 93	81.29 140	61.45 89	71.05 142	88.11 77	51.77 118	87.73 52	61.05 192	83.09 88	85.05 176

test_8					85.40 47	60.96 34	81.54 94	81.18 145	55.86 225	74.81 68	88.80 69	53.70 85	84.45 140

MAR-MVS		71.51 132	70.15 150	75.60 90	81.84 94	59.39 60	81.38 95	82.90 107	54.90 260	68.08 199	78.70 317	47.73 172	85.51 115	51.68 278	84.17 80	81.88 276
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 46	75.67 53	78.22 41	85.35 49	59.14 70	81.31 96	84.02 56	56.32 217	74.05 82	88.98 63	53.34 90	87.92 47	69.23 101	88.42 32	87.59 63

OpenMVS	61.03 9	68.85 201	67.56 206	72.70 184	74.26 305	53.99 158	81.21 97	81.34 138	52.70 297	62.75 306	85.55 165	38.86 292	84.14 144	48.41 303	83.01 89	79.97 317

DP-MVS Recon		72.15 122	70.73 137	76.40 72	86.57 25	57.99 88	81.15 98	82.96 105	57.03 198	66.78 228	85.56 163	44.50 222	88.11 42	51.77 276	80.23 130	83.10 248

balanced_conf03		76.58 42	76.55 41	76.68 66	81.73 95	52.90 187	80.94 99	85.70 28	61.12 98	74.90 66	87.17 107	56.46 42	88.14 40	72.87 73	88.03 42	89.00 9

Vis-MVSNet		72.18 118	71.37 123	74.61 111	81.29 104	55.41 136	80.90 100	78.28 216	60.73 107	69.23 175	88.09 78	44.36 224	82.65 190	57.68 223	81.75 110	85.77 140
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
jajsoiax		68.25 217	66.45 237	73.66 154	75.62 264	55.49 135	80.82 101	78.51 205	52.33 305	64.33 281	84.11 196	28.28 407	81.81 209	63.48 167	70.62 298	83.67 228

mvs_tets		68.18 220	66.36 243	73.63 157	75.61 265	55.35 139	80.77 102	78.56 203	52.48 304	64.27 283	84.10 197	27.45 415	81.84 208	63.45 168	70.56 300	83.69 227

DP-MVS		65.68 269	63.66 282	71.75 209	84.93 59	56.87 109	80.74 103	73.16 311	53.06 292	59.09 355	82.35 241	36.79 318	85.94 105	32.82 424	69.96 314	72.45 409

3Dnovator	64.47 5	72.49 111	71.39 122	75.79 82	77.70 202	58.99 76	80.66 104	83.15 101	62.24 73	65.46 257	86.59 127	42.38 245	85.52 114	59.59 206	84.72 71	82.85 253

ACMH+	57.40 11	66.12 265	64.06 274	72.30 197	77.79 198	52.83 192	80.39 105	78.03 219	57.30 191	57.47 373	82.55 235	27.68 413	84.17 143	45.54 331	69.78 318	79.90 319

viewdifsd2359ckpt09		73.42 88	72.45 105	76.30 75	77.25 222	53.27 178	80.36 106	82.48 113	57.96 178	72.24 126	85.73 160	53.22 91	86.27 94	63.79 163	79.06 159	89.36 5

sasdasda		74.67 66	74.98 61	73.71 151	78.94 155	50.56 238	80.23 107	83.87 65	60.30 123	77.15 41	86.56 129	59.65 20	82.00 204	66.01 137	82.12 101	88.58 24

canonicalmvs		74.67 66	74.98 61	73.71 151	78.94 155	50.56 238	80.23 107	83.87 65	60.30 123	77.15 41	86.56 129	59.65 20	82.00 204	66.01 137	82.12 101	88.58 24

IS-MVSNet		71.57 131	71.00 132	73.27 171	78.86 157	45.63 323	80.22 109	78.69 195	64.14 37	66.46 236	87.36 97	49.30 153	85.60 111	50.26 287	83.71 86	88.59 23

Effi-MVS+-dtu		69.64 178	67.53 209	75.95 78	76.10 256	62.29 15	80.20 110	76.06 256	59.83 138	65.26 264	77.09 350	41.56 260	84.02 148	60.60 197	71.09 295	81.53 280

nrg030		72.96 100	73.01 95	72.84 180	75.41 271	50.24 247	80.02 111	82.89 109	58.36 169	74.44 75	86.73 119	58.90 27	80.83 236	65.84 140	74.46 234	87.44 68

Anonymous20231211		69.28 190	68.47 185	71.73 210	80.28 121	47.18 307	79.98 112	82.37 115	54.61 265	67.24 220	84.01 199	39.43 283	82.41 198	55.45 244	72.83 267	85.62 149

DPM-MVS		75.47 58	75.00 60	76.88 61	81.38 103	59.16 67	79.94 113	85.71 27	56.59 211	72.46 123	86.76 115	56.89 39	87.86 49	66.36 133	88.91 29	83.64 232

PVSNet_Blended_VisFu		71.45 135	70.39 143	74.65 109	82.01 90	58.82 79	79.93 114	80.35 164	55.09 248	65.82 253	82.16 250	49.17 156	82.64 191	60.34 198	78.62 171	82.50 264

PAPM_NR		72.63 108	71.80 113	75.13 97	81.72 96	53.42 175	79.91 115	83.28 94	59.14 151	66.31 240	85.90 153	51.86 115	86.06 100	57.45 225	80.62 121	85.91 131

LS3D		64.71 283	62.50 300	71.34 231	79.72 135	55.71 127	79.82 116	74.72 284	48.50 359	56.62 379	84.62 182	33.59 351	82.34 199	29.65 446	75.23 229	75.97 370

UGNet		68.81 202	67.39 214	73.06 175	78.33 179	54.47 149	79.77 117	75.40 270	60.45 114	63.22 294	84.40 191	32.71 364	80.91 235	51.71 277	80.56 125	83.81 220
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		71.78 127	71.59 116	72.32 196	83.40 75	46.38 312	79.75 118	71.08 327	64.18 34	72.80 117	88.64 72	42.58 242	83.72 153	57.41 226	84.49 76	86.86 90

OMC-MVS		71.40 136	70.60 139	73.78 144	76.60 248	53.15 181	79.74 119	79.78 170	58.37 168	68.75 180	86.45 134	45.43 208	80.60 240	62.58 177	77.73 186	87.58 64

casdiffmvs_mvg		76.14 50	76.30 43	75.66 87	76.46 252	51.83 217	79.67 120	85.08 38	65.02 19	75.84 49	88.58 73	59.42 25	85.08 124	72.75 74	83.93 82	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							79.66 121	74.30 291	48.40 361				80.78 238	53.62 259		79.03 334

Effi-MVS+		73.31 92	72.54 103	75.62 89	77.87 195	53.64 165	79.62 122	79.61 174	61.63 88	72.02 130	82.61 229	56.44 43	85.97 104	63.99 156	79.07 158	87.25 79

GDP-MVS		72.64 107	71.28 126	76.70 64	77.72 201	54.22 155	79.57 123	84.45 48	55.30 242	71.38 140	86.97 110	39.94 276	87.00 70	67.02 127	79.20 152	88.89 12

PAPR		71.72 130	70.82 135	74.41 120	81.20 108	51.17 222	79.55 124	83.33 91	55.81 228	66.93 227	84.61 183	50.95 132	86.06 100	55.79 239	79.20 152	86.00 127

ACMH	55.70 15	65.20 278	63.57 283	70.07 259	78.07 189	52.01 213	79.48 125	79.69 171	55.75 230	56.59 380	80.98 275	27.12 418	80.94 232	42.90 360	71.58 287	77.25 358
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ETV-MVS		74.46 71	73.84 79	76.33 74	79.27 145	55.24 140	79.22 126	85.00 43	64.97 21	72.65 120	79.46 307	53.65 88	87.87 48	67.45 121	82.91 93	85.89 132

BP-MVS1		73.41 89	72.25 107	76.88 61	76.68 245	53.70 163	79.15 127	81.07 148	60.66 109	71.81 131	87.39 96	40.93 270	87.24 59	71.23 90	81.29 114	89.71 2

原ACMM2							79.02 128

fmvsm_l_conf0.5_n_3		73.23 94	73.13 94	73.55 161	74.40 300	55.13 141	78.97 129	74.96 282	56.64 204	74.76 71	88.75 71	55.02 63	78.77 284	76.33 41	78.31 179	86.74 95

GeoE		71.01 141	70.15 150	73.60 159	79.57 138	52.17 208	78.93 130	78.12 218	58.02 175	67.76 212	83.87 202	52.36 106	82.72 188	56.90 228	75.79 219	85.92 130

fmvsm_s_conf0.5_n_11		73.16 95	73.35 90	72.58 185	75.48 268	52.41 206	78.84 131	76.85 242	58.64 162	73.58 93	87.25 104	54.09 75	79.47 261	76.19 44	79.27 148	85.86 133

UA-Net		73.13 97	72.93 96	73.76 146	83.58 71	51.66 219	78.75 132	77.66 225	67.75 4	72.61 121	89.42 56	49.82 145	83.29 163	53.61 260	83.14 87	86.32 117

VDDNet		71.81 126	71.33 124	73.26 172	82.80 83	47.60 303	78.74 133	75.27 272	59.59 144	72.94 112	89.40 57	41.51 262	83.91 150	58.75 218	82.99 90	88.26 32

v10		70.21 160	69.02 170	73.81 143	73.51 318	50.92 228	78.74 133	81.39 132	60.05 130	66.39 238	81.83 258	47.58 176	85.41 121	62.80 176	68.86 336	85.09 175

viewdifsd2359ckpt13		72.40 115	71.79 114	74.22 126	75.63 263	51.77 218	78.67 135	83.13 103	57.08 195	71.59 136	85.36 170	53.10 94	82.64 191	63.07 173	78.51 173	88.24 34

CANet_DTU		68.18 220	67.71 205	69.59 269	74.83 285	46.24 314	78.66 136	76.85 242	59.60 141	63.45 292	82.09 254	35.25 329	77.41 308	59.88 203	78.76 166	85.14 171

MVSMamba_PlusPlus		75.75 56	75.44 54	76.67 67	80.84 112	53.06 184	78.62 137	85.13 37	59.65 139	71.53 138	87.47 92	56.92 38	88.17 39	72.18 80	86.63 62	88.80 13

v8		70.33 158	69.28 165	73.49 163	73.15 324	50.22 248	78.62 137	80.78 155	60.79 105	66.45 237	82.11 253	49.35 152	84.98 127	63.58 166	68.71 337	85.28 167

alignmvs		73.86 81	73.99 75	73.45 165	78.20 182	50.50 240	78.57 139	82.43 114	59.40 147	76.57 46	86.71 121	56.42 44	81.23 223	65.84 140	81.79 107	88.62 21

PLC	56.13 14	65.09 279	63.21 292	70.72 248	81.04 110	54.87 146	78.57 139	77.47 228	48.51 358	55.71 388	81.89 256	33.71 348	79.71 256	41.66 369	70.37 303	77.58 351
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
v7n		69.01 198	67.36 216	73.98 138	72.51 338	52.65 196	78.54 141	81.30 139	60.26 125	62.67 307	81.62 262	43.61 230	84.49 139	57.01 227	68.70 338	84.79 186

COLMAP_ROB	52.97 17	61.27 331	58.81 341	68.64 285	74.63 292	52.51 201	78.42 142	73.30 307	49.92 339	50.96 426	81.51 266	23.06 438	79.40 263	31.63 434	65.85 360	74.01 397
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
Elysia		70.19 162	68.29 192	75.88 80	74.15 307	54.33 153	78.26 143	83.21 96	55.04 254	67.28 218	83.59 210	30.16 387	86.11 98	63.67 164	79.26 149	87.20 80

StellarMVS		70.19 162	68.29 192	75.88 80	74.15 307	54.33 153	78.26 143	83.21 96	55.04 254	67.28 218	83.59 210	30.16 387	86.11 98	63.67 164	79.26 149	87.20 80

fmvsm_s_conf0.5_n_a		69.54 182	68.74 178	71.93 202	72.47 339	53.82 161	78.25 145	62.26 408	49.78 340	73.12 108	86.21 141	52.66 100	76.79 325	75.02 56	68.88 334	85.18 170

E6		74.10 76	74.09 73	74.15 130	77.14 226	50.74 232	78.24 146	83.85 69	62.34 71	73.95 85	87.27 101	55.98 54	82.95 175	68.17 106	79.85 134	88.77 16

E5		74.10 76	74.09 73	74.15 130	77.14 226	50.74 232	78.24 146	83.86 68	62.34 71	73.95 85	87.27 101	55.97 55	82.95 175	68.16 107	79.86 133	88.77 16

fmvsm_s_conf0.5_n_8		74.30 73	74.39 68	74.01 136	75.33 273	52.89 189	78.24 146	77.32 235	61.65 85	78.13 32	88.90 65	52.82 98	81.54 214	78.46 22	78.67 169	87.60 62

CLD-MVS		73.33 91	72.68 101	75.29 96	78.82 159	53.33 177	78.23 149	84.79 46	61.30 93	70.41 150	81.04 273	52.41 105	87.12 66	64.61 152	82.49 100	85.41 161
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		72.81 102	72.33 106	74.24 125	69.89 389	55.81 125	78.22 150	75.40 270	54.17 274	75.00 62	88.03 83	53.82 81	80.23 250	78.08 25	78.34 178	86.69 97

test_fmvsmconf_n		73.01 99	72.59 102	74.27 124	71.28 366	55.88 124	78.21 151	75.56 265	54.31 272	74.86 67	87.80 87	54.72 67	80.23 250	78.07 26	78.48 174	86.70 96

casdiffmvs		74.80 63	74.89 63	74.53 116	75.59 266	50.37 244	78.17 152	85.06 40	62.80 63	74.40 76	87.86 85	57.88 30	83.61 156	69.46 100	82.79 97	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		72.69 106	72.80 99	72.37 195	74.11 310	53.21 180	78.12 153	73.31 306	53.98 277	76.81 45	88.05 80	53.38 89	77.37 310	76.64 38	80.78 117	86.53 105

fmvsm_s_conf0.1_n_a		69.32 189	68.44 187	71.96 200	70.91 370	53.78 162	78.12 153	62.30 407	49.35 346	73.20 102	86.55 131	51.99 113	76.79 325	74.83 58	68.68 339	85.32 165

F-COLMAP		63.05 307	60.87 327	69.58 271	76.99 241	53.63 166	78.12 153	76.16 252	47.97 368	52.41 421	81.61 263	27.87 410	78.11 291	40.07 376	66.66 355	77.00 361

fmvsm_s_conf0.5_n_10		74.11 75	73.98 76	74.48 118	74.61 293	52.86 191	78.10 156	77.06 239	57.14 194	78.24 31	88.79 70	52.83 97	82.26 200	77.79 28	81.30 113	88.32 30

test_fmvsmconf0.01_n		72.17 119	71.50 118	74.16 128	67.96 410	55.58 133	78.06 157	74.67 285	54.19 273	74.54 74	88.23 74	50.35 140	80.24 249	78.07 26	77.46 192	86.65 101

EG-PatchMatch MVS		64.71 283	62.87 295	70.22 255	77.68 203	53.48 170	77.99 158	78.82 190	53.37 289	56.03 387	77.41 346	24.75 435	84.04 146	46.37 321	73.42 257	73.14 400

fmvsm_s_conf0.5_n		69.58 180	68.84 175	71.79 208	72.31 345	52.90 187	77.90 159	62.43 406	49.97 338	72.85 116	85.90 153	52.21 108	76.49 332	75.75 47	70.26 308	85.97 128

SSM_0404		70.84 144	69.41 163	75.12 98	79.20 147	53.86 159	77.89 160	80.00 168	53.88 279	69.40 169	84.61 183	43.21 234	86.56 81	58.80 216	77.68 188	84.95 181

dcpmvs_2		74.55 70	75.23 58	72.48 190	82.34 87	53.34 176	77.87 161	81.46 130	57.80 184	75.49 52	86.81 114	62.22 15	77.75 301	71.09 91	82.02 104	86.34 113

tttt0517		67.83 230	65.66 256	74.33 122	76.69 244	50.82 230	77.86 162	73.99 298	54.54 268	64.64 278	82.53 238	35.06 331	85.50 116	55.71 240	69.91 315	86.67 99

fmvsm_s_conf0.1_n		69.41 188	68.60 181	71.83 205	71.07 368	52.88 190	77.85 163	62.44 405	49.58 343	72.97 111	86.22 140	51.68 120	76.48 333	75.53 51	70.10 311	86.14 123

v1144		70.42 155	69.31 164	73.76 146	73.22 322	50.64 235	77.83 164	81.43 131	58.58 164	69.40 169	81.16 270	47.53 178	85.29 123	64.01 155	70.64 297	85.34 164

CNLPA		65.43 273	64.02 275	69.68 267	78.73 162	58.07 87	77.82 165	70.71 331	51.49 317	61.57 327	83.58 213	38.23 300	70.82 368	43.90 347	70.10 311	80.16 314

fmvsm_s_conf0.5_n_3		73.55 86	74.39 68	71.03 241	74.09 311	51.86 216	77.77 166	75.60 263	61.18 96	78.67 29	88.98 63	55.88 57	77.73 302	78.69 16	78.68 168	83.50 235

VDD-MVS		72.50 110	72.09 109	73.75 148	81.58 97	49.69 263	77.76 167	77.63 226	63.21 50	73.21 101	89.02 62	42.14 246	83.32 162	61.72 186	82.50 99	88.25 33

v1192		69.97 167	68.68 179	73.85 141	73.19 323	50.94 226	77.68 168	81.36 134	57.51 190	68.95 179	80.85 280	45.28 211	85.33 122	62.97 175	70.37 303	85.27 168

v2v482		70.50 153	69.45 162	73.66 154	72.62 334	50.03 253	77.58 169	80.51 159	59.90 133	69.52 165	82.14 251	47.53 178	84.88 133	65.07 147	70.17 309	86.09 125

WR-MVS_H		67.02 248	66.92 229	67.33 302	77.95 194	37.75 401	77.57 170	82.11 119	62.03 81	62.65 308	82.48 239	50.57 137	79.46 262	42.91 359	64.01 375	84.79 186

Anonymous20240529		69.91 168	69.02 170	72.56 187	80.19 126	47.65 301	77.56 171	80.99 151	55.45 239	69.88 161	86.76 115	39.24 287	82.18 202	54.04 255	77.10 201	87.85 50

v144192		69.71 173	68.51 182	73.33 170	73.10 325	50.13 250	77.54 172	80.64 156	56.65 203	68.57 183	80.55 283	46.87 192	84.96 129	62.98 174	69.66 322	84.89 183

baseline		74.61 68	74.70 64	74.34 121	75.70 261	49.99 254	77.54 172	84.63 47	62.73 64	73.98 83	87.79 88	57.67 33	83.82 152	69.49 98	82.74 98	89.20 8

viewmacassd2359aftdt		73.15 96	73.16 93	73.11 174	75.15 279	49.31 270	77.53 174	83.21 96	60.42 115	73.20 102	87.34 98	53.82 81	81.05 229	67.02 127	80.79 116	88.96 10

Fast-Effi-MVS+-dtu		67.37 238	65.33 264	73.48 164	72.94 329	57.78 92	77.47 175	76.88 241	57.60 189	61.97 319	76.85 354	39.31 284	80.49 244	54.72 249	70.28 307	82.17 272

fmvsm_l_conf0.5_n_9		73.27 93	73.66 83	72.09 199	73.82 312	52.72 195	77.45 176	74.28 292	56.61 210	77.10 43	88.16 76	56.17 47	77.09 315	78.27 24	81.13 115	86.48 107

v1921920		69.47 186	68.17 196	73.36 169	73.06 326	50.10 251	77.39 177	80.56 157	56.58 212	68.59 181	80.37 285	44.72 219	84.98 127	62.47 180	69.82 317	85.00 177

tt0805		67.77 232	67.24 223	69.34 274	74.87 283	40.08 377	77.36 178	81.37 133	55.31 241	66.33 239	84.65 181	37.35 308	82.55 194	55.65 242	72.28 278	85.39 162

GBi-Net		67.21 240	66.55 235	69.19 275	77.63 206	43.33 345	77.31 179	77.83 222	56.62 207	65.04 270	82.70 225	41.85 252	80.33 246	47.18 314	72.76 268	83.92 215

test1		67.21 240	66.55 235	69.19 275	77.63 206	43.33 345	77.31 179	77.83 222	56.62 207	65.04 270	82.70 225	41.85 252	80.33 246	47.18 314	72.76 268	83.92 215

FMVSNet1		66.70 255	65.87 252	69.19 275	77.49 214	43.33 345	77.31 179	77.83 222	56.45 213	64.60 279	82.70 225	38.08 302	80.33 246	46.08 324	72.31 277	83.92 215

fmvsm_s_conf0.5_n_9		75.16 60	75.22 59	75.01 99	78.34 178	55.37 138	77.30 182	73.95 299	61.40 90	79.46 23	90.14 41	57.07 37	81.15 224	80.00 5	79.31 147	88.51 26

MVS_111021_HR		74.02 78	73.46 87	75.69 86	83.01 80	60.63 40	77.29 183	78.40 213	61.18 96	70.58 148	85.97 151	54.18 73	84.00 149	67.52 118	82.98 92	82.45 265

SSM_0407		70.41 156	68.96 173	74.75 104	78.65 164	53.46 171	77.28 184	80.00 168	53.88 279	68.14 193	84.61 183	43.21 234	86.26 95	58.80 216	76.11 212	84.54 191

EIA-MVS		71.78 127	70.60 139	75.30 95	79.85 132	53.54 169	77.27 185	83.26 95	57.92 180	66.49 235	79.39 309	52.07 112	86.69 77	60.05 200	79.14 157	85.66 147

viewmanbaseed2359cas		72.92 101	72.89 97	73.00 176	75.16 277	49.25 273	77.25 186	83.11 104	59.52 146	72.93 113	86.63 124	54.11 74	80.98 230	66.63 131	80.67 120	88.76 19

v1240		69.24 192	67.91 201	73.25 173	73.02 328	49.82 255	77.21 187	80.54 158	56.43 214	68.34 188	80.51 284	43.33 233	84.99 125	62.03 184	69.77 320	84.95 181

fmvsm_l_conf0.5_n		70.99 142	70.82 135	71.48 219	71.45 359	54.40 151	77.18 188	70.46 333	48.67 355	75.17 57	86.86 112	53.77 83	76.86 323	76.33 41	77.51 191	83.17 247

E4		73.91 80	73.83 80	74.15 130	77.13 228	50.47 241	77.15 189	83.79 71	62.21 74	73.61 91	87.19 106	56.08 52	83.03 168	67.91 112	79.35 145	88.94 11

jason		69.65 177	68.39 189	73.43 167	78.27 181	56.88 108	77.12 190	73.71 302	46.53 387	69.34 171	83.22 219	43.37 232	79.18 268	64.77 149	79.20 152	84.23 203
jason: jason.
PAPM		67.92 227	66.69 233	71.63 216	78.09 188	49.02 276	77.09 191	81.24 143	51.04 325	60.91 333	83.98 200	47.71 173	84.99 125	40.81 373	79.32 146	80.90 299

EI-MVSNet-Vis-set		72.42 114	71.59 116	74.91 100	78.47 171	54.02 157	77.05 192	79.33 180	65.03 18	71.68 134	79.35 311	52.75 99	84.89 131	66.46 132	74.23 238	85.83 136

PEN-MVS		66.60 257	66.45 237	67.04 303	77.11 232	36.56 414	77.03 193	80.42 162	62.95 55	62.51 313	84.03 198	46.69 193	79.07 275	44.22 341	63.08 385	85.51 152

E2		73.72 83	73.60 84	74.06 133	77.16 224	50.40 242	76.97 194	83.74 72	61.64 86	73.36 96	86.75 118	56.14 48	82.99 170	67.50 119	79.18 155	88.80 13

E3		73.72 83	73.60 84	74.06 133	77.16 224	50.40 242	76.97 194	83.74 72	61.64 86	73.36 96	86.76 115	56.13 49	82.99 170	67.50 119	79.18 155	88.80 13

FIs		70.82 147	71.43 120	68.98 281	78.33 179	38.14 397	76.96 196	83.59 80	61.02 99	67.33 217	86.73 119	55.07 61	81.64 210	54.61 252	79.22 151	87.14 83

PS-CasMVS		66.42 261	66.32 245	66.70 307	77.60 212	36.30 419	76.94 197	79.61 174	62.36 70	62.43 316	83.66 208	45.69 200	78.37 287	45.35 337	63.26 383	85.42 160

h-mvs33		72.71 105	71.49 119	76.40 72	81.99 92	59.58 57	76.92 198	76.74 247	60.40 116	74.81 68	85.95 152	45.54 204	85.76 109	70.41 95	70.61 299	83.86 219

fmvsm_l_conf0.5_n_a		70.50 153	70.27 146	71.18 235	71.30 365	54.09 156	76.89 199	69.87 337	47.90 369	74.37 77	86.49 132	53.07 96	76.69 329	75.41 52	77.11 200	82.76 254

thisisatest0530		67.92 227	65.78 254	74.33 122	76.29 253	51.03 225	76.89 199	74.25 293	53.67 286	65.59 255	81.76 260	35.15 330	85.50 116	55.94 235	72.47 273	86.47 108

viewcassd2359sk11		73.56 85	73.41 89	74.00 137	77.13 228	50.35 245	76.86 201	83.69 76	61.23 95	73.14 105	86.38 136	56.09 51	82.96 173	67.15 123	79.01 160	88.70 20

test_0402		63.25 303	61.01 323	69.96 260	80.00 130	54.37 152	76.86 201	72.02 322	54.58 267	58.71 358	80.79 282	35.00 332	84.36 141	26.41 458	64.71 369	71.15 428

CP-MVSNet		66.49 260	66.41 241	66.72 305	77.67 204	36.33 417	76.83 203	79.52 176	62.45 68	62.54 311	83.47 216	46.32 196	78.37 287	45.47 335	63.43 382	85.45 157

E3new		73.41 89	73.22 92	73.95 140	77.06 233	50.31 246	76.78 204	83.66 77	60.90 102	72.93 113	86.02 149	55.99 53	82.95 175	66.89 130	78.77 165	88.61 22

fmvsm_s_conf0.5_n_4		72.04 123	71.85 112	72.58 185	73.74 315	52.49 202	76.69 205	72.42 317	56.42 215	75.32 54	87.04 108	52.13 111	78.01 293	79.29 12	73.65 248	87.26 78

EI-MVSNet-UG-set		71.92 124	71.06 131	74.52 117	77.98 193	53.56 168	76.62 206	79.16 181	64.40 29	71.18 141	78.95 316	52.19 109	84.66 138	65.47 143	73.57 251	85.32 165

RRT-MVS		71.46 134	70.70 138	73.74 149	77.76 200	49.30 271	76.60 207	80.45 161	61.25 94	68.17 191	84.78 176	44.64 220	84.90 130	64.79 148	77.88 185	87.03 85

lupinMVS		69.57 181	68.28 194	73.44 166	78.76 160	57.15 104	76.57 208	73.29 308	46.19 390	69.49 166	82.18 247	43.99 228	79.23 267	64.66 150	79.37 142	83.93 214

TranMVSNet+NR-MVSNet		70.36 157	70.10 152	71.17 236	78.64 167	42.97 351	76.53 209	81.16 147	66.95 6	68.53 184	85.42 168	51.61 121	83.07 167	52.32 268	69.70 321	87.46 67

TAPA-MVS	59.36 10	66.60 257	65.20 266	70.81 245	76.63 247	48.75 282	76.52 210	80.04 167	50.64 330	65.24 265	84.93 173	39.15 288	78.54 286	36.77 400	76.88 203	85.14 171
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
DTE-MVSNet		65.58 271	65.34 263	66.31 315	76.06 257	34.79 427	76.43 211	79.38 179	62.55 66	61.66 325	83.83 203	45.60 202	79.15 272	41.64 371	60.88 401	85.00 177

anonymousdsp		67.00 249	64.82 269	73.57 160	70.09 385	56.13 117	76.35 212	77.35 233	48.43 360	64.99 273	80.84 281	33.01 357	80.34 245	64.66 150	67.64 347	84.23 203

MVP-Stereo		65.41 274	63.80 279	70.22 255	77.62 210	55.53 134	76.30 213	78.53 204	50.59 331	56.47 383	78.65 320	39.84 279	82.68 189	44.10 345	72.12 281	72.44 410
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
fmvsm_s_conf0.5_n_6		72.59 109	72.87 98	71.73 210	75.14 280	51.96 214	76.28 214	77.12 238	57.63 188	73.85 88	86.91 111	51.54 122	77.87 298	77.18 32	80.18 131	85.37 163

MVS_Test		72.45 112	72.46 104	72.42 194	74.88 282	48.50 288	76.28 214	83.14 102	59.40 147	72.46 123	84.68 179	55.66 58	81.12 225	65.98 139	79.66 138	87.63 60

LuminaMVS		68.24 218	66.82 231	72.51 189	73.46 321	53.60 167	76.23 216	78.88 189	52.78 296	68.08 199	80.13 291	32.70 365	81.41 216	63.16 172	75.97 216	82.53 261

IterMVS-LS		69.22 193	68.48 183	71.43 225	74.44 299	49.40 267	76.23 216	77.55 227	59.60 141	65.85 252	81.59 265	51.28 127	81.58 213	59.87 204	69.90 316	83.30 238
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
新几何2							76.12 218

FMVSNet2		66.93 250	66.31 246	68.79 284	77.63 206	42.98 350	76.11 219	77.47 228	56.62 207	65.22 267	82.17 249	41.85 252	80.18 252	47.05 317	72.72 271	83.20 242

旧先验2							76.08 220		45.32 398	76.55 47			65.56 404	58.75 218

BH-untuned		68.27 216	67.29 218	71.21 233	79.74 133	53.22 179	76.06 221	77.46 230	57.19 193	66.10 244	81.61 263	45.37 210	83.50 159	45.42 336	76.68 207	76.91 364

FC-MVSNet-test		69.80 172	70.58 141	67.46 298	77.61 211	34.73 430	76.05 222	83.19 100	60.84 104	65.88 251	86.46 133	54.52 70	80.76 239	52.52 267	78.12 181	86.91 88

PCF-MVS	61.88 8	70.95 143	69.49 160	75.35 93	77.63 206	55.71 127	76.04 223	81.81 123	50.30 333	69.66 164	85.40 169	52.51 102	84.89 131	51.82 275	80.24 129	85.45 157
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
UniMVSNet_NR-MVSNet		71.11 138	71.00 132	71.44 223	79.20 147	44.13 337	76.02 224	82.60 112	66.48 11	68.20 189	84.60 186	56.82 40	82.82 186	54.62 250	70.43 301	87.36 76

UniMVSNet (Re)		70.63 150	70.20 147	71.89 203	78.55 168	45.29 326	75.94 225	82.92 106	63.68 42	68.16 192	83.59 210	53.89 79	83.49 160	53.97 256	71.12 292	86.89 89

KinetiMVS		71.26 137	70.16 149	74.57 114	74.59 294	52.77 194	75.91 226	81.20 144	60.72 108	69.10 178	85.71 161	41.67 257	83.53 158	63.91 159	78.62 171	87.42 69

test_fmvsmvis_n_1920		70.84 144	70.38 144	72.22 198	71.16 367	55.39 137	75.86 227	72.21 320	49.03 350	73.28 100	86.17 143	51.83 117	77.29 312	75.80 46	78.05 182	83.98 212

EPNet_dtu		61.90 322	61.97 307	61.68 367	72.89 330	39.78 381	75.85 228	65.62 375	55.09 248	54.56 404	79.36 310	37.59 305	67.02 395	39.80 381	76.95 202	78.25 340
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MGCFI-Net		72.45 112	73.34 91	69.81 266	77.77 199	43.21 348	75.84 229	81.18 145	59.59 144	75.45 53	86.64 122	57.74 31	77.94 294	63.92 157	81.90 106	88.30 31

v148		68.24 218	67.19 226	71.40 226	70.43 378	47.77 300	75.76 230	77.03 240	58.91 155	67.36 216	80.10 293	48.60 164	81.89 206	60.01 201	66.52 357	84.53 194

test_fmvsm_n_1920		71.73 129	71.14 129	73.50 162	72.52 337	56.53 111	75.60 231	76.16 252	48.11 365	77.22 40	85.56 163	53.10 94	77.43 307	74.86 57	77.14 199	86.55 104

SixPastTwentyTwo		61.65 325	58.80 343	70.20 257	75.80 259	47.22 306	75.59 232	69.68 339	54.61 265	54.11 408	79.26 312	27.07 419	82.96 173	43.27 354	49.79 447	80.41 308

DELS-MVS		74.76 64	74.46 67	75.65 88	77.84 197	52.25 207	75.59 232	84.17 54	63.76 40	73.15 104	82.79 224	59.58 23	86.80 74	67.24 122	86.04 65	87.89 47
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)		69.82 170	68.48 183	73.84 142	78.44 172	50.04 252	75.58 234	78.99 187	58.16 171	67.59 213	82.14 251	42.66 240	85.63 110	56.60 229	76.19 211	85.84 135

Baseline_NR-MVSNet		67.05 247	67.56 206	65.50 333	75.65 262	37.70 403	75.42 235	74.65 286	59.90 133	68.14 193	83.15 222	49.12 159	77.20 313	52.23 269	69.78 318	81.60 278

OpenMVS_ROB	52.78 18	60.03 340	58.14 350	65.69 330	70.47 377	44.82 328	75.33 236	70.86 330	45.04 399	56.06 386	76.00 370	26.89 422	79.65 257	35.36 413	67.29 350	72.60 405

viewdifsd2359ckpt07		71.90 125	71.97 111	71.69 213	74.81 286	48.08 294	75.30 237	80.49 160	60.00 131	71.63 135	86.33 138	56.34 45	79.25 266	65.40 144	77.41 193	87.76 55

xiu_mvs_v1_base_debu		68.58 208	67.28 219	72.48 190	78.19 183	57.19 101	75.28 238	75.09 278	51.61 313	70.04 154	81.41 267	32.79 360	79.02 277	63.81 160	77.31 194	81.22 290

xiu_mvs_v1_base		68.58 208	67.28 219	72.48 190	78.19 183	57.19 101	75.28 238	75.09 278	51.61 313	70.04 154	81.41 267	32.79 360	79.02 277	63.81 160	77.31 194	81.22 290

xiu_mvs_v1_base_debi		68.58 208	67.28 219	72.48 190	78.19 183	57.19 101	75.28 238	75.09 278	51.61 313	70.04 154	81.41 267	32.79 360	79.02 277	63.81 160	77.31 194	81.22 290

EI-MVSNet		69.27 191	68.44 187	71.73 210	74.47 297	49.39 268	75.20 241	78.45 209	59.60 141	69.16 176	76.51 363	51.29 126	82.50 195	59.86 205	71.45 289	83.30 238

CVMVSNet		59.63 346	59.14 337	61.08 376	74.47 297	38.84 390	75.20 241	68.74 350	31.15 453	58.24 365	76.51 363	32.39 373	68.58 382	49.77 289	65.84 361	75.81 372

ET-MVSNet_ETH3D		67.96 226	65.72 255	74.68 107	76.67 246	55.62 132	75.11 243	74.74 283	52.91 294	60.03 341	80.12 292	33.68 349	82.64 191	61.86 185	76.34 209	85.78 137

xiu_mvs_v2_base		70.52 151	69.75 154	72.84 180	81.21 107	55.63 130	75.11 243	78.92 188	54.92 259	69.96 160	79.68 302	47.00 191	82.09 203	61.60 188	79.37 142	80.81 301

K. test v3		60.47 337	57.11 356	70.56 251	73.74 315	48.22 291	75.10 245	62.55 403	58.27 170	53.62 414	76.31 367	27.81 411	81.59 212	47.42 310	39.18 462	81.88 276

Fast-Effi-MVS+		70.28 159	69.12 169	73.73 150	78.50 169	51.50 220	75.01 246	79.46 178	56.16 222	68.59 181	79.55 305	53.97 77	84.05 145	53.34 262	77.53 190	85.65 148

DU-MVS		70.01 165	69.53 159	71.44 223	78.05 190	44.13 337	75.01 246	81.51 129	64.37 30	68.20 189	84.52 187	49.12 159	82.82 186	54.62 250	70.43 301	87.37 74

FMVSNet3		66.32 264	65.61 257	68.46 287	76.48 251	42.34 355	74.98 248	77.15 237	55.83 227	65.04 270	81.16 270	39.91 277	80.14 253	47.18 314	72.76 268	82.90 252

mvsmamba		68.47 212	66.56 234	74.21 127	79.60 136	52.95 185	74.94 249	75.48 268	52.09 308	60.10 339	83.27 218	36.54 319	84.70 135	59.32 210	77.69 187	84.99 179

MTAPA		76.90 38	76.42 42	78.35 39	86.08 38	63.57 2	74.92 250	80.97 152	65.13 15	75.77 50	90.88 20	48.63 162	86.66 78	77.23 30	88.17 37	84.81 185

PS-MVSNAJ		70.51 152	69.70 156	72.93 178	81.52 98	55.79 126	74.92 250	79.00 186	55.04 254	69.88 161	78.66 319	47.05 187	82.19 201	61.61 187	79.58 139	80.83 300

MVS_111021_LR		69.50 185	68.78 177	71.65 215	78.38 174	59.33 61	74.82 252	70.11 335	58.08 172	67.83 208	84.68 179	41.96 248	76.34 336	65.62 142	77.54 189	79.30 330

ECVR-MVS		67.72 233	67.51 210	68.35 289	79.46 140	36.29 420	74.79 253	66.93 364	58.72 158	67.19 221	88.05 80	36.10 321	81.38 218	52.07 271	84.25 78	87.39 72

test_yl		69.69 174	69.13 167	71.36 229	78.37 176	45.74 319	74.71 254	80.20 165	57.91 181	70.01 158	83.83 203	42.44 243	82.87 182	54.97 246	79.72 136	85.48 153

DCV-MVSNet		69.69 174	69.13 167	71.36 229	78.37 176	45.74 319	74.71 254	80.20 165	57.91 181	70.01 158	83.83 203	42.44 243	82.87 182	54.97 246	79.72 136	85.48 153

TransMVSNet (Re)		64.72 282	64.33 272	65.87 328	75.22 274	38.56 392	74.66 256	75.08 281	58.90 156	61.79 322	82.63 228	51.18 128	78.07 292	43.63 352	55.87 425	80.99 298

BH-w/o		66.85 251	65.83 253	69.90 264	79.29 142	52.46 203	74.66 256	76.65 248	54.51 269	64.85 275	78.12 327	45.59 203	82.95 175	43.26 355	75.54 223	74.27 394

IMVS_0403		69.09 196	68.14 197	71.95 201	77.06 233	49.73 257	74.51 258	78.60 198	52.70 297	66.69 231	82.58 230	46.43 195	83.38 161	59.20 211	75.46 225	82.74 255

PVSNet_BlendedMVS		68.56 211	67.72 203	71.07 240	77.03 239	50.57 236	74.50 259	81.52 127	53.66 287	64.22 286	79.72 301	49.13 157	82.87 182	55.82 237	73.92 242	79.77 325

MonoMVSNet		64.15 292	63.31 290	66.69 308	70.51 376	44.12 339	74.47 260	74.21 294	57.81 183	63.03 299	76.62 359	38.33 297	77.31 311	54.22 254	60.59 407	78.64 337

c3_l		68.33 215	67.56 206	70.62 250	70.87 371	46.21 315	74.47 260	78.80 192	56.22 221	66.19 241	78.53 324	51.88 114	81.40 217	62.08 181	69.04 332	84.25 202

test2506		65.33 276	64.61 270	67.50 297	79.46 140	34.19 435	74.43 262	51.92 446	58.72 158	66.75 230	88.05 80	25.99 427	80.92 234	51.94 273	84.25 78	87.39 72

IMVS_0407		68.90 200	67.93 200	71.82 206	77.06 233	49.73 257	74.40 263	78.60 198	52.70 297	66.19 241	82.58 230	45.17 214	83.00 169	59.20 211	75.46 225	82.74 255

BH-RMVSNet		68.81 202	67.42 213	72.97 177	80.11 129	52.53 200	74.26 264	76.29 251	58.48 166	68.38 187	84.20 193	42.59 241	83.83 151	46.53 319	75.91 217	82.56 259

NR-MVSNet		69.54 182	68.85 174	71.59 217	78.05 190	43.81 342	74.20 265	80.86 154	65.18 14	62.76 305	84.52 187	52.35 107	83.59 157	50.96 283	70.78 296	87.37 74

UniMVSNet_ETH3D		67.60 235	67.07 228	69.18 278	77.39 217	42.29 356	74.18 266	75.59 264	60.37 119	66.77 229	86.06 147	37.64 304	78.93 282	52.16 270	73.49 253	86.32 117

VPA-MVSNet		69.02 197	69.47 161	67.69 296	77.42 216	41.00 372	74.04 267	79.68 172	60.06 129	69.26 174	84.81 175	51.06 131	77.58 305	54.44 253	74.43 236	84.48 196

miper_ehance_all_eth		68.03 223	67.24 223	70.40 254	70.54 375	46.21 315	73.98 268	78.68 196	55.07 251	66.05 245	77.80 338	52.16 110	81.31 220	61.53 191	69.32 326	83.67 228

hse-mvs2		71.04 139	69.86 153	74.60 112	79.58 137	57.12 106	73.96 269	75.25 273	60.40 116	74.81 68	81.95 255	45.54 204	82.90 179	70.41 95	66.83 354	83.77 224

1314		64.61 286	63.21 292	68.80 283	71.87 352	47.46 304	73.95 270	78.39 214	42.88 420	59.97 342	76.60 362	38.11 301	79.39 264	54.84 248	72.32 276	79.55 326

MVS		67.37 238	66.33 244	70.51 253	75.46 269	50.94 226	73.95 270	81.85 122	41.57 427	62.54 311	78.57 323	47.98 168	85.47 118	52.97 265	82.05 103	75.14 380

AUN-MVS		68.45 214	66.41 241	74.57 114	79.53 139	57.08 107	73.93 272	75.23 274	54.44 270	66.69 231	81.85 257	37.10 314	82.89 180	62.07 182	66.84 353	83.75 225

OurMVSNet-221017-0		61.37 330	58.63 345	69.61 268	72.05 348	48.06 295	73.93 272	72.51 316	47.23 380	54.74 401	80.92 277	21.49 445	81.24 222	48.57 302	56.22 424	79.53 327

test1111		67.21 240	67.14 227	67.42 299	79.24 146	34.76 429	73.89 274	65.65 374	58.71 160	66.96 226	87.95 84	36.09 322	80.53 241	52.03 272	83.79 84	86.97 87

cl22		67.47 237	66.45 237	70.54 252	69.85 391	46.49 311	73.85 275	77.35 233	55.07 251	65.51 256	77.92 333	47.64 175	81.10 226	61.58 189	69.32 326	84.01 211

TAMVS		66.78 254	65.27 265	71.33 232	79.16 151	53.67 164	73.84 276	69.59 341	52.32 306	65.28 260	81.72 261	44.49 223	77.40 309	42.32 363	78.66 170	82.92 250

WR-MVS		68.47 212	68.47 185	68.44 288	80.20 125	39.84 380	73.75 277	76.07 255	64.68 24	68.11 197	83.63 209	50.39 139	79.14 273	49.78 288	69.66 322	86.34 113

eth_miper_zixun_eth		67.63 234	66.28 247	71.67 214	71.60 355	48.33 290	73.68 278	77.88 220	55.80 229	65.91 248	78.62 322	47.35 184	82.88 181	59.45 207	66.25 358	83.81 220

guyue		68.10 222	67.23 225	70.71 249	73.67 317	49.27 272	73.65 279	76.04 257	55.62 235	67.84 207	82.26 245	41.24 267	78.91 283	61.01 193	73.72 246	83.94 213

TR-MVS		66.59 259	65.07 267	71.17 236	79.18 149	49.63 265	73.48 280	75.20 276	52.95 293	67.90 201	80.33 288	39.81 280	83.68 154	43.20 356	73.56 252	80.20 313

VortexMVS		66.41 262	65.50 259	69.16 279	73.75 313	48.14 292	73.41 281	78.28 216	53.73 284	64.98 274	78.33 325	40.62 272	79.07 275	58.88 215	67.50 348	80.26 312

fmvsm_s_conf0.1_n_2		69.64 178	69.01 172	71.52 218	71.66 354	51.04 224	73.39 282	67.14 362	55.02 257	75.11 58	87.64 89	42.94 239	77.01 318	75.55 50	72.63 272	86.52 106

fmvsm_s_conf0.5_n_2		69.82 170	69.27 166	71.46 220	72.00 349	51.08 223	73.30 283	67.79 356	55.06 253	75.24 56	87.51 90	44.02 227	77.00 319	75.67 48	72.86 266	86.31 120

cl____		67.18 243	66.26 248	69.94 261	70.20 382	45.74 319	73.30 283	76.83 244	55.10 246	65.27 261	79.57 304	47.39 182	80.53 241	59.41 209	69.22 330	83.53 234

DIV-MVS_self_test		67.18 243	66.26 248	69.94 261	70.20 382	45.74 319	73.29 285	76.83 244	55.10 246	65.27 261	79.58 303	47.38 183	80.53 241	59.43 208	69.22 330	83.54 233

AstraMVS		67.86 229	66.83 230	70.93 243	73.50 319	49.34 269	73.28 286	74.01 297	55.45 239	68.10 198	83.28 217	38.93 291	79.14 273	63.22 171	71.74 284	84.30 201

CDS-MVSNet		66.80 253	65.37 262	71.10 239	78.98 154	53.13 183	73.27 287	71.07 328	52.15 307	64.72 276	80.23 290	43.56 231	77.10 314	45.48 334	78.88 161	83.05 249
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
viewdifsd2359ckpt11		69.13 194	68.38 190	71.38 227	71.57 356	48.61 285	73.22 288	73.18 309	57.65 186	70.67 146	84.73 177	50.03 141	79.80 254	63.25 169	71.10 293	85.74 143

viewmsd2359difaftdt		69.13 194	68.38 190	71.38 227	71.57 356	48.61 285	73.22 288	73.18 309	57.65 186	70.67 146	84.73 177	50.03 141	79.80 254	63.25 169	71.10 293	85.74 143

diffmvs_AUTHOR		71.02 140	70.87 134	71.45 222	69.89 389	48.97 279	73.16 290	78.33 215	57.79 185	72.11 129	85.26 171	51.84 116	77.89 297	71.00 92	78.47 176	87.49 66

pmmvs6		63.69 297	62.82 297	66.27 317	70.63 373	39.27 387	73.13 291	75.47 269	52.69 302	59.75 348	82.30 243	39.71 281	77.03 317	47.40 311	64.35 374	82.53 261

IB-MVS	56.42 12	65.40 275	62.73 298	73.40 168	74.89 281	52.78 193	73.09 292	75.13 277	55.69 231	58.48 364	73.73 396	32.86 359	86.32 92	50.63 284	70.11 310	81.10 294
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		70.69 149	70.43 142	71.46 220	69.45 396	48.95 280	72.93 293	78.46 208	57.27 192	71.69 133	83.97 201	51.48 124	77.92 296	70.70 94	77.95 184	87.53 65
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
FE-MVSNET2		62.01 321	60.88 325	65.42 335	68.74 404	38.43 395	72.92 294	77.39 231	54.74 264	55.40 393	76.71 356	35.46 327	76.72 328	44.25 340	62.31 391	81.10 294

V42		68.65 206	67.35 217	72.56 187	68.93 403	50.18 249	72.90 295	79.47 177	56.92 200	69.45 168	80.26 289	46.29 197	82.99 170	64.07 153	67.82 345	84.53 194

miper_enhance_ethall		67.11 246	66.09 250	70.17 258	69.21 399	45.98 317	72.85 296	78.41 212	51.38 319	65.65 254	75.98 373	51.17 129	81.25 221	60.82 195	69.32 326	83.29 240

thres100view900		63.28 302	62.41 301	65.89 326	77.31 220	38.66 391	72.65 297	69.11 348	57.07 196	62.45 314	81.03 274	37.01 316	79.17 269	31.84 430	73.25 260	79.83 322

testdata1							72.65 297		60.50 113

FE-MVS		65.91 267	63.33 289	73.63 157	77.36 218	51.95 215	72.62 299	75.81 259	53.70 285	65.31 259	78.96 315	28.81 402	86.39 89	43.93 346	73.48 254	82.55 260

pm-mvs1		65.24 277	64.97 268	66.04 323	72.38 342	39.40 386	72.62 299	75.63 262	55.53 236	62.35 318	83.18 221	47.45 180	76.47 334	49.06 298	66.54 356	82.24 269

test222					83.14 76	58.68 81	72.57 301	63.45 396	41.78 423	67.56 214	86.12 144	37.13 313			78.73 167	74.98 384

PVSNet_Blended		68.59 207	67.72 203	71.19 234	77.03 239	50.57 236	72.51 302	81.52 127	51.91 310	64.22 286	77.77 341	49.13 157	82.87 182	55.82 237	79.58 139	80.14 315

EU-MVSNet		55.61 380	54.41 383	59.19 387	65.41 428	33.42 440	72.44 303	71.91 323	28.81 455	51.27 424	73.87 395	24.76 434	69.08 379	43.04 357	58.20 415	75.06 381

thres600view7		63.30 301	62.27 303	66.41 313	77.18 223	38.87 389	72.35 304	69.11 348	56.98 199	62.37 317	80.96 276	37.01 316	79.00 280	31.43 437	73.05 264	81.36 285

pmmvs-eth3d		58.81 351	56.31 368	66.30 316	67.61 412	52.42 205	72.30 305	64.76 382	43.55 413	54.94 399	74.19 391	28.95 399	72.60 354	43.31 353	57.21 419	73.88 398

viewmambaseed2359dif		68.91 199	68.18 195	71.11 238	70.21 381	48.05 297	72.28 306	75.90 258	51.96 309	70.93 143	84.47 190	51.37 125	78.59 285	61.55 190	74.97 230	86.68 98

cascas		65.98 266	63.42 287	73.64 156	77.26 221	52.58 199	72.26 307	77.21 236	48.56 356	61.21 330	74.60 388	32.57 371	85.82 108	50.38 286	76.75 206	82.52 263

VPNet		67.52 236	68.11 198	65.74 329	79.18 149	36.80 412	72.17 308	72.83 314	62.04 80	67.79 210	85.83 156	48.88 161	76.60 331	51.30 279	72.97 265	83.81 220

MS-PatchMatch		62.42 313	61.46 313	65.31 339	75.21 275	52.10 209	72.05 309	74.05 296	46.41 388	57.42 375	74.36 389	34.35 340	77.57 306	45.62 330	73.67 247	66.26 447

mvs_anonymous		68.03 223	67.51 210	69.59 269	72.08 347	44.57 334	71.99 310	75.23 274	51.67 311	67.06 224	82.57 234	54.68 68	77.94 294	56.56 232	75.71 221	86.26 122

patch_mono-2		69.85 169	71.09 130	66.16 319	79.11 152	54.80 147	71.97 311	74.31 290	53.50 288	70.90 144	84.17 194	57.63 34	63.31 413	66.17 134	82.02 104	80.38 309

tfpn200view9		63.18 304	62.18 305	66.21 318	76.85 242	39.62 383	71.96 312	69.44 344	56.63 205	62.61 309	79.83 296	37.18 310	79.17 269	31.84 430	73.25 260	79.83 322

thres400		63.31 300	62.18 305	66.72 305	76.85 242	39.62 383	71.96 312	69.44 344	56.63 205	62.61 309	79.83 296	37.18 310	79.17 269	31.84 430	73.25 260	81.36 285

SD_0403		63.07 306	63.49 286	61.82 366	75.16 277	31.14 452	71.89 314	73.47 303	53.34 290	58.22 366	81.81 259	45.17 214	73.86 349	37.43 394	74.87 232	80.45 306

baseline1		63.81 296	63.87 278	63.62 353	76.29 253	36.36 415	71.78 315	67.29 360	56.05 224	64.23 285	82.95 223	47.11 186	74.41 346	47.30 313	61.85 395	80.10 316

baseline2		63.42 299	61.26 318	69.89 265	72.55 336	47.62 302	71.54 316	68.38 352	50.11 335	54.82 400	75.55 378	43.06 237	80.96 231	48.13 306	67.16 352	81.11 293

pmmvs4		61.48 328	59.39 335	67.76 295	71.57 356	53.86 159	71.42 317	65.34 377	44.20 407	59.46 350	77.92 333	35.90 323	74.71 344	43.87 348	64.87 368	74.71 390

1112_ss		64.00 295	63.36 288	65.93 325	79.28 144	42.58 354	71.35 318	72.36 319	46.41 388	60.55 336	77.89 336	46.27 198	73.28 351	46.18 323	69.97 313	81.92 275

thisisatest0515		65.83 268	63.50 285	72.82 182	73.75 313	49.50 266	71.32 319	73.12 313	49.39 345	63.82 288	76.50 365	34.95 333	84.84 134	53.20 264	75.49 224	84.13 208

CostFormer		64.04 294	62.51 299	68.61 286	71.88 351	45.77 318	71.30 320	70.60 332	47.55 374	64.31 282	76.61 361	41.63 258	79.62 259	49.74 290	69.00 333	80.42 307

tfpnnormal		62.47 312	61.63 311	64.99 342	74.81 286	39.01 388	71.22 321	73.72 301	55.22 245	60.21 337	80.09 294	41.26 266	76.98 321	30.02 444	68.09 343	78.97 335

IterMVS		62.79 309	61.27 317	67.35 301	69.37 397	52.04 212	71.17 322	68.24 354	52.63 303	59.82 345	76.91 353	37.32 309	72.36 356	52.80 266	63.19 384	77.66 350
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Vis-MVSNet (Re-imp)		63.69 297	63.88 277	63.14 358	74.75 288	31.04 453	71.16 323	63.64 394	56.32 217	59.80 346	84.99 172	44.51 221	75.46 341	39.12 385	80.62 121	82.92 250

IterMVS-SCA-FT		62.49 311	61.52 312	65.40 336	71.99 350	50.80 231	71.15 324	69.63 340	45.71 396	60.61 335	77.93 332	37.45 306	65.99 402	55.67 241	63.50 381	79.42 328

Anonymous202405211		66.84 252	65.99 251	69.40 273	80.19 126	42.21 358	71.11 325	71.31 326	58.80 157	67.90 201	86.39 135	29.83 392	79.65 257	49.60 294	78.78 164	86.33 115

Anonymous20240521		55.30 381	54.41 383	57.96 398	60.92 453	41.73 362	71.09 326	71.06 329	41.18 428	48.65 438	73.31 399	16.93 451	59.25 429	42.54 361	64.01 375	72.90 402

tpm2		62.07 318	60.10 331	67.99 293	72.79 331	43.86 341	71.05 327	66.85 365	43.14 418	62.77 304	75.39 382	38.32 298	80.80 237	41.69 368	68.88 334	79.32 329

TDRefinement		53.44 395	50.72 405	61.60 368	64.31 434	46.96 308	70.89 328	65.27 379	41.78 423	44.61 451	77.98 330	11.52 466	66.36 399	28.57 450	51.59 441	71.49 423

blend_shiyan4		61.38 329	59.10 339	68.20 291	68.94 402	44.64 332	70.81 329	76.52 249	51.63 312	57.56 372	69.94 426	28.30 406	79.61 260	47.44 309	60.78 403	80.36 310

XVG-ACMP-BASELINE		64.36 290	62.23 304	70.74 247	72.35 343	52.45 204	70.80 330	78.45 209	53.84 281	59.87 344	81.10 272	16.24 454	79.32 265	55.64 243	71.76 283	80.47 305

mmtdpeth		60.40 338	59.12 338	64.27 348	69.59 393	48.99 277	70.67 331	70.06 336	54.96 258	62.78 303	73.26 401	27.00 420	67.66 388	58.44 221	45.29 454	76.16 369

XVG-OURS-SEG-HR		68.81 202	67.47 212	72.82 182	74.40 300	56.87 109	70.59 332	79.04 185	54.77 262	66.99 225	86.01 150	39.57 282	78.21 290	62.54 178	73.33 258	83.37 237

VNet		69.68 176	70.19 148	68.16 292	79.73 134	41.63 365	70.53 333	77.38 232	60.37 119	70.69 145	86.63 124	51.08 130	77.09 315	53.61 260	81.69 112	85.75 142

GA-MVS		65.53 272	63.70 281	71.02 242	70.87 371	48.10 293	70.48 334	74.40 288	56.69 202	64.70 277	76.77 355	33.66 350	81.10 226	55.42 245	70.32 306	83.87 218

MSDG		61.81 324	59.23 336	69.55 272	72.64 333	52.63 198	70.45 335	75.81 259	51.38 319	53.70 411	76.11 368	29.52 394	81.08 228	37.70 392	65.79 362	74.93 385

ab-mvs		66.65 256	66.42 240	67.37 300	76.17 255	41.73 362	70.41 336	76.14 254	53.99 276	65.98 246	83.51 214	49.48 149	76.24 337	48.60 301	73.46 255	84.14 207

fmvsm_s_conf0.5_n_7		69.54 182	69.67 157	69.15 280	73.47 320	51.41 221	70.35 337	73.34 305	57.05 197	68.41 185	85.83 156	49.86 144	72.84 353	71.86 84	76.83 204	83.19 243

EGC-MVSNET		42.47 425	38.48 433	54.46 416	74.33 302	48.73 283	70.33 338	51.10 449	0.03 486	0.18 487	67.78 438	13.28 460	66.49 398	18.91 469	50.36 445	48.15 466

MVSTER		67.16 245	65.58 258	71.88 204	70.37 380	49.70 261	70.25 339	78.45 209	51.52 316	69.16 176	80.37 285	38.45 295	82.50 195	60.19 199	71.46 288	83.44 236

reproduce_monomvs		62.56 310	61.20 320	66.62 310	70.62 374	44.30 336	70.13 340	73.13 312	54.78 261	61.13 331	76.37 366	25.63 430	75.63 340	58.75 218	60.29 408	79.93 318

XVG-OURS		68.76 205	67.37 215	72.90 179	74.32 303	57.22 99	70.09 341	78.81 191	55.24 244	67.79 210	85.81 159	36.54 319	78.28 289	62.04 183	75.74 220	83.19 243

HY-MVS	56.14 13	64.55 287	63.89 276	66.55 311	74.73 289	41.02 369	69.96 342	74.43 287	49.29 347	61.66 325	80.92 277	47.43 181	76.68 330	44.91 339	71.69 285	81.94 274

AllTest		57.08 365	54.65 379	64.39 346	71.44 360	49.03 274	69.92 343	67.30 358	45.97 393	47.16 442	79.77 298	17.47 448	67.56 391	33.65 418	59.16 412	76.57 365

testing3		56.54 369	55.92 371	58.41 392	77.52 213	27.93 463	69.72 344	56.36 433	54.75 263	58.63 362	77.80 338	20.88 446	71.75 363	25.31 460	62.25 392	75.53 376

sc_t1		59.76 343	57.84 354	65.54 331	74.87 283	42.95 352	69.61 345	64.16 389	48.90 352	58.68 359	77.12 348	28.19 408	72.35 357	43.75 351	55.28 427	81.31 288

FE-MVSNET3		64.34 291	63.57 283	66.66 309	72.44 341	40.74 375	69.60 346	76.80 246	53.21 291	61.73 324	77.92 333	41.92 251	77.68 304	46.23 322	72.25 279	81.57 279

thres200		62.20 317	61.16 321	65.34 338	75.38 272	39.99 379	69.60 346	69.29 346	55.64 234	61.87 321	76.99 351	37.07 315	78.96 281	31.28 438	73.28 259	77.06 359

tpmrst		58.24 356	58.70 344	56.84 403	66.97 416	34.32 433	69.57 348	61.14 414	47.17 381	58.58 363	71.60 412	41.28 265	60.41 423	49.20 296	62.84 386	75.78 373

PatchmatchNet		59.84 342	58.24 348	64.65 344	73.05 327	46.70 310	69.42 349	62.18 409	47.55 374	58.88 357	71.96 409	34.49 338	69.16 378	42.99 358	63.60 379	78.07 342
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
WB-MVSnew		59.66 345	59.69 333	59.56 380	75.19 276	35.78 424	69.34 350	64.28 386	46.88 384	61.76 323	75.79 374	40.61 273	65.20 405	32.16 426	71.21 290	77.70 349

GG-mvs-BLEND				62.34 363	71.36 364	37.04 410	69.20 351	57.33 430		54.73 402	65.48 449	30.37 383	77.82 299	34.82 414	74.93 231	72.17 415

HyFIR lowres test		65.67 270	63.01 294	73.67 153	79.97 131	55.65 129	69.07 352	75.52 266	42.68 421	63.53 291	77.95 331	40.43 274	81.64 210	46.01 325	71.91 282	83.73 226

UWE-MVS		60.18 339	59.78 332	61.39 372	77.67 204	33.92 438	69.04 353	63.82 392	48.56 356	64.27 283	77.64 343	27.20 417	70.40 373	33.56 421	76.24 210	79.83 322

test_post1							68.67 354				3.64 484	32.39 373	69.49 377	44.17 342

tt0320		58.59 352	56.81 362	63.92 351	75.46 269	41.32 367	68.63 355	64.06 390	47.05 382	56.19 385	74.19 391	30.34 384	71.36 364	39.92 380	55.45 426	79.09 331

testing222		62.29 316	61.31 316	65.25 340	77.87 195	38.53 393	68.34 356	66.31 370	56.37 216	63.15 298	77.58 344	28.47 404	76.18 339	37.04 398	76.65 208	81.05 297

tt0320-xc		58.33 355	56.41 367	64.08 349	75.79 260	41.34 366	68.30 357	62.72 402	47.90 369	56.29 384	74.16 393	28.53 403	71.04 367	41.50 372	52.50 439	79.88 320

Test_1112_low_res		62.32 314	61.77 309	64.00 350	79.08 153	39.53 385	68.17 358	70.17 334	43.25 416	59.03 356	79.90 295	44.08 225	71.24 366	43.79 349	68.42 340	81.25 289

tpm cat1		59.25 349	56.95 359	66.15 320	72.19 346	46.96 308	68.09 359	65.76 373	40.03 437	57.81 370	70.56 419	38.32 298	74.51 345	38.26 390	61.50 398	77.00 361

ppachtmachnet_test		58.06 359	55.38 375	66.10 322	69.51 394	48.99 277	68.01 360	66.13 372	44.50 404	54.05 409	70.74 418	32.09 376	72.34 358	36.68 403	56.71 423	76.99 363

tpmvs		58.47 353	56.95 359	63.03 360	70.20 382	41.21 368	67.90 361	67.23 361	49.62 342	54.73 402	70.84 417	34.14 341	76.24 337	36.64 404	61.29 399	71.64 420

testing91		64.46 288	63.80 279	66.47 312	78.43 173	40.06 378	67.63 362	69.59 341	59.06 152	63.18 296	78.05 329	34.05 342	76.99 320	48.30 304	75.87 218	82.37 267

CL-MVSNet_self_test		61.53 326	60.94 324	63.30 356	68.95 401	36.93 411	67.60 363	72.80 315	55.67 232	59.95 343	76.63 358	45.01 217	72.22 360	39.74 382	62.09 394	80.74 303

testing11		62.81 308	61.90 308	65.54 331	78.38 174	40.76 374	67.59 364	66.78 366	55.48 237	60.13 338	77.11 349	31.67 378	76.79 325	45.53 332	74.45 235	79.06 332

test_vis1_n_1920		58.86 350	59.06 340	58.25 393	63.76 435	43.14 349	67.49 365	66.36 369	40.22 435	65.89 250	71.95 410	31.04 379	59.75 427	59.94 202	64.90 367	71.85 418

tpm		57.34 363	58.16 349	54.86 413	71.80 353	34.77 428	67.47 366	56.04 437	48.20 364	60.10 339	76.92 352	37.17 312	53.41 456	40.76 374	65.01 366	76.40 367

testing99		64.05 293	63.29 291	66.34 314	78.17 186	39.76 382	67.33 367	68.00 355	58.60 163	63.03 299	78.10 328	32.57 371	76.94 322	48.22 305	75.58 222	82.34 268

FE-MVSNET		55.16 385	53.75 391	59.41 382	65.29 429	33.20 442	67.21 368	66.21 371	48.39 362	49.56 436	73.53 398	29.03 398	72.51 355	30.38 442	54.10 433	72.52 407

gg-mvs-nofinetune		57.86 360	56.43 366	62.18 364	72.62 334	35.35 425	66.57 369	56.33 434	50.65 329	57.64 371	57.10 461	30.65 381	76.36 335	37.38 395	78.88 161	74.82 387

TinyColmap		54.14 388	51.72 400	61.40 371	66.84 418	41.97 359	66.52 370	68.51 351	44.81 400	42.69 456	75.77 375	11.66 464	72.94 352	31.96 428	56.77 422	69.27 441

pmmvs5		56.47 371	55.68 373	58.86 389	61.41 447	36.71 413	66.37 371	62.75 401	40.38 434	53.70 411	76.62 359	34.56 336	67.05 394	40.02 378	65.27 364	72.83 403

CHOSEN 1792x2688		65.08 280	62.84 296	71.82 206	81.49 100	56.26 115	66.32 372	74.20 295	40.53 433	63.16 297	78.65 320	41.30 263	77.80 300	45.80 327	74.09 239	81.40 284

our_test_3		56.49 370	54.42 382	62.68 362	69.51 394	45.48 324	66.08 373	61.49 412	44.11 410	50.73 430	69.60 430	33.05 355	68.15 383	38.38 389	56.86 420	74.40 392

mvs5depth		55.64 379	53.81 390	61.11 375	59.39 456	40.98 373	65.89 374	68.28 353	50.21 334	58.11 368	75.42 381	17.03 450	67.63 390	43.79 349	46.21 451	74.73 389

PM-MVS		52.33 399	50.19 408	58.75 390	62.10 444	45.14 327	65.75 375	40.38 472	43.60 412	53.52 415	72.65 402	9.16 472	65.87 403	50.41 285	54.18 432	65.24 449

D2MVS		62.30 315	60.29 330	68.34 290	66.46 422	48.42 289	65.70 376	73.42 304	47.71 372	58.16 367	75.02 384	30.51 382	77.71 303	53.96 257	71.68 286	78.90 336

MIMVSNet1		55.17 384	54.31 385	57.77 400	70.03 386	32.01 448	65.68 377	64.81 381	49.19 348	46.75 445	76.00 370	25.53 431	64.04 409	28.65 449	62.13 393	77.26 357

PatchMatch-RL		56.25 374	54.55 381	61.32 373	77.06 233	56.07 119	65.57 378	54.10 443	44.13 409	53.49 417	71.27 416	25.20 432	66.78 396	36.52 406	63.66 378	61.12 451

Syy-MVS		56.00 376	56.23 369	55.32 410	74.69 290	26.44 469	65.52 379	57.49 428	50.97 326	56.52 381	72.18 405	39.89 278	68.09 384	24.20 461	64.59 372	71.44 424

myMVS_eth3d		54.86 387	54.61 380	55.61 409	74.69 290	27.31 466	65.52 379	57.49 428	50.97 326	56.52 381	72.18 405	21.87 444	68.09 384	27.70 452	64.59 372	71.44 424

test-LLR		58.15 358	58.13 351	58.22 394	68.57 405	44.80 329	65.46 381	57.92 425	50.08 336	55.44 391	69.82 427	32.62 368	57.44 439	49.66 292	73.62 249	72.41 411

TESTMET0.1,1		55.28 382	54.90 378	56.42 405	66.56 420	43.67 343	65.46 381	56.27 435	39.18 440	53.83 410	67.44 439	24.21 436	55.46 450	48.04 307	73.11 263	70.13 435

test-mter		56.42 372	55.82 372	58.22 394	68.57 405	44.80 329	65.46 381	57.92 425	39.94 438	55.44 391	69.82 427	21.92 441	57.44 439	49.66 292	73.62 249	72.41 411

SDMVSNet		68.03 223	68.10 199	67.84 294	77.13 228	48.72 284	65.32 384	79.10 182	58.02 175	65.08 268	82.55 235	47.83 171	73.40 350	63.92 157	73.92 242	81.41 282

CR-MVSNet		59.91 341	57.90 353	65.96 324	69.96 387	52.07 210	65.31 385	63.15 399	42.48 422	59.36 351	74.84 385	35.83 324	70.75 369	45.50 333	64.65 370	75.06 381

RPMNet		61.53 326	58.42 346	70.86 244	69.96 387	52.07 210	65.31 385	81.36 134	43.20 417	59.36 351	70.15 424	35.37 328	85.47 118	36.42 407	64.65 370	75.06 381

USDC		56.35 373	54.24 386	62.69 361	64.74 431	40.31 376	65.05 387	73.83 300	43.93 411	47.58 440	77.71 342	15.36 457	75.05 343	38.19 391	61.81 396	72.70 404

MDTV_nov1_ep13			57.00 358		72.73 332	38.26 396	65.02 388	64.73 383	44.74 401	55.46 390	72.48 403	32.61 370	70.47 370	37.47 393	67.75 346

ETVMVS		59.51 348	58.81 341	61.58 369	77.46 215	34.87 426	64.94 389	59.35 419	54.06 275	61.08 332	76.67 357	29.54 393	71.87 362	32.16 426	74.07 240	78.01 347

CMPMVS	42.80 21	57.81 361	55.97 370	63.32 355	60.98 451	47.38 305	64.66 390	69.50 343	32.06 451	46.83 444	77.80 338	29.50 395	71.36 364	48.68 300	73.75 245	71.21 427
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
WBMVS		60.54 335	60.61 328	60.34 378	78.00 192	35.95 422	64.55 391	64.89 380	49.63 341	63.39 293	78.70 317	33.85 347	67.65 389	42.10 365	70.35 305	77.43 353

IMVS_0404		64.63 285	64.22 273	65.88 327	77.06 233	49.73 257	64.40 392	78.60 198	52.70 297	53.16 418	82.58 230	34.82 334	65.16 406	59.20 211	75.46 225	82.74 255

RPSCF		55.80 378	54.22 387	60.53 377	65.13 430	42.91 353	64.30 393	57.62 427	36.84 444	58.05 369	82.28 244	28.01 409	56.24 447	37.14 397	58.61 414	82.44 266

XXY-MVS		60.68 332	61.67 310	57.70 401	70.43 378	38.45 394	64.19 394	66.47 367	48.05 367	63.22 294	80.86 279	49.28 154	60.47 422	45.25 338	67.28 351	74.19 395

FMVSNet5		55.86 377	54.93 377	58.66 391	71.05 369	36.35 416	64.18 395	62.48 404	46.76 386	50.66 431	74.73 387	25.80 428	64.04 409	33.11 422	65.57 363	75.59 375

UBG		59.62 347	59.53 334	59.89 379	78.12 187	35.92 423	64.11 396	60.81 416	49.45 344	61.34 328	75.55 378	33.05 355	67.39 393	38.68 387	74.62 233	76.35 368

testing3-2		62.06 319	62.36 302	61.17 374	79.29 142	30.31 455	64.09 397	63.49 395	63.50 44	62.84 302	82.22 246	32.35 375	69.02 380	40.01 379	73.43 256	84.17 206

icg_test_0407_2		66.41 262	66.75 232	65.37 337	77.06 233	49.73 257	63.79 398	78.60 198	52.70 297	66.19 241	82.58 230	45.17 214	63.65 412	59.20 211	75.46 225	82.74 255

test_cas_vis1_n_1920		56.91 366	56.71 363	57.51 402	59.13 457	45.40 325	63.58 399	61.29 413	36.24 445	67.14 223	71.85 411	29.89 391	56.69 443	57.65 224	63.58 380	70.46 432

UWE-MVS-28		52.25 400	52.35 398	51.93 434	66.99 415	22.79 477	63.48 400	48.31 458	46.78 385	52.73 420	76.11 368	27.78 412	57.82 438	20.58 467	68.41 341	75.17 379

SCA		60.49 336	58.38 347	66.80 304	74.14 309	48.06 295	63.35 401	63.23 398	49.13 349	59.33 354	72.10 407	37.45 306	74.27 347	44.17 342	62.57 388	78.05 343

myMVS_eth3d28		60.66 333	61.04 322	59.51 381	77.32 219	31.58 450	63.11 402	63.87 391	59.00 153	60.90 334	78.26 326	32.69 366	66.15 401	36.10 409	78.13 180	80.81 301

Patchmtry		57.16 364	56.47 365	59.23 385	69.17 400	34.58 431	62.98 403	63.15 399	44.53 403	56.83 378	74.84 385	35.83 324	68.71 381	40.03 377	60.91 400	74.39 393

Anonymous20231206		55.10 386	55.30 376	54.48 415	69.81 392	33.94 437	62.91 404	62.13 410	41.08 429	55.18 396	75.65 376	32.75 363	56.59 445	30.32 443	67.86 344	72.91 401

sd_testset		64.46 288	64.45 271	64.51 345	77.13 228	42.25 357	62.67 405	72.11 321	58.02 175	65.08 268	82.55 235	41.22 268	69.88 376	47.32 312	73.92 242	81.41 282

MIMVSNet		57.35 362	57.07 357	58.22 394	74.21 306	37.18 406	62.46 406	60.88 415	48.88 353	55.29 395	75.99 372	31.68 377	62.04 418	31.87 429	72.35 275	75.43 378

dp		51.89 402	51.60 401	52.77 428	68.44 408	32.45 447	62.36 407	54.57 440	44.16 408	49.31 437	67.91 435	28.87 401	56.61 444	33.89 417	54.89 429	69.24 442

EPMVS		53.96 389	53.69 392	54.79 414	66.12 425	31.96 449	62.34 408	49.05 454	44.42 406	55.54 389	71.33 415	30.22 386	56.70 442	41.65 370	62.54 389	75.71 374

pmmvs3		44.92 420	41.95 427	53.86 418	52.58 466	43.55 344	62.11 409	46.90 464	26.05 462	40.63 458	60.19 457	11.08 469	57.91 437	31.83 433	46.15 452	60.11 452

test_vis1_n		49.89 411	48.69 413	53.50 422	53.97 461	37.38 405	61.53 410	47.33 462	28.54 456	59.62 349	67.10 443	13.52 459	52.27 460	49.07 297	57.52 417	70.84 430

PVSNet	50.76 19	58.40 354	57.39 355	61.42 370	75.53 267	44.04 340	61.43 411	63.45 396	47.04 383	56.91 377	73.61 397	27.00 420	64.76 407	39.12 385	72.40 274	75.47 377

LCM-MVSNet-Re		61.88 323	61.35 315	63.46 354	74.58 295	31.48 451	61.42 412	58.14 424	58.71 160	53.02 419	79.55 305	43.07 236	76.80 324	45.69 328	77.96 183	82.11 273

test20.03		53.87 391	54.02 388	53.41 424	61.47 446	28.11 462	61.30 413	59.21 420	51.34 321	52.09 422	77.43 345	33.29 354	58.55 434	29.76 445	60.27 409	73.58 399

MDTV_nov1_ep13_2view						25.89 471	61.22 414		40.10 436	51.10 425		32.97 358		38.49 388		78.61 338

PMMVS		53.96 389	53.26 395	56.04 406	62.60 442	50.92 228	61.17 415	56.09 436	32.81 450	53.51 416	66.84 444	34.04 343	59.93 426	44.14 344	68.18 342	57.27 459

test_fmvs1_n		51.37 404	50.35 407	54.42 417	52.85 464	37.71 402	61.16 416	51.93 445	28.15 457	63.81 289	69.73 429	13.72 458	53.95 454	51.16 280	60.65 405	71.59 421

WTY-MVS		59.75 344	60.39 329	57.85 399	72.32 344	37.83 400	61.05 417	64.18 387	45.95 395	61.91 320	79.11 314	47.01 190	60.88 421	42.50 362	69.49 325	74.83 386

dmvs_testset		50.16 409	51.90 399	44.94 445	66.49 421	11.78 485	61.01 418	51.50 447	51.17 324	50.30 434	67.44 439	39.28 285	60.29 424	22.38 464	57.49 418	62.76 450

Patchmatch-RL test		58.16 357	55.49 374	66.15 320	67.92 411	48.89 281	60.66 419	51.07 450	47.86 371	59.36 351	62.71 455	34.02 344	72.27 359	56.41 233	59.40 411	77.30 355

test_fmvs1		51.32 406	50.48 406	53.81 419	53.57 462	37.51 404	60.63 420	51.16 448	28.02 459	63.62 290	69.23 432	16.41 453	53.93 455	51.01 281	60.70 404	69.99 436

LTVRE_ROB	55.42 16	63.15 305	61.23 319	68.92 282	76.57 249	47.80 298	59.92 421	76.39 250	54.35 271	58.67 360	82.46 240	29.44 396	81.49 215	42.12 364	71.14 291	77.46 352
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		60.57 334	61.39 314	58.12 397	74.29 304	32.63 445	59.52 422	65.53 376	59.90 133	62.45 314	79.75 300	41.96 248	63.90 411	39.47 383	69.65 324	77.84 348

test0.0.03 1		53.32 396	53.59 393	52.50 430	62.81 441	29.45 457	59.51 423	54.11 442	50.08 336	54.40 406	74.31 390	32.62 368	55.92 448	30.50 441	63.95 377	72.15 416

UnsupCasMVSNet_eth		53.16 398	52.47 396	55.23 411	59.45 455	33.39 441	59.43 424	69.13 347	45.98 392	50.35 433	72.32 404	29.30 397	58.26 436	42.02 367	44.30 455	74.05 396

MVS-HIRNet		45.52 419	44.48 421	48.65 439	68.49 407	34.05 436	59.41 425	44.50 467	27.03 460	37.96 467	50.47 469	26.16 426	64.10 408	26.74 457	59.52 410	47.82 468

testgi		51.90 401	52.37 397	50.51 437	60.39 454	23.55 476	58.42 426	58.15 423	49.03 350	51.83 423	79.21 313	22.39 439	55.59 449	29.24 448	62.64 387	72.40 413

dmvs_re		56.77 368	56.83 361	56.61 404	69.23 398	41.02 369	58.37 427	64.18 387	50.59 331	57.45 374	71.42 413	35.54 326	58.94 432	37.23 396	67.45 349	69.87 437

PatchT		53.17 397	53.44 394	52.33 431	68.29 409	25.34 473	58.21 428	54.41 441	44.46 405	54.56 404	69.05 433	33.32 353	60.94 420	36.93 399	61.76 397	70.73 431

WB-MVS		43.26 422	43.41 422	42.83 449	63.32 438	10.32 487	58.17 429	45.20 465	45.42 397	40.44 460	67.26 442	34.01 345	58.98 431	11.96 478	24.88 472	59.20 453

sss		56.17 375	56.57 364	54.96 412	66.93 417	36.32 418	57.94 430	61.69 411	41.67 425	58.64 361	75.32 383	38.72 293	56.25 446	42.04 366	66.19 359	72.31 414

ttmdpeth		45.56 418	42.95 423	53.39 425	52.33 467	29.15 458	57.77 431	48.20 459	31.81 452	49.86 435	77.21 347	8.69 473	59.16 430	27.31 453	33.40 469	71.84 419

test_fmvs2		48.69 413	47.49 418	52.29 432	48.63 471	33.06 444	57.76 432	48.05 460	25.71 463	59.76 347	69.60 430	11.57 465	52.23 461	49.45 295	56.86 420	71.58 422

KD-MVS_self_test		55.22 383	53.89 389	59.21 386	57.80 460	27.47 465	57.75 433	74.32 289	47.38 376	50.90 427	70.00 425	28.45 405	70.30 374	40.44 375	57.92 416	79.87 321

UnsupCasMVSNet_bld		50.07 410	48.87 411	53.66 420	60.97 452	33.67 439	57.62 434	64.56 384	39.47 439	47.38 441	64.02 453	27.47 414	59.32 428	34.69 415	43.68 456	67.98 445

mamv4		56.85 367	58.00 352	53.43 423	72.46 340	54.47 149	57.56 435	54.74 438	38.81 441	57.42 375	79.45 308	47.57 177	38.70 476	60.88 194	53.07 436	67.11 446

SSC-MVS		41.96 427	41.99 426	41.90 450	62.46 443	9.28 489	57.41 436	44.32 468	43.38 414	38.30 466	66.45 445	32.67 367	58.42 435	10.98 479	21.91 475	57.99 457

ANet_high		41.38 428	37.47 435	53.11 426	39.73 482	24.45 474	56.94 437	69.69 338	47.65 373	26.04 474	52.32 464	12.44 462	62.38 417	21.80 465	10.61 483	72.49 408

MDA-MVSNet-bldmvs		53.87 391	50.81 404	63.05 359	66.25 423	48.58 287	56.93 438	63.82 392	48.09 366	41.22 457	70.48 422	30.34 384	68.00 387	34.24 416	45.92 453	72.57 406

test123		4.73 454	6.30 457	0.02 469	0.01 492	0.01 494	56.36 439	0.00 493	0.01 487	0.04 488	0.21 488	0.01 491	0.00 488	0.03 488	0.00 486	0.04 484

miper_lstm_enhance		62.03 320	60.88 325	65.49 334	66.71 419	46.25 313	56.29 440	75.70 261	50.68 328	61.27 329	75.48 380	40.21 275	68.03 386	56.31 234	65.25 365	82.18 270

KD-MVS_2432*1600		53.45 393	51.50 402	59.30 383	62.82 439	37.14 407	55.33 441	71.79 324	47.34 378	55.09 397	70.52 420	21.91 442	70.45 371	35.72 411	42.97 457	70.31 433

miper_refine_blended		53.45 393	51.50 402	59.30 383	62.82 439	37.14 407	55.33 441	71.79 324	47.34 378	55.09 397	70.52 420	21.91 442	70.45 371	35.72 411	42.97 457	70.31 433

LF4IMVS		42.95 423	42.26 425	45.04 443	48.30 472	32.50 446	54.80 443	48.49 456	28.03 458	40.51 459	70.16 423	9.24 471	43.89 471	31.63 434	49.18 449	58.72 455

PMVS	28.69 22	36.22 435	33.29 440	45.02 444	36.82 484	35.98 421	54.68 444	48.74 455	26.31 461	21.02 477	51.61 466	2.88 485	60.10 425	9.99 482	47.58 450	38.99 475
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVStest1		42.65 424	39.29 431	52.71 429	47.26 474	34.58 431	54.41 445	50.84 453	23.35 465	39.31 465	74.08 394	12.57 461	55.09 451	23.32 462	28.47 471	68.47 444

PVSNet_0	43.31 20	47.46 417	45.64 420	52.92 427	67.60 413	44.65 331	54.06 446	54.64 439	41.59 426	46.15 447	58.75 458	30.99 380	58.66 433	32.18 425	24.81 473	55.46 461

testmvs		4.52 455	6.03 458	0.01 470	0.01 492	0.00 495	53.86 447	0.00 493	0.01 487	0.04 488	0.27 487	0.00 492	0.00 488	0.04 487	0.00 486	0.03 485

test_fmvs3		44.30 421	42.55 424	49.55 438	42.83 476	27.15 468	53.03 448	44.93 466	22.03 471	53.69 413	64.94 450	4.21 480	49.63 463	47.47 308	49.82 446	71.88 417

APD_test1		37.39 434	34.94 437	44.72 446	48.88 470	33.19 443	52.95 449	44.00 469	19.49 472	27.28 473	58.59 459	3.18 484	52.84 458	18.92 468	41.17 460	48.14 467

dongtai		34.52 437	34.94 437	33.26 459	61.06 450	16.00 484	52.79 450	23.78 485	40.71 432	39.33 464	48.65 473	16.91 452	48.34 465	12.18 477	19.05 477	35.44 476

YYNet1		50.73 407	48.96 409	56.03 407	61.10 449	41.78 361	51.94 451	56.44 432	40.94 431	44.84 449	67.80 437	30.08 389	55.08 452	36.77 400	50.71 443	71.22 426

MDA-MVSNet_test_wron		50.71 408	48.95 410	56.00 408	61.17 448	41.84 360	51.90 452	56.45 431	40.96 430	44.79 450	67.84 436	30.04 390	55.07 453	36.71 402	50.69 444	71.11 429

kuosan		29.62 444	30.82 443	26.02 464	52.99 463	16.22 483	51.09 453	22.71 486	33.91 449	33.99 468	40.85 474	15.89 455	33.11 481	7.59 485	18.37 478	28.72 478

ADS-MVSNet2		51.33 405	48.76 412	59.07 388	66.02 426	44.60 333	50.90 454	59.76 418	36.90 442	50.74 428	66.18 447	26.38 423	63.11 414	27.17 454	54.76 430	69.50 439

ADS-MVSNet		48.48 414	47.77 415	50.63 436	66.02 426	29.92 456	50.90 454	50.87 452	36.90 442	50.74 428	66.18 447	26.38 423	52.47 459	27.17 454	54.76 430	69.50 439

mamba_0408		67.78 231	65.42 260	74.85 103	78.65 164	53.46 171	50.83 456	79.09 183	53.75 282	68.14 193	83.83 203	41.79 255	86.56 81	56.58 230	76.11 212	84.54 191

SSM_04072		64.98 281	65.42 260	63.68 352	78.65 164	53.46 171	50.83 456	79.09 183	53.75 282	68.14 193	83.83 203	41.79 255	53.03 457	56.58 230	76.11 212	84.54 191

FPMVS		42.18 426	41.11 428	45.39 442	58.03 459	41.01 371	49.50 458	53.81 444	30.07 454	33.71 469	64.03 451	11.69 463	52.08 462	14.01 473	55.11 428	43.09 470

N_pmnet		39.35 432	40.28 429	36.54 456	63.76 435	1.62 493	49.37 459	0.76 492	34.62 448	43.61 454	66.38 446	26.25 425	42.57 472	26.02 459	51.77 440	65.44 448

new-patchmatchnet		47.56 416	47.73 416	47.06 440	58.81 458	9.37 488	48.78 460	59.21 420	43.28 415	44.22 452	68.66 434	25.67 429	57.20 441	31.57 436	49.35 448	74.62 391

test_vis1_rt		41.35 429	39.45 430	47.03 441	46.65 475	37.86 399	47.76 461	38.65 473	23.10 467	44.21 453	51.22 467	11.20 468	44.08 470	39.27 384	53.02 437	59.14 454

JIA-IIPM		51.56 403	47.68 417	63.21 357	64.61 432	50.73 234	47.71 462	58.77 422	42.90 419	48.46 439	51.72 465	24.97 433	70.24 375	36.06 410	53.89 434	68.64 443

ambc				65.13 341	63.72 437	37.07 409	47.66 463	78.78 193		54.37 407	71.42 413	11.24 467	80.94 232	45.64 329	53.85 435	77.38 354

testf1		31.46 442	28.89 446	39.16 452	41.99 479	28.78 460	46.45 464	37.56 474	14.28 479	21.10 475	48.96 470	1.48 488	47.11 466	13.63 474	34.56 466	41.60 471

APD_test2		31.46 442	28.89 446	39.16 452	41.99 479	28.78 460	46.45 464	37.56 474	14.28 479	21.10 475	48.96 470	1.48 488	47.11 466	13.63 474	34.56 466	41.60 471

Patchmatch-test		49.08 412	48.28 414	51.50 435	64.40 433	30.85 454	45.68 466	48.46 457	35.60 446	46.10 448	72.10 407	34.47 339	46.37 468	27.08 456	60.65 405	77.27 356

DSMNet-mixed		39.30 433	38.72 432	41.03 451	51.22 468	19.66 480	45.53 467	31.35 479	15.83 478	39.80 462	67.42 441	22.19 440	45.13 469	22.43 463	52.69 438	58.31 456

LCM-MVSNet		40.30 430	35.88 436	53.57 421	42.24 477	29.15 458	45.21 468	60.53 417	22.23 470	28.02 472	50.98 468	3.72 482	61.78 419	31.22 439	38.76 463	69.78 438

new_pmnet		34.13 438	34.29 439	33.64 458	52.63 465	18.23 482	44.43 469	33.90 478	22.81 468	30.89 471	53.18 463	10.48 470	35.72 480	20.77 466	39.51 461	46.98 469

mvsany_test1		39.38 431	38.16 434	43.02 448	49.05 469	34.28 434	44.16 470	25.94 483	22.74 469	46.57 446	62.21 456	23.85 437	41.16 475	33.01 423	35.91 465	53.63 462

E-PMN		23.77 446	22.73 450	26.90 462	42.02 478	20.67 479	42.66 471	35.70 476	17.43 474	10.28 484	25.05 480	6.42 475	42.39 473	10.28 481	14.71 480	17.63 479

EMVS		22.97 447	21.84 451	26.36 463	40.20 481	19.53 481	41.95 472	34.64 477	17.09 475	9.73 485	22.83 481	7.29 474	42.22 474	9.18 483	13.66 481	17.32 480

test_vis3_rt		32.09 440	30.20 445	37.76 455	35.36 486	27.48 464	40.60 473	28.29 482	16.69 476	32.52 470	40.53 475	1.96 486	37.40 478	33.64 420	42.21 459	48.39 465

CHOSEN 280x420		47.83 415	46.36 419	52.24 433	67.37 414	49.78 256	38.91 474	43.11 470	35.00 447	43.27 455	63.30 454	28.95 399	49.19 464	36.53 405	60.80 402	57.76 458

mvsany_test3		32.62 439	30.57 444	38.77 454	36.16 485	24.20 475	38.10 475	20.63 487	19.14 473	40.36 461	57.43 460	5.06 477	36.63 479	29.59 447	28.66 470	55.49 460

test_f		31.86 441	31.05 442	34.28 457	32.33 488	21.86 478	32.34 476	30.46 480	16.02 477	39.78 463	55.45 462	4.80 478	32.36 482	30.61 440	37.66 464	48.64 464

PMMVS2		27.40 445	25.91 448	31.87 461	39.46 483	6.57 490	31.17 477	28.52 481	23.96 464	20.45 478	48.94 472	4.20 481	37.94 477	16.51 470	19.97 476	51.09 463

wuyk23d		13.32 451	12.52 454	15.71 466	47.54 473	26.27 470	31.06 478	1.98 491	4.93 483	5.18 486	1.94 486	0.45 490	18.54 485	6.81 486	12.83 482	2.33 483

Gipuma		34.77 436	31.91 441	43.33 447	62.05 445	37.87 398	20.39 479	67.03 363	23.23 466	18.41 479	25.84 479	4.24 479	62.73 415	14.71 472	51.32 442	29.38 477
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVE	17.77 23	21.41 448	17.77 453	32.34 460	34.34 487	25.44 472	16.11 480	24.11 484	11.19 481	13.22 481	31.92 477	1.58 487	30.95 483	10.47 480	17.03 479	40.62 474
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
tmp_tt		9.43 452	11.14 455	4.30 468	2.38 491	4.40 491	13.62 481	16.08 489	0.39 485	15.89 480	13.06 482	15.80 456	5.54 487	12.63 476	10.46 484	2.95 482

test_method		19.68 449	18.10 452	24.41 465	13.68 490	3.11 492	12.06 482	42.37 471	2.00 484	11.97 482	36.38 476	5.77 476	29.35 484	15.06 471	23.65 474	40.76 473

mmdepth		0.00 457	0.00 460	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	0.00 489	0.00 492	0.00 488	0.00 489	0.00 486	0.00 486

monomultidepth		0.00 457	0.00 460	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	0.00 489	0.00 492	0.00 488	0.00 489	0.00 486	0.00 486

test_blank		0.00 457	0.00 460	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	0.00 489	0.00 492	0.00 488	0.00 489	0.00 486	0.00 486

uanet_test		0.00 457	0.00 460	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	0.00 489	0.00 492	0.00 488	0.00 489	0.00 486	0.00 486

DCPMVS		0.00 457	0.00 460	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	0.00 489	0.00 492	0.00 488	0.00 489	0.00 486	0.00 486

cdsmvs_eth3d_5k		17.50 450	23.34 449	0.00 471	0.00 494	0.00 495	0.00 483	78.63 197	0.00 489	0.00 490	82.18 247	49.25 155	0.00 488	0.00 489	0.00 486	0.00 486

pcd_1.5k_mvsjas		3.92 456	5.23 459	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	0.00 489	47.05 187	0.00 488	0.00 489	0.00 486	0.00 486

sosnet-low-res		0.00 457	0.00 460	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	0.00 489	0.00 492	0.00 488	0.00 489	0.00 486	0.00 486

sosnet		0.00 457	0.00 460	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	0.00 489	0.00 492	0.00 488	0.00 489	0.00 486	0.00 486

uncertanet		0.00 457	0.00 460	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	0.00 489	0.00 492	0.00 488	0.00 489	0.00 486	0.00 486

Regformer		0.00 457	0.00 460	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	0.00 489	0.00 492	0.00 488	0.00 489	0.00 486	0.00 486

ab-mvs-re		6.49 453	8.65 456	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	77.89 336	0.00 492	0.00 488	0.00 489	0.00 486	0.00 486

uanet		0.00 457	0.00 460	0.00 471	0.00 494	0.00 495	0.00 483	0.00 493	0.00 489	0.00 490	0.00 489	0.00 492	0.00 488	0.00 489	0.00 486	0.00 486

WAC-MVS						27.31 466								27.77 451

MSC_two_6792asdad				79.95 4	87.24 14	61.04 31		85.62 29					90.96 1	79.31 10	90.65 8	87.85 50

PC_three_1452									55.09 248	84.46 4	89.84 52	66.68 5	89.41 22	74.24 61	91.38 2	88.42 27

No_MVS				79.95 4	87.24 14	61.04 31		85.62 29					90.96 1	79.31 10	90.65 8	87.85 50

test_one_0601					87.58 9	59.30 62		86.84 7	65.01 20	83.80 11	91.86 6	64.03 13

eth-test2					0.00 494

eth-test					0.00 494

ZD-MVS					86.64 21	60.38 45		82.70 111	57.95 179	78.10 33	90.06 45	56.12 50	88.84 30	74.05 64	87.00 55

IU-MVS					87.77 4	59.15 68		85.53 31	53.93 278	84.64 3				79.07 13	90.87 5	88.37 29

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 59

test_241102_ONE					87.77 4	58.90 77		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 12	90.75 8	79.48 7	90.63 10	88.09 43

GSMVS																78.05 343

test_part2					87.58 9	60.47 42				83.42 15

sam_mvs1												34.74 335				78.05 343

sam_mvs												33.43 352

MTGPA								80.97 152

test_post											3.55 485	33.90 346	66.52 397

patchmatchnet-post											64.03 451	34.50 337	74.27 347

gm-plane-assit					71.40 363	41.72 364			48.85 354		73.31 399		82.48 197	48.90 299

test9_res														75.28 54	88.31 36	83.81 220

agg_prior2														73.09 72	87.93 44	84.33 198

agg_prior					85.04 54	59.96 50		81.04 150		74.68 72			84.04 146

TestCases				64.39 346	71.44 360	49.03 274		67.30 358	45.97 393	47.16 442	79.77 298	17.47 448	67.56 391	33.65 418	59.16 412	76.57 365

test_prior				76.69 65	84.20 65	57.27 98		84.88 44					86.43 88			86.38 109

新几何1				70.76 246	85.66 42	61.13 30		66.43 368	44.68 402	70.29 151	86.64 122	41.29 264	75.23 342	49.72 291	81.75 110	75.93 371

旧先验1					83.04 78	53.15 181		67.52 357			87.85 86	44.08 225			80.76 119	78.03 346

原ACMM1				74.69 106	85.39 48	59.40 59		83.42 85	51.47 318	70.27 152	86.61 126	48.61 163	86.51 86	53.85 258	87.96 43	78.16 341

testdata2													72.18 361	46.95 318

segment_acmp												54.23 72

testdata				64.66 343	81.52 98	52.93 186		65.29 378	46.09 391	73.88 87	87.46 93	38.08 302	66.26 400	53.31 263	78.48 174	74.78 388

test12				77.76 50	84.52 62	58.41 83		83.36 88		72.93 113		54.61 69	88.05 43		88.12 38	86.81 92

plane_prior7					81.41 101	55.96 121

plane_prior6					81.20 108	56.24 116						45.26 212

plane_prior5								84.01 57					87.21 63	68.16 107	80.58 123	84.65 189

plane_prior4											86.10 145

plane_prior3						56.09 118			63.92 38	69.27 172

plane_prior1					81.27 106

n2								0.00 493

nn								0.00 493

door-mid								47.19 463

lessismore_v0				69.91 263	71.42 362	47.80 298		50.90 451		50.39 432	75.56 377	27.43 416	81.33 219	45.91 326	34.10 468	80.59 304

LGP-MVS_train				75.76 83	80.22 123	57.51 96		83.40 86	61.32 91	66.67 233	87.33 99	39.15 288	86.59 79	67.70 115	77.30 197	83.19 243

test11								83.47 83

door								47.60 461

HQP5-MVS						54.94 143

BP-MVS														67.04 125

HQP4-MVS										67.85 203			86.93 71			84.32 199

HQP3-MVS								83.90 62							80.35 127

HQP2-MVS												45.46 206

NP-MVS					80.98 111	56.05 120					85.54 166

ACMMP++_ref															74.07 240

ACMMP++															72.16 280

Test By Simon												48.33 166

ITE_SJBPF				62.09 365	66.16 424	44.55 335		64.32 385	47.36 377	55.31 394	80.34 287	19.27 447	62.68 416	36.29 408	62.39 390	79.04 333

DeepMVS_CX				12.03 467	17.97 489	10.91 486		10.60 490	7.46 482	11.07 483	28.36 478	3.28 483	11.29 486	8.01 484	9.74 485	13.89 481

High-resolution multi-view benchmark