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 26

FOURS1					86.12 37	60.82 37	88.18 1	83.61 78	60.87 102	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 92
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	85.45 156
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 60

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 34

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 34

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 70	90.06 14	78.42 23	89.02 27	87.69 56
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 83	62.44 69	72.68 118	90.50 31	48.18 166	87.34 58	73.59 69	85.71 66	84.76 187

MED-MVS test				79.09 23	85.30 50	59.25 64	86.84 11	85.86 21	60.95 99	83.65 12	90.57 25		89.91 16	77.02 34	89.43 22	88.10 39

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 39

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 99	83.65 12	90.57 25	64.70 10	89.91 16	76.25 43	89.43 22	87.96 45

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 77	88.68 31	76.48 39	89.63 20	87.16 81

HPM-MVS++		79.88 12	80.14 12	79.10 21	88.17 1	64.80 1	86.59 16	83.70 74	65.37 13	78.78 28	90.64 22	58.63 28	87.24 59	79.00 14	90.37 14	85.26 168

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 36
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 91	88.35 35	74.02 65	87.05 51	86.13 123

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 97	90.58 24	49.90 142	88.21 38	73.78 67	87.03 52	86.29 120

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 93	90.56 29	49.80 145	88.24 37	74.02 65	87.03 52	86.32 116

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 42
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	17.08 486

MP-MVS		78.35 23	78.26 24	78.64 35	86.54 26	63.47 4	86.02 24	83.55 80	63.89 39	73.60 91	90.60 23	54.85 65	86.72 76	77.20 31	88.06 40	85.74 142
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	60.53 111	78.99 27	91.45 12	51.51 122	87.78 51	75.65 49	87.55 47	87.10 83

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	52.56 100	88.53 33	74.79 59	88.34 33	86.63 101

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	72.17 126	90.01 49	47.95 168	88.01 44	71.55 88	86.74 59	86.37 110

X-MVStestdata		70.21 159	67.28 218	79.00 26	86.32 30	62.62 11	85.83 27	83.92 60	64.55 25	72.17 126	6.49 481	47.95 168	88.01 44	71.55 88	86.74 59	86.37 110

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	67.80 208	89.24 60	42.03 246	89.38 23	64.07 152	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	82.28 115	62.90 57	71.77 131	90.26 39	46.61 193	86.55 84	71.71 86	85.66 67	84.97 179

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 90
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 39

SR-MVS		76.13 51	75.70 52	77.40 57	85.87 41	61.20 29	85.52 33	82.19 116	59.99 131	75.10 59	90.35 36	47.66 173	86.52 85	71.64 87	82.99 90	84.47 196

APD-MVS		78.02 26	78.04 26	77.98 45	86.44 28	60.81 38	85.52 33	84.36 51	60.61 109	79.05 26	90.30 38	55.54 58	88.32 36	73.48 70	87.03 52	84.83 183
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	69.80 162	89.74 55	45.43 207	87.16 65	72.01 81	82.87 95	85.14 170
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 59	89.18 25	74.19 63	87.34 50	86.38 108

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 82	79.16 25	90.75 21	57.96 29	87.09 68	77.08 33	90.18 15	87.87 48

reproduce-ours		76.90 38	76.58 38	77.87 47	83.99 66	60.46 43	84.75 38	83.34 88	60.22 125	77.85 36	91.42 14	50.67 134	87.69 53	72.46 76	84.53 74	85.46 154

our_new_method		76.90 38	76.58 38	77.87 47	83.99 66	60.46 43	84.75 38	83.34 88	60.22 125	77.85 36	91.42 14	50.67 134	87.69 53	72.46 76	84.53 74	85.46 154

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 81	73.06 109	88.88 66	53.72 83	89.06 27	68.27 103	88.04 41	87.42 68
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	81.64 125	68.35 2	75.77 50	90.38 34	53.98 75	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	82.90 106	59.65 138	77.31 39	91.43 13	49.62 147	87.24 59	71.99 82	83.75 85	85.14 170

SD-MVS		77.70 30	77.62 30	77.93 46	84.47 63	61.88 21	84.55 43	83.87 65	60.37 118	79.89 22	89.38 58	54.97 63	85.58 113	76.12 45	84.94 70	86.33 114
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 97	87.27 101	55.06 61	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 84

NormalMVS		76.26 48	75.74 51	77.83 49	82.75 84	59.89 52	84.36 46	83.21 95	64.69 22	74.21 80	87.40 94	49.48 148	86.17 96	68.04 109	87.55 47	87.42 68

SymmetryMVS		75.28 59	74.60 65	77.30 58	83.85 69	59.89 52	84.36 46	75.51 265	64.69 22	74.21 80	87.40 94	49.48 148	86.17 96	68.04 109	83.88 83	85.85 133

SR-MVS-dyc-post		74.57 69	73.90 76	76.58 70	83.49 72	59.87 54	84.29 48	81.36 133	58.07 172	73.14 104	90.07 43	44.74 217	85.84 107	68.20 104	81.76 108	84.03 208

RE-MVS-def			73.71 81		83.49 72	59.87 54	84.29 48	81.36 133	58.07 172	73.14 104	90.07 43	43.06 236		68.20 104	81.76 108	84.03 208

PHI-MVS		75.87 53	75.36 55	77.41 55	80.62 119	55.91 123	84.28 50	85.78 25	56.08 222	73.41 94	86.58 127	50.94 132	88.54 32	70.79 93	89.71 17	87.79 53

HQP_MVS		74.31 72	73.73 80	76.06 77	81.41 101	56.31 112	84.22 51	84.01 57	64.52 27	69.27 171	86.10 144	45.26 211	87.21 63	68.16 107	80.58 123	84.65 188

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 88	90.25 40	57.68 32	89.96 15	74.62 60	89.03 26	87.89 46
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	59.90 132	78.57 30	90.36 35	57.51 35	86.86 73	77.39 29	89.52 21

CPTT-MVS		72.78 102	72.08 109	74.87 102	84.88 61	61.41 26	84.15 54	77.86 220	55.27 242	67.51 214	88.08 79	41.93 249	81.85 206	69.04 102	80.01 132	81.35 286

TSAR-MVS + MP.		78.44 22	78.28 22	78.90 30	84.96 56	61.41 26	84.03 56	83.82 69	59.34 148	79.37 24	89.76 54	59.84 19	87.62 56	76.69 37	86.74 59	87.68 57
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
API-MVS		72.17 118	71.41 120	74.45 119	81.95 93	57.22 99	84.03 56	80.38 162	59.89 136	68.40 185	82.33 241	49.64 146	87.83 50	51.87 273	84.16 81	78.30 337

save fliter					86.17 34	61.30 28	83.98 58	79.66 172	59.00 152

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 78	71.49 138	86.03 147	53.83 79	86.36 91	67.74 113	86.91 56	88.19 36

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	52.51 101	88.39 34	79.34 9	90.52 13	86.78 93

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	72.77 117	87.25 103	53.13 92	87.93 46	71.97 83	85.57 68	86.66 99

APD-MVS_3200maxsize		74.96 61	74.39 68	76.67 67	82.20 88	58.24 85	83.67 62	83.29 92	58.41 166	73.71 89	90.14 41	45.62 200	85.99 103	69.64 97	82.85 96	85.78 136

HPM-MVS_fast		74.30 73	73.46 86	76.80 63	84.45 64	59.04 74	83.65 63	81.05 148	60.15 127	70.43 148	89.84 52	41.09 268	85.59 112	67.61 116	82.90 94	85.77 139

plane_prior						56.31 112	83.58 64		63.19 51						80.48 126

QAPM		70.05 163	68.81 175	73.78 143	76.54 249	53.43 174	83.23 65	83.48 81	52.89 294	65.90 248	86.29 138	41.55 260	86.49 87	51.01 280	78.40 176	81.42 280

MCST-MVS		77.48 32	77.45 31	77.54 52	86.67 20	58.36 84	83.22 66	86.93 5	56.91 200	74.91 65	88.19 75	59.15 26	87.68 55	73.67 68	87.45 49	86.57 102

EPNet		73.09 97	72.16 107	75.90 79	75.95 257	56.28 114	83.05 67	72.39 316	66.53 10	65.27 260	87.00 108	50.40 137	85.47 118	62.48 178	86.32 64	85.94 128
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 38

CSCG		76.92 37	76.75 35	77.41 55	83.96 68	59.60 56	82.95 69	86.50 14	60.78 105	75.27 55	84.83 173	60.76 18	86.56 81	67.86 112	87.87 45	86.06 125

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 74	76.41 48	91.51 11	52.47 103	86.78 75	80.66 4	89.64 19	87.80 52
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	73.09 108	89.97 50	50.90 133	87.48 57	75.30 53	86.85 57	87.33 76
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
MVSFormer		71.50 132	70.38 143	74.88 101	78.76 160	57.15 104	82.79 72	78.48 205	51.26 320	69.49 165	83.22 218	43.99 227	83.24 164	66.06 134	79.37 141	84.23 202

test_djsdf		69.45 186	67.74 201	74.58 113	74.57 295	54.92 145	82.79 72	78.48 205	51.26 320	65.41 257	83.49 214	38.37 295	83.24 164	66.06 134	69.25 328	85.56 149

ACMP	63.53 6	72.30 115	71.20 127	75.59 91	80.28 121	57.54 94	82.74 74	82.84 109	60.58 110	65.24 264	86.18 141	39.25 285	86.03 102	66.95 128	76.79 204	83.22 240
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMM	61.98 7	70.80 147	69.73 154	74.02 134	80.59 120	58.59 82	82.68 75	82.02 119	55.46 237	67.18 221	84.39 191	38.51 293	83.17 166	60.65 195	76.10 214	80.30 309
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
AdaColmap		69.99 165	68.66 179	73.97 138	84.94 58	57.83 90	82.63 76	78.71 193	56.28 218	64.34 279	84.14 194	41.57 258	87.06 69	46.45 318	78.88 160	77.02 358

OPM-MVS		74.73 65	74.25 71	76.19 76	80.81 113	59.01 75	82.60 77	83.64 77	63.74 41	72.52 121	87.49 91	47.18 184	85.88 106	69.47 99	80.78 117	83.66 229
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 71	61.71 83	72.45 124	90.34 37	48.48 164	88.13 41	72.32 78	86.85 57	85.78 136

LPG-MVS_test		72.74 103	71.74 114	75.76 83	80.22 123	57.51 96	82.55 78	83.40 85	61.32 90	66.67 232	87.33 99	39.15 287	86.59 79	67.70 114	77.30 196	83.19 242

CANet		76.46 44	75.93 48	78.06 43	81.29 104	57.53 95	82.35 80	83.31 91	67.78 3	70.09 152	86.34 136	54.92 64	88.90 29	72.68 75	84.55 73	87.76 54

114514_t		70.83 145	69.56 157	74.64 110	86.21 32	54.63 148	82.34 81	81.81 122	48.22 361	63.01 300	85.83 155	40.92 270	87.10 67	57.91 221	79.79 134	82.18 269

HQP-NCC					80.66 115		82.31 82		62.10 75	67.85 202

ACMP_Plane					80.66 115		82.31 82		62.10 75	67.85 202

HQP-MVS		73.45 86	72.80 98	75.40 92	80.66 115	54.94 143	82.31 82	83.90 62	62.10 75	67.85 202	85.54 165	45.46 205	86.93 71	67.04 124	80.35 127	84.32 198

MSLP-MVS++		73.77 81	73.47 85	74.66 108	83.02 79	59.29 63	82.30 85	81.88 120	59.34 148	71.59 135	86.83 112	45.94 198	83.65 155	65.09 145	85.22 69	81.06 295

EPP-MVSNet		72.16 120	71.31 124	74.71 105	78.68 163	49.70 260	82.10 86	81.65 124	60.40 115	65.94 246	85.84 154	51.74 118	86.37 90	55.93 235	79.55 140	88.07 44

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	78.57 201	58.58 163	74.32 78	84.51 188	55.94 55	87.22 62	67.11 123	84.48 77	85.52 150

test_prior2							81.75 89		60.37 118	75.01 61	89.06 61	56.22 46		72.19 79	88.96 28

PS-MVSNAJss		72.24 116	71.21 126	75.31 94	78.50 169	55.93 122	81.63 90	82.12 117	56.24 219	70.02 156	85.68 161	47.05 186	84.34 142	65.27 144	74.41 236	85.67 145

TEST9					85.58 44	61.59 24	81.62 91	81.26 140	55.65 232	74.93 63	88.81 67	53.70 84	84.68 136

train_agg		76.27 47	76.15 44	76.64 69	85.58 44	61.59 24	81.62 91	81.26 140	55.86 224	74.93 63	88.81 67	53.70 84	84.68 136	75.24 55	88.33 34	83.65 230

MG-MVS		73.96 78	73.89 77	74.16 128	85.65 43	49.69 262	81.59 93	81.29 139	61.45 88	71.05 141	88.11 77	51.77 117	87.73 52	61.05 191	83.09 88	85.05 175

test_8					85.40 47	60.96 34	81.54 94	81.18 144	55.86 224	74.81 68	88.80 69	53.70 84	84.45 140

MAR-MVS		71.51 131	70.15 149	75.60 90	81.84 94	59.39 60	81.38 95	82.90 106	54.90 259	68.08 198	78.70 316	47.73 171	85.51 115	51.68 277	84.17 80	81.88 275
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	56.32 216	74.05 82	88.98 63	53.34 89	87.92 47	69.23 101	88.42 32	87.59 62

OpenMVS	61.03 9	68.85 200	67.56 205	72.70 183	74.26 304	53.99 158	81.21 97	81.34 137	52.70 296	62.75 305	85.55 164	38.86 291	84.14 144	48.41 302	83.01 89	79.97 315

DP-MVS Recon		72.15 121	70.73 136	76.40 72	86.57 25	57.99 88	81.15 98	82.96 104	57.03 197	66.78 227	85.56 162	44.50 221	88.11 42	51.77 275	80.23 130	83.10 247

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 97	74.90 66	87.17 106	56.46 42	88.14 40	72.87 73	88.03 42	89.00 9

Vis-MVSNet		72.18 117	71.37 122	74.61 111	81.29 104	55.41 136	80.90 100	78.28 215	60.73 106	69.23 174	88.09 78	44.36 223	82.65 189	57.68 222	81.75 110	85.77 139
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
jajsoiax		68.25 216	66.45 236	73.66 153	75.62 263	55.49 135	80.82 101	78.51 204	52.33 304	64.33 280	84.11 195	28.28 405	81.81 208	63.48 166	70.62 297	83.67 227

mvs_tets		68.18 219	66.36 242	73.63 156	75.61 264	55.35 139	80.77 102	78.56 202	52.48 303	64.27 282	84.10 196	27.45 413	81.84 207	63.45 167	70.56 299	83.69 226

DP-MVS		65.68 268	63.66 281	71.75 208	84.93 59	56.87 109	80.74 103	73.16 309	53.06 291	59.09 354	82.35 240	36.79 317	85.94 105	32.82 422	69.96 313	72.45 407

3Dnovator	64.47 5	72.49 110	71.39 121	75.79 82	77.70 202	58.99 76	80.66 104	83.15 100	62.24 72	65.46 256	86.59 126	42.38 244	85.52 114	59.59 205	84.72 71	82.85 252

ACMH+	57.40 11	66.12 264	64.06 273	72.30 196	77.79 198	52.83 192	80.39 105	78.03 218	57.30 190	57.47 371	82.55 234	27.68 411	84.17 143	45.54 329	69.78 317	79.90 317

viewdifsd2359ckpt09		73.42 87	72.45 104	76.30 75	77.25 222	53.27 178	80.36 106	82.48 112	57.96 177	72.24 125	85.73 159	53.22 90	86.27 94	63.79 162	79.06 158	89.36 5

sasdasda		74.67 66	74.98 61	73.71 150	78.94 155	50.56 237	80.23 107	83.87 65	60.30 122	77.15 41	86.56 128	59.65 20	82.00 203	66.01 136	82.12 101	88.58 23

canonicalmvs		74.67 66	74.98 61	73.71 150	78.94 155	50.56 237	80.23 107	83.87 65	60.30 122	77.15 41	86.56 128	59.65 20	82.00 203	66.01 136	82.12 101	88.58 23

IS-MVSNet		71.57 130	71.00 131	73.27 170	78.86 157	45.63 322	80.22 109	78.69 194	64.14 37	66.46 235	87.36 97	49.30 152	85.60 111	50.26 286	83.71 86	88.59 22

Effi-MVS+-dtu		69.64 177	67.53 208	75.95 78	76.10 255	62.29 15	80.20 110	76.06 254	59.83 137	65.26 263	77.09 349	41.56 259	84.02 148	60.60 196	71.09 294	81.53 279

nrg030		72.96 99	73.01 94	72.84 179	75.41 270	50.24 246	80.02 111	82.89 108	58.36 168	74.44 75	86.73 118	58.90 27	80.83 235	65.84 139	74.46 233	87.44 67

Anonymous20231211		69.28 189	68.47 184	71.73 209	80.28 121	47.18 306	79.98 112	82.37 114	54.61 264	67.24 219	84.01 198	39.43 282	82.41 197	55.45 243	72.83 266	85.62 148

DPM-MVS		75.47 58	75.00 60	76.88 61	81.38 103	59.16 67	79.94 113	85.71 27	56.59 210	72.46 122	86.76 114	56.89 39	87.86 49	66.36 132	88.91 29	83.64 231

PVSNet_Blended_VisFu		71.45 134	70.39 142	74.65 109	82.01 90	58.82 79	79.93 114	80.35 163	55.09 247	65.82 252	82.16 249	49.17 155	82.64 190	60.34 197	78.62 170	82.50 263

PAPM_NR		72.63 107	71.80 112	75.13 97	81.72 96	53.42 175	79.91 115	83.28 93	59.14 150	66.31 239	85.90 152	51.86 114	86.06 100	57.45 224	80.62 121	85.91 130

LS3D		64.71 282	62.50 299	71.34 230	79.72 135	55.71 127	79.82 116	74.72 282	48.50 357	56.62 377	84.62 181	33.59 350	82.34 198	29.65 444	75.23 228	75.97 368

UGNet		68.81 201	67.39 213	73.06 174	78.33 179	54.47 149	79.77 117	75.40 268	60.45 113	63.22 293	84.40 190	32.71 363	80.91 234	51.71 276	80.56 125	83.81 219
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		71.78 126	71.59 115	72.32 195	83.40 75	46.38 311	79.75 118	71.08 325	64.18 34	72.80 116	88.64 72	42.58 241	83.72 153	57.41 225	84.49 76	86.86 89

OMC-MVS		71.40 135	70.60 138	73.78 143	76.60 247	53.15 181	79.74 119	79.78 169	58.37 167	68.75 179	86.45 133	45.43 207	80.60 239	62.58 176	77.73 185	87.58 63

casdiffmvs_mvg		76.14 50	76.30 43	75.66 87	76.46 251	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	74.30 289	48.40 359				80.78 237	53.62 258		79.03 332

Effi-MVS+		73.31 91	72.54 102	75.62 89	77.87 195	53.64 165	79.62 122	79.61 173	61.63 87	72.02 129	82.61 228	56.44 43	85.97 104	63.99 155	79.07 157	87.25 78

GDP-MVS		72.64 106	71.28 125	76.70 64	77.72 201	54.22 155	79.57 123	84.45 48	55.30 241	71.38 139	86.97 109	39.94 275	87.00 70	67.02 126	79.20 151	88.89 12

PAPR		71.72 129	70.82 134	74.41 120	81.20 108	51.17 222	79.55 124	83.33 90	55.81 227	66.93 226	84.61 182	50.95 131	86.06 100	55.79 238	79.20 151	86.00 126

ACMH	55.70 15	65.20 277	63.57 282	70.07 258	78.07 189	52.01 213	79.48 125	79.69 170	55.75 229	56.59 378	80.98 274	27.12 416	80.94 231	42.90 358	71.58 286	77.25 356
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ETV-MVS		74.46 71	73.84 78	76.33 74	79.27 145	55.24 140	79.22 126	85.00 43	64.97 21	72.65 119	79.46 306	53.65 87	87.87 48	67.45 120	82.91 93	85.89 131

BP-MVS1		73.41 88	72.25 106	76.88 61	76.68 244	53.70 163	79.15 127	81.07 147	60.66 108	71.81 130	87.39 96	40.93 269	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 93	73.13 93	73.55 160	74.40 299	55.13 141	78.97 129	74.96 280	56.64 203	74.76 71	88.75 71	55.02 62	78.77 282	76.33 41	78.31 178	86.74 94

GeoE		71.01 140	70.15 149	73.60 158	79.57 138	52.17 208	78.93 130	78.12 217	58.02 174	67.76 211	83.87 201	52.36 105	82.72 187	56.90 227	75.79 218	85.92 129

fmvsm_s_conf0.5_n_11		73.16 94	73.35 89	72.58 184	75.48 267	52.41 206	78.84 131	76.85 241	58.64 161	73.58 92	87.25 103	54.09 74	79.47 259	76.19 44	79.27 147	85.86 132

UA-Net		73.13 96	72.93 95	73.76 145	83.58 71	51.66 219	78.75 132	77.66 224	67.75 4	72.61 120	89.42 56	49.82 144	83.29 163	53.61 259	83.14 87	86.32 116

VDDNet		71.81 125	71.33 123	73.26 171	82.80 83	47.60 302	78.74 133	75.27 270	59.59 143	72.94 111	89.40 57	41.51 261	83.91 150	58.75 217	82.99 90	88.26 31

v10		70.21 159	69.02 169	73.81 142	73.51 317	50.92 228	78.74 133	81.39 131	60.05 129	66.39 237	81.83 257	47.58 175	85.41 121	62.80 175	68.86 335	85.09 174

viewdifsd2359ckpt13		72.40 114	71.79 113	74.22 126	75.63 262	51.77 218	78.67 135	83.13 102	57.08 194	71.59 135	85.36 169	53.10 93	82.64 190	63.07 172	78.51 172	88.24 33

CANet_DTU		68.18 219	67.71 204	69.59 268	74.83 284	46.24 313	78.66 136	76.85 241	59.60 140	63.45 291	82.09 253	35.25 328	77.41 306	59.88 202	78.76 165	85.14 170

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

v8		70.33 157	69.28 164	73.49 162	73.15 323	50.22 247	78.62 137	80.78 154	60.79 104	66.45 236	82.11 252	49.35 151	84.98 127	63.58 165	68.71 336	85.28 166

alignmvs		73.86 80	73.99 74	73.45 164	78.20 182	50.50 239	78.57 139	82.43 113	59.40 146	76.57 46	86.71 120	56.42 44	81.23 222	65.84 139	81.79 107	88.62 20

PLC	56.13 14	65.09 278	63.21 291	70.72 247	81.04 110	54.87 146	78.57 139	77.47 227	48.51 356	55.71 386	81.89 255	33.71 347	79.71 255	41.66 367	70.37 302	77.58 349
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
v7n		69.01 197	67.36 215	73.98 137	72.51 337	52.65 196	78.54 141	81.30 138	60.26 124	62.67 306	81.62 261	43.61 229	84.49 139	57.01 226	68.70 337	84.79 185

COLMAP_ROB	52.97 17	61.27 329	58.81 339	68.64 284	74.63 291	52.51 201	78.42 142	73.30 305	49.92 337	50.96 424	81.51 265	23.06 436	79.40 261	31.63 432	65.85 359	74.01 395
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
Elysia		70.19 161	68.29 191	75.88 80	74.15 306	54.33 153	78.26 143	83.21 95	55.04 253	67.28 217	83.59 209	30.16 386	86.11 98	63.67 163	79.26 148	87.20 79

StellarMVS		70.19 161	68.29 191	75.88 80	74.15 306	54.33 153	78.26 143	83.21 95	55.04 253	67.28 217	83.59 209	30.16 386	86.11 98	63.67 163	79.26 148	87.20 79

fmvsm_s_conf0.5_n_a		69.54 181	68.74 177	71.93 201	72.47 338	53.82 161	78.25 145	62.26 406	49.78 338	73.12 107	86.21 140	52.66 99	76.79 323	75.02 56	68.88 333	85.18 169

E6		74.10 76	74.09 73	74.15 130	77.14 226	50.74 232	78.24 146	83.85 68	62.34 71	73.95 85	87.27 101	55.98 54	82.95 175	68.17 106	79.85 133	88.77 16

fmvsm_s_conf0.5_n_8		74.30 73	74.39 68	74.01 135	75.33 272	52.89 189	78.24 146	77.32 234	61.65 84	78.13 32	88.90 65	52.82 97	81.54 213	78.46 22	78.67 168	87.60 61

CLD-MVS		73.33 90	72.68 100	75.29 96	78.82 159	53.33 177	78.23 148	84.79 46	61.30 92	70.41 149	81.04 272	52.41 104	87.12 66	64.61 151	82.49 100	85.41 160
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		72.81 101	72.33 105	74.24 125	69.89 388	55.81 125	78.22 149	75.40 268	54.17 273	75.00 62	88.03 83	53.82 80	80.23 249	78.08 25	78.34 177	86.69 96

test_fmvsmconf_n		73.01 98	72.59 101	74.27 124	71.28 365	55.88 124	78.21 150	75.56 263	54.31 271	74.86 67	87.80 87	54.72 66	80.23 249	78.07 26	78.48 173	86.70 95

casdiffmvs		74.80 63	74.89 63	74.53 116	75.59 265	50.37 243	78.17 151	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		72.69 105	72.80 98	72.37 194	74.11 309	53.21 180	78.12 152	73.31 304	53.98 276	76.81 45	88.05 80	53.38 88	77.37 308	76.64 38	80.78 117	86.53 104

fmvsm_s_conf0.1_n_a		69.32 188	68.44 186	71.96 199	70.91 369	53.78 162	78.12 152	62.30 405	49.35 344	73.20 101	86.55 130	51.99 112	76.79 323	74.83 58	68.68 338	85.32 164

F-COLMAP		63.05 306	60.87 326	69.58 270	76.99 240	53.63 166	78.12 152	76.16 250	47.97 366	52.41 419	81.61 262	27.87 408	78.11 289	40.07 374	66.66 354	77.00 359

fmvsm_s_conf0.5_n_10		74.11 75	73.98 75	74.48 118	74.61 292	52.86 191	78.10 155	77.06 238	57.14 193	78.24 31	88.79 70	52.83 96	82.26 199	77.79 28	81.30 113	88.32 29

test_fmvsmconf0.01_n		72.17 118	71.50 117	74.16 128	67.96 408	55.58 133	78.06 156	74.67 283	54.19 272	74.54 74	88.23 74	50.35 139	80.24 248	78.07 26	77.46 191	86.65 100

EG-PatchMatch MVS		64.71 282	62.87 294	70.22 254	77.68 203	53.48 170	77.99 157	78.82 189	53.37 288	56.03 385	77.41 345	24.75 433	84.04 146	46.37 319	73.42 256	73.14 398

fmvsm_s_conf0.5_n		69.58 179	68.84 174	71.79 207	72.31 344	52.90 187	77.90 158	62.43 404	49.97 336	72.85 115	85.90 152	52.21 107	76.49 330	75.75 47	70.26 307	85.97 127

SSM_0404		70.84 143	69.41 162	75.12 98	79.20 147	53.86 159	77.89 159	80.00 167	53.88 278	69.40 168	84.61 182	43.21 233	86.56 81	58.80 215	77.68 187	84.95 180

dcpmvs_2		74.55 70	75.23 58	72.48 189	82.34 87	53.34 176	77.87 160	81.46 129	57.80 183	75.49 52	86.81 113	62.22 15	77.75 299	71.09 91	82.02 104	86.34 112

tttt0517		67.83 229	65.66 255	74.33 122	76.69 243	50.82 230	77.86 161	73.99 296	54.54 267	64.64 277	82.53 237	35.06 330	85.50 116	55.71 239	69.91 314	86.67 98

fmvsm_s_conf0.1_n		69.41 187	68.60 180	71.83 204	71.07 367	52.88 190	77.85 162	62.44 403	49.58 341	72.97 110	86.22 139	51.68 119	76.48 331	75.53 51	70.10 310	86.14 122

v1144		70.42 154	69.31 163	73.76 145	73.22 321	50.64 234	77.83 163	81.43 130	58.58 163	69.40 168	81.16 269	47.53 177	85.29 123	64.01 154	70.64 296	85.34 163

CNLPA		65.43 272	64.02 274	69.68 266	78.73 162	58.07 87	77.82 164	70.71 329	51.49 315	61.57 326	83.58 212	38.23 299	70.82 366	43.90 345	70.10 310	80.16 312

fmvsm_s_conf0.5_n_3		73.55 85	74.39 68	71.03 240	74.09 310	51.86 216	77.77 165	75.60 261	61.18 95	78.67 29	88.98 63	55.88 56	77.73 300	78.69 16	78.68 167	83.50 234

VDD-MVS		72.50 109	72.09 108	73.75 147	81.58 97	49.69 262	77.76 166	77.63 225	63.21 50	73.21 100	89.02 62	42.14 245	83.32 162	61.72 185	82.50 99	88.25 32

v1192		69.97 166	68.68 178	73.85 140	73.19 322	50.94 226	77.68 167	81.36 133	57.51 189	68.95 178	80.85 279	45.28 210	85.33 122	62.97 174	70.37 302	85.27 167

v2v482		70.50 152	69.45 161	73.66 153	72.62 333	50.03 252	77.58 168	80.51 158	59.90 132	69.52 164	82.14 250	47.53 177	84.88 133	65.07 146	70.17 308	86.09 124

WR-MVS_H		67.02 247	66.92 228	67.33 300	77.95 194	37.75 399	77.57 169	82.11 118	62.03 80	62.65 307	82.48 238	50.57 136	79.46 260	42.91 357	64.01 374	84.79 185

Anonymous20240529		69.91 167	69.02 169	72.56 186	80.19 126	47.65 300	77.56 170	80.99 150	55.45 238	69.88 160	86.76 114	39.24 286	82.18 201	54.04 254	77.10 200	87.85 49

v144192		69.71 172	68.51 181	73.33 169	73.10 324	50.13 249	77.54 171	80.64 155	56.65 202	68.57 182	80.55 282	46.87 191	84.96 129	62.98 173	69.66 321	84.89 182

baseline		74.61 68	74.70 64	74.34 121	75.70 260	49.99 253	77.54 171	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 95	73.16 92	73.11 173	75.15 278	49.31 269	77.53 173	83.21 95	60.42 114	73.20 101	87.34 98	53.82 80	81.05 228	67.02 126	80.79 116	88.96 10

Fast-Effi-MVS+-dtu		67.37 237	65.33 263	73.48 163	72.94 328	57.78 92	77.47 174	76.88 240	57.60 188	61.97 318	76.85 353	39.31 283	80.49 243	54.72 248	70.28 306	82.17 271

fmvsm_l_conf0.5_n_9		73.27 92	73.66 82	72.09 198	73.82 311	52.72 195	77.45 175	74.28 290	56.61 209	77.10 43	88.16 76	56.17 47	77.09 313	78.27 24	81.13 115	86.48 106

v1921920		69.47 185	68.17 195	73.36 168	73.06 325	50.10 250	77.39 176	80.56 156	56.58 211	68.59 180	80.37 284	44.72 218	84.98 127	62.47 179	69.82 316	85.00 176

tt0805		67.77 231	67.24 222	69.34 273	74.87 282	40.08 375	77.36 177	81.37 132	55.31 240	66.33 238	84.65 180	37.35 307	82.55 193	55.65 241	72.28 277	85.39 161

GBi-Net		67.21 239	66.55 234	69.19 274	77.63 206	43.33 343	77.31 178	77.83 221	56.62 206	65.04 269	82.70 224	41.85 251	80.33 245	47.18 312	72.76 267	83.92 214

test1		67.21 239	66.55 234	69.19 274	77.63 206	43.33 343	77.31 178	77.83 221	56.62 206	65.04 269	82.70 224	41.85 251	80.33 245	47.18 312	72.76 267	83.92 214

FMVSNet1		66.70 254	65.87 251	69.19 274	77.49 214	43.33 343	77.31 178	77.83 221	56.45 212	64.60 278	82.70 224	38.08 301	80.33 245	46.08 322	72.31 276	83.92 214

fmvsm_s_conf0.5_n_9		75.16 60	75.22 59	75.01 99	78.34 178	55.37 138	77.30 181	73.95 297	61.40 89	79.46 23	90.14 41	57.07 37	81.15 223	80.00 5	79.31 146	88.51 25

MVS_111021_HR		74.02 77	73.46 86	75.69 86	83.01 80	60.63 40	77.29 182	78.40 212	61.18 95	70.58 147	85.97 150	54.18 72	84.00 149	67.52 117	82.98 92	82.45 264

SSM_0407		70.41 155	68.96 172	74.75 104	78.65 164	53.46 171	77.28 183	80.00 167	53.88 278	68.14 192	84.61 182	43.21 233	86.26 95	58.80 215	76.11 211	84.54 190

EIA-MVS		71.78 126	70.60 138	75.30 95	79.85 132	53.54 169	77.27 184	83.26 94	57.92 179	66.49 234	79.39 308	52.07 111	86.69 77	60.05 199	79.14 156	85.66 146

viewmanbaseed2359cas		72.92 100	72.89 96	73.00 175	75.16 276	49.25 272	77.25 185	83.11 103	59.52 145	72.93 112	86.63 123	54.11 73	80.98 229	66.63 130	80.67 120	88.76 18

v1240		69.24 191	67.91 200	73.25 172	73.02 327	49.82 254	77.21 186	80.54 157	56.43 213	68.34 187	80.51 283	43.33 232	84.99 125	62.03 183	69.77 319	84.95 180

fmvsm_l_conf0.5_n		70.99 141	70.82 134	71.48 218	71.45 358	54.40 151	77.18 187	70.46 331	48.67 353	75.17 57	86.86 111	53.77 82	76.86 321	76.33 41	77.51 190	83.17 246

E4		73.91 79	73.83 79	74.15 130	77.13 227	50.47 240	77.15 188	83.79 70	62.21 73	73.61 90	87.19 105	56.08 52	83.03 168	67.91 111	79.35 144	88.94 11

jason		69.65 176	68.39 188	73.43 166	78.27 181	56.88 108	77.12 189	73.71 300	46.53 385	69.34 170	83.22 218	43.37 231	79.18 266	64.77 148	79.20 151	84.23 202
jason: jason.
PAPM		67.92 226	66.69 232	71.63 215	78.09 188	49.02 275	77.09 190	81.24 142	51.04 323	60.91 332	83.98 199	47.71 172	84.99 125	40.81 371	79.32 145	80.90 298

EI-MVSNet-Vis-set		72.42 113	71.59 115	74.91 100	78.47 171	54.02 157	77.05 191	79.33 179	65.03 18	71.68 133	79.35 310	52.75 98	84.89 131	66.46 131	74.23 237	85.83 135

PEN-MVS		66.60 256	66.45 236	67.04 301	77.11 231	36.56 412	77.03 192	80.42 161	62.95 55	62.51 312	84.03 197	46.69 192	79.07 273	44.22 339	63.08 384	85.51 151

E2		73.72 82	73.60 83	74.06 132	77.16 224	50.40 241	76.97 193	83.74 71	61.64 85	73.36 95	86.75 117	56.14 48	82.99 170	67.50 118	79.18 154	88.80 13

E3		73.72 82	73.60 83	74.06 132	77.16 224	50.40 241	76.97 193	83.74 71	61.64 85	73.36 95	86.76 114	56.13 49	82.99 170	67.50 118	79.18 154	88.80 13

FIs		70.82 146	71.43 119	68.98 280	78.33 179	38.14 395	76.96 195	83.59 79	61.02 98	67.33 216	86.73 118	55.07 60	81.64 209	54.61 251	79.22 150	87.14 82

PS-CasMVS		66.42 260	66.32 244	66.70 305	77.60 212	36.30 417	76.94 196	79.61 173	62.36 70	62.43 315	83.66 207	45.69 199	78.37 285	45.35 335	63.26 382	85.42 159

h-mvs33		72.71 104	71.49 118	76.40 72	81.99 92	59.58 57	76.92 197	76.74 246	60.40 115	74.81 68	85.95 151	45.54 203	85.76 109	70.41 95	70.61 298	83.86 218

fmvsm_l_conf0.5_n_a		70.50 152	70.27 145	71.18 234	71.30 364	54.09 156	76.89 198	69.87 335	47.90 367	74.37 77	86.49 131	53.07 95	76.69 327	75.41 52	77.11 199	82.76 253

thisisatest0530		67.92 226	65.78 253	74.33 122	76.29 252	51.03 225	76.89 198	74.25 291	53.67 285	65.59 254	81.76 259	35.15 329	85.50 116	55.94 234	72.47 272	86.47 107

viewcassd2359sk11		73.56 84	73.41 88	74.00 136	77.13 227	50.35 244	76.86 200	83.69 75	61.23 94	73.14 104	86.38 135	56.09 51	82.96 173	67.15 122	79.01 159	88.70 19

test_0402		63.25 302	61.01 322	69.96 259	80.00 130	54.37 152	76.86 200	72.02 320	54.58 266	58.71 357	80.79 281	35.00 331	84.36 141	26.41 456	64.71 368	71.15 426

CP-MVSNet		66.49 259	66.41 240	66.72 303	77.67 204	36.33 415	76.83 202	79.52 175	62.45 68	62.54 310	83.47 215	46.32 195	78.37 285	45.47 333	63.43 381	85.45 156

E3new		73.41 88	73.22 91	73.95 139	77.06 232	50.31 245	76.78 203	83.66 76	60.90 101	72.93 112	86.02 148	55.99 53	82.95 175	66.89 129	78.77 164	88.61 21

fmvsm_s_conf0.5_n_4		72.04 122	71.85 111	72.58 184	73.74 314	52.49 202	76.69 204	72.42 315	56.42 214	75.32 54	87.04 107	52.13 110	78.01 291	79.29 12	73.65 247	87.26 77

EI-MVSNet-UG-set		71.92 123	71.06 130	74.52 117	77.98 193	53.56 168	76.62 205	79.16 180	64.40 29	71.18 140	78.95 315	52.19 108	84.66 138	65.47 142	73.57 250	85.32 164

RRT-MVS		71.46 133	70.70 137	73.74 148	77.76 200	49.30 270	76.60 206	80.45 160	61.25 93	68.17 190	84.78 175	44.64 219	84.90 130	64.79 147	77.88 184	87.03 84

lupinMVS		69.57 180	68.28 193	73.44 165	78.76 160	57.15 104	76.57 207	73.29 306	46.19 388	69.49 165	82.18 246	43.99 227	79.23 265	64.66 149	79.37 141	83.93 213

TranMVSNet+NR-MVSNet		70.36 156	70.10 151	71.17 235	78.64 167	42.97 349	76.53 208	81.16 146	66.95 6	68.53 183	85.42 167	51.61 120	83.07 167	52.32 267	69.70 320	87.46 66

TAPA-MVS	59.36 10	66.60 256	65.20 265	70.81 244	76.63 246	48.75 281	76.52 209	80.04 166	50.64 328	65.24 264	84.93 172	39.15 287	78.54 284	36.77 398	76.88 202	85.14 170
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
DTE-MVSNet		65.58 270	65.34 262	66.31 313	76.06 256	34.79 425	76.43 210	79.38 178	62.55 66	61.66 324	83.83 202	45.60 201	79.15 270	41.64 369	60.88 400	85.00 176

anonymousdsp		67.00 248	64.82 268	73.57 159	70.09 384	56.13 117	76.35 211	77.35 232	48.43 358	64.99 272	80.84 280	33.01 356	80.34 244	64.66 149	67.64 346	84.23 202

MVP-Stereo		65.41 273	63.80 278	70.22 254	77.62 210	55.53 134	76.30 212	78.53 203	50.59 329	56.47 381	78.65 319	39.84 278	82.68 188	44.10 343	72.12 280	72.44 408
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
fmvsm_s_conf0.5_n_6		72.59 108	72.87 97	71.73 209	75.14 279	51.96 214	76.28 213	77.12 237	57.63 187	73.85 87	86.91 110	51.54 121	77.87 296	77.18 32	80.18 131	85.37 162

MVS_Test		72.45 111	72.46 103	72.42 193	74.88 281	48.50 287	76.28 213	83.14 101	59.40 146	72.46 122	84.68 178	55.66 57	81.12 224	65.98 138	79.66 137	87.63 59

LuminaMVS		68.24 217	66.82 230	72.51 188	73.46 320	53.60 167	76.23 215	78.88 188	52.78 295	68.08 198	80.13 290	32.70 364	81.41 215	63.16 171	75.97 215	82.53 260

IterMVS-LS		69.22 192	68.48 182	71.43 224	74.44 298	49.40 266	76.23 215	77.55 226	59.60 140	65.85 251	81.59 264	51.28 126	81.58 212	59.87 203	69.90 315	83.30 237
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
新几何2							76.12 217

FMVSNet2		66.93 249	66.31 245	68.79 283	77.63 206	42.98 348	76.11 218	77.47 227	56.62 206	65.22 266	82.17 248	41.85 251	80.18 251	47.05 315	72.72 270	83.20 241

旧先验2							76.08 219		45.32 396	76.55 47			65.56 402	58.75 217

BH-untuned		68.27 215	67.29 217	71.21 232	79.74 133	53.22 179	76.06 220	77.46 229	57.19 192	66.10 243	81.61 262	45.37 209	83.50 159	45.42 334	76.68 206	76.91 362

FC-MVSNet-test		69.80 171	70.58 140	67.46 296	77.61 211	34.73 428	76.05 221	83.19 99	60.84 103	65.88 250	86.46 132	54.52 69	80.76 238	52.52 266	78.12 180	86.91 87

PCF-MVS	61.88 8	70.95 142	69.49 159	75.35 93	77.63 206	55.71 127	76.04 222	81.81 122	50.30 331	69.66 163	85.40 168	52.51 101	84.89 131	51.82 274	80.24 129	85.45 156
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
UniMVSNet_NR-MVSNet		71.11 137	71.00 131	71.44 222	79.20 147	44.13 335	76.02 223	82.60 111	66.48 11	68.20 188	84.60 185	56.82 40	82.82 185	54.62 249	70.43 300	87.36 75

UniMVSNet (Re)		70.63 149	70.20 146	71.89 202	78.55 168	45.29 325	75.94 224	82.92 105	63.68 42	68.16 191	83.59 209	53.89 78	83.49 160	53.97 255	71.12 291	86.89 88

KinetiMVS		71.26 136	70.16 148	74.57 114	74.59 293	52.77 194	75.91 225	81.20 143	60.72 107	69.10 177	85.71 160	41.67 256	83.53 158	63.91 158	78.62 170	87.42 68

test_fmvsmvis_n_1920		70.84 143	70.38 143	72.22 197	71.16 366	55.39 137	75.86 226	72.21 318	49.03 348	73.28 99	86.17 142	51.83 116	77.29 310	75.80 46	78.05 181	83.98 211

EPNet_dtu		61.90 321	61.97 306	61.68 365	72.89 329	39.78 379	75.85 227	65.62 373	55.09 247	54.56 402	79.36 309	37.59 304	67.02 393	39.80 379	76.95 201	78.25 338
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MGCFI-Net		72.45 111	73.34 90	69.81 265	77.77 199	43.21 346	75.84 228	81.18 144	59.59 143	75.45 53	86.64 121	57.74 31	77.94 292	63.92 156	81.90 106	88.30 30

v148		68.24 217	67.19 225	71.40 225	70.43 377	47.77 299	75.76 229	77.03 239	58.91 154	67.36 215	80.10 292	48.60 163	81.89 205	60.01 200	66.52 356	84.53 193

test_fmvsm_n_1920		71.73 128	71.14 128	73.50 161	72.52 336	56.53 111	75.60 230	76.16 250	48.11 363	77.22 40	85.56 162	53.10 93	77.43 305	74.86 57	77.14 198	86.55 103

SixPastTwentyTwo		61.65 324	58.80 341	70.20 256	75.80 258	47.22 305	75.59 231	69.68 337	54.61 264	54.11 406	79.26 311	27.07 417	82.96 173	43.27 352	49.79 445	80.41 307

DELS-MVS		74.76 64	74.46 67	75.65 88	77.84 197	52.25 207	75.59 231	84.17 54	63.76 40	73.15 103	82.79 223	59.58 23	86.80 74	67.24 121	86.04 65	87.89 46
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)		69.82 169	68.48 182	73.84 141	78.44 172	50.04 251	75.58 233	78.99 186	58.16 170	67.59 212	82.14 250	42.66 239	85.63 110	56.60 228	76.19 210	85.84 134

Baseline_NR-MVSNet		67.05 246	67.56 205	65.50 331	75.65 261	37.70 401	75.42 234	74.65 284	59.90 132	68.14 192	83.15 221	49.12 158	77.20 311	52.23 268	69.78 317	81.60 277

OpenMVS_ROB	52.78 18	60.03 338	58.14 348	65.69 328	70.47 376	44.82 327	75.33 235	70.86 328	45.04 397	56.06 384	76.00 369	26.89 420	79.65 256	35.36 411	67.29 349	72.60 403

viewdifsd2359ckpt07		71.90 124	71.97 110	71.69 212	74.81 285	48.08 293	75.30 236	80.49 159	60.00 130	71.63 134	86.33 137	56.34 45	79.25 264	65.40 143	77.41 192	87.76 54

xiu_mvs_v1_base_debu		68.58 207	67.28 218	72.48 189	78.19 183	57.19 101	75.28 237	75.09 276	51.61 311	70.04 153	81.41 266	32.79 359	79.02 275	63.81 159	77.31 193	81.22 289

xiu_mvs_v1_base		68.58 207	67.28 218	72.48 189	78.19 183	57.19 101	75.28 237	75.09 276	51.61 311	70.04 153	81.41 266	32.79 359	79.02 275	63.81 159	77.31 193	81.22 289

xiu_mvs_v1_base_debi		68.58 207	67.28 218	72.48 189	78.19 183	57.19 101	75.28 237	75.09 276	51.61 311	70.04 153	81.41 266	32.79 359	79.02 275	63.81 159	77.31 193	81.22 289

EI-MVSNet		69.27 190	68.44 186	71.73 209	74.47 296	49.39 267	75.20 240	78.45 208	59.60 140	69.16 175	76.51 362	51.29 125	82.50 194	59.86 204	71.45 288	83.30 237

CVMVSNet		59.63 344	59.14 336	61.08 374	74.47 296	38.84 388	75.20 240	68.74 348	31.15 451	58.24 364	76.51 362	32.39 372	68.58 380	49.77 288	65.84 360	75.81 370

ET-MVSNet_ETH3D		67.96 225	65.72 254	74.68 107	76.67 245	55.62 132	75.11 242	74.74 281	52.91 293	60.03 340	80.12 291	33.68 348	82.64 190	61.86 184	76.34 208	85.78 136

xiu_mvs_v2_base		70.52 150	69.75 153	72.84 179	81.21 107	55.63 130	75.11 242	78.92 187	54.92 258	69.96 159	79.68 301	47.00 190	82.09 202	61.60 187	79.37 141	80.81 300

K. test v3		60.47 335	57.11 354	70.56 250	73.74 314	48.22 290	75.10 244	62.55 401	58.27 169	53.62 412	76.31 366	27.81 409	81.59 211	47.42 308	39.18 460	81.88 275

Fast-Effi-MVS+		70.28 158	69.12 168	73.73 149	78.50 169	51.50 220	75.01 245	79.46 177	56.16 221	68.59 180	79.55 304	53.97 76	84.05 145	53.34 261	77.53 189	85.65 147

DU-MVS		70.01 164	69.53 158	71.44 222	78.05 190	44.13 335	75.01 245	81.51 128	64.37 30	68.20 188	84.52 186	49.12 158	82.82 185	54.62 249	70.43 300	87.37 73

FMVSNet3		66.32 263	65.61 256	68.46 286	76.48 250	42.34 353	74.98 247	77.15 236	55.83 226	65.04 269	81.16 269	39.91 276	80.14 252	47.18 312	72.76 267	82.90 251

mvsmamba		68.47 211	66.56 233	74.21 127	79.60 136	52.95 185	74.94 248	75.48 266	52.09 307	60.10 338	83.27 217	36.54 318	84.70 135	59.32 209	77.69 186	84.99 178

MTAPA		76.90 38	76.42 42	78.35 39	86.08 38	63.57 2	74.92 249	80.97 151	65.13 15	75.77 50	90.88 20	48.63 161	86.66 78	77.23 30	88.17 37	84.81 184

PS-MVSNAJ		70.51 151	69.70 155	72.93 177	81.52 98	55.79 126	74.92 249	79.00 185	55.04 253	69.88 160	78.66 318	47.05 186	82.19 200	61.61 186	79.58 138	80.83 299

MVS_111021_LR		69.50 184	68.78 176	71.65 214	78.38 174	59.33 61	74.82 251	70.11 333	58.08 171	67.83 207	84.68 178	41.96 247	76.34 334	65.62 141	77.54 188	79.30 328

ECVR-MVS		67.72 232	67.51 209	68.35 288	79.46 140	36.29 418	74.79 252	66.93 362	58.72 157	67.19 220	88.05 80	36.10 320	81.38 217	52.07 270	84.25 78	87.39 71

test_yl		69.69 173	69.13 166	71.36 228	78.37 176	45.74 318	74.71 253	80.20 164	57.91 180	70.01 157	83.83 202	42.44 242	82.87 181	54.97 245	79.72 135	85.48 152

DCV-MVSNet		69.69 173	69.13 166	71.36 228	78.37 176	45.74 318	74.71 253	80.20 164	57.91 180	70.01 157	83.83 202	42.44 242	82.87 181	54.97 245	79.72 135	85.48 152

TransMVSNet (Re)		64.72 281	64.33 271	65.87 326	75.22 273	38.56 390	74.66 255	75.08 279	58.90 155	61.79 321	82.63 227	51.18 127	78.07 290	43.63 350	55.87 423	80.99 297

BH-w/o		66.85 250	65.83 252	69.90 263	79.29 142	52.46 203	74.66 255	76.65 247	54.51 268	64.85 274	78.12 326	45.59 202	82.95 175	43.26 353	75.54 222	74.27 392

IMVS_0403		69.09 195	68.14 196	71.95 200	77.06 232	49.73 256	74.51 257	78.60 197	52.70 296	66.69 230	82.58 229	46.43 194	83.38 161	59.20 210	75.46 224	82.74 254

PVSNet_BlendedMVS		68.56 210	67.72 202	71.07 239	77.03 238	50.57 235	74.50 258	81.52 126	53.66 286	64.22 285	79.72 300	49.13 156	82.87 181	55.82 236	73.92 241	79.77 323

MonoMVSNet		64.15 291	63.31 289	66.69 306	70.51 375	44.12 337	74.47 259	74.21 292	57.81 182	63.03 298	76.62 358	38.33 296	77.31 309	54.22 253	60.59 405	78.64 335

c3_l		68.33 214	67.56 205	70.62 249	70.87 370	46.21 314	74.47 259	78.80 191	56.22 220	66.19 240	78.53 323	51.88 113	81.40 216	62.08 180	69.04 331	84.25 201

test2506		65.33 275	64.61 269	67.50 295	79.46 140	34.19 433	74.43 261	51.92 444	58.72 157	66.75 229	88.05 80	25.99 425	80.92 233	51.94 272	84.25 78	87.39 71

IMVS_0407		68.90 199	67.93 199	71.82 205	77.06 232	49.73 256	74.40 262	78.60 197	52.70 296	66.19 240	82.58 229	45.17 213	83.00 169	59.20 210	75.46 224	82.74 254

BH-RMVSNet		68.81 201	67.42 212	72.97 176	80.11 129	52.53 200	74.26 263	76.29 249	58.48 165	68.38 186	84.20 192	42.59 240	83.83 151	46.53 317	75.91 216	82.56 258

NR-MVSNet		69.54 181	68.85 173	71.59 216	78.05 190	43.81 340	74.20 264	80.86 153	65.18 14	62.76 304	84.52 186	52.35 106	83.59 157	50.96 282	70.78 295	87.37 73

UniMVSNet_ETH3D		67.60 234	67.07 227	69.18 277	77.39 217	42.29 354	74.18 265	75.59 262	60.37 118	66.77 228	86.06 146	37.64 303	78.93 280	52.16 269	73.49 252	86.32 116

VPA-MVSNet		69.02 196	69.47 160	67.69 294	77.42 216	41.00 370	74.04 266	79.68 171	60.06 128	69.26 173	84.81 174	51.06 130	77.58 303	54.44 252	74.43 235	84.48 195

miper_ehance_all_eth		68.03 222	67.24 222	70.40 253	70.54 374	46.21 314	73.98 267	78.68 195	55.07 250	66.05 244	77.80 337	52.16 109	81.31 219	61.53 190	69.32 325	83.67 227

hse-mvs2		71.04 138	69.86 152	74.60 112	79.58 137	57.12 106	73.96 268	75.25 271	60.40 115	74.81 68	81.95 254	45.54 203	82.90 178	70.41 95	66.83 353	83.77 223

1314		64.61 285	63.21 291	68.80 282	71.87 351	47.46 303	73.95 269	78.39 213	42.88 418	59.97 341	76.60 361	38.11 300	79.39 262	54.84 247	72.32 275	79.55 324

MVS		67.37 237	66.33 243	70.51 252	75.46 268	50.94 226	73.95 269	81.85 121	41.57 425	62.54 310	78.57 322	47.98 167	85.47 118	52.97 264	82.05 103	75.14 378

AUN-MVS		68.45 213	66.41 240	74.57 114	79.53 139	57.08 107	73.93 271	75.23 272	54.44 269	66.69 230	81.85 256	37.10 313	82.89 179	62.07 181	66.84 352	83.75 224

OurMVSNet-221017-0		61.37 328	58.63 343	69.61 267	72.05 347	48.06 294	73.93 271	72.51 314	47.23 378	54.74 399	80.92 276	21.49 443	81.24 221	48.57 301	56.22 422	79.53 325

test1111		67.21 239	67.14 226	67.42 297	79.24 146	34.76 427	73.89 273	65.65 372	58.71 159	66.96 225	87.95 84	36.09 321	80.53 240	52.03 271	83.79 84	86.97 86

cl22		67.47 236	66.45 236	70.54 251	69.85 390	46.49 310	73.85 274	77.35 232	55.07 250	65.51 255	77.92 332	47.64 174	81.10 225	61.58 188	69.32 325	84.01 210

TAMVS		66.78 253	65.27 264	71.33 231	79.16 151	53.67 164	73.84 275	69.59 339	52.32 305	65.28 259	81.72 260	44.49 222	77.40 307	42.32 361	78.66 169	82.92 249

WR-MVS		68.47 211	68.47 184	68.44 287	80.20 125	39.84 378	73.75 276	76.07 253	64.68 24	68.11 196	83.63 208	50.39 138	79.14 271	49.78 287	69.66 321	86.34 112

eth_miper_zixun_eth		67.63 233	66.28 246	71.67 213	71.60 354	48.33 289	73.68 277	77.88 219	55.80 228	65.91 247	78.62 321	47.35 183	82.88 180	59.45 206	66.25 357	83.81 219

guyue		68.10 221	67.23 224	70.71 248	73.67 316	49.27 271	73.65 278	76.04 255	55.62 234	67.84 206	82.26 244	41.24 266	78.91 281	61.01 192	73.72 245	83.94 212

TR-MVS		66.59 258	65.07 266	71.17 235	79.18 149	49.63 264	73.48 279	75.20 274	52.95 292	67.90 200	80.33 287	39.81 279	83.68 154	43.20 354	73.56 251	80.20 311

VortexMVS		66.41 261	65.50 258	69.16 278	73.75 312	48.14 291	73.41 280	78.28 215	53.73 283	64.98 273	78.33 324	40.62 271	79.07 273	58.88 214	67.50 347	80.26 310

fmvsm_s_conf0.1_n_2		69.64 177	69.01 171	71.52 217	71.66 353	51.04 224	73.39 281	67.14 360	55.02 256	75.11 58	87.64 89	42.94 238	77.01 316	75.55 50	72.63 271	86.52 105

fmvsm_s_conf0.5_n_2		69.82 169	69.27 165	71.46 219	72.00 348	51.08 223	73.30 282	67.79 354	55.06 252	75.24 56	87.51 90	44.02 226	77.00 317	75.67 48	72.86 265	86.31 119

cl____		67.18 242	66.26 247	69.94 260	70.20 381	45.74 318	73.30 282	76.83 243	55.10 245	65.27 260	79.57 303	47.39 181	80.53 240	59.41 208	69.22 329	83.53 233

DIV-MVS_self_test		67.18 242	66.26 247	69.94 260	70.20 381	45.74 318	73.29 284	76.83 243	55.10 245	65.27 260	79.58 302	47.38 182	80.53 240	59.43 207	69.22 329	83.54 232

AstraMVS		67.86 228	66.83 229	70.93 242	73.50 318	49.34 268	73.28 285	74.01 295	55.45 238	68.10 197	83.28 216	38.93 290	79.14 271	63.22 170	71.74 283	84.30 200

CDS-MVSNet		66.80 252	65.37 261	71.10 238	78.98 154	53.13 183	73.27 286	71.07 326	52.15 306	64.72 275	80.23 289	43.56 230	77.10 312	45.48 332	78.88 160	83.05 248
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
viewdifsd2359ckpt11		69.13 193	68.38 189	71.38 226	71.57 355	48.61 284	73.22 287	73.18 307	57.65 185	70.67 145	84.73 176	50.03 140	79.80 253	63.25 168	71.10 292	85.74 142

viewmsd2359difaftdt		69.13 193	68.38 189	71.38 226	71.57 355	48.61 284	73.22 287	73.18 307	57.65 185	70.67 145	84.73 176	50.03 140	79.80 253	63.25 168	71.10 292	85.74 142

diffmvs_AUTHOR		71.02 139	70.87 133	71.45 221	69.89 388	48.97 278	73.16 289	78.33 214	57.79 184	72.11 128	85.26 170	51.84 115	77.89 295	71.00 92	78.47 175	87.49 65

pmmvs6		63.69 296	62.82 296	66.27 315	70.63 372	39.27 385	73.13 290	75.47 267	52.69 301	59.75 347	82.30 242	39.71 280	77.03 315	47.40 309	64.35 373	82.53 260

IB-MVS	56.42 12	65.40 274	62.73 297	73.40 167	74.89 280	52.78 193	73.09 291	75.13 275	55.69 230	58.48 363	73.73 395	32.86 358	86.32 92	50.63 283	70.11 309	81.10 293
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		70.69 148	70.43 141	71.46 219	69.45 395	48.95 279	72.93 292	78.46 207	57.27 191	71.69 132	83.97 200	51.48 123	77.92 294	70.70 94	77.95 183	87.53 64
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		62.01 320	60.88 324	65.42 333	68.74 402	38.43 393	72.92 293	77.39 230	54.74 263	55.40 391	76.71 355	35.46 326	76.72 326	44.25 338	62.31 390	81.10 293

V42		68.65 205	67.35 216	72.56 186	68.93 401	50.18 248	72.90 294	79.47 176	56.92 199	69.45 167	80.26 288	46.29 196	82.99 170	64.07 152	67.82 344	84.53 193

miper_enhance_ethall		67.11 245	66.09 249	70.17 257	69.21 398	45.98 316	72.85 295	78.41 211	51.38 317	65.65 253	75.98 372	51.17 128	81.25 220	60.82 194	69.32 325	83.29 239

thres100view900		63.28 301	62.41 300	65.89 324	77.31 220	38.66 389	72.65 296	69.11 346	57.07 195	62.45 313	81.03 273	37.01 315	79.17 267	31.84 428	73.25 259	79.83 320

testdata1							72.65 296		60.50 112

FE-MVS		65.91 266	63.33 288	73.63 156	77.36 218	51.95 215	72.62 298	75.81 257	53.70 284	65.31 258	78.96 314	28.81 401	86.39 89	43.93 344	73.48 253	82.55 259

pm-mvs1		65.24 276	64.97 267	66.04 321	72.38 341	39.40 384	72.62 298	75.63 260	55.53 235	62.35 317	83.18 220	47.45 179	76.47 332	49.06 297	66.54 355	82.24 268

test222					83.14 76	58.68 81	72.57 300	63.45 394	41.78 421	67.56 213	86.12 143	37.13 312			78.73 166	74.98 382

PVSNet_Blended		68.59 206	67.72 202	71.19 233	77.03 238	50.57 235	72.51 301	81.52 126	51.91 309	64.22 285	77.77 340	49.13 156	82.87 181	55.82 236	79.58 138	80.14 313

EU-MVSNet		55.61 378	54.41 381	59.19 385	65.41 426	33.42 438	72.44 302	71.91 321	28.81 453	51.27 422	73.87 394	24.76 432	69.08 377	43.04 355	58.20 413	75.06 379

thres600view7		63.30 300	62.27 302	66.41 311	77.18 223	38.87 387	72.35 303	69.11 346	56.98 198	62.37 316	80.96 275	37.01 315	79.00 278	31.43 435	73.05 263	81.36 284

pmmvs-eth3d		58.81 349	56.31 366	66.30 314	67.61 410	52.42 205	72.30 304	64.76 380	43.55 411	54.94 397	74.19 390	28.95 398	72.60 352	43.31 351	57.21 417	73.88 396

viewmambaseed2359dif		68.91 198	68.18 194	71.11 237	70.21 380	48.05 296	72.28 305	75.90 256	51.96 308	70.93 142	84.47 189	51.37 124	78.59 283	61.55 189	74.97 229	86.68 97

cascas		65.98 265	63.42 286	73.64 155	77.26 221	52.58 199	72.26 306	77.21 235	48.56 354	61.21 329	74.60 387	32.57 370	85.82 108	50.38 285	76.75 205	82.52 262

VPNet		67.52 235	68.11 197	65.74 327	79.18 149	36.80 410	72.17 307	72.83 312	62.04 79	67.79 209	85.83 155	48.88 160	76.60 329	51.30 278	72.97 264	83.81 219

MS-PatchMatch		62.42 312	61.46 312	65.31 337	75.21 274	52.10 209	72.05 308	74.05 294	46.41 386	57.42 373	74.36 388	34.35 339	77.57 304	45.62 328	73.67 246	66.26 445

mvs_anonymous		68.03 222	67.51 209	69.59 268	72.08 346	44.57 332	71.99 309	75.23 272	51.67 310	67.06 223	82.57 233	54.68 67	77.94 292	56.56 231	75.71 220	86.26 121

patch_mono-2		69.85 168	71.09 129	66.16 317	79.11 152	54.80 147	71.97 310	74.31 288	53.50 287	70.90 143	84.17 193	57.63 34	63.31 411	66.17 133	82.02 104	80.38 308

tfpn200view9		63.18 303	62.18 304	66.21 316	76.85 241	39.62 381	71.96 311	69.44 342	56.63 204	62.61 308	79.83 295	37.18 309	79.17 267	31.84 428	73.25 259	79.83 320

thres400		63.31 299	62.18 304	66.72 303	76.85 241	39.62 381	71.96 311	69.44 342	56.63 204	62.61 308	79.83 295	37.18 309	79.17 267	31.84 428	73.25 259	81.36 284

SD_0403		63.07 305	63.49 285	61.82 364	75.16 276	31.14 450	71.89 313	73.47 301	53.34 289	58.22 365	81.81 258	45.17 213	73.86 347	37.43 392	74.87 231	80.45 305

baseline1		63.81 295	63.87 277	63.62 351	76.29 252	36.36 413	71.78 314	67.29 358	56.05 223	64.23 284	82.95 222	47.11 185	74.41 344	47.30 311	61.85 394	80.10 314

baseline2		63.42 298	61.26 317	69.89 264	72.55 335	47.62 301	71.54 315	68.38 350	50.11 333	54.82 398	75.55 377	43.06 236	80.96 230	48.13 305	67.16 351	81.11 292

pmmvs4		61.48 327	59.39 334	67.76 293	71.57 355	53.86 159	71.42 316	65.34 375	44.20 405	59.46 349	77.92 332	35.90 322	74.71 342	43.87 346	64.87 367	74.71 388

1112_ss		64.00 294	63.36 287	65.93 323	79.28 144	42.58 352	71.35 317	72.36 317	46.41 386	60.55 335	77.89 335	46.27 197	73.28 349	46.18 321	69.97 312	81.92 274

thisisatest0515		65.83 267	63.50 284	72.82 181	73.75 312	49.50 265	71.32 318	73.12 311	49.39 343	63.82 287	76.50 364	34.95 332	84.84 134	53.20 263	75.49 223	84.13 207

CostFormer		64.04 293	62.51 298	68.61 285	71.88 350	45.77 317	71.30 319	70.60 330	47.55 372	64.31 281	76.61 360	41.63 257	79.62 258	49.74 289	69.00 332	80.42 306

tfpnnormal		62.47 311	61.63 310	64.99 340	74.81 285	39.01 386	71.22 320	73.72 299	55.22 244	60.21 336	80.09 293	41.26 265	76.98 319	30.02 442	68.09 342	78.97 333

IterMVS		62.79 308	61.27 316	67.35 299	69.37 396	52.04 212	71.17 321	68.24 352	52.63 302	59.82 344	76.91 352	37.32 308	72.36 354	52.80 265	63.19 383	77.66 348
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Vis-MVSNet (Re-imp)		63.69 296	63.88 276	63.14 356	74.75 287	31.04 451	71.16 322	63.64 392	56.32 216	59.80 345	84.99 171	44.51 220	75.46 339	39.12 383	80.62 121	82.92 249

IterMVS-SCA-FT		62.49 310	61.52 311	65.40 334	71.99 349	50.80 231	71.15 323	69.63 338	45.71 394	60.61 334	77.93 331	37.45 305	65.99 400	55.67 240	63.50 380	79.42 326

Anonymous202405211		66.84 251	65.99 250	69.40 272	80.19 126	42.21 356	71.11 324	71.31 324	58.80 156	67.90 200	86.39 134	29.83 391	79.65 256	49.60 293	78.78 163	86.33 114

Anonymous20240521		55.30 379	54.41 381	57.96 396	60.92 451	41.73 360	71.09 325	71.06 327	41.18 426	48.65 436	73.31 398	16.93 449	59.25 427	42.54 359	64.01 374	72.90 400

tpm2		62.07 317	60.10 330	67.99 291	72.79 330	43.86 339	71.05 326	66.85 363	43.14 416	62.77 303	75.39 381	38.32 297	80.80 236	41.69 366	68.88 333	79.32 327

TDRefinement		53.44 393	50.72 403	61.60 366	64.31 432	46.96 307	70.89 327	65.27 377	41.78 421	44.61 449	77.98 329	11.52 464	66.36 397	28.57 448	51.59 439	71.49 421

XVG-ACMP-BASELINE		64.36 289	62.23 303	70.74 246	72.35 342	52.45 204	70.80 328	78.45 208	53.84 280	59.87 343	81.10 271	16.24 452	79.32 263	55.64 242	71.76 282	80.47 304

mmtdpeth		60.40 336	59.12 337	64.27 346	69.59 392	48.99 276	70.67 329	70.06 334	54.96 257	62.78 302	73.26 400	27.00 418	67.66 386	58.44 220	45.29 452	76.16 367

XVG-OURS-SEG-HR		68.81 201	67.47 211	72.82 181	74.40 299	56.87 109	70.59 330	79.04 184	54.77 261	66.99 224	86.01 149	39.57 281	78.21 288	62.54 177	73.33 257	83.37 236

VNet		69.68 175	70.19 147	68.16 290	79.73 134	41.63 363	70.53 331	77.38 231	60.37 118	70.69 144	86.63 123	51.08 129	77.09 313	53.61 259	81.69 112	85.75 141

GA-MVS		65.53 271	63.70 280	71.02 241	70.87 370	48.10 292	70.48 332	74.40 286	56.69 201	64.70 276	76.77 354	33.66 349	81.10 225	55.42 244	70.32 305	83.87 217

MSDG		61.81 323	59.23 335	69.55 271	72.64 332	52.63 198	70.45 333	75.81 257	51.38 317	53.70 409	76.11 367	29.52 393	81.08 227	37.70 390	65.79 361	74.93 383

ab-mvs		66.65 255	66.42 239	67.37 298	76.17 254	41.73 360	70.41 334	76.14 252	53.99 275	65.98 245	83.51 213	49.48 148	76.24 335	48.60 300	73.46 254	84.14 206

fmvsm_s_conf0.5_n_7		69.54 181	69.67 156	69.15 279	73.47 319	51.41 221	70.35 335	73.34 303	57.05 196	68.41 184	85.83 155	49.86 143	72.84 351	71.86 84	76.83 203	83.19 242

EGC-MVSNET		42.47 423	38.48 431	54.46 414	74.33 301	48.73 282	70.33 336	51.10 447	0.03 484	0.18 485	67.78 436	13.28 458	66.49 396	18.91 467	50.36 443	48.15 464

MVSTER		67.16 244	65.58 257	71.88 203	70.37 379	49.70 260	70.25 337	78.45 208	51.52 314	69.16 175	80.37 284	38.45 294	82.50 194	60.19 198	71.46 287	83.44 235

reproduce_monomvs		62.56 309	61.20 319	66.62 308	70.62 373	44.30 334	70.13 338	73.13 310	54.78 260	61.13 330	76.37 365	25.63 428	75.63 338	58.75 217	60.29 406	79.93 316

XVG-OURS		68.76 204	67.37 214	72.90 178	74.32 302	57.22 99	70.09 339	78.81 190	55.24 243	67.79 209	85.81 158	36.54 318	78.28 287	62.04 182	75.74 219	83.19 242

HY-MVS	56.14 13	64.55 286	63.89 275	66.55 309	74.73 288	41.02 367	69.96 340	74.43 285	49.29 345	61.66 324	80.92 276	47.43 180	76.68 328	44.91 337	71.69 284	81.94 273

AllTest		57.08 363	54.65 377	64.39 344	71.44 359	49.03 273	69.92 341	67.30 356	45.97 391	47.16 440	79.77 297	17.47 446	67.56 389	33.65 416	59.16 410	76.57 363

testing3		56.54 367	55.92 369	58.41 390	77.52 213	27.93 461	69.72 342	56.36 431	54.75 262	58.63 361	77.80 337	20.88 444	71.75 361	25.31 458	62.25 391	75.53 374

sc_t1		59.76 341	57.84 352	65.54 329	74.87 282	42.95 350	69.61 343	64.16 387	48.90 350	58.68 358	77.12 347	28.19 406	72.35 355	43.75 349	55.28 425	81.31 287

FE-MVSNET3		64.34 290	63.57 282	66.66 307	72.44 340	40.74 373	69.60 344	76.80 245	53.21 290	61.73 323	77.92 332	41.92 250	77.68 302	46.23 320	72.25 278	81.57 278

thres200		62.20 316	61.16 320	65.34 336	75.38 271	39.99 377	69.60 344	69.29 344	55.64 233	61.87 320	76.99 350	37.07 314	78.96 279	31.28 436	73.28 258	77.06 357

tpmrst		58.24 354	58.70 342	56.84 401	66.97 414	34.32 431	69.57 346	61.14 412	47.17 379	58.58 362	71.60 411	41.28 264	60.41 421	49.20 295	62.84 385	75.78 371

PatchmatchNet		59.84 340	58.24 346	64.65 342	73.05 326	46.70 309	69.42 347	62.18 407	47.55 372	58.88 356	71.96 408	34.49 337	69.16 376	42.99 356	63.60 378	78.07 340
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
WB-MVSnew		59.66 343	59.69 332	59.56 378	75.19 275	35.78 422	69.34 348	64.28 384	46.88 382	61.76 322	75.79 373	40.61 272	65.20 403	32.16 424	71.21 289	77.70 347

GG-mvs-BLEND				62.34 361	71.36 363	37.04 408	69.20 349	57.33 428		54.73 400	65.48 447	30.37 382	77.82 297	34.82 412	74.93 230	72.17 413

HyFIR lowres test		65.67 269	63.01 293	73.67 152	79.97 131	55.65 129	69.07 350	75.52 264	42.68 419	63.53 290	77.95 330	40.43 273	81.64 209	46.01 323	71.91 281	83.73 225

UWE-MVS		60.18 337	59.78 331	61.39 370	77.67 204	33.92 436	69.04 351	63.82 390	48.56 354	64.27 282	77.64 342	27.20 415	70.40 371	33.56 419	76.24 209	79.83 320

test_post1							68.67 352				3.64 482	32.39 372	69.49 375	44.17 340

tt0320		58.59 350	56.81 360	63.92 349	75.46 268	41.32 365	68.63 353	64.06 388	47.05 380	56.19 383	74.19 390	30.34 383	71.36 362	39.92 378	55.45 424	79.09 329

testing222		62.29 315	61.31 315	65.25 338	77.87 195	38.53 391	68.34 354	66.31 368	56.37 215	63.15 297	77.58 343	28.47 403	76.18 337	37.04 396	76.65 207	81.05 296

tt0320-xc		58.33 353	56.41 365	64.08 347	75.79 259	41.34 364	68.30 355	62.72 400	47.90 367	56.29 382	74.16 392	28.53 402	71.04 365	41.50 370	52.50 437	79.88 318

Test_1112_low_res		62.32 313	61.77 308	64.00 348	79.08 153	39.53 383	68.17 356	70.17 332	43.25 414	59.03 355	79.90 294	44.08 224	71.24 364	43.79 347	68.42 339	81.25 288

tpm cat1		59.25 347	56.95 357	66.15 318	72.19 345	46.96 307	68.09 357	65.76 371	40.03 435	57.81 369	70.56 418	38.32 297	74.51 343	38.26 388	61.50 397	77.00 359

ppachtmachnet_test		58.06 357	55.38 373	66.10 320	69.51 393	48.99 276	68.01 358	66.13 370	44.50 402	54.05 407	70.74 417	32.09 375	72.34 356	36.68 401	56.71 421	76.99 361

tpmvs		58.47 351	56.95 357	63.03 358	70.20 381	41.21 366	67.90 359	67.23 359	49.62 340	54.73 400	70.84 416	34.14 340	76.24 335	36.64 402	61.29 398	71.64 418

testing91		64.46 287	63.80 278	66.47 310	78.43 173	40.06 376	67.63 360	69.59 339	59.06 151	63.18 295	78.05 328	34.05 341	76.99 318	48.30 303	75.87 217	82.37 266

CL-MVSNet_self_test		61.53 325	60.94 323	63.30 354	68.95 400	36.93 409	67.60 361	72.80 313	55.67 231	59.95 342	76.63 357	45.01 216	72.22 358	39.74 380	62.09 393	80.74 302

testing11		62.81 307	61.90 307	65.54 329	78.38 174	40.76 372	67.59 362	66.78 364	55.48 236	60.13 337	77.11 348	31.67 377	76.79 323	45.53 330	74.45 234	79.06 330

test_vis1_n_1920		58.86 348	59.06 338	58.25 391	63.76 433	43.14 347	67.49 363	66.36 367	40.22 433	65.89 249	71.95 409	31.04 378	59.75 425	59.94 201	64.90 366	71.85 416

tpm		57.34 361	58.16 347	54.86 411	71.80 352	34.77 426	67.47 364	56.04 435	48.20 362	60.10 338	76.92 351	37.17 311	53.41 454	40.76 372	65.01 365	76.40 365

testing99		64.05 292	63.29 290	66.34 312	78.17 186	39.76 380	67.33 365	68.00 353	58.60 162	63.03 298	78.10 327	32.57 370	76.94 320	48.22 304	75.58 221	82.34 267

FE-MVSNET		55.16 383	53.75 389	59.41 380	65.29 427	33.20 440	67.21 366	66.21 369	48.39 360	49.56 434	73.53 397	29.03 397	72.51 353	30.38 440	54.10 431	72.52 405

gg-mvs-nofinetune		57.86 358	56.43 364	62.18 362	72.62 333	35.35 423	66.57 367	56.33 432	50.65 327	57.64 370	57.10 459	30.65 380	76.36 333	37.38 393	78.88 160	74.82 385

TinyColmap		54.14 386	51.72 398	61.40 369	66.84 416	41.97 357	66.52 368	68.51 349	44.81 398	42.69 454	75.77 374	11.66 462	72.94 350	31.96 426	56.77 420	69.27 439

pmmvs5		56.47 369	55.68 371	58.86 387	61.41 445	36.71 411	66.37 369	62.75 399	40.38 432	53.70 409	76.62 358	34.56 335	67.05 392	40.02 376	65.27 363	72.83 401

CHOSEN 1792x2688		65.08 279	62.84 295	71.82 205	81.49 100	56.26 115	66.32 370	74.20 293	40.53 431	63.16 296	78.65 319	41.30 262	77.80 298	45.80 325	74.09 238	81.40 283

our_test_3		56.49 368	54.42 380	62.68 360	69.51 393	45.48 323	66.08 371	61.49 410	44.11 408	50.73 428	69.60 428	33.05 354	68.15 381	38.38 387	56.86 418	74.40 390

mvs5depth		55.64 377	53.81 388	61.11 373	59.39 454	40.98 371	65.89 372	68.28 351	50.21 332	58.11 367	75.42 380	17.03 448	67.63 388	43.79 347	46.21 449	74.73 387

PM-MVS		52.33 397	50.19 406	58.75 388	62.10 442	45.14 326	65.75 373	40.38 470	43.60 410	53.52 413	72.65 401	9.16 470	65.87 401	50.41 284	54.18 430	65.24 447

D2MVS		62.30 314	60.29 329	68.34 289	66.46 420	48.42 288	65.70 374	73.42 302	47.71 370	58.16 366	75.02 383	30.51 381	77.71 301	53.96 256	71.68 285	78.90 334

MIMVSNet1		55.17 382	54.31 383	57.77 398	70.03 385	32.01 446	65.68 375	64.81 379	49.19 346	46.75 443	76.00 369	25.53 429	64.04 407	28.65 447	62.13 392	77.26 355

PatchMatch-RL		56.25 372	54.55 379	61.32 371	77.06 232	56.07 119	65.57 376	54.10 441	44.13 407	53.49 415	71.27 415	25.20 430	66.78 394	36.52 404	63.66 377	61.12 449

Syy-MVS		56.00 374	56.23 367	55.32 408	74.69 289	26.44 467	65.52 377	57.49 426	50.97 324	56.52 379	72.18 404	39.89 277	68.09 382	24.20 459	64.59 371	71.44 422

myMVS_eth3d		54.86 385	54.61 378	55.61 407	74.69 289	27.31 464	65.52 377	57.49 426	50.97 324	56.52 379	72.18 404	21.87 442	68.09 382	27.70 450	64.59 371	71.44 422

test-LLR		58.15 356	58.13 349	58.22 392	68.57 403	44.80 328	65.46 379	57.92 423	50.08 334	55.44 389	69.82 425	32.62 367	57.44 437	49.66 291	73.62 248	72.41 409

TESTMET0.1,1		55.28 380	54.90 376	56.42 403	66.56 418	43.67 341	65.46 379	56.27 433	39.18 438	53.83 408	67.44 437	24.21 434	55.46 448	48.04 306	73.11 262	70.13 433

test-mter		56.42 370	55.82 370	58.22 392	68.57 403	44.80 328	65.46 379	57.92 423	39.94 436	55.44 389	69.82 425	21.92 439	57.44 437	49.66 291	73.62 248	72.41 409

SDMVSNet		68.03 222	68.10 198	67.84 292	77.13 227	48.72 283	65.32 382	79.10 181	58.02 174	65.08 267	82.55 234	47.83 170	73.40 348	63.92 156	73.92 241	81.41 281

CR-MVSNet		59.91 339	57.90 351	65.96 322	69.96 386	52.07 210	65.31 383	63.15 397	42.48 420	59.36 350	74.84 384	35.83 323	70.75 367	45.50 331	64.65 369	75.06 379

RPMNet		61.53 325	58.42 344	70.86 243	69.96 386	52.07 210	65.31 383	81.36 133	43.20 415	59.36 350	70.15 423	35.37 327	85.47 118	36.42 405	64.65 369	75.06 379

USDC		56.35 371	54.24 384	62.69 359	64.74 429	40.31 374	65.05 385	73.83 298	43.93 409	47.58 438	77.71 341	15.36 455	75.05 341	38.19 389	61.81 395	72.70 402

MDTV_nov1_ep13			57.00 356		72.73 331	38.26 394	65.02 386	64.73 381	44.74 399	55.46 388	72.48 402	32.61 369	70.47 368	37.47 391	67.75 345

ETVMVS		59.51 346	58.81 339	61.58 367	77.46 215	34.87 424	64.94 387	59.35 417	54.06 274	61.08 331	76.67 356	29.54 392	71.87 360	32.16 424	74.07 239	78.01 345

CMPMVS	42.80 21	57.81 359	55.97 368	63.32 353	60.98 449	47.38 304	64.66 388	69.50 341	32.06 449	46.83 442	77.80 337	29.50 394	71.36 362	48.68 299	73.75 244	71.21 425
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
WBMVS		60.54 333	60.61 327	60.34 376	78.00 192	35.95 420	64.55 389	64.89 378	49.63 339	63.39 292	78.70 316	33.85 346	67.65 387	42.10 363	70.35 304	77.43 351

IMVS_0404		64.63 284	64.22 272	65.88 325	77.06 232	49.73 256	64.40 390	78.60 197	52.70 296	53.16 416	82.58 229	34.82 333	65.16 404	59.20 210	75.46 224	82.74 254

RPSCF		55.80 376	54.22 385	60.53 375	65.13 428	42.91 351	64.30 391	57.62 425	36.84 442	58.05 368	82.28 243	28.01 407	56.24 445	37.14 395	58.61 412	82.44 265

XXY-MVS		60.68 330	61.67 309	57.70 399	70.43 377	38.45 392	64.19 392	66.47 365	48.05 365	63.22 293	80.86 278	49.28 153	60.47 420	45.25 336	67.28 350	74.19 393

FMVSNet5		55.86 375	54.93 375	58.66 389	71.05 368	36.35 414	64.18 393	62.48 402	46.76 384	50.66 429	74.73 386	25.80 426	64.04 407	33.11 420	65.57 362	75.59 373

UBG		59.62 345	59.53 333	59.89 377	78.12 187	35.92 421	64.11 394	60.81 414	49.45 342	61.34 327	75.55 377	33.05 354	67.39 391	38.68 385	74.62 232	76.35 366

testing3-2		62.06 318	62.36 301	61.17 372	79.29 142	30.31 453	64.09 395	63.49 393	63.50 44	62.84 301	82.22 245	32.35 374	69.02 378	40.01 377	73.43 255	84.17 205

icg_test_0407_2		66.41 261	66.75 231	65.37 335	77.06 232	49.73 256	63.79 396	78.60 197	52.70 296	66.19 240	82.58 229	45.17 213	63.65 410	59.20 210	75.46 224	82.74 254

test_cas_vis1_n_1920		56.91 364	56.71 361	57.51 400	59.13 455	45.40 324	63.58 397	61.29 411	36.24 443	67.14 222	71.85 410	29.89 390	56.69 441	57.65 223	63.58 379	70.46 430

UWE-MVS-28		52.25 398	52.35 396	51.93 432	66.99 413	22.79 475	63.48 398	48.31 456	46.78 383	52.73 418	76.11 367	27.78 410	57.82 436	20.58 465	68.41 340	75.17 377

SCA		60.49 334	58.38 345	66.80 302	74.14 308	48.06 294	63.35 399	63.23 396	49.13 347	59.33 353	72.10 406	37.45 305	74.27 345	44.17 340	62.57 387	78.05 341

myMVS_eth3d28		60.66 331	61.04 321	59.51 379	77.32 219	31.58 448	63.11 400	63.87 389	59.00 152	60.90 333	78.26 325	32.69 365	66.15 399	36.10 407	78.13 179	80.81 300

Patchmtry		57.16 362	56.47 363	59.23 383	69.17 399	34.58 429	62.98 401	63.15 397	44.53 401	56.83 376	74.84 384	35.83 323	68.71 379	40.03 375	60.91 399	74.39 391

Anonymous20231206		55.10 384	55.30 374	54.48 413	69.81 391	33.94 435	62.91 402	62.13 408	41.08 427	55.18 394	75.65 375	32.75 362	56.59 443	30.32 441	67.86 343	72.91 399

sd_testset		64.46 287	64.45 270	64.51 343	77.13 227	42.25 355	62.67 403	72.11 319	58.02 174	65.08 267	82.55 234	41.22 267	69.88 374	47.32 310	73.92 241	81.41 281

MIMVSNet		57.35 360	57.07 355	58.22 392	74.21 305	37.18 404	62.46 404	60.88 413	48.88 351	55.29 393	75.99 371	31.68 376	62.04 416	31.87 427	72.35 274	75.43 376

dp		51.89 400	51.60 399	52.77 426	68.44 406	32.45 445	62.36 405	54.57 438	44.16 406	49.31 435	67.91 433	28.87 400	56.61 442	33.89 415	54.89 427	69.24 440

EPMVS		53.96 387	53.69 390	54.79 412	66.12 423	31.96 447	62.34 406	49.05 452	44.42 404	55.54 387	71.33 414	30.22 385	56.70 440	41.65 368	62.54 388	75.71 372

pmmvs3		44.92 418	41.95 425	53.86 416	52.58 464	43.55 342	62.11 407	46.90 462	26.05 460	40.63 456	60.19 455	11.08 467	57.91 435	31.83 431	46.15 450	60.11 450

test_vis1_n		49.89 409	48.69 411	53.50 420	53.97 459	37.38 403	61.53 408	47.33 460	28.54 454	59.62 348	67.10 441	13.52 457	52.27 458	49.07 296	57.52 415	70.84 428

PVSNet	50.76 19	58.40 352	57.39 353	61.42 368	75.53 266	44.04 338	61.43 409	63.45 394	47.04 381	56.91 375	73.61 396	27.00 418	64.76 405	39.12 383	72.40 273	75.47 375

LCM-MVSNet-Re		61.88 322	61.35 314	63.46 352	74.58 294	31.48 449	61.42 410	58.14 422	58.71 159	53.02 417	79.55 304	43.07 235	76.80 322	45.69 326	77.96 182	82.11 272

test20.03		53.87 389	54.02 386	53.41 422	61.47 444	28.11 460	61.30 411	59.21 418	51.34 319	52.09 420	77.43 344	33.29 353	58.55 432	29.76 443	60.27 407	73.58 397

MDTV_nov1_ep13_2view						25.89 469	61.22 412		40.10 434	51.10 423		32.97 357		38.49 386		78.61 336

PMMVS		53.96 387	53.26 393	56.04 404	62.60 440	50.92 228	61.17 413	56.09 434	32.81 448	53.51 414	66.84 442	34.04 342	59.93 424	44.14 342	68.18 341	57.27 457

test_fmvs1_n		51.37 402	50.35 405	54.42 415	52.85 462	37.71 400	61.16 414	51.93 443	28.15 455	63.81 288	69.73 427	13.72 456	53.95 452	51.16 279	60.65 403	71.59 419

WTY-MVS		59.75 342	60.39 328	57.85 397	72.32 343	37.83 398	61.05 415	64.18 385	45.95 393	61.91 319	79.11 313	47.01 189	60.88 419	42.50 360	69.49 324	74.83 384

dmvs_testset		50.16 407	51.90 397	44.94 443	66.49 419	11.78 483	61.01 416	51.50 445	51.17 322	50.30 432	67.44 437	39.28 284	60.29 422	22.38 462	57.49 416	62.76 448

Patchmatch-RL test		58.16 355	55.49 372	66.15 318	67.92 409	48.89 280	60.66 417	51.07 448	47.86 369	59.36 350	62.71 453	34.02 343	72.27 357	56.41 232	59.40 409	77.30 353

test_fmvs1		51.32 404	50.48 404	53.81 417	53.57 460	37.51 402	60.63 418	51.16 446	28.02 457	63.62 289	69.23 430	16.41 451	53.93 453	51.01 280	60.70 402	69.99 434

LTVRE_ROB	55.42 16	63.15 304	61.23 318	68.92 281	76.57 248	47.80 297	59.92 419	76.39 248	54.35 270	58.67 359	82.46 239	29.44 395	81.49 214	42.12 362	71.14 290	77.46 350
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		60.57 332	61.39 313	58.12 395	74.29 303	32.63 443	59.52 420	65.53 374	59.90 132	62.45 313	79.75 299	41.96 247	63.90 409	39.47 381	69.65 323	77.84 346

test0.0.03 1		53.32 394	53.59 391	52.50 428	62.81 439	29.45 455	59.51 421	54.11 440	50.08 334	54.40 404	74.31 389	32.62 367	55.92 446	30.50 439	63.95 376	72.15 414

UnsupCasMVSNet_eth		53.16 396	52.47 394	55.23 409	59.45 453	33.39 439	59.43 422	69.13 345	45.98 390	50.35 431	72.32 403	29.30 396	58.26 434	42.02 365	44.30 453	74.05 394

MVS-HIRNet		45.52 417	44.48 419	48.65 437	68.49 405	34.05 434	59.41 423	44.50 465	27.03 458	37.96 465	50.47 467	26.16 424	64.10 406	26.74 455	59.52 408	47.82 466

testgi		51.90 399	52.37 395	50.51 435	60.39 452	23.55 474	58.42 424	58.15 421	49.03 348	51.83 421	79.21 312	22.39 437	55.59 447	29.24 446	62.64 386	72.40 411

dmvs_re		56.77 366	56.83 359	56.61 402	69.23 397	41.02 367	58.37 425	64.18 385	50.59 329	57.45 372	71.42 412	35.54 325	58.94 430	37.23 394	67.45 348	69.87 435

PatchT		53.17 395	53.44 392	52.33 429	68.29 407	25.34 471	58.21 426	54.41 439	44.46 403	54.56 402	69.05 431	33.32 352	60.94 418	36.93 397	61.76 396	70.73 429

WB-MVS		43.26 420	43.41 420	42.83 447	63.32 436	10.32 485	58.17 427	45.20 463	45.42 395	40.44 458	67.26 440	34.01 344	58.98 429	11.96 476	24.88 470	59.20 451

sss		56.17 373	56.57 362	54.96 410	66.93 415	36.32 416	57.94 428	61.69 409	41.67 423	58.64 360	75.32 382	38.72 292	56.25 444	42.04 364	66.19 358	72.31 412

ttmdpeth		45.56 416	42.95 421	53.39 423	52.33 465	29.15 456	57.77 429	48.20 457	31.81 450	49.86 433	77.21 346	8.69 471	59.16 428	27.31 451	33.40 467	71.84 417

test_fmvs2		48.69 411	47.49 416	52.29 430	48.63 469	33.06 442	57.76 430	48.05 458	25.71 461	59.76 346	69.60 428	11.57 463	52.23 459	49.45 294	56.86 418	71.58 420

KD-MVS_self_test		55.22 381	53.89 387	59.21 384	57.80 458	27.47 463	57.75 431	74.32 287	47.38 374	50.90 425	70.00 424	28.45 404	70.30 372	40.44 373	57.92 414	79.87 319

UnsupCasMVSNet_bld		50.07 408	48.87 409	53.66 418	60.97 450	33.67 437	57.62 432	64.56 382	39.47 437	47.38 439	64.02 451	27.47 412	59.32 426	34.69 413	43.68 454	67.98 443

mamv4		56.85 365	58.00 350	53.43 421	72.46 339	54.47 149	57.56 433	54.74 436	38.81 439	57.42 373	79.45 307	47.57 176	38.70 474	60.88 193	53.07 434	67.11 444

SSC-MVS		41.96 425	41.99 424	41.90 448	62.46 441	9.28 487	57.41 434	44.32 466	43.38 412	38.30 464	66.45 443	32.67 366	58.42 433	10.98 477	21.91 473	57.99 455

ANet_high		41.38 426	37.47 433	53.11 424	39.73 480	24.45 472	56.94 435	69.69 336	47.65 371	26.04 472	52.32 462	12.44 460	62.38 415	21.80 463	10.61 481	72.49 406

MDA-MVSNet-bldmvs		53.87 389	50.81 402	63.05 357	66.25 421	48.58 286	56.93 436	63.82 390	48.09 364	41.22 455	70.48 421	30.34 383	68.00 385	34.24 414	45.92 451	72.57 404

test123		4.73 452	6.30 455	0.02 467	0.01 490	0.01 492	56.36 437	0.00 491	0.01 485	0.04 486	0.21 486	0.01 489	0.00 486	0.03 486	0.00 484	0.04 482

miper_lstm_enhance		62.03 319	60.88 324	65.49 332	66.71 417	46.25 312	56.29 438	75.70 259	50.68 326	61.27 328	75.48 379	40.21 274	68.03 384	56.31 233	65.25 364	82.18 269

KD-MVS_2432*1600		53.45 391	51.50 400	59.30 381	62.82 437	37.14 405	55.33 439	71.79 322	47.34 376	55.09 395	70.52 419	21.91 440	70.45 369	35.72 409	42.97 455	70.31 431

miper_refine_blended		53.45 391	51.50 400	59.30 381	62.82 437	37.14 405	55.33 439	71.79 322	47.34 376	55.09 395	70.52 419	21.91 440	70.45 369	35.72 409	42.97 455	70.31 431

LF4IMVS		42.95 421	42.26 423	45.04 441	48.30 470	32.50 444	54.80 441	48.49 454	28.03 456	40.51 457	70.16 422	9.24 469	43.89 469	31.63 432	49.18 447	58.72 453

PMVS	28.69 22	36.22 433	33.29 438	45.02 442	36.82 482	35.98 419	54.68 442	48.74 453	26.31 459	21.02 475	51.61 464	2.88 483	60.10 423	9.99 480	47.58 448	38.99 473
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVStest1		42.65 422	39.29 429	52.71 427	47.26 472	34.58 429	54.41 443	50.84 451	23.35 463	39.31 463	74.08 393	12.57 459	55.09 449	23.32 460	28.47 469	68.47 442

PVSNet_0	43.31 20	47.46 415	45.64 418	52.92 425	67.60 411	44.65 330	54.06 444	54.64 437	41.59 424	46.15 445	58.75 456	30.99 379	58.66 431	32.18 423	24.81 471	55.46 459

testmvs		4.52 453	6.03 456	0.01 468	0.01 490	0.00 493	53.86 445	0.00 491	0.01 485	0.04 486	0.27 485	0.00 490	0.00 486	0.04 485	0.00 484	0.03 483

test_fmvs3		44.30 419	42.55 422	49.55 436	42.83 474	27.15 466	53.03 446	44.93 464	22.03 469	53.69 411	64.94 448	4.21 478	49.63 461	47.47 307	49.82 444	71.88 415

APD_test1		37.39 432	34.94 435	44.72 444	48.88 468	33.19 441	52.95 447	44.00 467	19.49 470	27.28 471	58.59 457	3.18 482	52.84 456	18.92 466	41.17 458	48.14 465

dongtai		34.52 435	34.94 435	33.26 457	61.06 448	16.00 482	52.79 448	23.78 483	40.71 430	39.33 462	48.65 471	16.91 450	48.34 463	12.18 475	19.05 475	35.44 474

YYNet1		50.73 405	48.96 407	56.03 405	61.10 447	41.78 359	51.94 449	56.44 430	40.94 429	44.84 447	67.80 435	30.08 388	55.08 450	36.77 398	50.71 441	71.22 424

MDA-MVSNet_test_wron		50.71 406	48.95 408	56.00 406	61.17 446	41.84 358	51.90 450	56.45 429	40.96 428	44.79 448	67.84 434	30.04 389	55.07 451	36.71 400	50.69 442	71.11 427

kuosan		29.62 442	30.82 441	26.02 462	52.99 461	16.22 481	51.09 451	22.71 484	33.91 447	33.99 466	40.85 472	15.89 453	33.11 479	7.59 483	18.37 476	28.72 476

ADS-MVSNet2		51.33 403	48.76 410	59.07 386	66.02 424	44.60 331	50.90 452	59.76 416	36.90 440	50.74 426	66.18 445	26.38 421	63.11 412	27.17 452	54.76 428	69.50 437

ADS-MVSNet		48.48 412	47.77 413	50.63 434	66.02 424	29.92 454	50.90 452	50.87 450	36.90 440	50.74 426	66.18 445	26.38 421	52.47 457	27.17 452	54.76 428	69.50 437

mamba_0408		67.78 230	65.42 259	74.85 103	78.65 164	53.46 171	50.83 454	79.09 182	53.75 281	68.14 192	83.83 202	41.79 254	86.56 81	56.58 229	76.11 211	84.54 190

SSM_04072		64.98 280	65.42 259	63.68 350	78.65 164	53.46 171	50.83 454	79.09 182	53.75 281	68.14 192	83.83 202	41.79 254	53.03 455	56.58 229	76.11 211	84.54 190

FPMVS		42.18 424	41.11 426	45.39 440	58.03 457	41.01 369	49.50 456	53.81 442	30.07 452	33.71 467	64.03 449	11.69 461	52.08 460	14.01 471	55.11 426	43.09 468

N_pmnet		39.35 430	40.28 427	36.54 454	63.76 433	1.62 491	49.37 457	0.76 490	34.62 446	43.61 452	66.38 444	26.25 423	42.57 470	26.02 457	51.77 438	65.44 446

new-patchmatchnet		47.56 414	47.73 414	47.06 438	58.81 456	9.37 486	48.78 458	59.21 418	43.28 413	44.22 450	68.66 432	25.67 427	57.20 439	31.57 434	49.35 446	74.62 389

test_vis1_rt		41.35 427	39.45 428	47.03 439	46.65 473	37.86 397	47.76 459	38.65 471	23.10 465	44.21 451	51.22 465	11.20 466	44.08 468	39.27 382	53.02 435	59.14 452

JIA-IIPM		51.56 401	47.68 415	63.21 355	64.61 430	50.73 233	47.71 460	58.77 420	42.90 417	48.46 437	51.72 463	24.97 431	70.24 373	36.06 408	53.89 432	68.64 441

ambc				65.13 339	63.72 435	37.07 407	47.66 461	78.78 192		54.37 405	71.42 412	11.24 465	80.94 231	45.64 327	53.85 433	77.38 352

testf1		31.46 440	28.89 444	39.16 450	41.99 477	28.78 458	46.45 462	37.56 472	14.28 477	21.10 473	48.96 468	1.48 486	47.11 464	13.63 472	34.56 464	41.60 469

APD_test2		31.46 440	28.89 444	39.16 450	41.99 477	28.78 458	46.45 462	37.56 472	14.28 477	21.10 473	48.96 468	1.48 486	47.11 464	13.63 472	34.56 464	41.60 469

Patchmatch-test		49.08 410	48.28 412	51.50 433	64.40 431	30.85 452	45.68 464	48.46 455	35.60 444	46.10 446	72.10 406	34.47 338	46.37 466	27.08 454	60.65 403	77.27 354

DSMNet-mixed		39.30 431	38.72 430	41.03 449	51.22 466	19.66 478	45.53 465	31.35 477	15.83 476	39.80 460	67.42 439	22.19 438	45.13 467	22.43 461	52.69 436	58.31 454

LCM-MVSNet		40.30 428	35.88 434	53.57 419	42.24 475	29.15 456	45.21 466	60.53 415	22.23 468	28.02 470	50.98 466	3.72 480	61.78 417	31.22 437	38.76 461	69.78 436

new_pmnet		34.13 436	34.29 437	33.64 456	52.63 463	18.23 480	44.43 467	33.90 476	22.81 466	30.89 469	53.18 461	10.48 468	35.72 478	20.77 464	39.51 459	46.98 467

mvsany_test1		39.38 429	38.16 432	43.02 446	49.05 467	34.28 432	44.16 468	25.94 481	22.74 467	46.57 444	62.21 454	23.85 435	41.16 473	33.01 421	35.91 463	53.63 460

E-PMN		23.77 444	22.73 448	26.90 460	42.02 476	20.67 477	42.66 469	35.70 474	17.43 472	10.28 482	25.05 478	6.42 473	42.39 471	10.28 479	14.71 478	17.63 477

EMVS		22.97 445	21.84 449	26.36 461	40.20 479	19.53 479	41.95 470	34.64 475	17.09 473	9.73 483	22.83 479	7.29 472	42.22 472	9.18 481	13.66 479	17.32 478

test_vis3_rt		32.09 438	30.20 443	37.76 453	35.36 484	27.48 462	40.60 471	28.29 480	16.69 474	32.52 468	40.53 473	1.96 484	37.40 476	33.64 418	42.21 457	48.39 463

CHOSEN 280x420		47.83 413	46.36 417	52.24 431	67.37 412	49.78 255	38.91 472	43.11 468	35.00 445	43.27 453	63.30 452	28.95 398	49.19 462	36.53 403	60.80 401	57.76 456

mvsany_test3		32.62 437	30.57 442	38.77 452	36.16 483	24.20 473	38.10 473	20.63 485	19.14 471	40.36 459	57.43 458	5.06 475	36.63 477	29.59 445	28.66 468	55.49 458

test_f		31.86 439	31.05 440	34.28 455	32.33 486	21.86 476	32.34 474	30.46 478	16.02 475	39.78 461	55.45 460	4.80 476	32.36 480	30.61 438	37.66 462	48.64 462

PMMVS2		27.40 443	25.91 446	31.87 459	39.46 481	6.57 488	31.17 475	28.52 479	23.96 462	20.45 476	48.94 470	4.20 479	37.94 475	16.51 468	19.97 474	51.09 461

wuyk23d		13.32 449	12.52 452	15.71 464	47.54 471	26.27 468	31.06 476	1.98 489	4.93 481	5.18 484	1.94 484	0.45 488	18.54 483	6.81 484	12.83 480	2.33 481

Gipuma		34.77 434	31.91 439	43.33 445	62.05 443	37.87 396	20.39 477	67.03 361	23.23 464	18.41 477	25.84 477	4.24 477	62.73 413	14.71 470	51.32 440	29.38 475
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVE	17.77 23	21.41 446	17.77 451	32.34 458	34.34 485	25.44 470	16.11 478	24.11 482	11.19 479	13.22 479	31.92 475	1.58 485	30.95 481	10.47 478	17.03 477	40.62 472
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
tmp_tt		9.43 450	11.14 453	4.30 466	2.38 489	4.40 489	13.62 479	16.08 487	0.39 483	15.89 478	13.06 480	15.80 454	5.54 485	12.63 474	10.46 482	2.95 480

test_method		19.68 447	18.10 450	24.41 463	13.68 488	3.11 490	12.06 480	42.37 469	2.00 482	11.97 480	36.38 474	5.77 474	29.35 482	15.06 469	23.65 472	40.76 471

mmdepth		0.00 455	0.00 458	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	0.00 487	0.00 490	0.00 486	0.00 487	0.00 484	0.00 484

monomultidepth		0.00 455	0.00 458	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	0.00 487	0.00 490	0.00 486	0.00 487	0.00 484	0.00 484

test_blank		0.00 455	0.00 458	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	0.00 487	0.00 490	0.00 486	0.00 487	0.00 484	0.00 484

uanet_test		0.00 455	0.00 458	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	0.00 487	0.00 490	0.00 486	0.00 487	0.00 484	0.00 484

DCPMVS		0.00 455	0.00 458	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	0.00 487	0.00 490	0.00 486	0.00 487	0.00 484	0.00 484

cdsmvs_eth3d_5k		17.50 448	23.34 447	0.00 469	0.00 492	0.00 493	0.00 481	78.63 196	0.00 487	0.00 488	82.18 246	49.25 154	0.00 486	0.00 487	0.00 484	0.00 484

pcd_1.5k_mvsjas		3.92 454	5.23 457	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	0.00 487	47.05 186	0.00 486	0.00 487	0.00 484	0.00 484

sosnet-low-res		0.00 455	0.00 458	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	0.00 487	0.00 490	0.00 486	0.00 487	0.00 484	0.00 484

sosnet		0.00 455	0.00 458	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	0.00 487	0.00 490	0.00 486	0.00 487	0.00 484	0.00 484

uncertanet		0.00 455	0.00 458	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	0.00 487	0.00 490	0.00 486	0.00 487	0.00 484	0.00 484

Regformer		0.00 455	0.00 458	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	0.00 487	0.00 490	0.00 486	0.00 487	0.00 484	0.00 484

ab-mvs-re		6.49 451	8.65 454	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	77.89 335	0.00 490	0.00 486	0.00 487	0.00 484	0.00 484

uanet		0.00 455	0.00 458	0.00 469	0.00 492	0.00 493	0.00 481	0.00 491	0.00 487	0.00 488	0.00 487	0.00 490	0.00 486	0.00 487	0.00 484	0.00 484

WAC-MVS						27.31 464								27.77 449

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 49

PC_three_1452									55.09 247	84.46 4	89.84 52	66.68 5	89.41 22	74.24 61	91.38 2	88.42 26

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 49

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					0.00 492

eth-test					0.00 492

ZD-MVS					86.64 21	60.38 45		82.70 110	57.95 178	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	53.93 277	84.64 3				79.07 13	90.87 5	88.37 28

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 58

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 42

GSMVS																78.05 341

test_part2					87.58 9	60.47 42				83.42 15

sam_mvs1												34.74 334				78.05 341

sam_mvs												33.43 351

MTGPA								80.97 151

test_post											3.55 483	33.90 345	66.52 395

patchmatchnet-post											64.03 449	34.50 336	74.27 345

gm-plane-assit					71.40 362	41.72 362			48.85 352		73.31 398		82.48 196	48.90 298

test9_res														75.28 54	88.31 36	83.81 219

agg_prior2														73.09 72	87.93 44	84.33 197

agg_prior					85.04 54	59.96 50		81.04 149		74.68 72			84.04 146

TestCases				64.39 344	71.44 359	49.03 273		67.30 356	45.97 391	47.16 440	79.77 297	17.47 446	67.56 389	33.65 416	59.16 410	76.57 363

test_prior				76.69 65	84.20 65	57.27 98		84.88 44					86.43 88			86.38 108

新几何1				70.76 245	85.66 42	61.13 30		66.43 366	44.68 400	70.29 150	86.64 121	41.29 263	75.23 340	49.72 290	81.75 110	75.93 369

旧先验1					83.04 78	53.15 181		67.52 355			87.85 86	44.08 224			80.76 119	78.03 344

原ACMM1				74.69 106	85.39 48	59.40 59		83.42 84	51.47 316	70.27 151	86.61 125	48.61 162	86.51 86	53.85 257	87.96 43	78.16 339

testdata2													72.18 359	46.95 316

segment_acmp												54.23 71

testdata				64.66 341	81.52 98	52.93 186		65.29 376	46.09 389	73.88 86	87.46 93	38.08 301	66.26 398	53.31 262	78.48 173	74.78 386

test12				77.76 50	84.52 62	58.41 83		83.36 87		72.93 112		54.61 68	88.05 43		88.12 38	86.81 91

plane_prior7					81.41 101	55.96 121

plane_prior6					81.20 108	56.24 116						45.26 211

plane_prior5								84.01 57					87.21 63	68.16 107	80.58 123	84.65 188

plane_prior4											86.10 144

plane_prior3						56.09 118			63.92 38	69.27 171

plane_prior1					81.27 106

n2								0.00 491

nn								0.00 491

door-mid								47.19 461

lessismore_v0				69.91 262	71.42 361	47.80 297		50.90 449		50.39 430	75.56 376	27.43 414	81.33 218	45.91 324	34.10 466	80.59 303

LGP-MVS_train				75.76 83	80.22 123	57.51 96		83.40 85	61.32 90	66.67 232	87.33 99	39.15 287	86.59 79	67.70 114	77.30 196	83.19 242

test11								83.47 82

door								47.60 459

HQP5-MVS						54.94 143

BP-MVS														67.04 124

HQP4-MVS										67.85 202			86.93 71			84.32 198

HQP3-MVS								83.90 62							80.35 127

HQP2-MVS												45.46 205

NP-MVS					80.98 111	56.05 120					85.54 165

ACMMP++_ref															74.07 239

ACMMP++															72.16 279

Test By Simon												48.33 165

ITE_SJBPF				62.09 363	66.16 422	44.55 333		64.32 383	47.36 375	55.31 392	80.34 286	19.27 445	62.68 414	36.29 406	62.39 389	79.04 331

DeepMVS_CX				12.03 465	17.97 487	10.91 484		10.60 488	7.46 480	11.07 481	28.36 476	3.28 481	11.29 484	8.01 482	9.74 483	13.89 479

High-resolution multi-view benchmark