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	17.08 492

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	6.49 487	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	75.51 271	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	78.30 343

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	72.39 322	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	38.37 300	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	38.51 298	83.17 166	60.65 197	76.10 216	80.30 315
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	46.45 324	78.88 162	77.02 364

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	48.22 367	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	79.97 321

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	28.28 411	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	27.45 419	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	73.16 315	53.06 293	59.09 356	82.35 242	36.79 322	85.94 105	32.82 428	69.96 315	72.45 413

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	27.68 417	84.17 143	45.54 335	69.78 319	79.90 323

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	76.06 260	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	74.72 288	48.50 363	56.62 383	84.62 183	33.59 355	82.34 200	29.65 450	75.23 230	75.97 374

UGNet		68.81 203	67.39 215	73.06 176	78.33 179	54.47 149	79.77 117	75.40 274	60.45 115	63.22 295	84.40 192	32.71 368	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	71.08 331	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	74.30 295	48.40 365				80.78 239	53.62 260		79.03 338

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	56.59 384	80.98 276	27.12 422	80.94 233	42.90 364	71.58 288	77.25 362
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	74.96 286	56.64 205	74.76 71	88.75 71	55.02 64	78.77 288	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	75.27 276	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	35.25 333	77.41 312	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	48.51 362	55.71 392	81.89 257	33.71 352	79.71 257	41.66 373	70.37 304	77.58 355
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	61.27 335	58.81 345	68.64 286	74.63 293	52.51 201	78.42 142	73.30 311	49.92 343	50.96 430	81.51 267	23.06 442	79.40 265	31.63 438	65.85 361	74.01 401
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	30.16 391	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	30.16 391	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	62.26 412	49.78 344	73.12 109	86.21 142	52.66 101	76.79 329	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	75.40 274	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	75.56 269	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	73.31 310	53.98 278	76.81 45	88.05 80	53.38 90	77.37 314	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	62.30 411	49.35 350	73.20 103	86.55 132	51.99 114	76.79 329	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	76.16 256	47.97 372	52.41 425	81.61 264	27.87 414	78.11 295	40.07 380	66.66 356	77.00 365

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	67.96 414	55.58 133	78.06 158	74.67 289	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	56.03 391	77.41 347	24.75 439	84.04 146	46.37 325	73.42 258	73.14 404

fmvsm_s_conf0.5_n		69.58 181	68.84 176	71.79 209	72.31 346	52.90 187	77.90 160	62.43 410	49.97 342	72.85 117	85.90 154	52.21 109	76.49 336	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	77.75 305	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	73.99 302	54.54 269	64.64 279	82.53 239	35.06 335	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	62.44 409	49.58 347	72.97 112	86.22 141	51.68 121	76.48 337	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	70.71 335	51.49 320	61.57 328	83.58 214	38.23 304	70.82 372	43.90 351	70.10 312	80.16 318

fmvsm_s_conf0.5_n_3		73.55 87	74.39 68	71.03 242	74.09 312	51.86 216	77.77 167	75.60 267	61.18 97	78.67 29	88.98 63	55.88 58	77.73 306	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	67.33 306	77.95 194	37.75 405	77.57 171	82.11 120	62.03 82	62.65 309	82.48 240	50.57 138	79.46 264	42.91 363	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	74.28 296	56.61 211	77.10 43	88.16 76	56.17 47	77.09 319	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	40.08 381	77.36 179	81.37 134	55.31 242	66.33 240	84.65 182	37.35 312	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	38.08 306	80.33 247	46.08 328	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	73.95 303	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	70.46 337	48.67 359	75.17 57	86.86 113	53.77 84	76.86 327	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	73.71 306	46.53 391	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	51.04 329	60.91 334	83.98 201	47.71 174	84.99 125	40.81 377	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	67.04 307	77.11 233	36.56 418	77.03 194	80.42 163	62.95 55	62.51 314	84.03 199	46.69 194	79.07 278	44.22 345	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	38.14 401	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	66.70 311	77.60 212	36.30 423	76.94 198	79.61 175	62.36 70	62.43 317	83.66 209	45.69 201	78.37 291	45.35 341	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	69.87 341	47.90 373	74.37 77	86.49 133	53.07 97	76.69 333	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	74.25 297	53.67 287	65.59 256	81.76 261	35.15 334	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	72.02 326	54.58 268	58.71 359	80.79 283	35.00 336	84.36 141	26.41 462	64.71 370	71.15 432

CP-MVSNet		66.49 261	66.41 242	66.72 309	77.67 204	36.33 421	76.83 204	79.52 177	62.45 68	62.54 312	83.47 217	46.32 197	78.37 291	45.47 339	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	72.42 321	56.42 216	75.32 54	87.04 109	52.13 112	78.01 297	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	73.29 312	46.19 394	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	42.97 355	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	50.64 334	65.24 266	84.93 174	39.15 290	78.54 290	36.77 404	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	66.31 319	76.06 258	34.79 431	76.43 212	79.38 180	62.55 66	61.66 326	83.83 204	45.60 203	79.15 274	41.64 375	60.88 405	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	48.43 364	64.99 274	80.84 282	33.01 361	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	50.59 335	56.47 387	78.65 321	39.84 280	82.68 190	44.10 349	72.12 282	72.44 414
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	77.87 302	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	32.70 369	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	42.98 354	76.11 220	77.47 229	56.62 208	65.22 268	82.17 250	41.85 253	80.18 253	47.05 321	72.72 272	83.20 243

旧先验2							76.08 221		45.32 402	76.55 47			65.56 408	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	45.42 340	76.68 208	76.91 368

FC-MVSNet-test		69.80 173	70.58 142	67.46 302	77.61 211	34.73 434	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	50.30 337	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	72.21 324	49.03 354	73.28 101	86.17 144	51.83 118	77.29 316	75.80 46	78.05 183	83.98 213

EPNet_dtu		61.90 326	61.97 308	61.68 371	72.89 331	39.78 385	75.85 229	65.62 379	55.09 249	54.56 408	79.36 311	37.59 309	67.02 399	39.80 385	76.95 203	78.25 344
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	77.94 298	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	76.16 256	48.11 369	77.22 40	85.56 164	53.10 95	77.43 311	74.86 57	77.14 200	86.55 105

SixPastTwentyTwo		61.65 329	58.80 347	70.20 258	75.80 260	47.22 307	75.59 233	69.68 343	54.61 266	54.11 412	79.26 313	27.07 423	82.96 173	43.27 358	49.79 451	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	65.50 337	75.65 263	37.70 407	75.42 236	74.65 290	59.90 134	68.14 194	83.15 223	49.12 160	77.20 317	52.23 270	69.78 319	81.60 279

OpenMVS_ROB	52.78 18	60.03 344	58.14 354	65.69 334	70.47 378	44.82 329	75.33 237	70.86 334	45.04 403	56.06 390	76.00 371	26.89 426	79.65 258	35.36 417	67.29 351	72.60 409

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	75.09 282	51.61 315	70.04 155	81.41 268	32.79 364	79.02 281	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	75.09 282	51.61 315	70.04 155	81.41 268	32.79 364	79.02 281	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	75.09 282	51.61 315	70.04 155	81.41 268	32.79 364	79.02 281	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		59.63 350	59.14 341	61.08 380	74.47 298	38.84 394	75.20 242	68.74 354	31.15 457	58.24 366	76.51 364	32.39 377	68.58 386	49.77 290	65.84 362	75.81 376

ET-MVSNet_ETH3D		67.96 227	65.72 256	74.68 107	76.67 247	55.62 132	75.11 244	74.74 287	52.91 295	60.03 342	80.12 293	33.68 353	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		60.47 341	57.11 360	70.56 252	73.74 316	48.22 292	75.10 246	62.55 407	58.27 171	53.62 418	76.31 368	27.81 415	81.59 213	47.42 312	39.18 466	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	42.34 359	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	75.48 272	52.09 309	60.10 340	83.27 219	36.54 323	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	70.11 339	58.08 173	67.83 209	84.68 180	41.96 249	76.34 340	65.62 143	77.54 190	79.30 334

ECVR-MVS		67.72 234	67.51 211	68.35 290	79.46 140	36.29 424	74.79 254	66.93 368	58.72 159	67.19 222	88.05 80	36.10 325	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	65.87 332	75.22 275	38.56 396	74.66 257	75.08 285	58.90 157	61.79 323	82.63 229	51.18 129	78.07 296	43.63 356	55.87 429	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	43.26 359	75.54 224	74.27 398

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	79.77 329

MonoMVSNet		64.15 293	63.31 291	66.69 312	70.51 377	44.12 341	74.47 261	74.21 298	57.81 184	63.03 300	76.62 360	38.33 301	77.31 315	54.22 255	60.59 411	78.64 341

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	34.19 439	74.43 263	51.92 450	58.72 159	66.75 231	88.05 80	25.99 431	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	76.29 255	58.48 167	68.38 188	84.20 194	42.59 242	83.83 151	46.53 323	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	42.29 360	74.18 267	75.59 268	60.37 120	66.77 230	86.06 148	37.64 308	78.93 286	52.16 271	73.49 254	86.32 118

VPA-MVSNet		69.02 198	69.47 162	67.69 299	77.42 216	41.00 376	74.04 268	79.68 173	60.06 130	69.26 175	84.81 176	51.06 132	77.58 309	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	75.25 277	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	42.88 424	59.97 343	76.60 363	38.11 305	79.39 266	54.84 249	72.32 277	79.55 330

MVS		67.37 239	66.33 245	70.51 254	75.46 270	50.94 226	73.95 271	81.85 123	41.57 431	62.54 312	78.57 324	47.98 169	85.47 118	52.97 266	82.05 103	75.14 384

AUN-MVS		68.45 215	66.41 242	74.57 114	79.53 139	57.08 107	73.93 273	75.23 278	54.44 271	66.69 232	81.85 258	37.10 318	82.89 181	62.07 183	66.84 354	83.75 226

OurMVSNet-221017-0		61.37 334	58.63 349	69.61 269	72.05 349	48.06 296	73.93 273	72.51 320	47.23 384	54.74 405	80.92 278	21.49 449	81.24 223	48.57 303	56.22 428	79.53 331

test1111		67.21 241	67.14 228	67.42 303	79.24 146	34.76 433	73.89 275	65.65 378	58.71 161	66.96 227	87.95 84	36.09 326	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	69.59 345	52.32 307	65.28 261	81.72 262	44.49 224	77.40 313	42.32 367	78.66 171	82.92 251

WR-MVS		68.47 213	68.47 186	68.44 289	80.20 125	39.84 384	73.75 278	76.07 259	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	76.04 261	55.62 236	67.84 208	82.26 246	41.24 268	78.91 287	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	75.20 280	52.95 294	67.90 202	80.33 289	39.81 281	83.68 154	43.20 360	73.56 253	80.20 317

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	80.26 316

fmvsm_s_conf0.1_n_2		69.64 179	69.01 173	71.52 219	71.66 355	51.04 224	73.39 284	67.14 366	55.02 258	75.11 58	87.64 89	42.94 240	77.01 322	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	67.79 360	55.06 254	75.24 56	87.51 90	44.02 228	77.00 323	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	74.01 301	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	71.07 332	52.15 308	64.72 277	80.23 291	43.56 232	77.10 318	45.48 338	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	73.18 313	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	73.18 313	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	77.89 301	71.00 92	78.47 177	87.49 67

pmmvs6		63.69 298	62.82 298	66.27 321	70.63 374	39.27 391	73.13 293	75.47 273	52.69 303	59.75 349	82.30 244	39.71 282	77.03 321	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	75.13 281	55.69 232	58.48 365	73.73 397	32.86 363	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	77.92 300	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	65.42 339	68.74 406	38.43 399	72.92 296	77.39 232	54.74 265	55.40 397	76.71 357	35.46 331	76.72 332	44.25 344	62.31 395	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	65.89 330	77.31 220	38.66 395	72.65 299	69.11 352	57.07 197	62.45 315	81.03 275	37.01 320	79.17 271	31.84 434	73.25 261	79.83 326

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	75.81 263	53.70 286	65.31 260	78.96 316	28.81 406	86.39 89	43.93 350	73.48 255	82.55 261

pm-mvs1		65.24 278	64.97 269	66.04 327	72.38 343	39.40 390	72.62 301	75.63 266	55.53 237	62.35 319	83.18 222	47.45 181	76.47 338	49.06 299	66.54 357	82.24 270

test222					83.14 76	58.68 81	72.57 303	63.45 400	41.78 427	67.56 215	86.12 145	37.13 317			78.73 168	74.98 388

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	80.14 319

EU-MVSNet		55.61 384	54.41 387	59.19 391	65.41 432	33.42 444	72.44 305	71.91 327	28.81 459	51.27 428	73.87 396	24.76 438	69.08 383	43.04 361	58.20 419	75.06 385

thres600view7		63.30 302	62.27 304	66.41 317	77.18 223	38.87 393	72.35 306	69.11 352	56.98 200	62.37 318	80.96 277	37.01 320	79.00 284	31.43 441	73.05 265	81.36 286

pmmvs-eth3d		58.81 355	56.31 372	66.30 320	67.61 416	52.42 205	72.30 307	64.76 386	43.55 417	54.94 403	74.19 392	28.95 403	72.60 358	43.31 357	57.21 423	73.88 402

viewmambaseed2359dif		68.91 200	68.18 196	71.11 239	70.21 382	48.05 298	72.28 308	75.90 262	51.96 310	70.93 144	84.47 191	51.37 126	78.59 289	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	48.56 360	61.21 331	74.60 389	32.57 375	85.82 108	50.38 287	76.75 207	82.52 264

VPNet		67.52 237	68.11 199	65.74 333	79.18 149	36.80 416	72.17 310	72.83 318	62.04 81	67.79 211	85.83 157	48.88 162	76.60 335	51.30 280	72.97 266	83.81 221

MS-PatchMatch		62.42 316	61.46 314	65.31 343	75.21 276	52.10 209	72.05 311	74.05 300	46.41 392	57.42 377	74.36 390	34.35 344	77.57 310	45.62 334	73.67 248	66.26 451

mvs_anonymous		68.03 224	67.51 211	69.59 270	72.08 348	44.57 336	71.99 312	75.23 278	51.67 313	67.06 225	82.57 235	54.68 69	77.94 298	56.56 233	75.71 222	86.26 123

patch_mono-2		69.85 170	71.09 131	66.16 323	79.11 152	54.80 147	71.97 313	74.31 294	53.50 289	70.90 145	84.17 195	57.63 34	63.31 417	66.17 135	82.02 104	80.38 311

tfpn200view9		63.18 305	62.18 306	66.21 322	76.85 243	39.62 387	71.96 314	69.44 348	56.63 206	62.61 310	79.83 297	37.18 314	79.17 271	31.84 434	73.25 261	79.83 326

thres400		63.31 301	62.18 306	66.72 309	76.85 243	39.62 387	71.96 314	69.44 348	56.63 206	62.61 310	79.83 297	37.18 314	79.17 271	31.84 434	73.25 261	81.36 286

SD_0403		63.07 307	63.49 287	61.82 370	75.16 278	31.14 456	71.89 316	73.47 307	53.34 291	58.22 367	81.81 260	45.17 215	73.86 353	37.43 398	74.87 233	80.45 308

baseline1		63.81 297	63.87 279	63.62 357	76.29 254	36.36 419	71.78 317	67.29 364	56.05 225	64.23 286	82.95 224	47.11 187	74.41 350	47.30 316	61.85 399	80.10 320

baseline2		63.42 300	61.26 319	69.89 266	72.55 337	47.62 303	71.54 318	68.38 356	50.11 339	54.82 404	75.55 379	43.06 238	80.96 232	48.13 307	67.16 353	81.11 294

pmmvs4		61.48 332	59.39 339	67.76 297	71.57 357	53.86 159	71.42 319	65.34 381	44.20 411	59.46 351	77.92 334	35.90 327	74.71 348	43.87 352	64.87 369	74.71 394

1112_ss		64.00 296	63.36 289	65.93 329	79.28 144	42.58 358	71.35 320	72.36 323	46.41 392	60.55 337	77.89 337	46.27 199	73.28 355	46.18 327	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	73.12 317	49.39 349	63.82 289	76.50 366	34.95 337	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	70.60 336	47.55 378	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	64.99 346	74.81 287	39.01 392	71.22 323	73.72 305	55.22 246	60.21 338	80.09 295	41.26 267	76.98 325	30.02 448	68.09 344	78.97 339

IterMVS		62.79 310	61.27 318	67.35 305	69.37 398	52.04 212	71.17 324	68.24 358	52.63 304	59.82 346	76.91 354	37.32 313	72.36 360	52.80 267	63.19 385	77.66 354
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	63.14 362	74.75 289	31.04 457	71.16 325	63.64 398	56.32 218	59.80 347	84.99 173	44.51 222	75.46 345	39.12 389	80.62 121	82.92 251

IterMVS-SCA-FT		62.49 313	61.52 313	65.40 340	71.99 351	50.80 231	71.15 326	69.63 344	45.71 400	60.61 336	77.93 333	37.45 310	65.99 406	55.67 242	63.50 382	79.42 332

Anonymous202405211		66.84 253	65.99 252	69.40 274	80.19 126	42.21 362	71.11 327	71.31 330	58.80 158	67.90 202	86.39 136	29.83 396	79.65 258	49.60 295	78.78 165	86.33 116

Anonymous20240521		55.30 385	54.41 387	57.96 402	60.92 457	41.73 366	71.09 328	71.06 333	41.18 432	48.65 442	73.31 400	16.93 455	59.25 433	42.54 365	64.01 376	72.90 406

tpm2		62.07 321	60.10 335	67.99 295	72.79 332	43.86 343	71.05 329	66.85 369	43.14 422	62.77 305	75.39 383	38.32 302	80.80 238	41.69 372	68.88 335	79.32 333

TDRefinement		53.44 399	50.72 409	61.60 372	64.31 438	46.96 309	70.89 330	65.27 383	41.78 427	44.61 455	77.98 331	11.52 470	66.36 403	28.57 454	51.59 445	71.49 427

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		61.38 333	59.10 343	68.20 292	68.94 404	44.64 333	70.81 332	76.52 251	51.63 314	57.56 374	69.94 430	28.30 410	79.61 261	47.44 310	60.78 407	80.36 314

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	16.24 458	79.32 267	55.64 244	71.76 284	80.47 307

mmtdpeth		60.40 342	59.12 342	64.27 352	69.59 394	48.99 278	70.67 334	70.06 340	54.96 259	62.78 304	73.26 402	27.00 424	67.66 392	58.44 222	45.29 458	76.16 373

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	78.21 294	62.54 179	73.33 259	83.37 238

VNet		69.68 177	70.19 149	68.16 294	79.73 134	41.63 369	70.53 336	77.38 233	60.37 120	70.69 146	86.63 125	51.08 131	77.09 319	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	74.40 292	56.69 203	64.70 278	76.77 356	33.66 354	81.10 227	55.42 246	70.32 307	83.87 219

MSDG		61.81 328	59.23 340	69.55 273	72.64 334	52.63 198	70.45 338	75.81 263	51.38 322	53.70 415	76.11 369	29.52 398	81.08 229	37.70 396	65.79 363	74.93 389

ab-mvs		66.65 257	66.42 241	67.37 304	76.17 256	41.73 366	70.41 339	76.14 258	53.99 277	65.98 247	83.51 215	49.48 150	76.24 341	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	73.34 309	57.05 198	68.41 186	85.83 157	49.86 145	72.84 357	71.86 84	76.83 205	83.19 244

EGC-MVSNET		42.47 429	38.48 437	54.46 420	74.33 303	48.73 284	70.33 341	51.10 453	0.03 490	0.18 491	67.78 442	13.28 464	66.49 402	18.91 473	50.36 449	48.15 470

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	38.45 299	82.50 196	60.19 200	71.46 289	83.44 237

reproduce_monomvs		62.56 312	61.20 321	66.62 314	70.62 375	44.30 338	70.13 343	73.13 316	54.78 262	61.13 332	76.37 367	25.63 434	75.63 344	58.75 219	60.29 412	79.93 322

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	36.54 323	78.28 293	62.04 184	75.74 221	83.19 244

HY-MVS	56.14 13	64.55 288	63.89 277	66.55 315	74.73 290	41.02 373	69.96 345	74.43 291	49.29 351	61.66 326	80.92 278	47.43 182	76.68 334	44.91 343	71.69 286	81.94 275

AllTest		57.08 369	54.65 383	64.39 350	71.44 361	49.03 275	69.92 346	67.30 362	45.97 397	47.16 446	79.77 299	17.47 452	67.56 395	33.65 422	59.16 416	76.57 369

testing3		56.54 373	55.92 375	58.41 396	77.52 213	27.93 467	69.72 347	56.36 437	54.75 264	58.63 363	77.80 339	20.88 450	71.75 367	25.31 464	62.25 396	75.53 380

FE-blended-shiyan7		62.00 325	60.17 334	67.49 301	68.53 409	43.07 353	69.65 348	76.38 254	51.26 325	57.10 379	69.95 428	38.83 295	79.04 280	47.14 320	62.67 388	80.37 312

sc_t1		59.76 347	57.84 358	65.54 335	74.87 284	42.95 356	69.61 349	64.16 393	48.90 356	58.68 360	77.12 349	28.19 412	72.35 361	43.75 355	55.28 431	81.31 289

FE-MVSNET3		64.34 292	63.57 284	66.66 313	72.44 342	40.74 379	69.60 350	76.80 248	53.21 292	61.73 325	77.92 334	41.92 252	77.68 308	46.23 326	72.25 280	81.57 280

thres200		62.20 320	61.16 322	65.34 342	75.38 273	39.99 383	69.60 350	69.29 350	55.64 235	61.87 322	76.99 352	37.07 319	78.96 285	31.28 442	73.28 260	77.06 363

tpmrst		58.24 360	58.70 348	56.84 407	66.97 420	34.32 437	69.57 352	61.14 418	47.17 385	58.58 364	71.60 413	41.28 266	60.41 427	49.20 297	62.84 387	75.78 377

PatchmatchNet		59.84 346	58.24 352	64.65 348	73.05 328	46.70 311	69.42 353	62.18 413	47.55 378	58.88 358	71.96 410	34.49 342	69.16 382	42.99 362	63.60 380	78.07 346
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
WB-MVSnew		59.66 349	59.69 337	59.56 384	75.19 277	35.78 428	69.34 354	64.28 390	46.88 388	61.76 324	75.79 375	40.61 274	65.20 409	32.16 430	71.21 291	77.70 353

GG-mvs-BLEND				62.34 367	71.36 365	37.04 414	69.20 355	57.33 434		54.73 406	65.48 453	30.37 387	77.82 303	34.82 418	74.93 232	72.17 419

HyFIR lowres test		65.67 271	63.01 295	73.67 154	79.97 131	55.65 129	69.07 356	75.52 270	42.68 425	63.53 292	77.95 332	40.43 275	81.64 211	46.01 329	71.91 283	83.73 227

UWE-MVS		60.18 343	59.78 336	61.39 376	77.67 204	33.92 442	69.04 357	63.82 396	48.56 360	64.27 284	77.64 344	27.20 421	70.40 377	33.56 425	76.24 211	79.83 326

test_post1							68.67 358				3.64 488	32.39 377	69.49 381	44.17 346

tt0320		58.59 356	56.81 366	63.92 355	75.46 270	41.32 371	68.63 359	64.06 394	47.05 386	56.19 389	74.19 392	30.34 388	71.36 368	39.92 384	55.45 430	79.09 335

testing222		62.29 319	61.31 317	65.25 344	77.87 195	38.53 397	68.34 360	66.31 374	56.37 217	63.15 299	77.58 345	28.47 408	76.18 343	37.04 402	76.65 209	81.05 298

tt0320-xc		58.33 359	56.41 371	64.08 353	75.79 261	41.34 370	68.30 361	62.72 406	47.90 373	56.29 388	74.16 394	28.53 407	71.04 371	41.50 376	52.50 443	79.88 324

Test_1112_low_res		62.32 317	61.77 310	64.00 354	79.08 153	39.53 389	68.17 362	70.17 338	43.25 420	59.03 357	79.90 296	44.08 226	71.24 370	43.79 353	68.42 341	81.25 290

tpm cat1		59.25 353	56.95 363	66.15 324	72.19 347	46.96 309	68.09 363	65.76 377	40.03 441	57.81 371	70.56 421	38.32 302	74.51 349	38.26 394	61.50 402	77.00 365

ppachtmachnet_test		58.06 363	55.38 379	66.10 326	69.51 395	48.99 278	68.01 364	66.13 376	44.50 408	54.05 413	70.74 420	32.09 380	72.34 362	36.68 407	56.71 427	76.99 367

tpmvs		58.47 357	56.95 363	63.03 364	70.20 383	41.21 372	67.90 365	67.23 365	49.62 346	54.73 406	70.84 419	34.14 345	76.24 341	36.64 408	61.29 403	71.64 424

testing91		64.46 289	63.80 280	66.47 316	78.43 173	40.06 382	67.63 366	69.59 345	59.06 153	63.18 297	78.05 330	34.05 346	76.99 324	48.30 305	75.87 219	82.37 268

CL-MVSNet_self_test		61.53 330	60.94 325	63.30 360	68.95 403	36.93 415	67.60 367	72.80 319	55.67 233	59.95 344	76.63 359	45.01 218	72.22 364	39.74 386	62.09 398	80.74 304

testing11		62.81 309	61.90 309	65.54 335	78.38 174	40.76 378	67.59 368	66.78 370	55.48 238	60.13 339	77.11 350	31.67 382	76.79 329	45.53 336	74.45 236	79.06 336

test_vis1_n_1920		58.86 354	59.06 344	58.25 397	63.76 439	43.14 352	67.49 369	66.36 373	40.22 439	65.89 251	71.95 411	31.04 383	59.75 431	59.94 203	64.90 368	71.85 422

tpm		57.34 367	58.16 353	54.86 417	71.80 354	34.77 432	67.47 370	56.04 441	48.20 368	60.10 340	76.92 353	37.17 316	53.41 460	40.76 378	65.01 367	76.40 371

testing99		64.05 294	63.29 292	66.34 318	78.17 186	39.76 386	67.33 371	68.00 359	58.60 164	63.03 300	78.10 329	32.57 375	76.94 326	48.22 306	75.58 223	82.34 269

FE-MVSNET		55.16 389	53.75 395	59.41 386	65.29 433	33.20 446	67.21 372	66.21 375	48.39 366	49.56 440	73.53 399	29.03 402	72.51 359	30.38 446	54.10 437	72.52 411

gg-mvs-nofinetune		57.86 364	56.43 370	62.18 368	72.62 335	35.35 429	66.57 373	56.33 438	50.65 333	57.64 372	57.10 465	30.65 385	76.36 339	37.38 399	78.88 162	74.82 391

TinyColmap		54.14 392	51.72 404	61.40 375	66.84 422	41.97 363	66.52 374	68.51 355	44.81 404	42.69 460	75.77 376	11.66 468	72.94 356	31.96 432	56.77 426	69.27 445

pmmvs5		56.47 375	55.68 377	58.86 393	61.41 451	36.71 417	66.37 375	62.75 405	40.38 438	53.70 415	76.62 360	34.56 340	67.05 398	40.02 382	65.27 365	72.83 407

CHOSEN 1792x2688		65.08 281	62.84 297	71.82 207	81.49 100	56.26 115	66.32 376	74.20 299	40.53 437	63.16 298	78.65 321	41.30 264	77.80 304	45.80 331	74.09 240	81.40 285

our_test_3		56.49 374	54.42 386	62.68 366	69.51 395	45.48 325	66.08 377	61.49 416	44.11 414	50.73 434	69.60 434	33.05 359	68.15 387	38.38 393	56.86 424	74.40 396

mvs5depth		55.64 383	53.81 394	61.11 379	59.39 460	40.98 377	65.89 378	68.28 357	50.21 338	58.11 369	75.42 382	17.03 454	67.63 394	43.79 353	46.21 455	74.73 393

PM-MVS		52.33 403	50.19 412	58.75 394	62.10 448	45.14 328	65.75 379	40.38 476	43.60 416	53.52 419	72.65 403	9.16 476	65.87 407	50.41 286	54.18 436	65.24 453

D2MVS		62.30 318	60.29 333	68.34 291	66.46 426	48.42 290	65.70 380	73.42 308	47.71 376	58.16 368	75.02 385	30.51 386	77.71 307	53.96 258	71.68 287	78.90 340

MIMVSNet1		55.17 388	54.31 389	57.77 404	70.03 387	32.01 452	65.68 381	64.81 385	49.19 352	46.75 449	76.00 371	25.53 435	64.04 413	28.65 453	62.13 397	77.26 361

PatchMatch-RL		56.25 378	54.55 385	61.32 377	77.06 234	56.07 119	65.57 382	54.10 447	44.13 413	53.49 421	71.27 418	25.20 436	66.78 400	36.52 410	63.66 379	61.12 455

Syy-MVS		56.00 380	56.23 373	55.32 414	74.69 291	26.44 473	65.52 383	57.49 432	50.97 330	56.52 385	72.18 406	39.89 279	68.09 388	24.20 465	64.59 373	71.44 428

myMVS_eth3d		54.86 391	54.61 384	55.61 413	74.69 291	27.31 470	65.52 383	57.49 432	50.97 330	56.52 385	72.18 406	21.87 448	68.09 388	27.70 456	64.59 373	71.44 428

test-LLR		58.15 362	58.13 355	58.22 398	68.57 407	44.80 330	65.46 385	57.92 429	50.08 340	55.44 395	69.82 431	32.62 372	57.44 443	49.66 293	73.62 250	72.41 415

TESTMET0.1,1		55.28 386	54.90 382	56.42 409	66.56 424	43.67 345	65.46 385	56.27 439	39.18 444	53.83 414	67.44 443	24.21 440	55.46 454	48.04 308	73.11 264	70.13 439

test-mter		56.42 376	55.82 376	58.22 398	68.57 407	44.80 330	65.46 385	57.92 429	39.94 442	55.44 395	69.82 431	21.92 445	57.44 443	49.66 293	73.62 250	72.41 415

SDMVSNet		68.03 224	68.10 200	67.84 296	77.13 229	48.72 285	65.32 388	79.10 183	58.02 176	65.08 269	82.55 236	47.83 172	73.40 354	63.92 158	73.92 243	81.41 283

CR-MVSNet		59.91 345	57.90 357	65.96 328	69.96 388	52.07 210	65.31 389	63.15 403	42.48 426	59.36 352	74.84 386	35.83 328	70.75 373	45.50 337	64.65 371	75.06 385

RPMNet		61.53 330	58.42 350	70.86 245	69.96 388	52.07 210	65.31 389	81.36 135	43.20 421	59.36 352	70.15 426	35.37 332	85.47 118	36.42 411	64.65 371	75.06 385

USDC		56.35 377	54.24 390	62.69 365	64.74 435	40.31 380	65.05 391	73.83 304	43.93 415	47.58 444	77.71 343	15.36 461	75.05 347	38.19 395	61.81 400	72.70 408

MDTV_nov1_ep13			57.00 362		72.73 333	38.26 400	65.02 392	64.73 387	44.74 405	55.46 394	72.48 404	32.61 374	70.47 374	37.47 397	67.75 347

ETVMVS		59.51 352	58.81 345	61.58 373	77.46 215	34.87 430	64.94 393	59.35 423	54.06 276	61.08 333	76.67 358	29.54 397	71.87 366	32.16 430	74.07 241	78.01 351

CMPMVS	42.80 21	57.81 365	55.97 374	63.32 359	60.98 455	47.38 306	64.66 394	69.50 347	32.06 455	46.83 448	77.80 339	29.50 399	71.36 368	48.68 301	73.75 246	71.21 431
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
WBMVS		60.54 339	60.61 331	60.34 382	78.00 192	35.95 426	64.55 395	64.89 384	49.63 345	63.39 294	78.70 318	33.85 351	67.65 393	42.10 369	70.35 306	77.43 357

IMVS_0404		64.63 286	64.22 274	65.88 331	77.06 234	49.73 258	64.40 396	78.60 199	52.70 298	53.16 422	82.58 231	34.82 338	65.16 410	59.20 212	75.46 226	82.74 256

RPSCF		55.80 382	54.22 391	60.53 381	65.13 434	42.91 357	64.30 397	57.62 431	36.84 448	58.05 370	82.28 245	28.01 413	56.24 451	37.14 401	58.61 418	82.44 267

XXY-MVS		60.68 336	61.67 311	57.70 405	70.43 379	38.45 398	64.19 398	66.47 371	48.05 371	63.22 295	80.86 280	49.28 155	60.47 426	45.25 342	67.28 352	74.19 399

FMVSNet5		55.86 381	54.93 381	58.66 395	71.05 370	36.35 420	64.18 399	62.48 408	46.76 390	50.66 435	74.73 388	25.80 432	64.04 413	33.11 426	65.57 364	75.59 379

UBG		59.62 351	59.53 338	59.89 383	78.12 187	35.92 427	64.11 400	60.81 420	49.45 348	61.34 329	75.55 379	33.05 359	67.39 397	38.68 391	74.62 234	76.35 372

testing3-2		62.06 322	62.36 303	61.17 378	79.29 142	30.31 459	64.09 401	63.49 399	63.50 44	62.84 303	82.22 247	32.35 379	69.02 384	40.01 383	73.43 257	84.17 207

icg_test_0407_2		66.41 263	66.75 233	65.37 341	77.06 234	49.73 258	63.79 402	78.60 199	52.70 298	66.19 242	82.58 231	45.17 215	63.65 416	59.20 212	75.46 226	82.74 256

test_cas_vis1_n_1920		56.91 370	56.71 367	57.51 406	59.13 461	45.40 326	63.58 403	61.29 417	36.24 449	67.14 224	71.85 412	29.89 395	56.69 447	57.65 225	63.58 381	70.46 436

UWE-MVS-28		52.25 404	52.35 402	51.93 438	66.99 419	22.79 481	63.48 404	48.31 462	46.78 389	52.73 424	76.11 369	27.78 416	57.82 442	20.58 471	68.41 342	75.17 383

SCA		60.49 340	58.38 351	66.80 308	74.14 310	48.06 296	63.35 405	63.23 402	49.13 353	59.33 355	72.10 408	37.45 310	74.27 351	44.17 346	62.57 392	78.05 347

myMVS_eth3d28		60.66 337	61.04 323	59.51 385	77.32 219	31.58 454	63.11 406	63.87 395	59.00 154	60.90 335	78.26 327	32.69 370	66.15 405	36.10 413	78.13 181	80.81 302

Patchmtry		57.16 368	56.47 369	59.23 389	69.17 401	34.58 435	62.98 407	63.15 403	44.53 407	56.83 382	74.84 386	35.83 328	68.71 385	40.03 381	60.91 404	74.39 397

Anonymous20231206		55.10 390	55.30 380	54.48 419	69.81 393	33.94 441	62.91 408	62.13 414	41.08 433	55.18 400	75.65 377	32.75 367	56.59 449	30.32 447	67.86 345	72.91 405

sd_testset		64.46 289	64.45 272	64.51 349	77.13 229	42.25 361	62.67 409	72.11 325	58.02 176	65.08 269	82.55 236	41.22 269	69.88 380	47.32 315	73.92 243	81.41 283

MIMVSNet		57.35 366	57.07 361	58.22 398	74.21 307	37.18 410	62.46 410	60.88 419	48.88 357	55.29 399	75.99 373	31.68 381	62.04 422	31.87 433	72.35 276	75.43 382

dp		51.89 406	51.60 405	52.77 432	68.44 412	32.45 451	62.36 411	54.57 444	44.16 412	49.31 441	67.91 439	28.87 405	56.61 448	33.89 421	54.89 433	69.24 446

EPMVS		53.96 393	53.69 396	54.79 418	66.12 429	31.96 453	62.34 412	49.05 458	44.42 410	55.54 393	71.33 417	30.22 390	56.70 446	41.65 374	62.54 393	75.71 378

pmmvs3		44.92 424	41.95 431	53.86 422	52.58 470	43.55 346	62.11 413	46.90 468	26.05 466	40.63 462	60.19 461	11.08 473	57.91 441	31.83 437	46.15 456	60.11 456

test_vis1_n		49.89 415	48.69 417	53.50 426	53.97 465	37.38 409	61.53 414	47.33 466	28.54 460	59.62 350	67.10 447	13.52 463	52.27 464	49.07 298	57.52 421	70.84 434

PVSNet	50.76 19	58.40 358	57.39 359	61.42 374	75.53 268	44.04 342	61.43 415	63.45 400	47.04 387	56.91 381	73.61 398	27.00 424	64.76 411	39.12 389	72.40 275	75.47 381

LCM-MVSNet-Re		61.88 327	61.35 316	63.46 358	74.58 296	31.48 455	61.42 416	58.14 428	58.71 161	53.02 423	79.55 306	43.07 237	76.80 328	45.69 332	77.96 184	82.11 274

test20.03		53.87 395	54.02 392	53.41 428	61.47 450	28.11 466	61.30 417	59.21 424	51.34 324	52.09 426	77.43 346	33.29 358	58.55 438	29.76 449	60.27 413	73.58 403

MDTV_nov1_ep13_2view						25.89 475	61.22 418		40.10 440	51.10 429		32.97 362		38.49 392		78.61 342

PMMVS		53.96 393	53.26 399	56.04 410	62.60 446	50.92 228	61.17 419	56.09 440	32.81 454	53.51 420	66.84 448	34.04 347	59.93 430	44.14 348	68.18 343	57.27 463

test_fmvs1_n		51.37 408	50.35 411	54.42 421	52.85 468	37.71 406	61.16 420	51.93 449	28.15 461	63.81 290	69.73 433	13.72 462	53.95 458	51.16 281	60.65 409	71.59 425

WTY-MVS		59.75 348	60.39 332	57.85 403	72.32 345	37.83 404	61.05 421	64.18 391	45.95 399	61.91 321	79.11 315	47.01 191	60.88 425	42.50 366	69.49 326	74.83 390

dmvs_testset		50.16 413	51.90 403	44.94 449	66.49 425	11.78 489	61.01 422	51.50 451	51.17 328	50.30 438	67.44 443	39.28 287	60.29 428	22.38 468	57.49 422	62.76 454

Patchmatch-RL test		58.16 361	55.49 378	66.15 324	67.92 415	48.89 282	60.66 423	51.07 454	47.86 375	59.36 352	62.71 459	34.02 348	72.27 363	56.41 234	59.40 415	77.30 359

test_fmvs1		51.32 410	50.48 410	53.81 423	53.57 466	37.51 408	60.63 424	51.16 452	28.02 463	63.62 291	69.23 436	16.41 457	53.93 459	51.01 282	60.70 408	69.99 440

LTVRE_ROB	55.42 16	63.15 306	61.23 320	68.92 283	76.57 250	47.80 299	59.92 425	76.39 253	54.35 272	58.67 361	82.46 241	29.44 400	81.49 216	42.12 368	71.14 292	77.46 356
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		60.57 338	61.39 315	58.12 401	74.29 305	32.63 449	59.52 426	65.53 380	59.90 134	62.45 315	79.75 301	41.96 249	63.90 415	39.47 387	69.65 325	77.84 352

test0.0.03 1		53.32 400	53.59 397	52.50 434	62.81 445	29.45 461	59.51 427	54.11 446	50.08 340	54.40 410	74.31 391	32.62 372	55.92 452	30.50 445	63.95 378	72.15 420

UnsupCasMVSNet_eth		53.16 402	52.47 400	55.23 415	59.45 459	33.39 445	59.43 428	69.13 351	45.98 396	50.35 437	72.32 405	29.30 401	58.26 440	42.02 371	44.30 459	74.05 400

MVS-HIRNet		45.52 423	44.48 425	48.65 443	68.49 411	34.05 440	59.41 429	44.50 471	27.03 464	37.96 471	50.47 473	26.16 430	64.10 412	26.74 461	59.52 414	47.82 472

testgi		51.90 405	52.37 401	50.51 441	60.39 458	23.55 480	58.42 430	58.15 427	49.03 354	51.83 427	79.21 314	22.39 443	55.59 453	29.24 452	62.64 391	72.40 417

dmvs_re		56.77 372	56.83 365	56.61 408	69.23 399	41.02 373	58.37 431	64.18 391	50.59 335	57.45 376	71.42 414	35.54 330	58.94 436	37.23 400	67.45 350	69.87 441

PatchT		53.17 401	53.44 398	52.33 435	68.29 413	25.34 477	58.21 432	54.41 445	44.46 409	54.56 408	69.05 437	33.32 357	60.94 424	36.93 403	61.76 401	70.73 435

WB-MVS		43.26 426	43.41 426	42.83 453	63.32 442	10.32 491	58.17 433	45.20 469	45.42 401	40.44 464	67.26 446	34.01 349	58.98 435	11.96 482	24.88 476	59.20 457

sss		56.17 379	56.57 368	54.96 416	66.93 421	36.32 422	57.94 434	61.69 415	41.67 429	58.64 362	75.32 384	38.72 297	56.25 450	42.04 370	66.19 360	72.31 418

ttmdpeth		45.56 422	42.95 427	53.39 429	52.33 471	29.15 462	57.77 435	48.20 463	31.81 456	49.86 439	77.21 348	8.69 477	59.16 434	27.31 457	33.40 473	71.84 423

test_fmvs2		48.69 417	47.49 422	52.29 436	48.63 475	33.06 448	57.76 436	48.05 464	25.71 467	59.76 348	69.60 434	11.57 469	52.23 465	49.45 296	56.86 424	71.58 426

KD-MVS_self_test		55.22 387	53.89 393	59.21 390	57.80 464	27.47 469	57.75 437	74.32 293	47.38 380	50.90 431	70.00 427	28.45 409	70.30 378	40.44 379	57.92 420	79.87 325

UnsupCasMVSNet_bld		50.07 414	48.87 415	53.66 424	60.97 456	33.67 443	57.62 438	64.56 388	39.47 443	47.38 445	64.02 457	27.47 418	59.32 432	34.69 419	43.68 460	67.98 449

mamv4		56.85 371	58.00 356	53.43 427	72.46 341	54.47 149	57.56 439	54.74 442	38.81 445	57.42 377	79.45 309	47.57 178	38.70 480	60.88 195	53.07 440	67.11 450

SSC-MVS		41.96 431	41.99 430	41.90 454	62.46 447	9.28 493	57.41 440	44.32 472	43.38 418	38.30 470	66.45 449	32.67 371	58.42 439	10.98 483	21.91 479	57.99 461

ANet_high		41.38 432	37.47 439	53.11 430	39.73 486	24.45 478	56.94 441	69.69 342	47.65 377	26.04 478	52.32 468	12.44 466	62.38 421	21.80 469	10.61 487	72.49 412

MDA-MVSNet-bldmvs		53.87 395	50.81 408	63.05 363	66.25 427	48.58 288	56.93 442	63.82 396	48.09 370	41.22 461	70.48 424	30.34 388	68.00 391	34.24 420	45.92 457	72.57 410

test123		4.73 458	6.30 461	0.02 473	0.01 496	0.01 498	56.36 443	0.00 497	0.01 491	0.04 492	0.21 492	0.01 495	0.00 492	0.03 492	0.00 490	0.04 488

miper_lstm_enhance		62.03 323	60.88 326	65.49 338	66.71 423	46.25 314	56.29 444	75.70 265	50.68 332	61.27 330	75.48 381	40.21 276	68.03 390	56.31 235	65.25 366	82.18 271

KD-MVS_2432*1600		53.45 397	51.50 406	59.30 387	62.82 443	37.14 411	55.33 445	71.79 328	47.34 382	55.09 401	70.52 422	21.91 446	70.45 375	35.72 415	42.97 461	70.31 437

miper_refine_blended		53.45 397	51.50 406	59.30 387	62.82 443	37.14 411	55.33 445	71.79 328	47.34 382	55.09 401	70.52 422	21.91 446	70.45 375	35.72 415	42.97 461	70.31 437

LF4IMVS		42.95 427	42.26 429	45.04 447	48.30 476	32.50 450	54.80 447	48.49 460	28.03 462	40.51 463	70.16 425	9.24 475	43.89 475	31.63 438	49.18 453	58.72 459

PMVS	28.69 22	36.22 439	33.29 444	45.02 448	36.82 488	35.98 425	54.68 448	48.74 459	26.31 465	21.02 481	51.61 470	2.88 489	60.10 429	9.99 486	47.58 454	38.99 479
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVStest1		42.65 428	39.29 435	52.71 433	47.26 478	34.58 435	54.41 449	50.84 457	23.35 469	39.31 469	74.08 395	12.57 465	55.09 455	23.32 466	28.47 475	68.47 448

PVSNet_0	43.31 20	47.46 421	45.64 424	52.92 431	67.60 417	44.65 332	54.06 450	54.64 443	41.59 430	46.15 451	58.75 462	30.99 384	58.66 437	32.18 429	24.81 477	55.46 465

testmvs		4.52 459	6.03 462	0.01 474	0.01 496	0.00 499	53.86 451	0.00 497	0.01 491	0.04 492	0.27 491	0.00 496	0.00 492	0.04 491	0.00 490	0.03 489

test_fmvs3		44.30 425	42.55 428	49.55 442	42.83 480	27.15 472	53.03 452	44.93 470	22.03 475	53.69 417	64.94 454	4.21 484	49.63 467	47.47 309	49.82 450	71.88 421

APD_test1		37.39 438	34.94 441	44.72 450	48.88 474	33.19 447	52.95 453	44.00 473	19.49 476	27.28 477	58.59 463	3.18 488	52.84 462	18.92 472	41.17 464	48.14 471

dongtai		34.52 441	34.94 441	33.26 463	61.06 454	16.00 488	52.79 454	23.78 489	40.71 436	39.33 468	48.65 477	16.91 456	48.34 469	12.18 481	19.05 481	35.44 480

YYNet1		50.73 411	48.96 413	56.03 411	61.10 453	41.78 365	51.94 455	56.44 436	40.94 435	44.84 453	67.80 441	30.08 393	55.08 456	36.77 404	50.71 447	71.22 430

MDA-MVSNet_test_wron		50.71 412	48.95 414	56.00 412	61.17 452	41.84 364	51.90 456	56.45 435	40.96 434	44.79 454	67.84 440	30.04 394	55.07 457	36.71 406	50.69 448	71.11 433

kuosan		29.62 448	30.82 447	26.02 468	52.99 467	16.22 487	51.09 457	22.71 490	33.91 453	33.99 472	40.85 478	15.89 459	33.11 485	7.59 489	18.37 482	28.72 482

ADS-MVSNet2		51.33 409	48.76 416	59.07 392	66.02 430	44.60 335	50.90 458	59.76 422	36.90 446	50.74 432	66.18 451	26.38 427	63.11 418	27.17 458	54.76 434	69.50 443

ADS-MVSNet		48.48 418	47.77 419	50.63 440	66.02 430	29.92 460	50.90 458	50.87 456	36.90 446	50.74 432	66.18 451	26.38 427	52.47 463	27.17 458	54.76 434	69.50 443

mamba_0408		67.78 232	65.42 261	74.85 103	78.65 164	53.46 171	50.83 460	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	63.68 356	78.65 164	53.46 171	50.83 460	79.09 184	53.75 283	68.14 194	83.83 204	41.79 256	53.03 461	56.58 231	76.11 213	84.54 192

FPMVS		42.18 430	41.11 432	45.39 446	58.03 463	41.01 375	49.50 462	53.81 448	30.07 458	33.71 473	64.03 455	11.69 467	52.08 466	14.01 477	55.11 432	43.09 474

N_pmnet		39.35 436	40.28 433	36.54 460	63.76 439	1.62 497	49.37 463	0.76 496	34.62 452	43.61 458	66.38 450	26.25 429	42.57 476	26.02 463	51.77 444	65.44 452

new-patchmatchnet		47.56 420	47.73 420	47.06 444	58.81 462	9.37 492	48.78 464	59.21 424	43.28 419	44.22 456	68.66 438	25.67 433	57.20 445	31.57 440	49.35 452	74.62 395

test_vis1_rt		41.35 433	39.45 434	47.03 445	46.65 479	37.86 403	47.76 465	38.65 477	23.10 471	44.21 457	51.22 471	11.20 472	44.08 474	39.27 388	53.02 441	59.14 458

JIA-IIPM		51.56 407	47.68 421	63.21 361	64.61 436	50.73 235	47.71 466	58.77 426	42.90 423	48.46 443	51.72 469	24.97 437	70.24 379	36.06 414	53.89 438	68.64 447

ambc				65.13 345	63.72 441	37.07 413	47.66 467	78.78 194		54.37 411	71.42 414	11.24 471	80.94 233	45.64 333	53.85 439	77.38 358

testf1		31.46 446	28.89 450	39.16 456	41.99 483	28.78 464	46.45 468	37.56 478	14.28 483	21.10 479	48.96 474	1.48 492	47.11 470	13.63 478	34.56 470	41.60 475

APD_test2		31.46 446	28.89 450	39.16 456	41.99 483	28.78 464	46.45 468	37.56 478	14.28 483	21.10 479	48.96 474	1.48 492	47.11 470	13.63 478	34.56 470	41.60 475

Patchmatch-test		49.08 416	48.28 418	51.50 439	64.40 437	30.85 458	45.68 470	48.46 461	35.60 450	46.10 452	72.10 408	34.47 343	46.37 472	27.08 460	60.65 409	77.27 360

DSMNet-mixed		39.30 437	38.72 436	41.03 455	51.22 472	19.66 484	45.53 471	31.35 483	15.83 482	39.80 466	67.42 445	22.19 444	45.13 473	22.43 467	52.69 442	58.31 460

LCM-MVSNet		40.30 434	35.88 440	53.57 425	42.24 481	29.15 462	45.21 472	60.53 421	22.23 474	28.02 476	50.98 472	3.72 486	61.78 423	31.22 443	38.76 467	69.78 442

new_pmnet		34.13 442	34.29 443	33.64 462	52.63 469	18.23 486	44.43 473	33.90 482	22.81 472	30.89 475	53.18 467	10.48 474	35.72 484	20.77 470	39.51 465	46.98 473

mvsany_test1		39.38 435	38.16 438	43.02 452	49.05 473	34.28 438	44.16 474	25.94 487	22.74 473	46.57 450	62.21 460	23.85 441	41.16 479	33.01 427	35.91 469	53.63 466

E-PMN		23.77 450	22.73 454	26.90 466	42.02 482	20.67 483	42.66 475	35.70 480	17.43 478	10.28 488	25.05 484	6.42 479	42.39 477	10.28 485	14.71 484	17.63 483

EMVS		22.97 451	21.84 455	26.36 467	40.20 485	19.53 485	41.95 476	34.64 481	17.09 479	9.73 489	22.83 485	7.29 478	42.22 478	9.18 487	13.66 485	17.32 484

test_vis3_rt		32.09 444	30.20 449	37.76 459	35.36 490	27.48 468	40.60 477	28.29 486	16.69 480	32.52 474	40.53 479	1.96 490	37.40 482	33.64 424	42.21 463	48.39 469

CHOSEN 280x420		47.83 419	46.36 423	52.24 437	67.37 418	49.78 257	38.91 478	43.11 474	35.00 451	43.27 459	63.30 458	28.95 403	49.19 468	36.53 409	60.80 406	57.76 462

mvsany_test3		32.62 443	30.57 448	38.77 458	36.16 489	24.20 479	38.10 479	20.63 491	19.14 477	40.36 465	57.43 464	5.06 481	36.63 483	29.59 451	28.66 474	55.49 464

test_f		31.86 445	31.05 446	34.28 461	32.33 492	21.86 482	32.34 480	30.46 484	16.02 481	39.78 467	55.45 466	4.80 482	32.36 486	30.61 444	37.66 468	48.64 468

PMMVS2		27.40 449	25.91 452	31.87 465	39.46 487	6.57 494	31.17 481	28.52 485	23.96 468	20.45 482	48.94 476	4.20 485	37.94 481	16.51 474	19.97 480	51.09 467

wuyk23d		13.32 455	12.52 458	15.71 470	47.54 477	26.27 474	31.06 482	1.98 495	4.93 487	5.18 490	1.94 490	0.45 494	18.54 489	6.81 490	12.83 486	2.33 487

Gipuma		34.77 440	31.91 445	43.33 451	62.05 449	37.87 402	20.39 483	67.03 367	23.23 470	18.41 483	25.84 483	4.24 483	62.73 419	14.71 476	51.32 446	29.38 481
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVE	17.77 23	21.41 452	17.77 457	32.34 464	34.34 491	25.44 476	16.11 484	24.11 488	11.19 485	13.22 485	31.92 481	1.58 491	30.95 487	10.47 484	17.03 483	40.62 478
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
tmp_tt		9.43 456	11.14 459	4.30 472	2.38 495	4.40 495	13.62 485	16.08 493	0.39 489	15.89 484	13.06 486	15.80 460	5.54 491	12.63 480	10.46 488	2.95 486

test_method		19.68 453	18.10 456	24.41 469	13.68 494	3.11 496	12.06 486	42.37 475	2.00 488	11.97 486	36.38 480	5.77 480	29.35 488	15.06 475	23.65 478	40.76 477

mmdepth		0.00 461	0.00 464	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	0.00 493	0.00 496	0.00 492	0.00 493	0.00 490	0.00 490

monomultidepth		0.00 461	0.00 464	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	0.00 493	0.00 496	0.00 492	0.00 493	0.00 490	0.00 490

test_blank		0.00 461	0.00 464	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	0.00 493	0.00 496	0.00 492	0.00 493	0.00 490	0.00 490

uanet_test		0.00 461	0.00 464	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	0.00 493	0.00 496	0.00 492	0.00 493	0.00 490	0.00 490

DCPMVS		0.00 461	0.00 464	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	0.00 493	0.00 496	0.00 492	0.00 493	0.00 490	0.00 490

cdsmvs_eth3d_5k		17.50 454	23.34 453	0.00 475	0.00 498	0.00 499	0.00 487	78.63 198	0.00 493	0.00 494	82.18 248	49.25 156	0.00 492	0.00 493	0.00 490	0.00 490

pcd_1.5k_mvsjas		3.92 460	5.23 463	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	0.00 493	47.05 188	0.00 492	0.00 493	0.00 490	0.00 490

sosnet-low-res		0.00 461	0.00 464	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	0.00 493	0.00 496	0.00 492	0.00 493	0.00 490	0.00 490

sosnet		0.00 461	0.00 464	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	0.00 493	0.00 496	0.00 492	0.00 493	0.00 490	0.00 490

uncertanet		0.00 461	0.00 464	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	0.00 493	0.00 496	0.00 492	0.00 493	0.00 490	0.00 490

Regformer		0.00 461	0.00 464	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	0.00 493	0.00 496	0.00 492	0.00 493	0.00 490	0.00 490

ab-mvs-re		6.49 457	8.65 460	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	77.89 337	0.00 496	0.00 492	0.00 493	0.00 490	0.00 490

uanet		0.00 461	0.00 464	0.00 475	0.00 498	0.00 499	0.00 487	0.00 497	0.00 493	0.00 494	0.00 493	0.00 496	0.00 492	0.00 493	0.00 490	0.00 490

WAC-MVS						27.31 470								27.77 455

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					0.00 498

eth-test					0.00 498

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																78.05 347

test_part2					87.58 9	60.47 42				83.42 15

sam_mvs1												34.74 339				78.05 347

sam_mvs												33.43 356

MTGPA								80.97 153

test_post											3.55 489	33.90 350	66.52 401

patchmatchnet-post											64.03 455	34.50 341	74.27 351

gm-plane-assit					71.40 364	41.72 368			48.85 358		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				64.39 350	71.44 361	49.03 275		67.30 362	45.97 397	47.16 446	79.77 299	17.47 452	67.56 395	33.65 422	59.16 416	76.57 369

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		66.43 372	44.68 406	70.29 152	86.64 123	41.29 265	75.23 346	49.72 292	81.75 110	75.93 375

旧先验1					83.04 78	53.15 181		67.52 361			87.85 86	44.08 226			80.76 119	78.03 350

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	78.16 345

testdata2													72.18 365	46.95 322

segment_acmp												54.23 73

testdata				64.66 347	81.52 98	52.93 186		65.29 382	46.09 395	73.88 88	87.46 93	38.08 306	66.26 404	53.31 264	78.48 175	74.78 392

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								0.00 497

nn								0.00 497

door-mid								47.19 467

lessismore_v0				69.91 264	71.42 363	47.80 299		50.90 455		50.39 436	75.56 378	27.43 420	81.33 220	45.91 330	34.10 472	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								47.60 465

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				62.09 369	66.16 428	44.55 337		64.32 389	47.36 381	55.31 398	80.34 288	19.27 451	62.68 420	36.29 412	62.39 394	79.04 337

DeepMVS_CX				12.03 471	17.97 493	10.91 490		10.60 494	7.46 486	11.07 487	28.36 482	3.28 487	11.29 490	8.01 488	9.74 489	13.89 485

High-resolution multi-view benchmark