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 28

FOURS1					86.12 37	60.82 37	88.18 1	83.61 80	60.87 104	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 94
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	85.45 158
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 62

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 36

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 36

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 72	90.06 14	78.42 23	89.02 27	87.69 58
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 85	62.44 69	72.68 120	90.50 31	48.18 168	87.34 58	73.59 69	85.71 66	84.76 189

MED-MVS test				79.09 23	85.30 50	59.25 64	86.84 11	85.86 21	60.95 101	83.65 12	90.57 25		89.91 16	77.02 34	89.43 22	88.10 41

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 41

TestfortrainingZip a		79.97 11	80.40 8	78.69 34	85.30 50	58.20 86	86.84 11	85.86 21	60.95 101	83.65 12	90.57 25	64.70 10	89.91 16	76.25 43	89.43 22	87.96 47

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 79	88.68 31	76.48 39	89.63 20	87.16 83

HPM-MVS++		79.88 12	80.14 12	79.10 21	88.17 1	64.80 1	86.59 16	83.70 76	65.37 13	78.78 28	90.64 22	58.63 28	87.24 59	79.00 14	90.37 14	85.26 170

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 38
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 93	88.35 35	74.02 65	87.05 51	86.13 125

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 99	90.58 24	49.90 144	88.21 38	73.78 67	87.03 52	86.29 122

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 95	90.56 29	49.80 147	88.24 37	74.02 65	87.03 52	86.32 118

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 44
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	17.08 491

MP-MVS		78.35 23	78.26 24	78.64 35	86.54 26	63.47 4	86.02 24	83.55 82	63.89 39	73.60 93	90.60 23	54.85 67	86.72 76	77.20 31	88.06 40	85.74 144
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	60.53 113	78.99 27	91.45 12	51.51 124	87.78 51	75.65 49	87.55 47	87.10 85

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	52.56 102	88.53 33	74.79 59	88.34 33	86.63 103

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	72.17 128	90.01 49	47.95 170	88.01 44	71.55 88	86.74 59	86.37 112

X-MVStestdata		70.21 161	67.28 220	79.00 26	86.32 30	62.62 11	85.83 27	83.92 60	64.55 25	72.17 128	6.49 486	47.95 170	88.01 44	71.55 88	86.74 59	86.37 112

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	67.80 210	89.24 60	42.03 248	89.38 23	64.07 154	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	82.28 117	62.90 57	71.77 133	90.26 39	46.61 195	86.55 84	71.71 86	85.66 67	84.97 181

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 92
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 41

SR-MVS		76.13 51	75.70 52	77.40 57	85.87 41	61.20 29	85.52 33	82.19 118	59.99 133	75.10 59	90.35 36	47.66 175	86.52 85	71.64 87	82.99 90	84.47 198

APD-MVS		78.02 26	78.04 26	77.98 45	86.44 28	60.81 38	85.52 33	84.36 51	60.61 111	79.05 26	90.30 38	55.54 60	88.32 36	73.48 70	87.03 52	84.83 185
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	69.80 164	89.74 55	45.43 209	87.16 65	72.01 81	82.87 95	85.14 172
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 61	89.18 25	74.19 63	87.34 50	86.38 110

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 84	79.16 25	90.75 21	57.96 29	87.09 68	77.08 33	90.18 15	87.87 50

reproduce-ours		76.90 38	76.58 38	77.87 47	83.99 66	60.46 43	84.75 38	83.34 90	60.22 127	77.85 36	91.42 14	50.67 136	87.69 53	72.46 76	84.53 74	85.46 156

our_new_method		76.90 38	76.58 38	77.87 47	83.99 66	60.46 43	84.75 38	83.34 90	60.22 127	77.85 36	91.42 14	50.67 136	87.69 53	72.46 76	84.53 74	85.46 156

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 83	73.06 111	88.88 66	53.72 85	89.06 27	68.27 103	88.04 41	87.42 70
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	81.64 127	68.35 2	75.77 50	90.38 34	53.98 77	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	82.90 108	59.65 140	77.31 39	91.43 13	49.62 149	87.24 59	71.99 82	83.75 85	85.14 172

SD-MVS		77.70 30	77.62 30	77.93 46	84.47 63	61.88 21	84.55 43	83.87 65	60.37 120	79.89 22	89.38 58	54.97 65	85.58 113	76.12 45	84.94 70	86.33 116
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 99	87.27 101	55.06 63	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 86

NormalMVS		76.26 48	75.74 51	77.83 49	82.75 84	59.89 52	84.36 46	83.21 97	64.69 22	74.21 80	87.40 94	49.48 150	86.17 96	68.04 111	87.55 47	87.42 70

SymmetryMVS		75.28 59	74.60 65	77.30 58	83.85 69	59.89 52	84.36 46	75.51 270	64.69 22	74.21 80	87.40 94	49.48 150	86.17 96	68.04 111	83.88 83	85.85 135

SR-MVS-dyc-post		74.57 69	73.90 78	76.58 70	83.49 72	59.87 54	84.29 48	81.36 135	58.07 174	73.14 106	90.07 43	44.74 219	85.84 107	68.20 104	81.76 108	84.03 210

RE-MVS-def			73.71 83		83.49 72	59.87 54	84.29 48	81.36 135	58.07 174	73.14 106	90.07 43	43.06 238		68.20 104	81.76 108	84.03 210

PHI-MVS		75.87 53	75.36 55	77.41 55	80.62 119	55.91 123	84.28 50	85.78 25	56.08 224	73.41 96	86.58 129	50.94 134	88.54 32	70.79 93	89.71 17	87.79 55

HQP_MVS		74.31 72	73.73 82	76.06 77	81.41 101	56.31 112	84.22 51	84.01 57	64.52 27	69.27 173	86.10 146	45.26 213	87.21 63	68.16 108	80.58 123	84.65 190

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 90	90.25 40	57.68 32	89.96 15	74.62 60	89.03 26	87.89 48
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	59.90 134	78.57 30	90.36 35	57.51 35	86.86 73	77.39 29	89.52 21

CPTT-MVS		72.78 104	72.08 111	74.87 102	84.88 61	61.41 26	84.15 54	77.86 222	55.27 244	67.51 216	88.08 79	41.93 251	81.85 208	69.04 102	80.01 132	81.35 288

TSAR-MVS + MP.		78.44 22	78.28 22	78.90 30	84.96 56	61.41 26	84.03 56	83.82 71	59.34 150	79.37 24	89.76 54	59.84 19	87.62 56	76.69 37	86.74 59	87.68 59
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
API-MVS		72.17 120	71.41 122	74.45 119	81.95 93	57.22 99	84.03 56	80.38 164	59.89 138	68.40 187	82.33 243	49.64 148	87.83 50	51.87 275	84.16 81	78.30 342

save fliter					86.17 34	61.30 28	83.98 58	79.66 174	59.00 154

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 80	71.49 140	86.03 149	53.83 81	86.36 91	67.74 115	86.91 56	88.19 38

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	52.51 103	88.39 34	79.34 9	90.52 13	86.78 95

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	72.77 119	87.25 105	53.13 94	87.93 46	71.97 83	85.57 68	86.66 101

APD-MVS_3200maxsize		74.96 61	74.39 68	76.67 67	82.20 88	58.24 85	83.67 62	83.29 94	58.41 168	73.71 91	90.14 41	45.62 202	85.99 103	69.64 97	82.85 96	85.78 138

HPM-MVS_fast		74.30 73	73.46 88	76.80 63	84.45 64	59.04 74	83.65 63	81.05 150	60.15 129	70.43 150	89.84 52	41.09 270	85.59 112	67.61 118	82.90 94	85.77 141

plane_prior						56.31 112	83.58 64		63.19 51						80.48 126

QAPM		70.05 165	68.81 177	73.78 145	76.54 251	53.43 174	83.23 65	83.48 83	52.89 296	65.90 250	86.29 140	41.55 262	86.49 87	51.01 282	78.40 178	81.42 282

MCST-MVS		77.48 32	77.45 31	77.54 52	86.67 20	58.36 84	83.22 66	86.93 5	56.91 202	74.91 65	88.19 75	59.15 26	87.68 55	73.67 68	87.45 49	86.57 104

EPNet		73.09 99	72.16 109	75.90 79	75.95 259	56.28 114	83.05 67	72.39 321	66.53 10	65.27 262	87.00 110	50.40 139	85.47 118	62.48 180	86.32 64	85.94 130
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 40

CSCG		76.92 37	76.75 35	77.41 55	83.96 68	59.60 56	82.95 69	86.50 14	60.78 107	75.27 55	84.83 175	60.76 18	86.56 81	67.86 114	87.87 45	86.06 127

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 76	76.41 48	91.51 11	52.47 105	86.78 75	80.66 4	89.64 19	87.80 54
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	73.09 110	89.97 50	50.90 135	87.48 57	75.30 53	86.85 57	87.33 78
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
MVSFormer		71.50 134	70.38 145	74.88 101	78.76 160	57.15 104	82.79 72	78.48 207	51.26 325	69.49 167	83.22 220	43.99 229	83.24 164	66.06 136	79.37 143	84.23 204

test_djsdf		69.45 188	67.74 203	74.58 113	74.57 297	54.92 145	82.79 72	78.48 207	51.26 325	65.41 259	83.49 216	38.37 299	83.24 164	66.06 136	69.25 330	85.56 151

ACMP	63.53 6	72.30 117	71.20 129	75.59 91	80.28 121	57.54 94	82.74 74	82.84 111	60.58 112	65.24 266	86.18 143	39.25 288	86.03 102	66.95 130	76.79 206	83.22 242
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMM	61.98 7	70.80 149	69.73 156	74.02 136	80.59 120	58.59 82	82.68 75	82.02 121	55.46 239	67.18 223	84.39 193	38.51 297	83.17 166	60.65 197	76.10 216	80.30 314
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
AdaColmap		69.99 167	68.66 181	73.97 140	84.94 58	57.83 90	82.63 76	78.71 195	56.28 220	64.34 281	84.14 196	41.57 260	87.06 69	46.45 323	78.88 162	77.02 363

OPM-MVS		74.73 65	74.25 71	76.19 76	80.81 113	59.01 75	82.60 77	83.64 79	63.74 41	72.52 123	87.49 91	47.18 186	85.88 106	69.47 99	80.78 117	83.66 231
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 73	61.71 85	72.45 126	90.34 37	48.48 166	88.13 41	72.32 78	86.85 57	85.78 138

LPG-MVS_test		72.74 105	71.74 116	75.76 83	80.22 123	57.51 96	82.55 78	83.40 87	61.32 92	66.67 234	87.33 99	39.15 290	86.59 79	67.70 116	77.30 198	83.19 244

CANet		76.46 44	75.93 48	78.06 43	81.29 104	57.53 95	82.35 80	83.31 93	67.78 3	70.09 154	86.34 138	54.92 66	88.90 29	72.68 75	84.55 73	87.76 56

114514_t		70.83 147	69.56 159	74.64 110	86.21 32	54.63 148	82.34 81	81.81 124	48.22 366	63.01 302	85.83 157	40.92 272	87.10 67	57.91 223	79.79 136	82.18 271

HQP-NCC					80.66 115		82.31 82		62.10 77	67.85 204

ACMP_Plane					80.66 115		82.31 82		62.10 77	67.85 204

HQP-MVS		73.45 88	72.80 100	75.40 92	80.66 115	54.94 143	82.31 82	83.90 62	62.10 77	67.85 204	85.54 167	45.46 207	86.93 71	67.04 126	80.35 127	84.32 200

MSLP-MVS++		73.77 83	73.47 87	74.66 108	83.02 79	59.29 63	82.30 85	81.88 122	59.34 150	71.59 137	86.83 114	45.94 200	83.65 155	65.09 147	85.22 69	81.06 297

EPP-MVSNet		72.16 122	71.31 126	74.71 105	78.68 163	49.70 262	82.10 86	81.65 126	60.40 117	65.94 248	85.84 156	51.74 120	86.37 90	55.93 237	79.55 142	88.07 46

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	78.57 203	58.58 165	74.32 78	84.51 190	55.94 57	87.22 62	67.11 125	84.48 77	85.52 152

test_prior2							81.75 89		60.37 120	75.01 61	89.06 61	56.22 46		72.19 79	88.96 28

PS-MVSNAJss		72.24 118	71.21 128	75.31 94	78.50 169	55.93 122	81.63 90	82.12 119	56.24 221	70.02 158	85.68 163	47.05 188	84.34 142	65.27 146	74.41 238	85.67 147

TEST9					85.58 44	61.59 24	81.62 91	81.26 142	55.65 234	74.93 63	88.81 67	53.70 86	84.68 136

train_agg		76.27 47	76.15 44	76.64 69	85.58 44	61.59 24	81.62 91	81.26 142	55.86 226	74.93 63	88.81 67	53.70 86	84.68 136	75.24 55	88.33 34	83.65 232

MG-MVS		73.96 80	73.89 79	74.16 128	85.65 43	49.69 264	81.59 93	81.29 141	61.45 90	71.05 143	88.11 77	51.77 119	87.73 52	61.05 193	83.09 88	85.05 177

test_8					85.40 47	60.96 34	81.54 94	81.18 146	55.86 226	74.81 68	88.80 69	53.70 86	84.45 140

MAR-MVS		71.51 133	70.15 151	75.60 90	81.84 94	59.39 60	81.38 95	82.90 108	54.90 261	68.08 200	78.70 318	47.73 173	85.51 115	51.68 279	84.17 80	81.88 277
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	56.32 218	74.05 82	88.98 63	53.34 91	87.92 47	69.23 101	88.42 32	87.59 64

OpenMVS	61.03 9	68.85 202	67.56 207	72.70 185	74.26 306	53.99 158	81.21 97	81.34 139	52.70 298	62.75 307	85.55 166	38.86 294	84.14 144	48.41 304	83.01 89	79.97 320

DP-MVS Recon		72.15 123	70.73 138	76.40 72	86.57 25	57.99 88	81.15 98	82.96 106	57.03 199	66.78 229	85.56 164	44.50 223	88.11 42	51.77 277	80.23 130	83.10 249

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 99	74.90 66	87.17 108	56.46 42	88.14 40	72.87 73	88.03 42	89.00 9

Vis-MVSNet		72.18 119	71.37 124	74.61 111	81.29 104	55.41 136	80.90 100	78.28 217	60.73 108	69.23 176	88.09 78	44.36 225	82.65 191	57.68 224	81.75 110	85.77 141
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
jajsoiax		68.25 218	66.45 238	73.66 155	75.62 265	55.49 135	80.82 101	78.51 206	52.33 306	64.33 282	84.11 197	28.28 410	81.81 210	63.48 168	70.62 299	83.67 229

mvs_tets		68.18 221	66.36 244	73.63 158	75.61 266	55.35 139	80.77 102	78.56 204	52.48 305	64.27 284	84.10 198	27.45 418	81.84 209	63.45 169	70.56 301	83.69 228

DP-MVS		65.68 270	63.66 283	71.75 210	84.93 59	56.87 109	80.74 103	73.16 314	53.06 293	59.09 356	82.35 242	36.79 321	85.94 105	32.82 427	69.96 315	72.45 412

3Dnovator	64.47 5	72.49 112	71.39 123	75.79 82	77.70 202	58.99 76	80.66 104	83.15 102	62.24 74	65.46 258	86.59 128	42.38 246	85.52 114	59.59 207	84.72 71	82.85 254

ACMH+	57.40 11	66.12 266	64.06 275	72.30 198	77.79 198	52.83 192	80.39 105	78.03 220	57.30 192	57.47 375	82.55 236	27.68 416	84.17 143	45.54 334	69.78 319	79.90 322

viewdifsd2359ckpt09		73.42 89	72.45 106	76.30 75	77.25 222	53.27 178	80.36 106	82.48 114	57.96 179	72.24 127	85.73 161	53.22 92	86.27 94	63.79 164	79.06 160	89.36 5

sasdasda		74.67 66	74.98 61	73.71 152	78.94 155	50.56 239	80.23 107	83.87 65	60.30 124	77.15 41	86.56 130	59.65 20	82.00 205	66.01 138	82.12 101	88.58 25

canonicalmvs		74.67 66	74.98 61	73.71 152	78.94 155	50.56 239	80.23 107	83.87 65	60.30 124	77.15 41	86.56 130	59.65 20	82.00 205	66.01 138	82.12 101	88.58 25

IS-MVSNet		71.57 132	71.00 133	73.27 172	78.86 157	45.63 324	80.22 109	78.69 196	64.14 37	66.46 237	87.36 97	49.30 154	85.60 111	50.26 288	83.71 86	88.59 24

Effi-MVS+-dtu		69.64 179	67.53 210	75.95 78	76.10 257	62.29 15	80.20 110	76.06 259	59.83 139	65.26 265	77.09 351	41.56 261	84.02 148	60.60 198	71.09 296	81.53 281

nrg030		72.96 101	73.01 96	72.84 181	75.41 272	50.24 248	80.02 111	82.89 110	58.36 170	74.44 75	86.73 120	58.90 27	80.83 237	65.84 141	74.46 235	87.44 69

Anonymous20231211		69.28 191	68.47 186	71.73 211	80.28 121	47.18 308	79.98 112	82.37 116	54.61 266	67.24 221	84.01 200	39.43 284	82.41 199	55.45 245	72.83 268	85.62 150

DPM-MVS		75.47 58	75.00 60	76.88 61	81.38 103	59.16 67	79.94 113	85.71 27	56.59 212	72.46 124	86.76 116	56.89 39	87.86 49	66.36 134	88.91 29	83.64 233

PVSNet_Blended_VisFu		71.45 136	70.39 144	74.65 109	82.01 90	58.82 79	79.93 114	80.35 165	55.09 249	65.82 254	82.16 251	49.17 157	82.64 192	60.34 199	78.62 172	82.50 265

PAPM_NR		72.63 109	71.80 114	75.13 97	81.72 96	53.42 175	79.91 115	83.28 95	59.14 152	66.31 241	85.90 154	51.86 116	86.06 100	57.45 226	80.62 121	85.91 132

LS3D		64.71 284	62.50 301	71.34 232	79.72 135	55.71 127	79.82 116	74.72 287	48.50 362	56.62 382	84.62 183	33.59 354	82.34 200	29.65 449	75.23 230	75.97 373

UGNet		68.81 203	67.39 215	73.06 176	78.33 179	54.47 149	79.77 117	75.40 273	60.45 115	63.22 295	84.40 192	32.71 367	80.91 236	51.71 278	80.56 125	83.81 221
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		71.78 128	71.59 117	72.32 197	83.40 75	46.38 313	79.75 118	71.08 330	64.18 34	72.80 118	88.64 72	42.58 243	83.72 153	57.41 227	84.49 76	86.86 91

OMC-MVS		71.40 137	70.60 140	73.78 145	76.60 249	53.15 181	79.74 119	79.78 171	58.37 169	68.75 181	86.45 135	45.43 209	80.60 241	62.58 178	77.73 187	87.58 65

casdiffmvs_mvg		76.14 50	76.30 43	75.66 87	76.46 253	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	74.30 294	48.40 364				80.78 239	53.62 260		79.03 337

Effi-MVS+		73.31 93	72.54 104	75.62 89	77.87 195	53.64 165	79.62 122	79.61 175	61.63 89	72.02 131	82.61 230	56.44 43	85.97 104	63.99 157	79.07 159	87.25 80

GDP-MVS		72.64 108	71.28 127	76.70 64	77.72 201	54.22 155	79.57 123	84.45 48	55.30 243	71.38 141	86.97 111	39.94 277	87.00 70	67.02 128	79.20 153	88.89 12

PAPR		71.72 131	70.82 136	74.41 120	81.20 108	51.17 222	79.55 124	83.33 92	55.81 229	66.93 228	84.61 184	50.95 133	86.06 100	55.79 240	79.20 153	86.00 128

ACMH	55.70 15	65.20 279	63.57 284	70.07 260	78.07 189	52.01 213	79.48 125	79.69 172	55.75 231	56.59 383	80.98 276	27.12 421	80.94 233	42.90 363	71.58 288	77.25 361
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ETV-MVS		74.46 71	73.84 80	76.33 74	79.27 145	55.24 140	79.22 126	85.00 43	64.97 21	72.65 121	79.46 308	53.65 89	87.87 48	67.45 122	82.91 93	85.89 133

BP-MVS1		73.41 90	72.25 108	76.88 61	76.68 246	53.70 163	79.15 127	81.07 149	60.66 110	71.81 132	87.39 96	40.93 271	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 95	73.13 95	73.55 162	74.40 301	55.13 141	78.97 129	74.96 285	56.64 205	74.76 71	88.75 71	55.02 64	78.77 287	76.33 41	78.31 180	86.74 96

GeoE		71.01 142	70.15 151	73.60 160	79.57 138	52.17 208	78.93 130	78.12 219	58.02 176	67.76 213	83.87 203	52.36 107	82.72 189	56.90 229	75.79 220	85.92 131

fmvsm_s_conf0.5_n_11		73.16 96	73.35 91	72.58 186	75.48 269	52.41 206	78.84 131	76.85 244	58.64 163	73.58 94	87.25 105	54.09 76	79.47 263	76.19 44	79.27 149	85.86 134

UA-Net		73.13 98	72.93 97	73.76 147	83.58 71	51.66 219	78.75 132	77.66 226	67.75 4	72.61 122	89.42 56	49.82 146	83.29 163	53.61 261	83.14 87	86.32 118

VDDNet		71.81 127	71.33 125	73.26 173	82.80 83	47.60 304	78.74 133	75.27 275	59.59 145	72.94 113	89.40 57	41.51 263	83.91 150	58.75 219	82.99 90	88.26 33

v10		70.21 161	69.02 171	73.81 144	73.51 319	50.92 228	78.74 133	81.39 133	60.05 131	66.39 239	81.83 259	47.58 177	85.41 121	62.80 177	68.86 337	85.09 176

viewdifsd2359ckpt13		72.40 116	71.79 115	74.22 126	75.63 264	51.77 218	78.67 135	83.13 104	57.08 196	71.59 137	85.36 171	53.10 95	82.64 192	63.07 174	78.51 174	88.24 35

CANet_DTU		68.18 221	67.71 206	69.59 270	74.83 286	46.24 315	78.66 136	76.85 244	59.60 142	63.45 293	82.09 255	35.25 332	77.41 311	59.88 204	78.76 167	85.14 172

MVSMamba_PlusPlus		75.75 56	75.44 54	76.67 67	80.84 112	53.06 184	78.62 137	85.13 37	59.65 140	71.53 139	87.47 92	56.92 38	88.17 39	72.18 80	86.63 62	88.80 13

v8		70.33 159	69.28 166	73.49 164	73.15 325	50.22 249	78.62 137	80.78 156	60.79 106	66.45 238	82.11 254	49.35 153	84.98 127	63.58 167	68.71 338	85.28 168

alignmvs		73.86 82	73.99 76	73.45 166	78.20 182	50.50 241	78.57 139	82.43 115	59.40 148	76.57 46	86.71 122	56.42 44	81.23 224	65.84 141	81.79 107	88.62 22

PLC	56.13 14	65.09 280	63.21 293	70.72 249	81.04 110	54.87 146	78.57 139	77.47 229	48.51 361	55.71 391	81.89 257	33.71 351	79.71 257	41.66 372	70.37 304	77.58 354
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
v7n		69.01 199	67.36 217	73.98 139	72.51 339	52.65 196	78.54 141	81.30 140	60.26 126	62.67 308	81.62 263	43.61 231	84.49 139	57.01 228	68.70 339	84.79 187

COLMAP_ROB	52.97 17	61.27 334	58.81 344	68.64 286	74.63 293	52.51 201	78.42 142	73.30 310	49.92 342	50.96 429	81.51 267	23.06 441	79.40 265	31.63 437	65.85 361	74.01 400
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
Elysia		70.19 163	68.29 193	75.88 80	74.15 308	54.33 153	78.26 143	83.21 97	55.04 255	67.28 219	83.59 211	30.16 390	86.11 98	63.67 165	79.26 150	87.20 81

StellarMVS		70.19 163	68.29 193	75.88 80	74.15 308	54.33 153	78.26 143	83.21 97	55.04 255	67.28 219	83.59 211	30.16 390	86.11 98	63.67 165	79.26 150	87.20 81

fmvsm_s_conf0.5_n_a		69.54 183	68.74 179	71.93 203	72.47 340	53.82 161	78.25 145	62.26 411	49.78 343	73.12 109	86.21 142	52.66 101	76.79 328	75.02 56	68.88 335	85.18 171

E6new		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

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 56	82.95 175	68.16 108	79.86 133	88.77 16

fmvsm_s_conf0.5_n_8		74.30 73	74.39 68	74.01 137	75.33 274	52.89 189	78.24 146	77.32 236	61.65 86	78.13 32	88.90 65	52.82 99	81.54 215	78.46 22	78.67 170	87.60 63

CLD-MVS		73.33 92	72.68 102	75.29 96	78.82 159	53.33 177	78.23 150	84.79 46	61.30 94	70.41 151	81.04 274	52.41 106	87.12 66	64.61 153	82.49 100	85.41 162
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		72.81 103	72.33 107	74.24 125	69.89 390	55.81 125	78.22 151	75.40 273	54.17 275	75.00 62	88.03 83	53.82 82	80.23 251	78.08 25	78.34 179	86.69 98

test_fmvsmconf_n		73.01 100	72.59 103	74.27 124	71.28 367	55.88 124	78.21 152	75.56 268	54.31 273	74.86 67	87.80 87	54.72 68	80.23 251	78.07 26	78.48 175	86.70 97

casdiffmvs		74.80 63	74.89 63	74.53 116	75.59 267	50.37 245	78.17 153	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		72.69 107	72.80 100	72.37 196	74.11 311	53.21 180	78.12 154	73.31 309	53.98 278	76.81 45	88.05 80	53.38 90	77.37 313	76.64 38	80.78 117	86.53 106

fmvsm_s_conf0.1_n_a		69.32 190	68.44 188	71.96 201	70.91 371	53.78 162	78.12 154	62.30 410	49.35 349	73.20 103	86.55 132	51.99 114	76.79 328	74.83 58	68.68 340	85.32 166

F-COLMAP		63.05 308	60.87 328	69.58 272	76.99 242	53.63 166	78.12 154	76.16 255	47.97 371	52.41 424	81.61 264	27.87 413	78.11 294	40.07 379	66.66 356	77.00 364

fmvsm_s_conf0.5_n_10		74.11 75	73.98 77	74.48 118	74.61 294	52.86 191	78.10 157	77.06 240	57.14 195	78.24 31	88.79 70	52.83 98	82.26 201	77.79 28	81.30 113	88.32 31

test_fmvsmconf0.01_n		72.17 120	71.50 119	74.16 128	67.96 413	55.58 133	78.06 158	74.67 288	54.19 274	74.54 74	88.23 74	50.35 141	80.24 250	78.07 26	77.46 193	86.65 102

EG-PatchMatch MVS		64.71 284	62.87 296	70.22 256	77.68 203	53.48 170	77.99 159	78.82 191	53.37 290	56.03 390	77.41 347	24.75 438	84.04 146	46.37 324	73.42 258	73.14 403

fmvsm_s_conf0.5_n		69.58 181	68.84 176	71.79 209	72.31 346	52.90 187	77.90 160	62.43 409	49.97 341	72.85 117	85.90 154	52.21 109	76.49 335	75.75 47	70.26 309	85.97 129

SSM_0404		70.84 145	69.41 164	75.12 98	79.20 147	53.86 159	77.89 161	80.00 169	53.88 280	69.40 170	84.61 184	43.21 235	86.56 81	58.80 217	77.68 189	84.95 182

dcpmvs_2		74.55 70	75.23 58	72.48 191	82.34 87	53.34 176	77.87 162	81.46 131	57.80 185	75.49 52	86.81 115	62.22 15	77.75 304	71.09 91	82.02 104	86.34 114

tttt0517		67.83 231	65.66 257	74.33 122	76.69 245	50.82 230	77.86 163	73.99 301	54.54 269	64.64 279	82.53 239	35.06 334	85.50 116	55.71 241	69.91 316	86.67 100

fmvsm_s_conf0.1_n		69.41 189	68.60 182	71.83 206	71.07 369	52.88 190	77.85 164	62.44 408	49.58 346	72.97 112	86.22 141	51.68 121	76.48 336	75.53 51	70.10 312	86.14 124

v1144		70.42 156	69.31 165	73.76 147	73.22 323	50.64 236	77.83 165	81.43 132	58.58 165	69.40 170	81.16 271	47.53 179	85.29 123	64.01 156	70.64 298	85.34 165

CNLPA		65.43 274	64.02 276	69.68 268	78.73 162	58.07 87	77.82 166	70.71 334	51.49 320	61.57 328	83.58 214	38.23 303	70.82 371	43.90 350	70.10 312	80.16 317

fmvsm_s_conf0.5_n_3		73.55 87	74.39 68	71.03 242	74.09 312	51.86 216	77.77 167	75.60 266	61.18 97	78.67 29	88.98 63	55.88 58	77.73 305	78.69 16	78.68 169	83.50 236

VDD-MVS		72.50 111	72.09 110	73.75 149	81.58 97	49.69 264	77.76 168	77.63 227	63.21 50	73.21 102	89.02 62	42.14 247	83.32 162	61.72 187	82.50 99	88.25 34

v1192		69.97 168	68.68 180	73.85 142	73.19 324	50.94 226	77.68 169	81.36 135	57.51 191	68.95 180	80.85 281	45.28 212	85.33 122	62.97 176	70.37 304	85.27 169

v2v482		70.50 154	69.45 163	73.66 155	72.62 335	50.03 254	77.58 170	80.51 160	59.90 134	69.52 166	82.14 252	47.53 179	84.88 133	65.07 148	70.17 310	86.09 126

WR-MVS_H		67.02 249	66.92 230	67.33 305	77.95 194	37.75 404	77.57 171	82.11 120	62.03 82	62.65 309	82.48 240	50.57 138	79.46 264	42.91 362	64.01 376	84.79 187

Anonymous20240529		69.91 169	69.02 171	72.56 188	80.19 126	47.65 302	77.56 172	80.99 152	55.45 240	69.88 162	86.76 116	39.24 289	82.18 203	54.04 256	77.10 202	87.85 51

v144192		69.71 174	68.51 183	73.33 171	73.10 326	50.13 251	77.54 173	80.64 157	56.65 204	68.57 184	80.55 284	46.87 193	84.96 129	62.98 175	69.66 323	84.89 184

baseline		74.61 68	74.70 64	74.34 121	75.70 262	49.99 255	77.54 173	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 97	73.16 94	73.11 175	75.15 280	49.31 271	77.53 175	83.21 97	60.42 116	73.20 103	87.34 98	53.82 82	81.05 230	67.02 128	80.79 116	88.96 10

Fast-Effi-MVS+-dtu		67.37 239	65.33 265	73.48 165	72.94 330	57.78 92	77.47 176	76.88 243	57.60 190	61.97 320	76.85 355	39.31 286	80.49 245	54.72 250	70.28 308	82.17 273

fmvsm_l_conf0.5_n_9		73.27 94	73.66 84	72.09 200	73.82 313	52.72 195	77.45 177	74.28 295	56.61 211	77.10 43	88.16 76	56.17 47	77.09 318	78.27 24	81.13 115	86.48 108

v1921920		69.47 187	68.17 197	73.36 170	73.06 327	50.10 252	77.39 178	80.56 158	56.58 213	68.59 182	80.37 286	44.72 220	84.98 127	62.47 181	69.82 318	85.00 178

tt0805		67.77 233	67.24 224	69.34 275	74.87 284	40.08 380	77.36 179	81.37 134	55.31 242	66.33 240	84.65 182	37.35 311	82.55 195	55.65 243	72.28 279	85.39 163

GBi-Net		67.21 241	66.55 236	69.19 276	77.63 206	43.33 348	77.31 180	77.83 223	56.62 208	65.04 271	82.70 226	41.85 253	80.33 247	47.18 317	72.76 269	83.92 216

test1		67.21 241	66.55 236	69.19 276	77.63 206	43.33 348	77.31 180	77.83 223	56.62 208	65.04 271	82.70 226	41.85 253	80.33 247	47.18 317	72.76 269	83.92 216

FMVSNet1		66.70 256	65.87 253	69.19 276	77.49 214	43.33 348	77.31 180	77.83 223	56.45 214	64.60 280	82.70 226	38.08 305	80.33 247	46.08 327	72.31 278	83.92 216

fmvsm_s_conf0.5_n_9		75.16 60	75.22 59	75.01 99	78.34 178	55.37 138	77.30 183	73.95 302	61.40 91	79.46 23	90.14 41	57.07 37	81.15 225	80.00 5	79.31 148	88.51 27

MVS_111021_HR		74.02 79	73.46 88	75.69 86	83.01 80	60.63 40	77.29 184	78.40 214	61.18 97	70.58 149	85.97 152	54.18 74	84.00 149	67.52 119	82.98 92	82.45 266

SSM_0407		70.41 157	68.96 174	74.75 104	78.65 164	53.46 171	77.28 185	80.00 169	53.88 280	68.14 194	84.61 184	43.21 235	86.26 95	58.80 217	76.11 213	84.54 192

EIA-MVS		71.78 128	70.60 140	75.30 95	79.85 132	53.54 169	77.27 186	83.26 96	57.92 181	66.49 236	79.39 310	52.07 113	86.69 77	60.05 201	79.14 158	85.66 148

viewmanbaseed2359cas		72.92 102	72.89 98	73.00 177	75.16 278	49.25 274	77.25 187	83.11 105	59.52 147	72.93 114	86.63 125	54.11 75	80.98 231	66.63 132	80.67 120	88.76 20

v1240		69.24 193	67.91 202	73.25 174	73.02 329	49.82 256	77.21 188	80.54 159	56.43 215	68.34 189	80.51 285	43.33 234	84.99 125	62.03 185	69.77 321	84.95 182

fmvsm_l_conf0.5_n		70.99 143	70.82 136	71.48 220	71.45 360	54.40 151	77.18 189	70.46 336	48.67 358	75.17 57	86.86 113	53.77 84	76.86 326	76.33 41	77.51 192	83.17 248

E4		73.91 81	73.83 81	74.15 130	77.13 229	50.47 242	77.15 190	83.79 72	62.21 75	73.61 92	87.19 107	56.08 52	83.03 168	67.91 113	79.35 146	88.94 11

jason		69.65 178	68.39 190	73.43 168	78.27 181	56.88 108	77.12 191	73.71 305	46.53 390	69.34 172	83.22 220	43.37 233	79.18 270	64.77 150	79.20 153	84.23 204
jason: jason.
PAPM		67.92 228	66.69 234	71.63 217	78.09 188	49.02 277	77.09 192	81.24 144	51.04 328	60.91 334	83.98 201	47.71 174	84.99 125	40.81 376	79.32 147	80.90 300

EI-MVSNet-Vis-set		72.42 115	71.59 117	74.91 100	78.47 171	54.02 157	77.05 193	79.33 181	65.03 18	71.68 135	79.35 312	52.75 100	84.89 131	66.46 133	74.23 239	85.83 137

PEN-MVS		66.60 258	66.45 238	67.04 306	77.11 233	36.56 417	77.03 194	80.42 163	62.95 55	62.51 314	84.03 199	46.69 194	79.07 278	44.22 344	63.08 386	85.51 153

E2		73.72 84	73.60 85	74.06 134	77.16 224	50.40 243	76.97 195	83.74 73	61.64 87	73.36 97	86.75 119	56.14 48	82.99 170	67.50 120	79.18 156	88.80 13

E3		73.72 84	73.60 85	74.06 134	77.16 224	50.40 243	76.97 195	83.74 73	61.64 87	73.36 97	86.76 116	56.13 49	82.99 170	67.50 120	79.18 156	88.80 13

FIs		70.82 148	71.43 121	68.98 282	78.33 179	38.14 400	76.96 197	83.59 81	61.02 100	67.33 218	86.73 120	55.07 62	81.64 211	54.61 253	79.22 152	87.14 84

PS-CasMVS		66.42 262	66.32 246	66.70 310	77.60 212	36.30 422	76.94 198	79.61 175	62.36 70	62.43 317	83.66 209	45.69 201	78.37 290	45.35 340	63.26 384	85.42 161

h-mvs33		72.71 106	71.49 120	76.40 72	81.99 92	59.58 57	76.92 199	76.74 249	60.40 117	74.81 68	85.95 153	45.54 205	85.76 109	70.41 95	70.61 300	83.86 220

fmvsm_l_conf0.5_n_a		70.50 154	70.27 147	71.18 236	71.30 366	54.09 156	76.89 200	69.87 340	47.90 372	74.37 77	86.49 133	53.07 97	76.69 332	75.41 52	77.11 201	82.76 255

thisisatest0530		67.92 228	65.78 255	74.33 122	76.29 254	51.03 225	76.89 200	74.25 296	53.67 287	65.59 256	81.76 261	35.15 333	85.50 116	55.94 236	72.47 274	86.47 109

viewcassd2359sk11		73.56 86	73.41 90	74.00 138	77.13 229	50.35 246	76.86 202	83.69 77	61.23 96	73.14 106	86.38 137	56.09 51	82.96 173	67.15 124	79.01 161	88.70 21

test_0402		63.25 304	61.01 324	69.96 261	80.00 130	54.37 152	76.86 202	72.02 325	54.58 268	58.71 359	80.79 283	35.00 335	84.36 141	26.41 461	64.71 370	71.15 431

CP-MVSNet		66.49 261	66.41 242	66.72 308	77.67 204	36.33 420	76.83 204	79.52 177	62.45 68	62.54 312	83.47 217	46.32 197	78.37 290	45.47 338	63.43 383	85.45 158

E3new		73.41 90	73.22 93	73.95 141	77.06 234	50.31 247	76.78 205	83.66 78	60.90 103	72.93 114	86.02 150	55.99 53	82.95 175	66.89 131	78.77 166	88.61 23

fmvsm_s_conf0.5_n_4		72.04 124	71.85 113	72.58 186	73.74 316	52.49 202	76.69 206	72.42 320	56.42 216	75.32 54	87.04 109	52.13 112	78.01 296	79.29 12	73.65 249	87.26 79

EI-MVSNet-UG-set		71.92 125	71.06 132	74.52 117	77.98 193	53.56 168	76.62 207	79.16 182	64.40 29	71.18 142	78.95 317	52.19 110	84.66 138	65.47 144	73.57 252	85.32 166

RRT-MVS		71.46 135	70.70 139	73.74 150	77.76 200	49.30 272	76.60 208	80.45 162	61.25 95	68.17 192	84.78 177	44.64 221	84.90 130	64.79 149	77.88 186	87.03 86

lupinMVS		69.57 182	68.28 195	73.44 167	78.76 160	57.15 104	76.57 209	73.29 311	46.19 393	69.49 167	82.18 248	43.99 229	79.23 269	64.66 151	79.37 143	83.93 215

TranMVSNet+NR-MVSNet		70.36 158	70.10 153	71.17 237	78.64 167	42.97 354	76.53 210	81.16 148	66.95 6	68.53 185	85.42 169	51.61 122	83.07 167	52.32 269	69.70 322	87.46 68

TAPA-MVS	59.36 10	66.60 258	65.20 267	70.81 246	76.63 248	48.75 283	76.52 211	80.04 168	50.64 333	65.24 266	84.93 174	39.15 290	78.54 289	36.77 403	76.88 204	85.14 172
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
DTE-MVSNet		65.58 272	65.34 264	66.31 318	76.06 258	34.79 430	76.43 212	79.38 180	62.55 66	61.66 326	83.83 204	45.60 203	79.15 274	41.64 374	60.88 404	85.00 178

anonymousdsp		67.00 250	64.82 270	73.57 161	70.09 386	56.13 117	76.35 213	77.35 234	48.43 363	64.99 274	80.84 282	33.01 360	80.34 246	64.66 151	67.64 348	84.23 204

MVP-Stereo		65.41 275	63.80 280	70.22 256	77.62 210	55.53 134	76.30 214	78.53 205	50.59 334	56.47 386	78.65 321	39.84 280	82.68 190	44.10 348	72.12 282	72.44 413
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
fmvsm_s_conf0.5_n_6		72.59 110	72.87 99	71.73 211	75.14 281	51.96 214	76.28 215	77.12 239	57.63 189	73.85 89	86.91 112	51.54 123	77.87 301	77.18 32	80.18 131	85.37 164

MVS_Test		72.45 113	72.46 105	72.42 195	74.88 283	48.50 289	76.28 215	83.14 103	59.40 148	72.46 124	84.68 180	55.66 59	81.12 226	65.98 140	79.66 139	87.63 61

LuminaMVS		68.24 219	66.82 232	72.51 190	73.46 322	53.60 167	76.23 217	78.88 190	52.78 297	68.08 200	80.13 292	32.70 368	81.41 217	63.16 173	75.97 217	82.53 262

IterMVS-LS		69.22 194	68.48 184	71.43 226	74.44 300	49.40 268	76.23 217	77.55 228	59.60 142	65.85 253	81.59 266	51.28 128	81.58 214	59.87 205	69.90 317	83.30 239
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
新几何2							76.12 219

FMVSNet2		66.93 251	66.31 247	68.79 285	77.63 206	42.98 353	76.11 220	77.47 229	56.62 208	65.22 268	82.17 250	41.85 253	80.18 253	47.05 320	72.72 272	83.20 243

旧先验2							76.08 221		45.32 401	76.55 47			65.56 407	58.75 219

BH-untuned		68.27 217	67.29 219	71.21 234	79.74 133	53.22 179	76.06 222	77.46 231	57.19 194	66.10 245	81.61 264	45.37 211	83.50 159	45.42 339	76.68 208	76.91 367

FC-MVSNet-test		69.80 173	70.58 142	67.46 301	77.61 211	34.73 433	76.05 223	83.19 101	60.84 105	65.88 252	86.46 134	54.52 71	80.76 240	52.52 268	78.12 182	86.91 89

PCF-MVS	61.88 8	70.95 144	69.49 161	75.35 93	77.63 206	55.71 127	76.04 224	81.81 124	50.30 336	69.66 165	85.40 170	52.51 103	84.89 131	51.82 276	80.24 129	85.45 158
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
UniMVSNet_NR-MVSNet		71.11 139	71.00 133	71.44 224	79.20 147	44.13 339	76.02 225	82.60 113	66.48 11	68.20 190	84.60 187	56.82 40	82.82 187	54.62 251	70.43 302	87.36 77

UniMVSNet (Re)		70.63 151	70.20 148	71.89 204	78.55 168	45.29 327	75.94 226	82.92 107	63.68 42	68.16 193	83.59 211	53.89 80	83.49 160	53.97 257	71.12 293	86.89 90

KinetiMVS		71.26 138	70.16 150	74.57 114	74.59 295	52.77 194	75.91 227	81.20 145	60.72 109	69.10 179	85.71 162	41.67 258	83.53 158	63.91 160	78.62 172	87.42 70

test_fmvsmvis_n_1920		70.84 145	70.38 145	72.22 199	71.16 368	55.39 137	75.86 228	72.21 323	49.03 353	73.28 101	86.17 144	51.83 118	77.29 315	75.80 46	78.05 183	83.98 213

EPNet_dtu		61.90 325	61.97 308	61.68 370	72.89 331	39.78 384	75.85 229	65.62 378	55.09 249	54.56 407	79.36 311	37.59 308	67.02 398	39.80 384	76.95 203	78.25 343
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MGCFI-Net		72.45 113	73.34 92	69.81 267	77.77 199	43.21 351	75.84 230	81.18 146	59.59 145	75.45 53	86.64 123	57.74 31	77.94 297	63.92 158	81.90 106	88.30 32

v148		68.24 219	67.19 227	71.40 227	70.43 379	47.77 301	75.76 231	77.03 241	58.91 156	67.36 217	80.10 294	48.60 165	81.89 207	60.01 202	66.52 358	84.53 195

test_fmvsm_n_1920		71.73 130	71.14 130	73.50 163	72.52 338	56.53 111	75.60 232	76.16 255	48.11 368	77.22 40	85.56 164	53.10 95	77.43 310	74.86 57	77.14 200	86.55 105

SixPastTwentyTwo		61.65 328	58.80 346	70.20 258	75.80 260	47.22 307	75.59 233	69.68 342	54.61 266	54.11 411	79.26 313	27.07 422	82.96 173	43.27 357	49.79 450	80.41 310

DELS-MVS		74.76 64	74.46 67	75.65 88	77.84 197	52.25 207	75.59 233	84.17 54	63.76 40	73.15 105	82.79 225	59.58 23	86.80 74	67.24 123	86.04 65	87.89 48
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)		69.82 171	68.48 184	73.84 143	78.44 172	50.04 253	75.58 235	78.99 188	58.16 172	67.59 214	82.14 252	42.66 241	85.63 110	56.60 230	76.19 212	85.84 136

Baseline_NR-MVSNet		67.05 248	67.56 207	65.50 336	75.65 263	37.70 406	75.42 236	74.65 289	59.90 134	68.14 194	83.15 223	49.12 160	77.20 316	52.23 270	69.78 319	81.60 279

OpenMVS_ROB	52.78 18	60.03 343	58.14 353	65.69 333	70.47 378	44.82 329	75.33 237	70.86 333	45.04 402	56.06 389	76.00 371	26.89 425	79.65 258	35.36 416	67.29 351	72.60 408

viewdifsd2359ckpt07		71.90 126	71.97 112	71.69 214	74.81 287	48.08 295	75.30 238	80.49 161	60.00 132	71.63 136	86.33 139	56.34 45	79.25 268	65.40 145	77.41 194	87.76 56

xiu_mvs_v1_base_debu		68.58 209	67.28 220	72.48 191	78.19 183	57.19 101	75.28 239	75.09 281	51.61 315	70.04 155	81.41 268	32.79 363	79.02 280	63.81 161	77.31 195	81.22 291

xiu_mvs_v1_base		68.58 209	67.28 220	72.48 191	78.19 183	57.19 101	75.28 239	75.09 281	51.61 315	70.04 155	81.41 268	32.79 363	79.02 280	63.81 161	77.31 195	81.22 291

xiu_mvs_v1_base_debi		68.58 209	67.28 220	72.48 191	78.19 183	57.19 101	75.28 239	75.09 281	51.61 315	70.04 155	81.41 268	32.79 363	79.02 280	63.81 161	77.31 195	81.22 291

EI-MVSNet		69.27 192	68.44 188	71.73 211	74.47 298	49.39 269	75.20 242	78.45 210	59.60 142	69.16 177	76.51 364	51.29 127	82.50 196	59.86 206	71.45 290	83.30 239

CVMVSNet		59.63 349	59.14 340	61.08 379	74.47 298	38.84 393	75.20 242	68.74 353	31.15 456	58.24 366	76.51 364	32.39 376	68.58 385	49.77 290	65.84 362	75.81 375

ET-MVSNet_ETH3D		67.96 227	65.72 256	74.68 107	76.67 247	55.62 132	75.11 244	74.74 286	52.91 295	60.03 342	80.12 293	33.68 352	82.64 192	61.86 186	76.34 210	85.78 138

xiu_mvs_v2_base		70.52 152	69.75 155	72.84 181	81.21 107	55.63 130	75.11 244	78.92 189	54.92 260	69.96 161	79.68 303	47.00 192	82.09 204	61.60 189	79.37 143	80.81 302

K. test v3		60.47 340	57.11 359	70.56 252	73.74 316	48.22 292	75.10 246	62.55 406	58.27 171	53.62 417	76.31 368	27.81 414	81.59 213	47.42 312	39.18 465	81.88 277

Fast-Effi-MVS+		70.28 160	69.12 170	73.73 151	78.50 169	51.50 220	75.01 247	79.46 179	56.16 223	68.59 182	79.55 306	53.97 78	84.05 145	53.34 263	77.53 191	85.65 149

DU-MVS		70.01 166	69.53 160	71.44 224	78.05 190	44.13 339	75.01 247	81.51 130	64.37 30	68.20 190	84.52 188	49.12 160	82.82 187	54.62 251	70.43 302	87.37 75

FMVSNet3		66.32 265	65.61 258	68.46 288	76.48 252	42.34 358	74.98 249	77.15 238	55.83 228	65.04 271	81.16 271	39.91 278	80.14 254	47.18 317	72.76 269	82.90 253

mvsmamba		68.47 213	66.56 235	74.21 127	79.60 136	52.95 185	74.94 250	75.48 271	52.09 309	60.10 340	83.27 219	36.54 322	84.70 135	59.32 211	77.69 188	84.99 180

MTAPA		76.90 38	76.42 42	78.35 39	86.08 38	63.57 2	74.92 251	80.97 153	65.13 15	75.77 50	90.88 20	48.63 163	86.66 78	77.23 30	88.17 37	84.81 186

PS-MVSNAJ		70.51 153	69.70 157	72.93 179	81.52 98	55.79 126	74.92 251	79.00 187	55.04 255	69.88 162	78.66 320	47.05 188	82.19 202	61.61 188	79.58 140	80.83 301

MVS_111021_LR		69.50 186	68.78 178	71.65 216	78.38 174	59.33 61	74.82 253	70.11 338	58.08 173	67.83 209	84.68 180	41.96 249	76.34 339	65.62 143	77.54 190	79.30 333

ECVR-MVS		67.72 234	67.51 211	68.35 290	79.46 140	36.29 423	74.79 254	66.93 367	58.72 159	67.19 222	88.05 80	36.10 324	81.38 219	52.07 272	84.25 78	87.39 73

test_yl		69.69 175	69.13 168	71.36 230	78.37 176	45.74 320	74.71 255	80.20 166	57.91 182	70.01 159	83.83 204	42.44 244	82.87 183	54.97 247	79.72 137	85.48 154

DCV-MVSNet		69.69 175	69.13 168	71.36 230	78.37 176	45.74 320	74.71 255	80.20 166	57.91 182	70.01 159	83.83 204	42.44 244	82.87 183	54.97 247	79.72 137	85.48 154

TransMVSNet (Re)		64.72 283	64.33 273	65.87 331	75.22 275	38.56 395	74.66 257	75.08 284	58.90 157	61.79 323	82.63 229	51.18 129	78.07 295	43.63 355	55.87 428	80.99 299

BH-w/o		66.85 252	65.83 254	69.90 265	79.29 142	52.46 203	74.66 257	76.65 250	54.51 270	64.85 276	78.12 328	45.59 204	82.95 175	43.26 358	75.54 224	74.27 397

IMVS_0403		69.09 197	68.14 198	71.95 202	77.06 234	49.73 258	74.51 259	78.60 199	52.70 298	66.69 232	82.58 231	46.43 196	83.38 161	59.20 212	75.46 226	82.74 256

PVSNet_BlendedMVS		68.56 212	67.72 204	71.07 241	77.03 240	50.57 237	74.50 260	81.52 128	53.66 288	64.22 287	79.72 302	49.13 158	82.87 183	55.82 238	73.92 243	79.77 328

MonoMVSNet		64.15 293	63.31 291	66.69 311	70.51 377	44.12 341	74.47 261	74.21 297	57.81 184	63.03 300	76.62 360	38.33 300	77.31 314	54.22 255	60.59 410	78.64 340

c3_l		68.33 216	67.56 207	70.62 251	70.87 372	46.21 316	74.47 261	78.80 193	56.22 222	66.19 242	78.53 325	51.88 115	81.40 218	62.08 182	69.04 333	84.25 203

test2506		65.33 277	64.61 271	67.50 300	79.46 140	34.19 438	74.43 263	51.92 449	58.72 159	66.75 231	88.05 80	25.99 430	80.92 235	51.94 274	84.25 78	87.39 73

IMVS_0407		68.90 201	67.93 201	71.82 207	77.06 234	49.73 258	74.40 264	78.60 199	52.70 298	66.19 242	82.58 231	45.17 215	83.00 169	59.20 212	75.46 226	82.74 256

BH-RMVSNet		68.81 203	67.42 214	72.97 178	80.11 129	52.53 200	74.26 265	76.29 254	58.48 167	68.38 188	84.20 194	42.59 242	83.83 151	46.53 322	75.91 218	82.56 260

NR-MVSNet		69.54 183	68.85 175	71.59 218	78.05 190	43.81 344	74.20 266	80.86 155	65.18 14	62.76 306	84.52 188	52.35 108	83.59 157	50.96 284	70.78 297	87.37 75

UniMVSNet_ETH3D		67.60 236	67.07 229	69.18 279	77.39 217	42.29 359	74.18 267	75.59 267	60.37 120	66.77 230	86.06 148	37.64 307	78.93 285	52.16 271	73.49 254	86.32 118

VPA-MVSNet		69.02 198	69.47 162	67.69 299	77.42 216	41.00 375	74.04 268	79.68 173	60.06 130	69.26 175	84.81 176	51.06 132	77.58 308	54.44 254	74.43 237	84.48 197

miper_ehance_all_eth		68.03 224	67.24 224	70.40 255	70.54 376	46.21 316	73.98 269	78.68 197	55.07 252	66.05 246	77.80 339	52.16 111	81.31 221	61.53 192	69.32 327	83.67 229

hse-mvs2		71.04 140	69.86 154	74.60 112	79.58 137	57.12 106	73.96 270	75.25 276	60.40 117	74.81 68	81.95 256	45.54 205	82.90 180	70.41 95	66.83 355	83.77 225

1314		64.61 287	63.21 293	68.80 284	71.87 353	47.46 305	73.95 271	78.39 215	42.88 423	59.97 343	76.60 363	38.11 304	79.39 266	54.84 249	72.32 277	79.55 329

MVS		67.37 239	66.33 245	70.51 254	75.46 270	50.94 226	73.95 271	81.85 123	41.57 430	62.54 312	78.57 324	47.98 169	85.47 118	52.97 266	82.05 103	75.14 383

AUN-MVS		68.45 215	66.41 242	74.57 114	79.53 139	57.08 107	73.93 273	75.23 277	54.44 271	66.69 232	81.85 258	37.10 317	82.89 181	62.07 183	66.84 354	83.75 226

OurMVSNet-221017-0		61.37 333	58.63 348	69.61 269	72.05 349	48.06 296	73.93 273	72.51 319	47.23 383	54.74 404	80.92 278	21.49 448	81.24 223	48.57 303	56.22 427	79.53 330

test1111		67.21 241	67.14 228	67.42 302	79.24 146	34.76 432	73.89 275	65.65 377	58.71 161	66.96 227	87.95 84	36.09 325	80.53 242	52.03 273	83.79 84	86.97 88

cl22		67.47 238	66.45 238	70.54 253	69.85 392	46.49 312	73.85 276	77.35 234	55.07 252	65.51 257	77.92 334	47.64 176	81.10 227	61.58 190	69.32 327	84.01 212

TAMVS		66.78 255	65.27 266	71.33 233	79.16 151	53.67 164	73.84 277	69.59 344	52.32 307	65.28 261	81.72 262	44.49 224	77.40 312	42.32 366	78.66 171	82.92 251

WR-MVS		68.47 213	68.47 186	68.44 289	80.20 125	39.84 383	73.75 278	76.07 258	64.68 24	68.11 198	83.63 210	50.39 140	79.14 275	49.78 289	69.66 323	86.34 114

eth_miper_zixun_eth		67.63 235	66.28 248	71.67 215	71.60 356	48.33 291	73.68 279	77.88 221	55.80 230	65.91 249	78.62 323	47.35 185	82.88 182	59.45 208	66.25 359	83.81 221

guyue		68.10 223	67.23 226	70.71 250	73.67 318	49.27 273	73.65 280	76.04 260	55.62 236	67.84 208	82.26 246	41.24 268	78.91 286	61.01 194	73.72 247	83.94 214

TR-MVS		66.59 260	65.07 268	71.17 237	79.18 149	49.63 266	73.48 281	75.20 279	52.95 294	67.90 202	80.33 289	39.81 281	83.68 154	43.20 359	73.56 253	80.20 316

usedtu_blend_shiyan5		62.63 311	60.77 329	68.20 292	68.53 409	44.64 333	73.47 282	77.00 242	51.91 311	57.10 379	69.95 428	38.83 295	79.61 261	47.44 310	62.67 388	80.37 312

VortexMVS		66.41 263	65.50 260	69.16 280	73.75 314	48.14 293	73.41 283	78.28 217	53.73 285	64.98 275	78.33 326	40.62 273	79.07 278	58.88 216	67.50 349	80.26 315

fmvsm_s_conf0.1_n_2		69.64 179	69.01 173	71.52 219	71.66 355	51.04 224	73.39 284	67.14 365	55.02 258	75.11 58	87.64 89	42.94 240	77.01 321	75.55 50	72.63 273	86.52 107

fmvsm_s_conf0.5_n_2		69.82 171	69.27 167	71.46 221	72.00 350	51.08 223	73.30 285	67.79 359	55.06 254	75.24 56	87.51 90	44.02 228	77.00 322	75.67 48	72.86 267	86.31 121

cl____		67.18 244	66.26 249	69.94 262	70.20 383	45.74 320	73.30 285	76.83 246	55.10 247	65.27 262	79.57 305	47.39 183	80.53 242	59.41 210	69.22 331	83.53 235

DIV-MVS_self_test		67.18 244	66.26 249	69.94 262	70.20 383	45.74 320	73.29 287	76.83 246	55.10 247	65.27 262	79.58 304	47.38 184	80.53 242	59.43 209	69.22 331	83.54 234

AstraMVS		67.86 230	66.83 231	70.93 244	73.50 320	49.34 270	73.28 288	74.01 300	55.45 240	68.10 199	83.28 218	38.93 293	79.14 275	63.22 172	71.74 285	84.30 202

CDS-MVSNet		66.80 254	65.37 263	71.10 240	78.98 154	53.13 183	73.27 289	71.07 331	52.15 308	64.72 277	80.23 291	43.56 232	77.10 317	45.48 337	78.88 162	83.05 250
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
viewdifsd2359ckpt11		69.13 195	68.38 191	71.38 228	71.57 357	48.61 286	73.22 290	73.18 312	57.65 187	70.67 147	84.73 178	50.03 142	79.80 255	63.25 170	71.10 294	85.74 144

viewmsd2359difaftdt		69.13 195	68.38 191	71.38 228	71.57 357	48.61 286	73.22 290	73.18 312	57.65 187	70.67 147	84.73 178	50.03 142	79.80 255	63.25 170	71.10 294	85.74 144

diffmvs_AUTHOR		71.02 141	70.87 135	71.45 223	69.89 390	48.97 280	73.16 292	78.33 216	57.79 186	72.11 130	85.26 172	51.84 117	77.89 300	71.00 92	78.47 177	87.49 67

pmmvs6		63.69 298	62.82 298	66.27 320	70.63 374	39.27 390	73.13 293	75.47 272	52.69 303	59.75 349	82.30 244	39.71 282	77.03 320	47.40 313	64.35 375	82.53 262

IB-MVS	56.42 12	65.40 276	62.73 299	73.40 169	74.89 282	52.78 193	73.09 294	75.13 280	55.69 232	58.48 365	73.73 397	32.86 362	86.32 92	50.63 285	70.11 311	81.10 295
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		70.69 150	70.43 143	71.46 221	69.45 397	48.95 281	72.93 295	78.46 209	57.27 193	71.69 134	83.97 202	51.48 125	77.92 299	70.70 94	77.95 185	87.53 66
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		62.01 324	60.88 326	65.42 338	68.74 406	38.43 398	72.92 296	77.39 232	54.74 265	55.40 396	76.71 357	35.46 330	76.72 331	44.25 343	62.31 394	81.10 295

V42		68.65 207	67.35 218	72.56 188	68.93 405	50.18 250	72.90 297	79.47 178	56.92 201	69.45 169	80.26 290	46.29 198	82.99 170	64.07 154	67.82 346	84.53 195

miper_enhance_ethall		67.11 247	66.09 251	70.17 259	69.21 400	45.98 318	72.85 298	78.41 213	51.38 322	65.65 255	75.98 374	51.17 130	81.25 222	60.82 196	69.32 327	83.29 241

thres100view900		63.28 303	62.41 302	65.89 329	77.31 220	38.66 394	72.65 299	69.11 351	57.07 197	62.45 315	81.03 275	37.01 319	79.17 271	31.84 433	73.25 261	79.83 325

testdata1							72.65 299		60.50 114

FE-MVS		65.91 268	63.33 290	73.63 158	77.36 218	51.95 215	72.62 301	75.81 262	53.70 286	65.31 260	78.96 316	28.81 405	86.39 89	43.93 349	73.48 255	82.55 261

pm-mvs1		65.24 278	64.97 269	66.04 326	72.38 343	39.40 389	72.62 301	75.63 265	55.53 237	62.35 319	83.18 222	47.45 181	76.47 337	49.06 299	66.54 357	82.24 270

test222					83.14 76	58.68 81	72.57 303	63.45 399	41.78 426	67.56 215	86.12 145	37.13 316			78.73 168	74.98 387

PVSNet_Blended		68.59 208	67.72 204	71.19 235	77.03 240	50.57 237	72.51 304	81.52 128	51.91 311	64.22 287	77.77 342	49.13 158	82.87 183	55.82 238	79.58 140	80.14 318

EU-MVSNet		55.61 383	54.41 386	59.19 390	65.41 431	33.42 443	72.44 305	71.91 326	28.81 458	51.27 427	73.87 396	24.76 437	69.08 382	43.04 360	58.20 418	75.06 384

thres600view7		63.30 302	62.27 304	66.41 316	77.18 223	38.87 392	72.35 306	69.11 351	56.98 200	62.37 318	80.96 277	37.01 319	79.00 283	31.43 440	73.05 265	81.36 286

pmmvs-eth3d		58.81 354	56.31 371	66.30 319	67.61 415	52.42 205	72.30 307	64.76 385	43.55 416	54.94 402	74.19 392	28.95 402	72.60 357	43.31 356	57.21 422	73.88 401

viewmambaseed2359dif		68.91 200	68.18 196	71.11 239	70.21 382	48.05 298	72.28 308	75.90 261	51.96 310	70.93 144	84.47 191	51.37 126	78.59 288	61.55 191	74.97 231	86.68 99

cascas		65.98 267	63.42 288	73.64 157	77.26 221	52.58 199	72.26 309	77.21 237	48.56 359	61.21 331	74.60 389	32.57 374	85.82 108	50.38 287	76.75 207	82.52 264

VPNet		67.52 237	68.11 199	65.74 332	79.18 149	36.80 415	72.17 310	72.83 317	62.04 81	67.79 211	85.83 157	48.88 162	76.60 334	51.30 280	72.97 266	83.81 221

MS-PatchMatch		62.42 316	61.46 314	65.31 342	75.21 276	52.10 209	72.05 311	74.05 299	46.41 391	57.42 377	74.36 390	34.35 343	77.57 309	45.62 333	73.67 248	66.26 450

mvs_anonymous		68.03 224	67.51 211	69.59 270	72.08 348	44.57 336	71.99 312	75.23 277	51.67 313	67.06 225	82.57 235	54.68 69	77.94 297	56.56 233	75.71 222	86.26 123

patch_mono-2		69.85 170	71.09 131	66.16 322	79.11 152	54.80 147	71.97 313	74.31 293	53.50 289	70.90 145	84.17 195	57.63 34	63.31 416	66.17 135	82.02 104	80.38 311

tfpn200view9		63.18 305	62.18 306	66.21 321	76.85 243	39.62 386	71.96 314	69.44 347	56.63 206	62.61 310	79.83 297	37.18 313	79.17 271	31.84 433	73.25 261	79.83 325

thres400		63.31 301	62.18 306	66.72 308	76.85 243	39.62 386	71.96 314	69.44 347	56.63 206	62.61 310	79.83 297	37.18 313	79.17 271	31.84 433	73.25 261	81.36 286

SD_0403		63.07 307	63.49 287	61.82 369	75.16 278	31.14 455	71.89 316	73.47 306	53.34 291	58.22 367	81.81 260	45.17 215	73.86 352	37.43 397	74.87 233	80.45 308

baseline1		63.81 297	63.87 279	63.62 356	76.29 254	36.36 418	71.78 317	67.29 363	56.05 225	64.23 286	82.95 224	47.11 187	74.41 349	47.30 316	61.85 398	80.10 319

baseline2		63.42 300	61.26 319	69.89 266	72.55 337	47.62 303	71.54 318	68.38 355	50.11 338	54.82 403	75.55 379	43.06 238	80.96 232	48.13 307	67.16 353	81.11 294

pmmvs4		61.48 331	59.39 338	67.76 297	71.57 357	53.86 159	71.42 319	65.34 380	44.20 410	59.46 351	77.92 334	35.90 326	74.71 347	43.87 351	64.87 369	74.71 393

1112_ss		64.00 296	63.36 289	65.93 328	79.28 144	42.58 357	71.35 320	72.36 322	46.41 391	60.55 337	77.89 337	46.27 199	73.28 354	46.18 326	69.97 314	81.92 276

thisisatest0515		65.83 269	63.50 286	72.82 183	73.75 314	49.50 267	71.32 321	73.12 316	49.39 348	63.82 289	76.50 366	34.95 336	84.84 134	53.20 265	75.49 225	84.13 209

CostFormer		64.04 295	62.51 300	68.61 287	71.88 352	45.77 319	71.30 322	70.60 335	47.55 377	64.31 283	76.61 362	41.63 259	79.62 260	49.74 291	69.00 334	80.42 309

tfpnnormal		62.47 314	61.63 312	64.99 345	74.81 287	39.01 391	71.22 323	73.72 304	55.22 246	60.21 338	80.09 295	41.26 267	76.98 324	30.02 447	68.09 344	78.97 338

IterMVS		62.79 310	61.27 318	67.35 304	69.37 398	52.04 212	71.17 324	68.24 357	52.63 304	59.82 346	76.91 354	37.32 312	72.36 359	52.80 267	63.19 385	77.66 353
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Vis-MVSNet (Re-imp)		63.69 298	63.88 278	63.14 361	74.75 289	31.04 456	71.16 325	63.64 397	56.32 218	59.80 347	84.99 173	44.51 222	75.46 344	39.12 388	80.62 121	82.92 251

IterMVS-SCA-FT		62.49 313	61.52 313	65.40 339	71.99 351	50.80 231	71.15 326	69.63 343	45.71 399	60.61 336	77.93 333	37.45 309	65.99 405	55.67 242	63.50 382	79.42 331

Anonymous202405211		66.84 253	65.99 252	69.40 274	80.19 126	42.21 361	71.11 327	71.31 329	58.80 158	67.90 202	86.39 136	29.83 395	79.65 258	49.60 295	78.78 165	86.33 116

Anonymous20240521		55.30 384	54.41 386	57.96 401	60.92 456	41.73 365	71.09 328	71.06 332	41.18 431	48.65 441	73.31 400	16.93 454	59.25 432	42.54 364	64.01 376	72.90 405

tpm2		62.07 321	60.10 334	67.99 295	72.79 332	43.86 343	71.05 329	66.85 368	43.14 421	62.77 305	75.39 383	38.32 301	80.80 238	41.69 371	68.88 335	79.32 332

TDRefinement		53.44 398	50.72 408	61.60 371	64.31 437	46.96 309	70.89 330	65.27 382	41.78 426	44.61 454	77.98 331	11.52 469	66.36 402	28.57 453	51.59 444	71.49 426

blended_shiyan6		62.46 315	60.71 330	67.71 298	69.14 402	43.42 347	70.82 331	76.52 251	51.50 319	57.64 372	71.37 416	39.38 285	79.08 277	47.36 314	62.67 388	80.65 305

blend_shiyan4		61.38 332	59.10 342	68.20 292	68.94 404	44.64 333	70.81 332	76.52 251	51.63 314	57.56 374	69.94 429	28.30 409	79.61 261	47.44 310	60.78 406	80.36 313

XVG-ACMP-BASELINE		64.36 291	62.23 305	70.74 248	72.35 344	52.45 204	70.80 333	78.45 210	53.84 282	59.87 345	81.10 273	16.24 457	79.32 267	55.64 244	71.76 284	80.47 307

mmtdpeth		60.40 341	59.12 341	64.27 351	69.59 394	48.99 278	70.67 334	70.06 339	54.96 259	62.78 304	73.26 402	27.00 423	67.66 391	58.44 222	45.29 457	76.16 372

XVG-OURS-SEG-HR		68.81 203	67.47 213	72.82 183	74.40 301	56.87 109	70.59 335	79.04 186	54.77 263	66.99 226	86.01 151	39.57 283	78.21 293	62.54 179	73.33 259	83.37 238

VNet		69.68 177	70.19 149	68.16 294	79.73 134	41.63 368	70.53 336	77.38 233	60.37 120	70.69 146	86.63 125	51.08 131	77.09 318	53.61 261	81.69 112	85.75 143

GA-MVS		65.53 273	63.70 282	71.02 243	70.87 372	48.10 294	70.48 337	74.40 291	56.69 203	64.70 278	76.77 356	33.66 353	81.10 227	55.42 246	70.32 307	83.87 219

MSDG		61.81 327	59.23 339	69.55 273	72.64 334	52.63 198	70.45 338	75.81 262	51.38 322	53.70 414	76.11 369	29.52 397	81.08 229	37.70 395	65.79 363	74.93 388

ab-mvs		66.65 257	66.42 241	67.37 303	76.17 256	41.73 365	70.41 339	76.14 257	53.99 277	65.98 247	83.51 215	49.48 150	76.24 340	48.60 302	73.46 256	84.14 208

fmvsm_s_conf0.5_n_7		69.54 183	69.67 158	69.15 281	73.47 321	51.41 221	70.35 340	73.34 308	57.05 198	68.41 186	85.83 157	49.86 145	72.84 356	71.86 84	76.83 205	83.19 244

EGC-MVSNET		42.47 428	38.48 436	54.46 419	74.33 303	48.73 284	70.33 341	51.10 452	0.03 489	0.18 490	67.78 441	13.28 463	66.49 401	18.91 472	50.36 448	48.15 469

MVSTER		67.16 246	65.58 259	71.88 205	70.37 381	49.70 262	70.25 342	78.45 210	51.52 318	69.16 177	80.37 286	38.45 298	82.50 196	60.19 200	71.46 289	83.44 237

reproduce_monomvs		62.56 312	61.20 321	66.62 313	70.62 375	44.30 338	70.13 343	73.13 315	54.78 262	61.13 332	76.37 367	25.63 433	75.63 343	58.75 219	60.29 411	79.93 321

XVG-OURS		68.76 206	67.37 216	72.90 180	74.32 304	57.22 99	70.09 344	78.81 192	55.24 245	67.79 211	85.81 160	36.54 322	78.28 292	62.04 184	75.74 221	83.19 244

HY-MVS	56.14 13	64.55 288	63.89 277	66.55 314	74.73 290	41.02 372	69.96 345	74.43 290	49.29 350	61.66 326	80.92 278	47.43 182	76.68 333	44.91 342	71.69 286	81.94 275

AllTest		57.08 368	54.65 382	64.39 349	71.44 361	49.03 275	69.92 346	67.30 361	45.97 396	47.16 445	79.77 299	17.47 451	67.56 394	33.65 421	59.16 415	76.57 368

testing3		56.54 372	55.92 374	58.41 395	77.52 213	27.93 466	69.72 347	56.36 436	54.75 264	58.63 363	77.80 339	20.88 449	71.75 366	25.31 463	62.25 395	75.53 379

sc_t1		59.76 346	57.84 357	65.54 334	74.87 284	42.95 355	69.61 348	64.16 392	48.90 355	58.68 360	77.12 349	28.19 411	72.35 360	43.75 354	55.28 430	81.31 289

FE-MVSNET3		64.34 292	63.57 284	66.66 312	72.44 342	40.74 378	69.60 349	76.80 248	53.21 292	61.73 325	77.92 334	41.92 252	77.68 307	46.23 325	72.25 280	81.57 280

thres200		62.20 320	61.16 322	65.34 341	75.38 273	39.99 382	69.60 349	69.29 349	55.64 235	61.87 322	76.99 352	37.07 318	78.96 284	31.28 441	73.28 260	77.06 362

tpmrst		58.24 359	58.70 347	56.84 406	66.97 419	34.32 436	69.57 351	61.14 417	47.17 384	58.58 364	71.60 413	41.28 266	60.41 426	49.20 297	62.84 387	75.78 376

PatchmatchNet		59.84 345	58.24 351	64.65 347	73.05 328	46.70 311	69.42 352	62.18 412	47.55 377	58.88 358	71.96 410	34.49 341	69.16 381	42.99 361	63.60 380	78.07 345
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
WB-MVSnew		59.66 348	59.69 336	59.56 383	75.19 277	35.78 427	69.34 353	64.28 389	46.88 387	61.76 324	75.79 375	40.61 274	65.20 408	32.16 429	71.21 291	77.70 352

GG-mvs-BLEND				62.34 366	71.36 365	37.04 413	69.20 354	57.33 433		54.73 405	65.48 452	30.37 386	77.82 302	34.82 417	74.93 232	72.17 418

HyFIR lowres test		65.67 271	63.01 295	73.67 154	79.97 131	55.65 129	69.07 355	75.52 269	42.68 424	63.53 292	77.95 332	40.43 275	81.64 211	46.01 328	71.91 283	83.73 227

UWE-MVS		60.18 342	59.78 335	61.39 375	77.67 204	33.92 441	69.04 356	63.82 395	48.56 359	64.27 284	77.64 344	27.20 420	70.40 376	33.56 424	76.24 211	79.83 325

test_post1							68.67 357				3.64 487	32.39 376	69.49 380	44.17 345

tt0320		58.59 355	56.81 365	63.92 354	75.46 270	41.32 370	68.63 358	64.06 393	47.05 385	56.19 388	74.19 392	30.34 387	71.36 367	39.92 383	55.45 429	79.09 334

testing222		62.29 319	61.31 317	65.25 343	77.87 195	38.53 396	68.34 359	66.31 373	56.37 217	63.15 299	77.58 345	28.47 407	76.18 342	37.04 401	76.65 209	81.05 298

tt0320-xc		58.33 358	56.41 370	64.08 352	75.79 261	41.34 369	68.30 360	62.72 405	47.90 372	56.29 387	74.16 394	28.53 406	71.04 370	41.50 375	52.50 442	79.88 323

Test_1112_low_res		62.32 317	61.77 310	64.00 353	79.08 153	39.53 388	68.17 361	70.17 337	43.25 419	59.03 357	79.90 296	44.08 226	71.24 369	43.79 352	68.42 341	81.25 290

tpm cat1		59.25 352	56.95 362	66.15 323	72.19 347	46.96 309	68.09 362	65.76 376	40.03 440	57.81 371	70.56 421	38.32 301	74.51 348	38.26 393	61.50 401	77.00 364

ppachtmachnet_test		58.06 362	55.38 378	66.10 325	69.51 395	48.99 278	68.01 363	66.13 375	44.50 407	54.05 412	70.74 420	32.09 379	72.34 361	36.68 406	56.71 426	76.99 366

tpmvs		58.47 356	56.95 362	63.03 363	70.20 383	41.21 371	67.90 364	67.23 364	49.62 345	54.73 405	70.84 419	34.14 344	76.24 340	36.64 407	61.29 402	71.64 423

testing91		64.46 289	63.80 280	66.47 315	78.43 173	40.06 381	67.63 365	69.59 344	59.06 153	63.18 297	78.05 330	34.05 345	76.99 323	48.30 305	75.87 219	82.37 268

CL-MVSNet_self_test		61.53 329	60.94 325	63.30 359	68.95 403	36.93 414	67.60 366	72.80 318	55.67 233	59.95 344	76.63 359	45.01 218	72.22 363	39.74 385	62.09 397	80.74 304

testing11		62.81 309	61.90 309	65.54 334	78.38 174	40.76 377	67.59 367	66.78 369	55.48 238	60.13 339	77.11 350	31.67 381	76.79 328	45.53 335	74.45 236	79.06 335

test_vis1_n_1920		58.86 353	59.06 343	58.25 396	63.76 438	43.14 352	67.49 368	66.36 372	40.22 438	65.89 251	71.95 411	31.04 382	59.75 430	59.94 203	64.90 368	71.85 421

tpm		57.34 366	58.16 352	54.86 416	71.80 354	34.77 431	67.47 369	56.04 440	48.20 367	60.10 340	76.92 353	37.17 315	53.41 459	40.76 377	65.01 367	76.40 370

testing99		64.05 294	63.29 292	66.34 317	78.17 186	39.76 385	67.33 370	68.00 358	58.60 164	63.03 300	78.10 329	32.57 374	76.94 325	48.22 306	75.58 223	82.34 269

FE-MVSNET		55.16 388	53.75 394	59.41 385	65.29 432	33.20 445	67.21 371	66.21 374	48.39 365	49.56 439	73.53 399	29.03 401	72.51 358	30.38 445	54.10 436	72.52 410

gg-mvs-nofinetune		57.86 363	56.43 369	62.18 367	72.62 335	35.35 428	66.57 372	56.33 437	50.65 332	57.64 372	57.10 464	30.65 384	76.36 338	37.38 398	78.88 162	74.82 390

TinyColmap		54.14 391	51.72 403	61.40 374	66.84 421	41.97 362	66.52 373	68.51 354	44.81 403	42.69 459	75.77 376	11.66 467	72.94 355	31.96 431	56.77 425	69.27 444

pmmvs5		56.47 374	55.68 376	58.86 392	61.41 450	36.71 416	66.37 374	62.75 404	40.38 437	53.70 414	76.62 360	34.56 339	67.05 397	40.02 381	65.27 365	72.83 406

CHOSEN 1792x2688		65.08 281	62.84 297	71.82 207	81.49 100	56.26 115	66.32 375	74.20 298	40.53 436	63.16 298	78.65 321	41.30 264	77.80 303	45.80 330	74.09 240	81.40 285

our_test_3		56.49 373	54.42 385	62.68 365	69.51 395	45.48 325	66.08 376	61.49 415	44.11 413	50.73 433	69.60 433	33.05 358	68.15 386	38.38 392	56.86 423	74.40 395

mvs5depth		55.64 382	53.81 393	61.11 378	59.39 459	40.98 376	65.89 377	68.28 356	50.21 337	58.11 369	75.42 382	17.03 453	67.63 393	43.79 352	46.21 454	74.73 392

PM-MVS		52.33 402	50.19 411	58.75 393	62.10 447	45.14 328	65.75 378	40.38 475	43.60 415	53.52 418	72.65 403	9.16 475	65.87 406	50.41 286	54.18 435	65.24 452

D2MVS		62.30 318	60.29 333	68.34 291	66.46 425	48.42 290	65.70 379	73.42 307	47.71 375	58.16 368	75.02 385	30.51 385	77.71 306	53.96 258	71.68 287	78.90 339

MIMVSNet1		55.17 387	54.31 388	57.77 403	70.03 387	32.01 451	65.68 380	64.81 384	49.19 351	46.75 448	76.00 371	25.53 434	64.04 412	28.65 452	62.13 396	77.26 360

PatchMatch-RL		56.25 377	54.55 384	61.32 376	77.06 234	56.07 119	65.57 381	54.10 446	44.13 412	53.49 420	71.27 418	25.20 435	66.78 399	36.52 409	63.66 379	61.12 454

Syy-MVS		56.00 379	56.23 372	55.32 413	74.69 291	26.44 472	65.52 382	57.49 431	50.97 329	56.52 384	72.18 406	39.89 279	68.09 387	24.20 464	64.59 373	71.44 427

myMVS_eth3d		54.86 390	54.61 383	55.61 412	74.69 291	27.31 469	65.52 382	57.49 431	50.97 329	56.52 384	72.18 406	21.87 447	68.09 387	27.70 455	64.59 373	71.44 427

test-LLR		58.15 361	58.13 354	58.22 397	68.57 407	44.80 330	65.46 384	57.92 428	50.08 339	55.44 394	69.82 430	32.62 371	57.44 442	49.66 293	73.62 250	72.41 414

TESTMET0.1,1		55.28 385	54.90 381	56.42 408	66.56 423	43.67 345	65.46 384	56.27 438	39.18 443	53.83 413	67.44 442	24.21 439	55.46 453	48.04 308	73.11 264	70.13 438

test-mter		56.42 375	55.82 375	58.22 397	68.57 407	44.80 330	65.46 384	57.92 428	39.94 441	55.44 394	69.82 430	21.92 444	57.44 442	49.66 293	73.62 250	72.41 414

SDMVSNet		68.03 224	68.10 200	67.84 296	77.13 229	48.72 285	65.32 387	79.10 183	58.02 176	65.08 269	82.55 236	47.83 172	73.40 353	63.92 158	73.92 243	81.41 283

CR-MVSNet		59.91 344	57.90 356	65.96 327	69.96 388	52.07 210	65.31 388	63.15 402	42.48 425	59.36 352	74.84 386	35.83 327	70.75 372	45.50 336	64.65 371	75.06 384

RPMNet		61.53 329	58.42 349	70.86 245	69.96 388	52.07 210	65.31 388	81.36 135	43.20 420	59.36 352	70.15 426	35.37 331	85.47 118	36.42 410	64.65 371	75.06 384

USDC		56.35 376	54.24 389	62.69 364	64.74 434	40.31 379	65.05 390	73.83 303	43.93 414	47.58 443	77.71 343	15.36 460	75.05 346	38.19 394	61.81 399	72.70 407

MDTV_nov1_ep13			57.00 361		72.73 333	38.26 399	65.02 391	64.73 386	44.74 404	55.46 393	72.48 404	32.61 373	70.47 373	37.47 396	67.75 347

ETVMVS		59.51 351	58.81 344	61.58 372	77.46 215	34.87 429	64.94 392	59.35 422	54.06 276	61.08 333	76.67 358	29.54 396	71.87 365	32.16 429	74.07 241	78.01 350

CMPMVS	42.80 21	57.81 364	55.97 373	63.32 358	60.98 454	47.38 306	64.66 393	69.50 346	32.06 454	46.83 447	77.80 339	29.50 398	71.36 367	48.68 301	73.75 246	71.21 430
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
WBMVS		60.54 338	60.61 331	60.34 381	78.00 192	35.95 425	64.55 394	64.89 383	49.63 344	63.39 294	78.70 318	33.85 350	67.65 392	42.10 368	70.35 306	77.43 356

IMVS_0404		64.63 286	64.22 274	65.88 330	77.06 234	49.73 258	64.40 395	78.60 199	52.70 298	53.16 421	82.58 231	34.82 337	65.16 409	59.20 212	75.46 226	82.74 256

RPSCF		55.80 381	54.22 390	60.53 380	65.13 433	42.91 356	64.30 396	57.62 430	36.84 447	58.05 370	82.28 245	28.01 412	56.24 450	37.14 400	58.61 417	82.44 267

XXY-MVS		60.68 335	61.67 311	57.70 404	70.43 379	38.45 397	64.19 397	66.47 370	48.05 370	63.22 295	80.86 280	49.28 155	60.47 425	45.25 341	67.28 352	74.19 398

FMVSNet5		55.86 380	54.93 380	58.66 394	71.05 370	36.35 419	64.18 398	62.48 407	46.76 389	50.66 434	74.73 388	25.80 431	64.04 412	33.11 425	65.57 364	75.59 378

UBG		59.62 350	59.53 337	59.89 382	78.12 187	35.92 426	64.11 399	60.81 419	49.45 347	61.34 329	75.55 379	33.05 358	67.39 396	38.68 390	74.62 234	76.35 371

testing3-2		62.06 322	62.36 303	61.17 377	79.29 142	30.31 458	64.09 400	63.49 398	63.50 44	62.84 303	82.22 247	32.35 378	69.02 383	40.01 382	73.43 257	84.17 207

icg_test_0407_2		66.41 263	66.75 233	65.37 340	77.06 234	49.73 258	63.79 401	78.60 199	52.70 298	66.19 242	82.58 231	45.17 215	63.65 415	59.20 212	75.46 226	82.74 256

test_cas_vis1_n_1920		56.91 369	56.71 366	57.51 405	59.13 460	45.40 326	63.58 402	61.29 416	36.24 448	67.14 224	71.85 412	29.89 394	56.69 446	57.65 225	63.58 381	70.46 435

UWE-MVS-28		52.25 403	52.35 401	51.93 437	66.99 418	22.79 480	63.48 403	48.31 461	46.78 388	52.73 423	76.11 369	27.78 415	57.82 441	20.58 470	68.41 342	75.17 382

SCA		60.49 339	58.38 350	66.80 307	74.14 310	48.06 296	63.35 404	63.23 401	49.13 352	59.33 355	72.10 408	37.45 309	74.27 350	44.17 345	62.57 391	78.05 346

myMVS_eth3d28		60.66 336	61.04 323	59.51 384	77.32 219	31.58 453	63.11 405	63.87 394	59.00 154	60.90 335	78.26 327	32.69 369	66.15 404	36.10 412	78.13 181	80.81 302

Patchmtry		57.16 367	56.47 368	59.23 388	69.17 401	34.58 434	62.98 406	63.15 402	44.53 406	56.83 381	74.84 386	35.83 327	68.71 384	40.03 380	60.91 403	74.39 396

Anonymous20231206		55.10 389	55.30 379	54.48 418	69.81 393	33.94 440	62.91 407	62.13 413	41.08 432	55.18 399	75.65 377	32.75 366	56.59 448	30.32 446	67.86 345	72.91 404

sd_testset		64.46 289	64.45 272	64.51 348	77.13 229	42.25 360	62.67 408	72.11 324	58.02 176	65.08 269	82.55 236	41.22 269	69.88 379	47.32 315	73.92 243	81.41 283

MIMVSNet		57.35 365	57.07 360	58.22 397	74.21 307	37.18 409	62.46 409	60.88 418	48.88 356	55.29 398	75.99 373	31.68 380	62.04 421	31.87 432	72.35 276	75.43 381

dp		51.89 405	51.60 404	52.77 431	68.44 411	32.45 450	62.36 410	54.57 443	44.16 411	49.31 440	67.91 438	28.87 404	56.61 447	33.89 420	54.89 432	69.24 445

EPMVS		53.96 392	53.69 395	54.79 417	66.12 428	31.96 452	62.34 411	49.05 457	44.42 409	55.54 392	71.33 417	30.22 389	56.70 445	41.65 373	62.54 392	75.71 377

pmmvs3		44.92 423	41.95 430	53.86 421	52.58 469	43.55 346	62.11 412	46.90 467	26.05 465	40.63 461	60.19 460	11.08 472	57.91 440	31.83 436	46.15 455	60.11 455

test_vis1_n		49.89 414	48.69 416	53.50 425	53.97 464	37.38 408	61.53 413	47.33 465	28.54 459	59.62 350	67.10 446	13.52 462	52.27 463	49.07 298	57.52 420	70.84 433

PVSNet	50.76 19	58.40 357	57.39 358	61.42 373	75.53 268	44.04 342	61.43 414	63.45 399	47.04 386	56.91 380	73.61 398	27.00 423	64.76 410	39.12 388	72.40 275	75.47 380

LCM-MVSNet-Re		61.88 326	61.35 316	63.46 357	74.58 296	31.48 454	61.42 415	58.14 427	58.71 161	53.02 422	79.55 306	43.07 237	76.80 327	45.69 331	77.96 184	82.11 274

test20.03		53.87 394	54.02 391	53.41 427	61.47 449	28.11 465	61.30 416	59.21 423	51.34 324	52.09 425	77.43 346	33.29 357	58.55 437	29.76 448	60.27 412	73.58 402

MDTV_nov1_ep13_2view						25.89 474	61.22 417		40.10 439	51.10 428		32.97 361		38.49 391		78.61 341

PMMVS		53.96 392	53.26 398	56.04 409	62.60 445	50.92 228	61.17 418	56.09 439	32.81 453	53.51 419	66.84 447	34.04 346	59.93 429	44.14 347	68.18 343	57.27 462

test_fmvs1_n		51.37 407	50.35 410	54.42 420	52.85 467	37.71 405	61.16 419	51.93 448	28.15 460	63.81 290	69.73 432	13.72 461	53.95 457	51.16 281	60.65 408	71.59 424

WTY-MVS		59.75 347	60.39 332	57.85 402	72.32 345	37.83 403	61.05 420	64.18 390	45.95 398	61.91 321	79.11 315	47.01 191	60.88 424	42.50 365	69.49 326	74.83 389

dmvs_testset		50.16 412	51.90 402	44.94 448	66.49 424	11.78 488	61.01 421	51.50 450	51.17 327	50.30 437	67.44 442	39.28 287	60.29 427	22.38 467	57.49 421	62.76 453

Patchmatch-RL test		58.16 360	55.49 377	66.15 323	67.92 414	48.89 282	60.66 422	51.07 453	47.86 374	59.36 352	62.71 458	34.02 347	72.27 362	56.41 234	59.40 414	77.30 358

test_fmvs1		51.32 409	50.48 409	53.81 422	53.57 465	37.51 407	60.63 423	51.16 451	28.02 462	63.62 291	69.23 435	16.41 456	53.93 458	51.01 282	60.70 407	69.99 439

LTVRE_ROB	55.42 16	63.15 306	61.23 320	68.92 283	76.57 250	47.80 299	59.92 424	76.39 253	54.35 272	58.67 361	82.46 241	29.44 399	81.49 216	42.12 367	71.14 292	77.46 355
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		60.57 337	61.39 315	58.12 400	74.29 305	32.63 448	59.52 425	65.53 379	59.90 134	62.45 315	79.75 301	41.96 249	63.90 414	39.47 386	69.65 325	77.84 351

test0.0.03 1		53.32 399	53.59 396	52.50 433	62.81 444	29.45 460	59.51 426	54.11 445	50.08 339	54.40 409	74.31 391	32.62 371	55.92 451	30.50 444	63.95 378	72.15 419

UnsupCasMVSNet_eth		53.16 401	52.47 399	55.23 414	59.45 458	33.39 444	59.43 427	69.13 350	45.98 395	50.35 436	72.32 405	29.30 400	58.26 439	42.02 370	44.30 458	74.05 399

MVS-HIRNet		45.52 422	44.48 424	48.65 442	68.49 410	34.05 439	59.41 428	44.50 470	27.03 463	37.96 470	50.47 472	26.16 429	64.10 411	26.74 460	59.52 413	47.82 471

testgi		51.90 404	52.37 400	50.51 440	60.39 457	23.55 479	58.42 429	58.15 426	49.03 353	51.83 426	79.21 314	22.39 442	55.59 452	29.24 451	62.64 390	72.40 416

dmvs_re		56.77 371	56.83 364	56.61 407	69.23 399	41.02 372	58.37 430	64.18 390	50.59 334	57.45 376	71.42 414	35.54 329	58.94 435	37.23 399	67.45 350	69.87 440

PatchT		53.17 400	53.44 397	52.33 434	68.29 412	25.34 476	58.21 431	54.41 444	44.46 408	54.56 407	69.05 436	33.32 356	60.94 423	36.93 402	61.76 400	70.73 434

WB-MVS		43.26 425	43.41 425	42.83 452	63.32 441	10.32 490	58.17 432	45.20 468	45.42 400	40.44 463	67.26 445	34.01 348	58.98 434	11.96 481	24.88 475	59.20 456

sss		56.17 378	56.57 367	54.96 415	66.93 420	36.32 421	57.94 433	61.69 414	41.67 428	58.64 362	75.32 384	38.72 296	56.25 449	42.04 369	66.19 360	72.31 417

ttmdpeth		45.56 421	42.95 426	53.39 428	52.33 470	29.15 461	57.77 434	48.20 462	31.81 455	49.86 438	77.21 348	8.69 476	59.16 433	27.31 456	33.40 472	71.84 422

test_fmvs2		48.69 416	47.49 421	52.29 435	48.63 474	33.06 447	57.76 435	48.05 463	25.71 466	59.76 348	69.60 433	11.57 468	52.23 464	49.45 296	56.86 423	71.58 425

KD-MVS_self_test		55.22 386	53.89 392	59.21 389	57.80 463	27.47 468	57.75 436	74.32 292	47.38 379	50.90 430	70.00 427	28.45 408	70.30 377	40.44 378	57.92 419	79.87 324

UnsupCasMVSNet_bld		50.07 413	48.87 414	53.66 423	60.97 455	33.67 442	57.62 437	64.56 387	39.47 442	47.38 444	64.02 456	27.47 417	59.32 431	34.69 418	43.68 459	67.98 448

mamv4		56.85 370	58.00 355	53.43 426	72.46 341	54.47 149	57.56 438	54.74 441	38.81 444	57.42 377	79.45 309	47.57 178	38.70 479	60.88 195	53.07 439	67.11 449

SSC-MVS		41.96 430	41.99 429	41.90 453	62.46 446	9.28 492	57.41 439	44.32 471	43.38 417	38.30 469	66.45 448	32.67 370	58.42 438	10.98 482	21.91 478	57.99 460

ANet_high		41.38 431	37.47 438	53.11 429	39.73 485	24.45 477	56.94 440	69.69 341	47.65 376	26.04 477	52.32 467	12.44 465	62.38 420	21.80 468	10.61 486	72.49 411

MDA-MVSNet-bldmvs		53.87 394	50.81 407	63.05 362	66.25 426	48.58 288	56.93 441	63.82 395	48.09 369	41.22 460	70.48 424	30.34 387	68.00 390	34.24 419	45.92 456	72.57 409

test123		4.73 457	6.30 460	0.02 472	0.01 495	0.01 497	56.36 442	0.00 496	0.01 490	0.04 491	0.21 491	0.01 494	0.00 491	0.03 491	0.00 489	0.04 487

miper_lstm_enhance		62.03 323	60.88 326	65.49 337	66.71 422	46.25 314	56.29 443	75.70 264	50.68 331	61.27 330	75.48 381	40.21 276	68.03 389	56.31 235	65.25 366	82.18 271

KD-MVS_2432*1600		53.45 396	51.50 405	59.30 386	62.82 442	37.14 410	55.33 444	71.79 327	47.34 381	55.09 400	70.52 422	21.91 445	70.45 374	35.72 414	42.97 460	70.31 436

miper_refine_blended		53.45 396	51.50 405	59.30 386	62.82 442	37.14 410	55.33 444	71.79 327	47.34 381	55.09 400	70.52 422	21.91 445	70.45 374	35.72 414	42.97 460	70.31 436

LF4IMVS		42.95 426	42.26 428	45.04 446	48.30 475	32.50 449	54.80 446	48.49 459	28.03 461	40.51 462	70.16 425	9.24 474	43.89 474	31.63 437	49.18 452	58.72 458

PMVS	28.69 22	36.22 438	33.29 443	45.02 447	36.82 487	35.98 424	54.68 447	48.74 458	26.31 464	21.02 480	51.61 469	2.88 488	60.10 428	9.99 485	47.58 453	38.99 478
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVStest1		42.65 427	39.29 434	52.71 432	47.26 477	34.58 434	54.41 448	50.84 456	23.35 468	39.31 468	74.08 395	12.57 464	55.09 454	23.32 465	28.47 474	68.47 447

PVSNet_0	43.31 20	47.46 420	45.64 423	52.92 430	67.60 416	44.65 332	54.06 449	54.64 442	41.59 429	46.15 450	58.75 461	30.99 383	58.66 436	32.18 428	24.81 476	55.46 464

testmvs		4.52 458	6.03 461	0.01 473	0.01 495	0.00 498	53.86 450	0.00 496	0.01 490	0.04 491	0.27 490	0.00 495	0.00 491	0.04 490	0.00 489	0.03 488

test_fmvs3		44.30 424	42.55 427	49.55 441	42.83 479	27.15 471	53.03 451	44.93 469	22.03 474	53.69 416	64.94 453	4.21 483	49.63 466	47.47 309	49.82 449	71.88 420

APD_test1		37.39 437	34.94 440	44.72 449	48.88 473	33.19 446	52.95 452	44.00 472	19.49 475	27.28 476	58.59 462	3.18 487	52.84 461	18.92 471	41.17 463	48.14 470

dongtai		34.52 440	34.94 440	33.26 462	61.06 453	16.00 487	52.79 453	23.78 488	40.71 435	39.33 467	48.65 476	16.91 455	48.34 468	12.18 480	19.05 480	35.44 479

YYNet1		50.73 410	48.96 412	56.03 410	61.10 452	41.78 364	51.94 454	56.44 435	40.94 434	44.84 452	67.80 440	30.08 392	55.08 455	36.77 403	50.71 446	71.22 429

MDA-MVSNet_test_wron		50.71 411	48.95 413	56.00 411	61.17 451	41.84 363	51.90 455	56.45 434	40.96 433	44.79 453	67.84 439	30.04 393	55.07 456	36.71 405	50.69 447	71.11 432

kuosan		29.62 447	30.82 446	26.02 467	52.99 466	16.22 486	51.09 456	22.71 489	33.91 452	33.99 471	40.85 477	15.89 458	33.11 484	7.59 488	18.37 481	28.72 481

ADS-MVSNet2		51.33 408	48.76 415	59.07 391	66.02 429	44.60 335	50.90 457	59.76 421	36.90 445	50.74 431	66.18 450	26.38 426	63.11 417	27.17 457	54.76 433	69.50 442

ADS-MVSNet		48.48 417	47.77 418	50.63 439	66.02 429	29.92 459	50.90 457	50.87 455	36.90 445	50.74 431	66.18 450	26.38 426	52.47 462	27.17 457	54.76 433	69.50 442

mamba_0408		67.78 232	65.42 261	74.85 103	78.65 164	53.46 171	50.83 459	79.09 184	53.75 283	68.14 194	83.83 204	41.79 256	86.56 81	56.58 231	76.11 213	84.54 192

SSM_04072		64.98 282	65.42 261	63.68 355	78.65 164	53.46 171	50.83 459	79.09 184	53.75 283	68.14 194	83.83 204	41.79 256	53.03 460	56.58 231	76.11 213	84.54 192

FPMVS		42.18 429	41.11 431	45.39 445	58.03 462	41.01 374	49.50 461	53.81 447	30.07 457	33.71 472	64.03 454	11.69 466	52.08 465	14.01 476	55.11 431	43.09 473

N_pmnet		39.35 435	40.28 432	36.54 459	63.76 438	1.62 496	49.37 462	0.76 495	34.62 451	43.61 457	66.38 449	26.25 428	42.57 475	26.02 462	51.77 443	65.44 451

new-patchmatchnet		47.56 419	47.73 419	47.06 443	58.81 461	9.37 491	48.78 463	59.21 423	43.28 418	44.22 455	68.66 437	25.67 432	57.20 444	31.57 439	49.35 451	74.62 394

test_vis1_rt		41.35 432	39.45 433	47.03 444	46.65 478	37.86 402	47.76 464	38.65 476	23.10 470	44.21 456	51.22 470	11.20 471	44.08 473	39.27 387	53.02 440	59.14 457

JIA-IIPM		51.56 406	47.68 420	63.21 360	64.61 435	50.73 235	47.71 465	58.77 425	42.90 422	48.46 442	51.72 468	24.97 436	70.24 378	36.06 413	53.89 437	68.64 446

ambc				65.13 344	63.72 440	37.07 412	47.66 466	78.78 194		54.37 410	71.42 414	11.24 470	80.94 233	45.64 332	53.85 438	77.38 357

testf1		31.46 445	28.89 449	39.16 455	41.99 482	28.78 463	46.45 467	37.56 477	14.28 482	21.10 478	48.96 473	1.48 491	47.11 469	13.63 477	34.56 469	41.60 474

APD_test2		31.46 445	28.89 449	39.16 455	41.99 482	28.78 463	46.45 467	37.56 477	14.28 482	21.10 478	48.96 473	1.48 491	47.11 469	13.63 477	34.56 469	41.60 474

Patchmatch-test		49.08 415	48.28 417	51.50 438	64.40 436	30.85 457	45.68 469	48.46 460	35.60 449	46.10 451	72.10 408	34.47 342	46.37 471	27.08 459	60.65 408	77.27 359

DSMNet-mixed		39.30 436	38.72 435	41.03 454	51.22 471	19.66 483	45.53 470	31.35 482	15.83 481	39.80 465	67.42 444	22.19 443	45.13 472	22.43 466	52.69 441	58.31 459

LCM-MVSNet		40.30 433	35.88 439	53.57 424	42.24 480	29.15 461	45.21 471	60.53 420	22.23 473	28.02 475	50.98 471	3.72 485	61.78 422	31.22 442	38.76 466	69.78 441

new_pmnet		34.13 441	34.29 442	33.64 461	52.63 468	18.23 485	44.43 472	33.90 481	22.81 471	30.89 474	53.18 466	10.48 473	35.72 483	20.77 469	39.51 464	46.98 472

mvsany_test1		39.38 434	38.16 437	43.02 451	49.05 472	34.28 437	44.16 473	25.94 486	22.74 472	46.57 449	62.21 459	23.85 440	41.16 478	33.01 426	35.91 468	53.63 465

E-PMN		23.77 449	22.73 453	26.90 465	42.02 481	20.67 482	42.66 474	35.70 479	17.43 477	10.28 487	25.05 483	6.42 478	42.39 476	10.28 484	14.71 483	17.63 482

EMVS		22.97 450	21.84 454	26.36 466	40.20 484	19.53 484	41.95 475	34.64 480	17.09 478	9.73 488	22.83 484	7.29 477	42.22 477	9.18 486	13.66 484	17.32 483

test_vis3_rt		32.09 443	30.20 448	37.76 458	35.36 489	27.48 467	40.60 476	28.29 485	16.69 479	32.52 473	40.53 478	1.96 489	37.40 481	33.64 423	42.21 462	48.39 468

CHOSEN 280x420		47.83 418	46.36 422	52.24 436	67.37 417	49.78 257	38.91 477	43.11 473	35.00 450	43.27 458	63.30 457	28.95 402	49.19 467	36.53 408	60.80 405	57.76 461

mvsany_test3		32.62 442	30.57 447	38.77 457	36.16 488	24.20 478	38.10 478	20.63 490	19.14 476	40.36 464	57.43 463	5.06 480	36.63 482	29.59 450	28.66 473	55.49 463

test_f		31.86 444	31.05 445	34.28 460	32.33 491	21.86 481	32.34 479	30.46 483	16.02 480	39.78 466	55.45 465	4.80 481	32.36 485	30.61 443	37.66 467	48.64 467

PMMVS2		27.40 448	25.91 451	31.87 464	39.46 486	6.57 493	31.17 480	28.52 484	23.96 467	20.45 481	48.94 475	4.20 484	37.94 480	16.51 473	19.97 479	51.09 466

wuyk23d		13.32 454	12.52 457	15.71 469	47.54 476	26.27 473	31.06 481	1.98 494	4.93 486	5.18 489	1.94 489	0.45 493	18.54 488	6.81 489	12.83 485	2.33 486

Gipuma		34.77 439	31.91 444	43.33 450	62.05 448	37.87 401	20.39 482	67.03 366	23.23 469	18.41 482	25.84 482	4.24 482	62.73 418	14.71 475	51.32 445	29.38 480
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVE	17.77 23	21.41 451	17.77 456	32.34 463	34.34 490	25.44 475	16.11 483	24.11 487	11.19 484	13.22 484	31.92 480	1.58 490	30.95 486	10.47 483	17.03 482	40.62 477
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
tmp_tt		9.43 455	11.14 458	4.30 471	2.38 494	4.40 494	13.62 484	16.08 492	0.39 488	15.89 483	13.06 485	15.80 459	5.54 490	12.63 479	10.46 487	2.95 485

test_method		19.68 452	18.10 455	24.41 468	13.68 493	3.11 495	12.06 485	42.37 474	2.00 487	11.97 485	36.38 479	5.77 479	29.35 487	15.06 474	23.65 477	40.76 476

mmdepth		0.00 460	0.00 463	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	0.00 492	0.00 495	0.00 491	0.00 492	0.00 489	0.00 489

monomultidepth		0.00 460	0.00 463	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	0.00 492	0.00 495	0.00 491	0.00 492	0.00 489	0.00 489

test_blank		0.00 460	0.00 463	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	0.00 492	0.00 495	0.00 491	0.00 492	0.00 489	0.00 489

uanet_test		0.00 460	0.00 463	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	0.00 492	0.00 495	0.00 491	0.00 492	0.00 489	0.00 489

DCPMVS		0.00 460	0.00 463	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	0.00 492	0.00 495	0.00 491	0.00 492	0.00 489	0.00 489

cdsmvs_eth3d_5k		17.50 453	23.34 452	0.00 474	0.00 497	0.00 498	0.00 486	78.63 198	0.00 492	0.00 493	82.18 248	49.25 156	0.00 491	0.00 492	0.00 489	0.00 489

pcd_1.5k_mvsjas		3.92 459	5.23 462	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	0.00 492	47.05 188	0.00 491	0.00 492	0.00 489	0.00 489

sosnet-low-res		0.00 460	0.00 463	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	0.00 492	0.00 495	0.00 491	0.00 492	0.00 489	0.00 489

sosnet		0.00 460	0.00 463	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	0.00 492	0.00 495	0.00 491	0.00 492	0.00 489	0.00 489

uncertanet		0.00 460	0.00 463	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	0.00 492	0.00 495	0.00 491	0.00 492	0.00 489	0.00 489

Regformer		0.00 460	0.00 463	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	0.00 492	0.00 495	0.00 491	0.00 492	0.00 489	0.00 489

ab-mvs-re		6.49 456	8.65 459	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	77.89 337	0.00 495	0.00 491	0.00 492	0.00 489	0.00 489

uanet		0.00 460	0.00 463	0.00 474	0.00 497	0.00 498	0.00 486	0.00 496	0.00 492	0.00 493	0.00 492	0.00 495	0.00 491	0.00 492	0.00 489	0.00 489

WAC-MVS						27.31 469								27.77 454

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 51

PC_three_1452									55.09 249	84.46 4	89.84 52	66.68 5	89.41 22	74.24 61	91.38 2	88.42 28

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 51

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					0.00 497

eth-test					0.00 497

ZD-MVS					86.64 21	60.38 45		82.70 112	57.95 180	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	53.93 279	84.64 3				79.07 13	90.87 5	88.37 30

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 60

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 44

GSMVS																78.05 346

test_part2					87.58 9	60.47 42				83.42 15

sam_mvs1												34.74 338				78.05 346

sam_mvs												33.43 355

MTGPA								80.97 153

test_post											3.55 488	33.90 349	66.52 400

patchmatchnet-post											64.03 454	34.50 340	74.27 350

gm-plane-assit					71.40 364	41.72 367			48.85 357		73.31 400		82.48 198	48.90 300

test9_res														75.28 54	88.31 36	83.81 221

agg_prior2														73.09 72	87.93 44	84.33 199

agg_prior					85.04 54	59.96 50		81.04 151		74.68 72			84.04 146

TestCases				64.39 349	71.44 361	49.03 275		67.30 361	45.97 396	47.16 445	79.77 299	17.47 451	67.56 394	33.65 421	59.16 415	76.57 368

test_prior				76.69 65	84.20 65	57.27 98		84.88 44					86.43 88			86.38 110

新几何1				70.76 247	85.66 42	61.13 30		66.43 371	44.68 405	70.29 152	86.64 123	41.29 265	75.23 345	49.72 292	81.75 110	75.93 374

旧先验1					83.04 78	53.15 181		67.52 360			87.85 86	44.08 226			80.76 119	78.03 349

原ACMM1				74.69 106	85.39 48	59.40 59		83.42 86	51.47 321	70.27 153	86.61 127	48.61 164	86.51 86	53.85 259	87.96 43	78.16 344

testdata2													72.18 364	46.95 321

segment_acmp												54.23 73

testdata				64.66 346	81.52 98	52.93 186		65.29 381	46.09 394	73.88 88	87.46 93	38.08 305	66.26 403	53.31 264	78.48 175	74.78 391

test12				77.76 50	84.52 62	58.41 83		83.36 89		72.93 114		54.61 70	88.05 43		88.12 38	86.81 93

plane_prior7					81.41 101	55.96 121

plane_prior6					81.20 108	56.24 116						45.26 213

plane_prior5								84.01 57					87.21 63	68.16 108	80.58 123	84.65 190

plane_prior4											86.10 146

plane_prior3						56.09 118			63.92 38	69.27 173

plane_prior1					81.27 106

n2								0.00 496

nn								0.00 496

door-mid								47.19 466

lessismore_v0				69.91 264	71.42 363	47.80 299		50.90 454		50.39 435	75.56 378	27.43 419	81.33 220	45.91 329	34.10 471	80.59 306

LGP-MVS_train				75.76 83	80.22 123	57.51 96		83.40 87	61.32 92	66.67 234	87.33 99	39.15 290	86.59 79	67.70 116	77.30 198	83.19 244

test11								83.47 84

door								47.60 464

HQP5-MVS						54.94 143

BP-MVS														67.04 126

HQP4-MVS										67.85 204			86.93 71			84.32 200

HQP3-MVS								83.90 62							80.35 127

HQP2-MVS												45.46 207

NP-MVS					80.98 111	56.05 120					85.54 167

ACMMP++_ref															74.07 241

ACMMP++															72.16 281

Test By Simon												48.33 167

ITE_SJBPF				62.09 368	66.16 427	44.55 337		64.32 388	47.36 380	55.31 397	80.34 288	19.27 450	62.68 419	36.29 411	62.39 393	79.04 336

DeepMVS_CX				12.03 470	17.97 492	10.91 489		10.60 493	7.46 485	11.07 486	28.36 481	3.28 486	11.29 489	8.01 487	9.74 488	13.89 484

High-resolution multi-view benchmark