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.

SteuartSystems-ACMMP		79.48 5	79.31 5	79.98 1	83.01 55	62.18 19	87.60 2	85.83 6	66.69 11	78.03 9	90.98 4	54.26 32	90.06 1	78.42 7	89.02 7	87.69 15
Skip Steuart: Steuart Systems R&D Blog.
DeepC-MVS	69.38 2	78.56 9	78.14 12	79.83 2	83.60 49	61.62 24	84.17 24	86.85 2	63.23 35	73.84 37	90.25 18	57.68 12	89.96 2	74.62 18	89.03 6	87.89 9
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
APDe-MVS		80.16 2	80.59 2	78.86 18	86.64 9	60.02 39	88.12 1	86.42 4	62.94 40	82.40 2	92.12 1	59.64 6	89.76 3	78.70 5	88.32 15	86.79 38

MVS_0304		76.73 29	76.04 30	78.78 19	81.32 72	58.89 53	82.50 49	84.07 26	67.73 5	72.08 59	87.28 54	49.49 73	89.57 4	73.52 27	86.40 39	87.87 11

3Dnovator+	66.72 4	75.84 38	74.57 41	79.66 3	82.40 59	59.92 42	85.83 10	86.32 5	66.92 9	67.80 122	89.24 32	42.03 165	89.38 5	64.07 86	86.50 38	89.69 1

HSP-MVS		80.69 1	81.20 1	79.14 8	86.21 16	62.73 12	86.09 8	85.03 12	65.51 15	83.81 1	90.51 11	63.71 1	89.23 6	81.51 1	88.44 11	85.45 78

NCCC		78.58 8	78.31 9	79.39 5	87.51 3	62.61 16	85.20 17	84.42 19	66.73 10	74.67 28	89.38 30	55.30 23	89.18 7	74.19 20	87.34 27	86.38 41

CNVR-MVS		79.84 4	79.97 4	79.45 4	87.90 2	62.17 20	84.37 20	85.03 12	66.96 6	77.58 10	90.06 20	59.47 8	89.13 8	78.67 6	89.73 3	87.03 33

DeepC-MVS_fast	68.24 3	77.25 22	76.63 25	79.12 10	86.15 18	60.86 33	84.71 18	84.85 16	61.98 59	73.06 48	88.88 38	53.72 39	89.06 9	68.27 47	88.04 21	87.42 24
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepPCF-MVS	69.58 1	79.03 6	79.00 6	79.13 9	84.92 41	60.32 37	83.03 37	85.33 9	62.86 43	80.17 3	90.03 21	61.76 2	88.95 10	74.21 19	88.67 10	88.12 7

CANet		76.46 31	75.93 32	78.06 29	81.29 73	57.53 68	82.35 50	83.31 50	67.78 3	70.09 73	86.34 69	54.92 26	88.90 11	72.68 30	84.55 47	87.76 14

PHI-MVS		75.87 37	75.36 36	77.41 36	80.62 85	55.91 95	84.28 21	85.78 7	56.08 157	73.41 43	86.58 65	50.94 64	88.54 12	70.79 40	89.71 4	87.79 13

ACMMP_Plus		78.77 7	78.78 7	78.74 20	85.44 29	61.04 31	83.84 28	85.16 10	62.88 42	78.10 8	91.26 3	52.51 48	88.39 13	79.34 3	90.52 1	86.78 39

HFP-MVS		78.01 14	77.65 14	79.10 11	86.71 6	62.81 10	86.29 5	84.32 21	62.82 44	73.96 32	90.50 12	53.20 45	88.35 14	74.02 21	87.05 28	86.13 52

#test#		77.83 15	77.41 17	79.10 11	86.71 6	62.81 10	85.69 14	84.32 21	61.61 62	73.96 32	90.50 12	53.20 45	88.35 14	73.68 24	87.05 28	86.13 52

APD-MVS		78.02 13	78.04 13	77.98 31	86.44 13	60.81 34	85.52 15	84.36 20	60.61 73	79.05 6	90.30 16	55.54 22	88.32 16	73.48 28	87.03 30	84.83 103
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ACMMPR		77.71 16	77.23 19	79.16 6	86.75 5	62.93 9	86.29 5	84.24 23	62.82 44	73.55 42	90.56 10	49.80 71	88.24 17	74.02 21	87.03 30	86.32 48

region2R		77.67 18	77.18 20	79.15 7	86.76 4	62.95 8	86.29 5	84.16 25	62.81 46	73.30 44	90.58 9	49.90 69	88.21 18	73.78 23	87.03 30	86.29 50

PGM-MVS		76.77 28	76.06 29	78.88 17	86.14 19	62.73 12	82.55 47	83.74 37	61.71 60	72.45 56	90.34 15	48.48 104	88.13 19	72.32 31	86.85 33	85.78 61

DP-MVS Recon		72.15 73	70.73 80	76.40 49	86.57 10	57.99 63	81.15 71	82.96 56	57.03 136	66.78 133	85.56 83	44.50 148	88.11 20	51.77 171	80.23 84	83.10 159

test12				77.76 33	84.52 43	58.41 58		83.36 48		72.93 50		54.61 30	88.05 21		88.12 19	86.81 37

XVS		77.17 23	76.56 26	79.00 14	86.32 14	62.62 14	85.83 10	83.92 30	64.55 22	72.17 57	90.01 22	47.95 109	88.01 22	71.55 36	86.74 35	86.37 44

X-MVStestdata		70.21 104	67.28 140	79.00 14	86.32 14	62.62 14	85.83 10	83.92 30	64.55 22	72.17 57	6.49 333	47.95 109	88.01 22	71.55 36	86.74 35	86.37 44

CDPH-MVS		76.31 32	75.67 35	78.22 27	85.35 32	59.14 49	81.31 69	84.02 27	56.32 151	74.05 31	88.98 36	53.34 43	87.92 24	69.23 44	88.42 12	87.59 18

API-MVS		72.17 71	71.41 69	74.45 80	81.95 63	57.22 73	84.03 26	80.38 113	59.89 92	68.40 107	82.33 132	49.64 72	87.83 25	51.87 169	84.16 51	78.30 221

MG-MVS		73.96 51	73.89 47	74.16 82	85.65 25	49.69 192	81.59 65	81.29 86	61.45 63	71.05 65	88.11 45	51.77 55	87.73 26	61.05 121	83.09 54	85.05 97

MCST-MVS		77.48 20	77.45 16	77.54 34	86.67 8	58.36 59	83.22 35	86.93 1	56.91 138	74.91 24	88.19 44	59.15 9	87.68 27	73.67 25	87.45 26	86.57 40

TSAR-MVS + MP.		78.44 10	78.28 10	78.90 16	84.96 37	61.41 27	84.03 26	83.82 36	59.34 113	79.37 5	89.76 26	59.84 4	87.62 28	76.69 11	86.74 35	87.68 16

HPM-MVS		77.28 21	76.85 22	78.54 22	85.00 36	60.81 34	82.91 40	85.08 11	62.57 47	73.09 47	89.97 23	50.90 65	87.48 29	75.30 13	86.85 33	87.33 28

CP-MVS		77.12 24	76.68 24	78.43 23	86.05 22	63.18 7	87.55 3	83.45 44	62.44 50	72.68 52	90.50 12	48.18 107	87.34 30	73.59 26	85.71 42	84.76 108

HPM-MVS++		79.88 3	80.14 3	79.10 11	88.17 1	64.80 1	86.59 4	83.70 38	65.37 16	78.78 7	90.64 7	58.63 11	87.24 31	79.00 4	90.37 2	85.26 91

TSAR-MVS + GP.		74.90 42	74.15 45	77.17 39	82.00 62	58.77 55	81.80 58	78.57 152	58.58 121	74.32 30	84.51 100	55.94 19	87.22 32	67.11 57	84.48 49	85.52 73

HQP_MVS		74.31 47	73.73 48	76.06 51	81.41 70	56.31 84	84.22 22	84.01 28	64.52 24	69.27 95	86.10 73	45.26 142	87.21 33	68.16 48	80.58 75	84.65 109

plane_prior5								84.01 28					87.21 33	68.16 48	80.58 75	84.65 109

ACMMP		76.02 35	75.33 37	78.07 28	85.20 33	61.91 22	85.49 16	84.44 18	63.04 38	69.80 83	89.74 27	45.43 138	87.16 35	72.01 34	82.87 59	85.14 93
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
CLD-MVS		73.33 56	72.68 58	75.29 67	78.82 111	53.33 123	78.23 109	84.79 17	61.30 66	70.41 69	81.04 168	52.41 51	87.12 36	64.61 76	82.49 62	85.41 85
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
114514_t		70.83 85	69.56 95	74.64 76	86.21 16	54.63 110	82.34 51	81.81 73	48.22 233	63.01 176	85.83 79	40.92 185	87.10 37	57.91 135	79.79 89	82.18 173

AdaColmap		69.99 108	68.66 112	73.97 85	84.94 39	57.83 64	82.63 45	78.71 149	56.28 153	64.34 165	84.14 104	41.57 173	87.06 38	46.45 205	78.88 102	77.02 235

HQP4-MVS										67.85 117			86.93 39			84.32 116

HQP-MVS		73.45 55	72.80 57	75.40 64	80.66 82	54.94 106	82.31 52	83.90 32	62.10 54	67.85 117	85.54 85	45.46 136	86.93 39	67.04 58	80.35 81	84.32 116

Regformer-2		75.63 39	74.99 38	77.54 34	80.43 87	58.32 60	79.50 92	82.92 57	67.84 1	75.94 15	80.75 177	55.73 20	86.80 41	71.44 38	80.38 79	87.50 20

DELS-MVS		74.76 43	74.46 42	75.65 60	77.84 137	52.25 139	75.59 168	84.17 24	63.76 32	73.15 46	82.79 121	59.58 7	86.80 41	67.24 56	86.04 41	87.89 9
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
MP-MVS-pluss		78.35 11	78.46 8	78.03 30	84.96 37	59.52 44	82.93 39	85.39 8	62.15 53	76.41 14	91.51 2	52.47 50	86.78 43	80.66 2	89.64 5	87.80 12
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MP-MVS		78.35 11	78.26 11	78.64 21	86.54 11	63.47 5	86.02 9	83.55 41	63.89 31	73.60 41	90.60 8	54.85 28	86.72 44	77.20 10	88.06 20	85.74 66

MPTG		77.61 19	77.36 18	78.35 24	86.08 20	63.57 2	83.37 33	80.97 96	65.13 18	75.77 16	90.88 5	48.63 100	86.66 45	77.23 8	88.17 17	84.81 104

MTAPA		76.90 26	76.42 27	78.35 24	86.08 20	63.57 2	74.92 184	80.97 96	65.13 18	75.77 16	90.88 5	48.63 100	86.66 45	77.23 8	88.17 17	84.81 104

abl_6		74.34 46	73.50 49	76.86 41	82.43 58	60.16 38	83.48 32	81.86 71	58.81 119	73.95 34	89.86 24	41.87 168	86.62 47	67.98 50	81.23 70	83.80 140

LPG-MVS_test		72.74 62	71.74 65	75.76 55	80.22 90	57.51 69	82.55 47	83.40 46	61.32 64	66.67 134	87.33 52	39.15 195	86.59 48	67.70 52	77.30 119	83.19 155

LGP-MVS_train				75.76 55	80.22 90	57.51 69		83.40 46	61.32 64	66.67 134	87.33 52	39.15 195	86.59 48	67.70 52	77.30 119	83.19 155

CSCG		76.92 25	76.75 23	77.41 36	83.96 48	59.60 43	82.95 38	86.50 3	60.78 71	75.27 19	84.83 91	60.76 3	86.56 50	67.86 51	87.87 25	86.06 55

mPP-MVS		76.54 30	75.93 32	78.34 26	86.47 12	63.50 4	85.74 13	82.28 64	62.90 41	71.77 61	90.26 17	46.61 127	86.55 51	71.71 35	85.66 43	84.97 100

原ACMM1				74.69 73	85.39 31	59.40 45		83.42 45	51.47 207	70.27 72	86.61 63	48.61 102	86.51 52	53.85 157	87.96 22	78.16 223

QAPM		70.05 106	68.81 109	73.78 89	76.54 164	53.43 121	83.23 34	83.48 42	52.89 191	65.90 144	86.29 70	41.55 176	86.49 53	51.01 175	78.40 110	81.42 183

test_prior3		76.89 27	76.96 21	76.69 44	84.20 46	57.27 71	81.75 59	84.88 14	60.37 78	75.01 20	89.06 33	56.22 17	86.43 54	72.19 32	88.96 8	86.38 41

test_prior				76.69 44	84.20 46	57.27 71		84.88 14					86.43 54			86.38 41

EPP-MVSNet		72.16 72	71.31 73	74.71 72	78.68 116	49.70 190	82.10 56	81.65 75	60.40 77	65.94 143	85.84 78	51.74 56	86.37 56	55.93 143	79.55 93	88.07 8

IB-MVS	56.42 12	65.40 191	62.73 202	73.40 113	74.89 180	52.78 130	73.09 207	75.13 198	55.69 163	58.48 237	73.73 265	32.86 248	86.32 57	50.63 177	70.11 198	81.10 194
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
Regformer-1		75.47 40	74.93 40	77.09 40	80.43 87	57.70 66	79.50 92	82.13 65	67.84 1	75.73 18	80.75 177	56.50 14	86.07 58	71.07 39	80.38 79	87.50 20

PAPM_NR		72.63 63	71.80 64	75.13 68	81.72 65	53.42 122	79.91 84	83.28 52	59.14 115	66.31 140	85.90 77	51.86 54	86.06 59	57.45 137	80.62 73	85.91 58

PAPR		71.72 77	70.82 79	74.41 81	81.20 77	51.17 149	79.55 91	83.33 49	55.81 161	66.93 132	84.61 96	50.95 63	86.06 59	55.79 146	79.20 99	86.00 56

ACMP	63.53 6	72.30 68	71.20 75	75.59 63	80.28 89	57.54 67	82.74 43	82.84 61	60.58 74	65.24 153	86.18 71	39.25 194	86.03 61	66.95 60	76.79 125	83.22 153
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
APD-MVS_3200maxsize		74.96 41	74.39 43	76.67 46	82.20 60	58.24 61	83.67 29	83.29 51	58.41 125	73.71 39	90.14 19	45.62 133	85.99 62	69.64 42	82.85 60	85.78 61

Regformer-4		74.25 49	73.48 50	76.57 48	79.75 96	56.54 83	78.54 103	81.49 79	66.93 8	73.90 35	80.30 187	53.84 38	85.98 63	69.76 41	76.84 123	87.17 30

Effi-MVS+		73.31 57	72.54 59	75.62 61	77.87 136	53.64 117	79.62 90	79.61 122	61.63 61	72.02 60	82.61 126	56.44 15	85.97 64	63.99 89	79.07 101	87.25 29

DP-MVS		65.68 185	63.66 192	71.75 154	84.93 40	56.87 81	80.74 75	73.16 215	53.06 189	59.09 229	82.35 131	36.79 220	85.94 65	32.82 284	69.96 201	72.45 277

OPM-MVS		74.73 44	74.25 44	76.19 50	80.81 81	59.01 51	82.60 46	83.64 39	63.74 33	72.52 54	87.49 49	47.18 119	85.88 66	69.47 43	80.78 71	83.66 146

cascas		65.98 184	63.42 194	73.64 99	77.26 155	52.58 133	72.26 217	77.21 177	48.56 228	61.21 205	74.60 260	32.57 257	85.82 67	50.38 179	76.75 126	82.52 168

IS-MVSNet		71.57 78	71.00 77	73.27 118	78.86 110	45.63 225	80.22 80	78.69 150	64.14 29	66.46 136	87.36 51	49.30 77	85.60 68	50.26 180	83.71 52	88.59 3

HPM-MVS_fast		74.30 48	73.46 52	76.80 43	84.45 45	59.04 50	83.65 30	81.05 92	60.15 84	70.43 68	89.84 25	41.09 182	85.59 69	67.61 54	82.90 58	85.77 63

SD-MVS		77.70 17	77.62 15	77.93 32	84.47 44	61.88 23	84.55 19	83.87 34	60.37 78	79.89 4	89.38 30	54.97 25	85.58 70	76.12 12	84.94 45	86.33 47

mvs-test1		70.44 99	68.19 119	77.18 38	76.10 167	63.22 6	80.59 77	76.06 188	59.83 94	66.32 139	79.87 193	41.56 174	85.53 71	60.60 123	72.77 156	82.80 165

3Dnovator	64.47 5	72.49 65	71.39 70	75.79 54	77.70 139	58.99 52	80.66 76	83.15 54	62.24 52	65.46 148	86.59 64	42.38 163	85.52 72	59.59 131	84.72 46	82.85 164

MAR-MVS		71.51 79	70.15 87	75.60 62	81.84 64	59.39 46	81.38 68	82.90 59	54.90 174	68.08 115	78.70 207	47.73 111	85.51 73	51.68 173	84.17 50	81.88 178
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
MVS		67.37 159	66.33 165	70.51 178	75.46 176	50.94 150	73.95 195	81.85 72	41.57 287	62.54 182	78.57 212	47.98 108	85.47 74	52.97 164	82.05 64	75.14 252

EPNet		73.09 59	72.16 61	75.90 53	75.95 170	56.28 86	83.05 36	72.39 218	66.53 13	65.27 151	87.00 55	50.40 67	85.47 74	62.48 103	86.32 40	85.94 57
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
v7		70.57 92	69.48 101	73.85 86	73.50 198	50.92 152	78.27 107	81.43 80	58.93 116	69.61 85	81.49 158	47.56 114	85.43 76	63.94 90	70.62 182	85.21 92

v10		70.21 104	69.02 107	73.81 88	73.51 197	50.92 152	78.74 97	81.39 82	60.05 86	66.39 138	81.83 147	47.58 113	85.41 77	62.80 100	68.86 214	85.09 96

v1192		69.97 109	68.68 111	73.85 86	73.19 209	50.94 150	77.68 129	81.36 83	57.51 133	68.95 101	80.85 173	45.28 141	85.33 78	62.97 99	70.37 190	85.27 90

v1144		70.42 100	69.31 104	73.76 91	73.22 206	50.64 159	77.83 123	81.43 80	58.58 121	69.40 93	81.16 165	47.53 115	85.29 79	64.01 88	70.64 181	85.34 87

v1240		69.24 123	67.91 123	73.25 120	73.02 218	49.82 187	77.21 139	80.54 109	56.43 150	68.34 109	80.51 181	43.33 159	84.99 80	62.03 114	69.77 206	84.95 101

PAPM		67.92 155	66.69 157	71.63 157	78.09 130	49.02 199	77.09 141	81.24 89	51.04 212	60.91 209	83.98 108	47.71 112	84.99 80	40.81 250	79.32 97	80.90 197

v1921920		69.47 118	68.17 120	73.36 114	73.06 216	50.10 182	77.39 134	80.56 108	56.58 148	68.59 103	80.37 183	44.72 144	84.98 82	62.47 104	69.82 203	85.00 98

v8		70.33 102	69.28 105	73.49 105	73.15 210	50.22 174	78.62 100	80.78 100	60.79 70	66.45 137	82.11 140	49.35 75	84.98 82	63.58 95	68.71 215	85.28 89

v144192		69.71 111	68.51 113	73.33 115	73.10 215	50.13 181	77.54 132	80.64 104	56.65 144	68.57 105	80.55 180	46.87 125	84.96 84	62.98 98	69.66 208	84.89 102

v1neww		70.66 88	69.70 91	73.53 102	73.15 210	50.22 174	78.11 112	80.68 101	59.65 100	69.83 80	81.67 150	49.29 79	84.96 84	64.55 77	70.38 188	85.42 81

v7new		70.66 88	69.70 91	73.53 102	73.15 210	50.22 174	78.11 112	80.68 101	59.65 100	69.83 80	81.67 150	49.29 79	84.96 84	64.55 77	70.38 188	85.42 81

v6		70.66 88	69.70 91	73.53 102	73.14 213	50.21 177	78.11 112	80.67 103	59.65 100	69.82 82	81.65 152	49.29 79	84.96 84	64.55 77	70.39 187	85.42 81

agg_prior3		76.13 34	75.89 34	76.85 42	85.76 23	62.02 21	81.65 61	81.01 95	55.51 166	73.73 38	88.60 43	53.23 44	84.90 88	75.24 15	88.33 13	83.65 147

EI-MVSNet-Vis-set		72.42 67	71.59 66	74.91 69	78.47 121	54.02 113	77.05 142	79.33 139	65.03 20	71.68 62	79.35 201	52.75 47	84.89 89	66.46 61	74.23 140	85.83 60

PCF-MVS	61.88 8	70.95 84	69.49 100	75.35 65	77.63 142	55.71 97	76.04 163	81.81 73	50.30 216	69.66 84	85.40 88	52.51 48	84.89 89	51.82 170	80.24 83	85.45 78
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
v2v482		70.50 95	69.45 103	73.66 97	72.62 227	50.03 183	77.58 130	80.51 110	59.90 90	69.52 89	82.14 139	47.53 115	84.88 91	65.07 72	70.17 197	86.09 54

v1141		70.50 95	69.53 96	73.41 111	72.92 220	50.00 184	77.69 126	80.60 105	59.50 108	69.60 86	81.43 159	49.24 89	84.77 92	64.48 81	70.30 194	85.46 77

divwei89l23v2f112		70.50 95	69.53 96	73.41 111	72.91 221	50.00 184	77.69 126	80.59 106	59.50 108	69.60 86	81.43 159	49.26 84	84.77 92	64.48 81	70.31 193	85.47 75

v1		70.50 95	69.53 96	73.42 110	72.91 221	50.00 184	77.69 126	80.59 106	59.50 108	69.59 88	81.42 161	49.26 84	84.77 92	64.49 80	70.30 194	85.47 75

TEST9					85.58 27	61.59 25	81.62 63	81.26 87	55.65 164	74.93 22	88.81 39	53.70 40	84.68 95

train_agg		76.27 33	76.15 28	76.64 47	85.58 27	61.59 25	81.62 63	81.26 87	55.86 158	74.93 22	88.81 39	53.70 40	84.68 95	75.24 15	88.33 13	83.65 147

EI-MVSNet-UG-set		71.92 74	71.06 76	74.52 79	77.98 134	53.56 119	76.62 148	79.16 141	64.40 26	71.18 64	78.95 206	52.19 53	84.66 97	65.47 69	73.57 149	85.32 88

Regformer-3		73.89 52	73.28 54	75.71 58	79.75 96	55.48 103	78.54 103	79.93 117	66.58 12	73.62 40	80.30 187	54.87 27	84.54 98	69.09 45	76.84 123	87.10 32

v7n		69.01 126	67.36 137	73.98 84	72.51 229	52.65 131	78.54 103	81.30 85	60.26 83	62.67 180	81.62 153	43.61 156	84.49 99	57.01 139	68.70 216	84.79 106

test_8					85.40 30	60.96 32	81.54 66	81.18 90	55.86 158	74.81 25	88.80 41	53.70 40	84.45 100

test_0402		63.25 206	61.01 217	69.96 184	80.00 94	54.37 112	76.86 146	72.02 220	54.58 177	58.71 232	80.79 175	35.00 228	84.36 101	26.41 309	64.71 240	71.15 289

PS-MVSNAJss		72.24 69	71.21 74	75.31 66	78.50 119	55.93 94	81.63 62	82.12 66	56.24 154	70.02 77	85.68 82	47.05 120	84.34 102	65.27 70	74.41 139	85.67 68

DI_MVS_plusplus_test		69.35 120	68.03 122	73.30 117	71.11 248	50.14 180	75.49 170	79.16 141	54.57 178	62.45 186	80.76 176	44.67 146	84.20 103	64.23 84	79.81 88	85.54 72

ACMH+	57.40 11	66.12 182	64.06 185	72.30 149	77.79 138	52.83 129	80.39 78	78.03 164	57.30 134	57.47 242	82.55 128	27.68 281	84.17 104	45.54 216	69.78 204	79.90 209

OpenMVS	61.03 9	68.85 127	67.56 129	72.70 132	74.26 193	53.99 114	81.21 70	81.34 84	52.70 192	62.75 179	85.55 84	38.86 198	84.14 105	48.41 195	83.01 55	79.97 208

Fast-Effi-MVS+		70.28 103	69.12 106	73.73 94	78.50 119	51.50 148	75.01 181	79.46 135	56.16 155	68.59 103	79.55 198	53.97 35	84.05 106	53.34 162	77.53 115	85.65 70

agg_prior1		75.94 36	76.01 31	75.72 57	85.04 34	59.96 40	81.44 67	81.04 93	56.14 156	74.68 26	88.90 37	53.91 36	84.04 107	75.01 17	87.92 24	83.16 158

agg_prior					85.04 34	59.96 40		81.04 93		74.68 26			84.04 107

EG-PatchMatch MVS		64.71 197	62.87 199	70.22 180	77.68 140	53.48 120	77.99 119	78.82 146	53.37 187	56.03 250	77.41 234	24.75 299	84.04 107	46.37 206	73.42 152	73.14 270

Effi-MVS+-dtu		69.64 114	67.53 131	75.95 52	76.10 167	62.29 18	80.20 81	76.06 188	59.83 94	65.26 152	77.09 235	41.56 174	84.02 110	60.60 123	71.09 179	81.53 181

MVS_111021_HR		74.02 50	73.46 52	75.69 59	83.01 55	60.63 36	77.29 138	78.40 161	61.18 67	70.58 67	85.97 76	54.18 34	84.00 111	67.52 55	82.98 57	82.45 170

VDDNet		71.81 75	71.33 72	73.26 119	82.80 57	47.60 213	78.74 97	75.27 195	59.59 106	72.94 49	89.40 29	41.51 177	83.91 112	58.75 133	82.99 56	88.26 5

test_normal		69.26 122	67.90 124	73.32 116	70.84 251	50.38 169	75.30 173	79.17 140	54.23 182	62.00 190	80.61 179	44.69 145	83.89 113	64.33 83	79.95 87	85.69 67

BH-RMVSNet		68.81 128	67.42 134	72.97 123	80.11 93	52.53 134	74.26 192	76.29 184	58.48 124	68.38 108	84.20 103	42.59 161	83.83 114	46.53 204	75.91 129	82.56 166

LFMVS		71.78 76	71.59 66	72.32 148	83.40 51	46.38 221	79.75 87	71.08 222	64.18 28	72.80 51	88.64 42	42.58 162	83.72 115	57.41 138	84.49 48	86.86 36

TR-MVS		66.59 178	65.07 181	71.17 167	79.18 104	49.63 194	73.48 203	75.20 197	52.95 190	67.90 116	80.33 186	39.81 189	83.68 116	43.20 235	73.56 150	80.20 205

MSLP-MVS++		73.77 54	73.47 51	74.66 74	83.02 54	59.29 48	82.30 55	81.88 70	59.34 113	71.59 63	86.83 56	45.94 131	83.65 117	65.09 71	85.22 44	81.06 195

NR-MVSNet		69.54 116	68.85 108	71.59 158	78.05 132	43.81 240	74.20 193	80.86 99	65.18 17	62.76 178	84.52 98	52.35 52	83.59 118	50.96 176	70.78 180	87.37 25

BH-untuned		68.27 145	67.29 139	71.21 165	79.74 98	53.22 124	76.06 161	77.46 174	57.19 135	66.10 141	81.61 154	45.37 140	83.50 119	45.42 220	76.68 127	76.91 238

UniMVSNet (Re)		70.63 91	70.20 85	71.89 151	78.55 118	45.29 226	75.94 165	82.92 57	63.68 34	68.16 112	83.59 112	53.89 37	83.49 120	53.97 156	71.12 178	86.89 35

v52		67.09 165	65.16 179	72.87 126	66.77 282	51.60 146	73.69 201	79.45 136	57.88 130	62.46 185	78.57 212	40.95 184	83.34 121	61.99 115	64.70 242	83.68 143

V4		67.09 165	65.16 179	72.87 126	66.76 283	51.60 146	73.69 201	79.45 136	57.88 130	62.45 186	78.58 211	40.96 183	83.34 121	61.99 115	64.71 240	83.68 143

VDD-MVS		72.50 64	72.09 62	73.75 93	81.58 66	49.69 192	77.76 125	77.63 170	63.21 36	73.21 45	89.02 35	42.14 164	83.32 123	61.72 118	82.50 61	88.25 6

UA-Net		73.13 58	72.93 56	73.76 91	83.58 50	51.66 145	78.75 96	77.66 169	67.75 4	72.61 53	89.42 28	49.82 70	83.29 124	53.61 160	83.14 53	86.32 48

MVSFormer		71.50 80	70.38 84	74.88 70	78.76 113	57.15 78	82.79 41	78.48 156	51.26 210	69.49 90	83.22 117	43.99 154	83.24 125	66.06 62	79.37 94	84.23 123

test_djsdf		69.45 119	67.74 125	74.58 78	74.57 187	54.92 108	82.79 41	78.48 156	51.26 210	65.41 149	83.49 115	38.37 202	83.24 125	66.06 62	69.25 211	85.56 71

ACMM	61.98 7	70.80 87	69.73 90	74.02 83	80.59 86	58.59 57	82.68 44	82.02 69	55.46 167	67.18 129	84.39 102	38.51 200	83.17 127	60.65 122	76.10 128	80.30 204
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
testing_2		66.02 183	63.77 190	72.76 131	66.03 288	50.48 167	72.93 208	80.36 114	54.41 180	54.25 267	76.76 240	30.89 262	83.16 128	64.19 85	74.08 142	84.65 109

Test4		67.77 156	65.97 168	73.19 121	68.64 268	50.58 161	74.80 187	80.48 111	54.13 183	59.11 228	79.07 205	33.89 239	83.12 129	63.61 94	79.98 86	85.87 59

TranMVSNet+NR-MVSNet		70.36 101	70.10 88	71.17 167	78.64 117	42.97 247	76.53 150	81.16 91	66.95 7	68.53 106	85.42 87	51.61 57	83.07 130	52.32 167	69.70 207	87.46 22

V42		68.65 132	67.35 138	72.56 136	68.93 267	50.18 178	72.90 209	79.47 134	56.92 137	69.45 92	80.26 189	46.29 129	82.99 131	64.07 86	67.82 221	84.53 112

SixPastTwentyTwo		61.65 223	58.80 228	70.20 182	75.80 171	47.22 216	75.59 168	69.68 232	54.61 176	54.11 268	79.26 202	27.07 286	82.96 132	43.27 233	49.79 306	80.41 203

BH-w/o		66.85 171	65.83 170	69.90 186	79.29 101	52.46 136	74.66 188	76.65 182	54.51 179	64.85 160	78.12 214	45.59 135	82.95 133	43.26 234	75.54 132	74.27 264

v18		68.33 142	66.96 148	72.42 145	73.13 214	50.16 179	77.97 120	79.57 131	59.57 107	61.80 193	77.50 232	49.30 77	82.90 134	62.31 107	61.50 264	84.20 129

v17		68.37 141	67.00 147	72.48 139	73.22 206	50.31 170	78.10 115	79.58 129	59.71 98	61.67 196	77.60 227	49.31 76	82.89 135	62.37 105	61.48 266	84.23 123

v16		68.38 140	67.01 146	72.47 143	73.22 206	50.29 171	78.10 115	79.59 127	59.71 98	61.72 195	77.60 227	49.28 82	82.89 135	62.36 106	61.54 263	84.23 123

PVSNet_BlendedMVS		68.56 137	67.72 126	71.07 170	77.03 158	50.57 162	74.50 190	81.52 76	53.66 186	64.22 169	79.72 196	49.13 93	82.87 137	55.82 144	73.92 144	79.77 211

PVSNet_Blended		68.59 133	67.72 126	71.19 166	77.03 158	50.57 162	72.51 214	81.52 76	51.91 200	64.22 169	77.77 222	49.13 93	82.87 137	55.82 144	79.58 91	80.14 207

UniMVSNet_NR-MVSNet		71.11 83	71.00 77	71.44 159	79.20 103	44.13 236	76.02 164	82.60 62	66.48 14	68.20 110	84.60 97	56.82 13	82.82 139	54.62 152	70.43 185	87.36 27

DU-MVS		70.01 107	69.53 96	71.44 159	78.05 132	44.13 236	75.01 181	81.51 78	64.37 27	68.20 110	84.52 98	49.12 95	82.82 139	54.62 152	70.43 185	87.37 25

v15		68.22 150	66.81 154	72.47 143	73.25 205	50.40 168	77.92 122	79.60 124	59.77 97	61.28 204	77.52 231	49.25 86	82.77 141	62.16 112	60.51 273	84.24 122

v13		68.29 143	66.84 150	72.63 133	73.50 198	50.83 155	78.25 108	79.58 129	60.05 86	60.76 211	77.68 224	49.11 98	82.77 141	62.17 110	60.45 277	84.30 118

v12		68.28 144	66.83 152	72.60 135	73.43 200	50.74 157	78.18 110	79.59 127	60.01 88	60.89 210	77.66 225	49.12 95	82.77 141	62.18 108	60.46 276	84.29 119

V14		68.25 147	66.82 153	72.52 138	73.33 204	50.53 165	78.02 118	79.60 124	59.83 94	61.16 206	77.57 229	49.19 90	82.77 141	62.18 108	60.50 274	84.26 121

V9		68.27 145	66.84 150	72.56 136	73.39 203	50.63 160	78.10 115	79.60 124	59.94 89	61.05 208	77.62 226	49.18 91	82.77 141	62.17 110	60.48 275	84.27 120

v11		68.15 153	66.73 155	72.42 145	73.43 200	50.28 172	77.94 121	79.65 121	59.88 93	61.11 207	77.55 230	48.25 106	82.75 146	61.88 117	60.85 270	84.23 123

MVP-Stereo		65.41 190	63.80 189	70.22 180	77.62 146	55.53 101	76.30 154	78.53 154	50.59 215	56.47 248	78.65 209	39.84 188	82.68 147	44.10 227	72.12 170	72.44 278
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
Vis-MVSNet		72.18 70	71.37 71	74.61 77	81.29 73	55.41 104	80.90 72	78.28 163	60.73 72	69.23 98	88.09 46	44.36 151	82.65 148	57.68 136	81.75 67	85.77 63
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PVSNet_Blended_VisFu		71.45 81	70.39 83	74.65 75	82.01 61	58.82 54	79.93 83	80.35 115	55.09 170	65.82 147	82.16 138	49.17 92	82.64 149	60.34 125	78.62 108	82.50 169

EI-MVSNet		69.27 121	68.44 116	71.73 155	74.47 188	49.39 196	75.20 177	78.45 158	59.60 103	69.16 99	76.51 244	51.29 58	82.50 150	59.86 130	71.45 176	83.30 151

MVSTER		67.16 164	65.58 173	71.88 152	70.37 256	49.70 190	70.25 240	78.45 158	51.52 205	69.16 99	80.37 183	38.45 201	82.50 150	60.19 126	71.46 175	83.44 149

gm-plane-assit					71.40 246	41.72 255			48.85 227		73.31 268		82.48 152	48.90 191

LS3D		64.71 197	62.50 204	71.34 163	79.72 100	55.71 97	79.82 85	74.72 204	48.50 230	56.62 246	84.62 95	33.59 242	82.34 153	29.65 300	75.23 133	75.97 242

PS-MVSNAJ		70.51 94	69.70 91	72.93 124	81.52 67	55.79 96	74.92 184	79.00 144	55.04 172	69.88 79	78.66 208	47.05 120	82.19 154	61.61 119	79.58 91	80.83 198

v748		67.26 161	65.67 171	72.02 150	69.90 262	49.77 189	76.24 156	79.57 131	58.58 121	60.49 214	80.38 182	44.47 150	82.17 155	56.16 142	65.26 237	84.12 131

xiu_mvs_v2_base		70.52 93	69.75 89	72.84 128	81.21 76	55.63 100	75.11 179	78.92 145	54.92 173	69.96 78	79.68 197	47.00 124	82.09 156	61.60 120	79.37 94	80.81 199

canonicalmvs		74.67 45	74.98 39	73.71 95	78.94 109	50.56 164	80.23 79	83.87 34	60.30 82	77.15 11	86.56 66	59.65 5	82.00 157	66.01 64	82.12 63	88.58 4

v148		68.24 149	67.19 144	71.40 162	70.43 254	47.77 211	75.76 167	77.03 179	58.91 117	67.36 127	80.10 191	48.60 103	81.89 158	60.01 127	66.52 229	84.53 112

CPTT-MVS		72.78 61	72.08 63	74.87 71	84.88 42	61.41 27	84.15 25	77.86 165	55.27 168	67.51 126	88.08 47	41.93 167	81.85 159	69.04 46	80.01 85	81.35 189

mvs_tets		68.18 151	66.36 164	73.63 100	75.61 174	55.35 105	80.77 74	78.56 153	52.48 195	64.27 168	84.10 106	27.45 283	81.84 160	63.45 97	70.56 184	83.69 142

jajsoiax		68.25 147	66.45 160	73.66 97	75.62 173	55.49 102	80.82 73	78.51 155	52.33 196	64.33 166	84.11 105	28.28 277	81.81 161	63.48 96	70.62 182	83.67 145

FIs		70.82 86	71.43 68	68.98 196	78.33 123	38.14 272	76.96 144	83.59 40	61.02 68	67.33 128	86.73 57	55.07 24	81.64 162	54.61 154	79.22 98	87.14 31

HyFIR lowres test		65.67 186	63.01 198	73.67 96	79.97 95	55.65 99	69.07 247	75.52 192	42.68 281	63.53 171	77.95 216	40.43 186	81.64 162	46.01 210	71.91 171	83.73 141

K. test v3		60.47 228	57.11 238	70.56 177	73.74 196	48.22 205	75.10 180	62.55 275	58.27 128	53.62 272	76.31 246	27.81 280	81.59 164	47.42 197	39.18 318	81.88 178

IterMVS-LS		69.22 124	68.48 114	71.43 161	74.44 190	49.40 195	76.23 157	77.55 171	59.60 103	65.85 146	81.59 156	51.28 59	81.58 165	59.87 129	69.90 202	83.30 151
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
LTVRE_ROB	55.42 16	63.15 207	61.23 216	68.92 197	76.57 163	47.80 209	59.92 285	76.39 183	54.35 181	58.67 233	82.46 130	29.44 272	81.49 166	42.12 242	71.14 177	77.46 228
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
tpmp4_e23		62.71 214	60.13 221	70.45 179	73.40 202	48.39 204	72.82 210	69.49 236	44.88 261	59.91 217	74.99 256	37.79 209	81.47 167	40.22 252	67.71 223	81.48 182

lessismore_v0				69.91 185	71.42 245	47.80 209		50.90 316		50.39 286	75.56 253	27.43 284	81.33 168	45.91 211	34.10 321	80.59 200

OurMVSNet-221017-0		61.37 225	58.63 230	69.61 188	72.05 236	48.06 207	73.93 198	72.51 217	47.23 243	54.74 260	80.92 170	21.49 306	81.24 169	48.57 194	56.22 287	79.53 213

alignmvs		73.86 53	73.99 46	73.45 107	78.20 126	50.50 166	78.57 101	82.43 63	59.40 111	76.57 12	86.71 59	56.42 16	81.23 170	65.84 66	81.79 65	88.62 2

MVS_Test		72.45 66	72.46 60	72.42 145	74.88 181	48.50 203	76.28 155	83.14 55	59.40 111	72.46 55	84.68 93	55.66 21	81.12 171	65.98 65	79.66 90	87.63 17

GA-MVS		65.53 188	63.70 191	71.02 171	70.87 250	48.10 206	70.48 236	74.40 207	56.69 143	64.70 162	76.77 239	33.66 241	81.10 172	55.42 149	70.32 192	83.87 136

MSDG		61.81 222	59.23 225	69.55 192	72.64 226	52.63 132	70.45 237	75.81 190	51.38 208	53.70 270	76.11 247	29.52 270	81.08 173	37.70 262	65.79 233	74.93 257

ambc				65.13 237	63.72 298	37.07 278	47.66 315	78.78 148		54.37 266	71.42 276	11.24 324	80.94 174	45.64 214	53.85 296	77.38 229

ACMH	55.70 15	65.20 193	63.57 193	70.07 183	78.07 131	52.01 144	79.48 94	79.69 119	55.75 162	56.59 247	80.98 169	27.12 285	80.94 174	42.90 239	71.58 174	77.25 234
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
UGNet		68.81 128	67.39 135	73.06 122	78.33 123	54.47 111	79.77 86	75.40 194	60.45 76	63.22 173	84.40 101	32.71 253	80.91 176	51.71 172	80.56 77	83.81 137
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
nrg030		72.96 60	73.01 55	72.84 128	75.41 177	50.24 173	80.02 82	82.89 60	58.36 127	74.44 29	86.73 57	58.90 10	80.83 177	65.84 66	74.46 137	87.44 23

tpm2		62.07 218	60.10 222	67.99 205	72.79 224	43.86 239	71.05 230	66.85 251	43.14 278	62.77 177	75.39 254	38.32 203	80.80 178	41.69 245	68.88 213	79.32 215

无先验							79.66 89	74.30 208	48.40 232				80.78 179	53.62 158		79.03 219

1121		68.53 138	67.16 145	72.63 133	85.64 26	61.14 29	73.95 195	66.46 253	44.61 265	70.28 71	86.68 60	41.42 178	80.78 179	53.62 158	81.79 65	75.97 242

FC-MVSNet-test		69.80 110	70.58 82	67.46 209	77.61 147	34.73 296	76.05 162	83.19 53	60.84 69	65.88 145	86.46 67	54.52 31	80.76 181	52.52 166	78.12 111	86.91 34

OMC-MVS		71.40 82	70.60 81	73.78 89	76.60 162	53.15 125	79.74 88	79.78 118	58.37 126	68.75 102	86.45 68	45.43 138	80.60 182	62.58 101	77.73 113	87.58 19

Fast-Effi-MVS+-dtu		67.37 159	65.33 176	73.48 106	72.94 219	57.78 65	77.47 133	76.88 180	57.60 132	61.97 191	76.85 238	39.31 193	80.49 183	54.72 151	70.28 196	82.17 174

anonymousdsp		67.00 169	64.82 183	73.57 101	70.09 258	56.13 89	76.35 153	77.35 176	48.43 231	64.99 159	80.84 174	33.01 246	80.34 184	64.66 74	67.64 224	84.23 123

GBi-Net		67.21 162	66.55 158	69.19 193	77.63 142	43.33 243	77.31 135	77.83 166	56.62 145	65.04 156	82.70 122	41.85 169	80.33 185	47.18 199	72.76 157	83.92 133

test1		67.21 162	66.55 158	69.19 193	77.63 142	43.33 243	77.31 135	77.83 166	56.62 145	65.04 156	82.70 122	41.85 169	80.33 185	47.18 199	72.76 157	83.92 133

FMVSNet1		66.70 174	65.87 169	69.19 193	77.49 149	43.33 243	77.31 135	77.83 166	56.45 149	64.60 163	82.70 122	38.08 207	80.33 185	46.08 209	72.31 168	83.92 133

FMVSNet2		66.93 170	66.31 167	68.79 199	77.63 142	42.98 246	76.11 159	77.47 172	56.62 145	65.22 155	82.17 137	41.85 169	80.18 188	47.05 202	72.72 160	83.20 154

FMVSNet3		66.32 181	65.61 172	68.46 202	76.48 165	42.34 250	74.98 183	77.15 178	55.83 160	65.04 156	81.16 165	39.91 187	80.14 189	47.18 199	72.76 157	82.90 163

PLC	56.13 14	65.09 194	63.21 196	70.72 175	81.04 79	54.87 109	78.57 101	77.47 172	48.51 229	55.71 251	81.89 146	33.71 240	79.71 190	41.66 246	70.37 190	77.58 227
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
OpenMVS_ROB	52.78 18	60.03 229	58.14 233	65.69 229	70.47 253	44.82 228	75.33 172	70.86 224	45.04 260	56.06 249	76.00 248	26.89 288	79.65 191	35.36 276	67.29 225	72.60 274

CostFormer		64.04 202	62.51 203	68.61 201	71.88 239	45.77 224	71.30 227	70.60 226	47.55 240	64.31 167	76.61 242	41.63 172	79.62 192	49.74 184	69.00 212	80.42 202

WR-MVS_H		67.02 168	66.92 149	67.33 212	77.95 135	37.75 275	77.57 131	82.11 67	62.03 58	62.65 181	82.48 129	50.57 66	79.46 193	42.91 238	64.01 246	84.79 106

COLMAP_ROB	52.97 17	61.27 226	58.81 227	68.64 200	74.63 185	52.51 135	78.42 106	73.30 213	49.92 220	50.96 282	81.51 157	23.06 302	79.40 194	31.63 289	65.85 231	74.01 267
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
1314		64.61 199	63.21 196	68.80 198	71.87 240	47.46 214	73.95 195	78.39 162	42.88 280	59.97 216	76.60 243	38.11 206	79.39 195	54.84 150	72.32 167	79.55 212

XVG-ACMP-BASELINE		64.36 201	62.23 205	70.74 174	72.35 231	52.45 137	70.80 233	78.45 158	53.84 185	59.87 218	81.10 167	16.24 312	79.32 196	55.64 148	71.76 172	80.47 201

lupinMVS		69.57 115	68.28 118	73.44 108	78.76 113	57.15 78	76.57 149	73.29 214	46.19 251	69.49 90	82.18 135	43.99 154	79.23 197	64.66 74	79.37 94	83.93 132

jason		69.65 113	68.39 117	73.43 109	78.27 125	56.88 80	77.12 140	73.71 212	46.53 247	69.34 94	83.22 117	43.37 158	79.18 198	64.77 73	79.20 99	84.23 123
jason: jason.
DTE-MVSNet		65.58 187	65.34 175	66.31 218	76.06 169	34.79 294	76.43 152	79.38 138	62.55 48	61.66 197	83.83 109	45.60 134	79.15 199	41.64 248	60.88 269	85.00 98

WR-MVS		68.47 139	68.47 115	68.44 203	80.20 92	39.84 262	73.75 200	76.07 187	64.68 21	68.11 114	83.63 111	50.39 68	79.14 200	49.78 182	69.66 208	86.34 46

PEN-MVS		66.60 176	66.45 160	67.04 213	77.11 156	36.56 286	77.03 143	80.42 112	62.95 39	62.51 184	84.03 107	46.69 126	79.07 201	44.22 224	63.08 254	85.51 74

xiu_mvs_v1_base_debu		68.58 134	67.28 140	72.48 139	78.19 127	57.19 75	75.28 174	75.09 199	51.61 202	70.04 74	81.41 162	32.79 249	79.02 202	63.81 91	77.31 116	81.22 191

xiu_mvs_v1_base		68.58 134	67.28 140	72.48 139	78.19 127	57.19 75	75.28 174	75.09 199	51.61 202	70.04 74	81.41 162	32.79 249	79.02 202	63.81 91	77.31 116	81.22 191

xiu_mvs_v1_base_debi		68.58 134	67.28 140	72.48 139	78.19 127	57.19 75	75.28 174	75.09 199	51.61 202	70.04 74	81.41 162	32.79 249	79.02 202	63.81 91	77.31 116	81.22 191

diffmvs		67.72 157	66.73 155	70.70 176	69.74 264	47.69 212	73.33 204	74.74 203	53.30 188	64.51 164	81.80 148	49.25 86	79.02 202	59.15 132	74.75 135	85.39 86

TAPA-MVS	59.36 10	66.60 176	65.20 178	70.81 172	76.63 161	48.75 201	76.52 151	80.04 116	50.64 214	65.24 153	84.93 90	39.15 195	78.54 206	36.77 267	76.88 122	85.14 93
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
view600		62.77 210	61.84 207	65.55 230	77.28 151	36.87 280	72.15 219	67.78 242	56.79 139	61.46 200	81.92 142	36.88 215	78.42 207	29.86 295	72.46 161	81.36 185

view800		62.77 210	61.84 207	65.55 230	77.28 151	36.87 280	72.15 219	67.78 242	56.79 139	61.46 200	81.92 142	36.88 215	78.42 207	29.86 295	72.46 161	81.36 185

conf0.05thres1000		62.77 210	61.84 207	65.55 230	77.28 151	36.87 280	72.15 219	67.78 242	56.79 139	61.46 200	81.92 142	36.88 215	78.42 207	29.86 295	72.46 161	81.36 185

tfpn		62.77 210	61.84 207	65.55 230	77.28 151	36.87 280	72.15 219	67.78 242	56.79 139	61.46 200	81.92 142	36.88 215	78.42 207	29.86 295	72.46 161	81.36 185

PS-CasMVS		66.42 180	66.32 166	66.70 216	77.60 148	36.30 290	76.94 145	79.61 122	62.36 51	62.43 188	83.66 110	45.69 132	78.37 211	45.35 221	63.26 252	85.42 81

CP-MVSNet		66.49 179	66.41 163	66.72 215	77.67 141	36.33 288	76.83 147	79.52 133	62.45 49	62.54 182	83.47 116	46.32 128	78.37 211	45.47 219	63.43 251	85.45 78

XVG-OURS		68.76 131	67.37 136	72.90 125	74.32 192	57.22 73	70.09 241	78.81 147	55.24 169	67.79 123	85.81 81	36.54 222	78.28 213	62.04 113	75.74 130	83.19 155

XVG-OURS-SEG-HR		68.81 128	67.47 133	72.82 130	74.40 191	56.87 81	70.59 234	79.04 143	54.77 175	66.99 131	86.01 75	39.57 192	78.21 214	62.54 102	73.33 153	83.37 150

F-COLMAP		63.05 208	60.87 218	69.58 191	76.99 160	53.63 118	78.12 111	76.16 185	47.97 237	52.41 277	81.61 154	27.87 279	78.11 215	40.07 253	66.66 227	77.00 236

TransMVSNet (Re)		64.72 196	64.33 184	65.87 227	75.22 178	38.56 269	74.66 188	75.08 202	58.90 118	61.79 194	82.63 125	51.18 60	78.07 216	43.63 231	55.87 288	80.99 196

mvs_anonymous		68.03 154	67.51 132	69.59 189	72.08 235	44.57 233	71.99 224	75.23 196	51.67 201	67.06 130	82.57 127	54.68 29	77.94 217	56.56 140	75.71 131	86.26 51

GG-mvs-BLEND				62.34 252	71.36 247	37.04 279	69.20 246	57.33 294		54.73 261	65.48 301	30.37 264	77.82 218	34.82 277	74.93 134	72.17 283

CHOSEN 1792x2688		65.08 195	62.84 200	71.82 153	81.49 69	56.26 87	66.32 256	74.20 209	40.53 293	63.16 175	78.65 209	41.30 179	77.80 219	45.80 212	74.09 141	81.40 184

DWT-MVSNet_test		61.90 219	59.93 223	67.83 206	71.98 238	46.09 223	71.03 231	69.71 230	50.09 217	58.51 236	70.62 280	30.21 267	77.63 220	49.28 188	67.91 219	79.78 210

VPA-MVSNet		69.02 125	69.47 102	67.69 208	77.42 150	41.00 260	74.04 194	79.68 120	60.06 85	69.26 97	84.81 92	51.06 62	77.58 221	54.44 155	74.43 138	84.48 114

MS-PatchMatch		62.42 215	61.46 213	65.31 236	75.21 179	52.10 140	72.05 223	74.05 210	46.41 249	57.42 243	74.36 261	34.35 234	77.57 222	45.62 215	73.67 146	66.26 300

CANet_DTU		68.18 151	67.71 128	69.59 189	74.83 182	46.24 222	78.66 99	76.85 181	59.60 103	63.45 172	82.09 141	35.25 227	77.41 223	59.88 128	78.76 105	85.14 93

TAMVS		66.78 173	65.27 177	71.33 164	79.16 106	53.67 116	73.84 199	69.59 234	52.32 197	65.28 150	81.72 149	44.49 149	77.40 224	42.32 241	78.66 107	82.92 161

Baseline_NR-MVSNet		67.05 167	67.56 129	65.50 234	75.65 172	37.70 276	75.42 171	74.65 205	59.90 90	68.14 113	83.15 120	49.12 95	77.20 225	52.23 168	69.78 204	81.60 180

CDS-MVSNet		66.80 172	65.37 174	71.10 169	78.98 108	53.13 127	73.27 205	71.07 223	52.15 198	64.72 161	80.23 190	43.56 157	77.10 226	45.48 218	78.88 102	83.05 160
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
VNet		69.68 112	70.19 86	68.16 204	79.73 99	41.63 256	70.53 235	77.38 175	60.37 78	70.69 66	86.63 62	51.08 61	77.09 227	53.61 160	81.69 69	85.75 65

pmmvs6		63.69 204	62.82 201	66.27 220	70.63 252	39.27 266	73.13 206	75.47 193	52.69 193	59.75 221	82.30 133	39.71 190	77.03 228	47.40 198	64.35 245	82.53 167

LCM-MVSNet-Re		61.88 221	61.35 214	63.46 244	74.58 186	31.48 309	61.42 279	58.14 290	58.71 120	53.02 276	79.55 198	43.07 160	76.80 229	45.69 213	77.96 112	82.11 175

Anonymous20231211		55.92 254	53.63 263	62.77 250	68.22 274	35.56 292	74.48 191	69.89 229	46.42 248	49.07 289	73.45 267	21.13 307	76.77 230	28.74 302	51.30 302	75.97 242

HY-MVS	56.14 13	64.55 200	63.89 187	66.55 217	74.73 184	41.02 258	69.96 242	74.43 206	49.29 222	61.66 197	80.92 170	47.43 118	76.68 231	44.91 223	71.69 173	81.94 176

VPNet		67.52 158	68.11 121	65.74 228	79.18 104	36.80 284	72.17 218	72.83 216	62.04 57	67.79 123	85.83 79	48.88 99	76.60 232	51.30 174	72.97 155	83.81 137

pm-mvs1		65.24 192	64.97 182	66.04 223	72.38 230	39.40 265	72.62 212	75.63 191	55.53 165	62.35 189	83.18 119	47.45 117	76.47 233	49.06 190	66.54 228	82.24 172

gg-mvs-nofinetune		57.86 243	56.43 245	62.18 253	72.62 227	35.35 293	66.57 253	56.33 299	50.65 213	57.64 241	57.10 315	30.65 263	76.36 234	37.38 264	78.88 102	74.82 259

MVS_111021_LR		69.50 117	68.78 110	71.65 156	78.38 122	59.33 47	74.82 186	70.11 228	58.08 129	67.83 121	84.68 93	41.96 166	76.34 235	65.62 68	77.54 114	79.30 216

tpmvs		58.47 238	56.95 241	63.03 249	70.20 257	41.21 257	67.90 251	67.23 249	49.62 221	54.73 261	70.84 279	34.14 235	76.24 236	36.64 270	61.29 267	71.64 285

ab-mvs		66.65 175	66.42 162	67.37 210	76.17 166	41.73 254	70.41 238	76.14 186	53.99 184	65.98 142	83.51 114	49.48 74	76.24 236	48.60 193	73.46 151	84.14 130

Vis-MVSNet (Re-imp)		63.69 204	63.88 188	63.14 247	74.75 183	31.04 310	71.16 229	63.64 267	56.32 151	59.80 220	84.99 89	44.51 147	75.46 238	39.12 257	80.62 73	82.92 161

新几何1				70.76 173	85.66 24	61.13 30		66.43 254	44.68 264	70.29 70	86.64 61	41.29 180	75.23 239	49.72 185	81.75 67	75.93 245

PatchFormer-LS_test		62.20 217	60.59 219	67.04 213	72.18 234	46.82 219	70.36 239	68.62 239	51.92 199	59.19 227	70.23 283	36.86 219	75.07 240	50.23 181	65.68 234	79.23 217

USDC		56.35 251	54.24 259	62.69 251	64.74 293	40.31 261	65.05 265	73.83 211	43.93 272	47.58 291	77.71 223	15.36 314	75.05 241	38.19 261	61.81 261	72.70 273

pmmvs4		61.48 224	59.39 224	67.76 207	71.57 242	53.86 115	71.42 225	65.34 257	44.20 269	59.46 222	77.92 218	35.90 223	74.71 242	43.87 229	64.87 239	74.71 261

tpm cat1		59.25 235	56.95 241	66.15 221	72.19 233	46.96 217	68.09 250	65.76 255	40.03 296	57.81 240	70.56 281	38.32 203	74.51 243	38.26 260	61.50 264	77.00 236

patchmatchnet-post											64.03 302	34.50 231	74.27 244

1112_ss		64.00 203	63.36 195	65.93 226	79.28 102	42.58 249	71.35 226	72.36 219	46.41 249	60.55 213	77.89 219	46.27 130	73.28 245	46.18 207	69.97 200	81.92 177

TinyColmap		54.14 261	51.72 269	61.40 258	66.84 281	41.97 251	66.52 254	68.51 240	44.81 262	42.69 310	75.77 251	11.66 322	72.94 246	31.96 286	56.77 286	69.27 296

pmmvs-eth3d		58.81 236	56.31 246	66.30 219	67.61 276	52.42 138	72.30 216	64.76 261	43.55 274	54.94 259	74.19 263	28.95 274	72.60 247	43.31 232	57.21 285	73.88 268

IterMVS		62.79 209	61.27 215	67.35 211	69.37 265	52.04 143	71.17 228	68.24 241	52.63 194	59.82 219	76.91 237	37.32 212	72.36 248	52.80 165	63.19 253	77.66 226
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Patchmatch-RL test		58.16 241	55.49 251	66.15 221	67.92 275	48.89 200	60.66 284	51.07 315	47.86 238	59.36 223	62.71 308	34.02 237	72.27 249	56.41 141	59.40 280	77.30 230

testdata2													72.18 250	46.95 203

CMPMVS	42.80 21	57.81 244	55.97 248	63.32 245	60.98 308	47.38 215	64.66 267	69.50 235	32.06 314	46.83 295	77.80 221	29.50 271	71.36 251	48.68 192	73.75 145	71.21 288
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
Test_1112_low_res		62.32 216	61.77 211	64.00 243	79.08 107	39.53 264	68.17 249	70.17 227	43.25 276	59.03 230	79.90 192	44.08 152	71.24 252	43.79 230	68.42 217	81.25 190

CNLPA		65.43 189	64.02 186	69.68 187	78.73 115	58.07 62	77.82 124	70.71 225	51.49 206	61.57 199	83.58 113	38.23 205	70.82 253	43.90 228	70.10 199	80.16 206

CR-MVSNet		59.91 230	57.90 236	65.96 224	69.96 260	52.07 141	65.31 263	63.15 271	42.48 282	59.36 223	74.84 257	35.83 224	70.75 254	45.50 217	64.65 243	75.06 253

RPMNet		58.70 237	56.29 247	65.96 224	69.96 260	52.07 141	65.31 263	62.15 278	43.20 277	59.36 223	70.15 285	35.37 226	70.75 254	36.42 273	64.65 243	75.06 253

MDTV_nov1_ep13			57.00 240		72.73 225	38.26 271	65.02 266	64.73 262	44.74 263	55.46 253	72.48 270	32.61 256	70.47 256	37.47 263	67.75 222

JIA-IIPM		51.56 273	47.68 281	63.21 246	64.61 294	50.73 158	47.71 314	58.77 288	42.90 279	48.46 290	51.72 319	24.97 297	70.24 257	36.06 275	53.89 295	68.64 298

Patchmatch-test1		59.75 232	58.00 235	64.98 238	74.14 195	48.06 207	63.35 271	63.23 270	49.13 224	59.33 226	71.46 275	37.45 211	69.59 258	41.39 249	62.57 257	77.30 230

test_post1							68.67 248				3.64 334	32.39 258	69.49 259	44.17 225

PatchmatchNet		59.84 231	58.24 231	64.65 240	73.05 217	46.70 220	69.42 245	62.18 277	47.55 240	58.88 231	71.96 273	34.49 232	69.16 260	42.99 237	63.60 249	78.07 224
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
EU-MVSNet		55.61 257	54.41 257	59.19 263	65.41 291	33.42 302	72.44 215	71.91 221	28.81 317	51.27 280	73.87 264	24.76 298	69.08 261	43.04 236	58.20 284	75.06 253

Patchmtry		57.16 247	56.47 244	59.23 262	69.17 266	34.58 297	62.98 272	63.15 271	44.53 266	56.83 245	74.84 257	35.83 224	68.71 262	40.03 254	60.91 268	74.39 263

CVMVSNet		59.63 234	59.14 226	61.08 260	74.47 188	38.84 267	75.20 177	68.74 238	31.15 315	58.24 238	76.51 244	32.39 258	68.58 263	49.77 183	65.84 232	75.81 246

MDA-MVSNet-bldmvs		53.87 264	50.81 271	63.05 248	66.25 285	48.58 202	56.93 294	63.82 266	48.09 235	41.22 311	70.48 282	30.34 265	68.00 264	34.24 279	45.92 313	72.57 275

AllTest		57.08 248	54.65 255	64.39 241	71.44 243	49.03 197	69.92 243	67.30 247	45.97 254	47.16 293	79.77 194	17.47 309	67.56 265	33.65 281	59.16 281	76.57 239

TestCases				64.39 241	71.44 243	49.03 197		67.30 247	45.97 254	47.16 293	79.77 194	17.47 309	67.56 265	33.65 281	59.16 281	76.57 239

pmmvs5		56.47 249	55.68 250	58.86 265	61.41 305	36.71 285	66.37 255	62.75 274	40.38 294	53.70 270	76.62 241	34.56 230	67.05 267	40.02 255	65.27 236	72.83 272

EPNet_dtu		61.90 219	61.97 206	61.68 255	72.89 223	39.78 263	75.85 166	65.62 256	55.09 170	54.56 263	79.36 200	37.59 210	67.02 268	39.80 256	76.95 121	78.25 222
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PatchMatch-RL		56.25 252	54.55 256	61.32 259	77.06 157	56.07 91	65.57 259	54.10 311	44.13 271	53.49 275	71.27 278	25.20 296	66.78 269	36.52 272	63.66 248	61.12 309

test_post											3.55 335	33.90 238	66.52 270

TDRefinement		53.44 266	50.72 272	61.60 256	64.31 296	46.96 217	70.89 232	65.27 259	41.78 283	44.61 302	77.98 215	11.52 323	66.36 271	28.57 304	51.59 300	71.49 286

testdata				64.66 239	81.52 67	52.93 128		65.29 258	46.09 252	73.88 36	87.46 50	38.08 207	66.26 272	53.31 163	78.48 109	74.78 260

no-one		40.85 295	36.09 299	55.14 281	48.55 325	38.72 268	42.15 323	62.92 273	34.60 311	23.55 324	49.74 323	12.21 320	66.16 273	26.27 310	24.84 323	60.54 310

semantic-postprocess				65.40 235	71.99 237	50.80 156		69.63 233	45.71 258	60.61 212	77.93 217	36.56 221	65.99 274	55.67 147	63.50 250	79.42 214

PM-MVS		52.33 270	50.19 273	58.75 266	62.10 302	45.14 227	65.75 257	40.38 328	43.60 273	53.52 273	72.65 269	9.16 328	65.87 275	50.41 178	54.18 294	65.24 302

旧先验2							76.08 160		45.32 259	76.55 13			65.56 276	58.75 133

PVSNet	50.76 19	58.40 239	57.39 237	61.42 257	75.53 175	44.04 238	61.43 278	63.45 268	47.04 245	56.91 244	73.61 266	27.00 287	64.76 277	39.12 257	72.40 165	75.47 250

MVS-HIRNet		45.52 286	44.48 288	48.65 301	68.49 271	34.05 299	59.41 288	44.50 326	27.03 319	37.96 317	50.47 322	26.16 292	64.10 278	26.74 308	59.52 279	47.82 319

FMVSNet5		55.86 255	54.93 253	58.66 267	71.05 249	36.35 287	64.18 270	62.48 276	46.76 246	50.66 285	74.73 259	25.80 293	64.04 279	33.11 283	65.57 235	75.59 249

MIMVSNet1		55.17 259	54.31 258	57.77 272	70.03 259	32.01 307	65.68 258	64.81 260	49.19 223	46.75 296	76.00 248	25.53 295	64.04 279	28.65 303	62.13 260	77.26 233

ADS-MVSNet2		51.33 274	48.76 277	59.07 264	66.02 289	44.60 232	50.90 309	59.76 285	36.90 304	50.74 283	66.18 299	26.38 289	63.11 281	27.17 305	54.76 292	69.50 294

LP		48.51 279	45.51 284	57.52 274	62.86 299	44.53 235	52.38 306	59.84 284	38.11 301	42.81 309	61.02 309	23.23 301	63.02 282	24.10 312	45.24 314	65.02 303

Gipuma		34.77 302	31.91 304	43.33 309	62.05 303	37.87 273	20.39 330	67.03 250	23.23 323	18.41 327	25.84 328	4.24 334	62.73 283	14.71 326	51.32 301	29.38 327
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
ITE_SJBPF				62.09 254	66.16 286	44.55 234		64.32 264	47.36 242	55.31 256	80.34 185	19.27 308	62.68 284	36.29 274	62.39 259	79.04 218

ANet_high		41.38 294	37.47 298	53.11 290	39.73 332	24.45 326	56.94 293	69.69 231	47.65 239	26.04 323	52.32 318	12.44 319	62.38 285	21.80 317	10.61 332	72.49 276

MIMVSNet		57.35 245	57.07 239	58.22 268	74.21 194	37.18 277	62.46 274	60.88 282	48.88 226	55.29 257	75.99 250	31.68 260	62.04 286	31.87 287	72.35 166	75.43 251

LCM-MVSNet		40.30 296	35.88 301	53.57 288	42.24 329	29.15 314	45.21 319	60.53 283	22.23 325	28.02 322	50.98 321	3.72 336	61.78 287	31.22 292	38.76 319	69.78 293

PatchT		53.17 268	53.44 265	52.33 294	68.29 273	25.34 324	58.21 290	54.41 308	44.46 267	54.56 263	69.05 288	33.32 244	60.94 288	36.93 266	61.76 262	70.73 291

WTY-MVS		59.75 232	60.39 220	57.85 271	72.32 232	37.83 274	61.05 283	64.18 265	45.95 256	61.91 192	79.11 204	47.01 123	60.88 289	42.50 240	69.49 210	74.83 258

XXY-MVS		60.68 227	61.67 212	57.70 273	70.43 254	38.45 270	64.19 269	66.47 252	48.05 236	63.22 173	80.86 172	49.28 82	60.47 290	45.25 222	67.28 226	74.19 265

tpmrst		58.24 240	58.70 229	56.84 275	66.97 279	34.32 298	69.57 244	61.14 281	47.17 244	58.58 235	71.60 274	41.28 181	60.41 291	49.20 189	62.84 255	75.78 247

PMVS	28.69 22	36.22 299	33.29 303	45.02 307	36.82 334	35.98 291	54.68 299	48.74 319	26.31 320	21.02 325	51.61 320	2.88 338	60.10 292	9.99 331	47.58 311	38.99 324
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PMMVS		53.96 262	53.26 266	56.04 277	62.60 301	50.92 152	61.17 282	56.09 301	32.81 312	53.51 274	66.84 295	34.04 236	59.93 293	44.14 226	68.18 218	57.27 315

UnsupCasMVSNet_bld		50.07 277	48.87 276	53.66 287	60.97 309	33.67 301	57.62 292	64.56 263	39.47 298	47.38 292	64.02 304	27.47 282	59.32 294	34.69 278	43.68 316	67.98 299

testpf		44.11 290	45.40 285	40.26 312	60.52 310	27.34 318	33.26 327	54.33 309	45.87 257	41.08 312	60.26 311	16.46 311	59.14 295	46.09 208	50.68 305	34.31 325

PVSNet_0	43.31 20	47.46 283	45.64 283	52.92 291	67.60 277	44.65 231	54.06 300	54.64 306	41.59 286	46.15 297	58.75 314	30.99 261	58.66 296	32.18 285	24.81 324	55.46 316

test20.03		53.87 264	54.02 261	53.41 289	61.47 304	28.11 316	61.30 280	59.21 286	51.34 209	52.09 278	77.43 233	33.29 245	58.55 297	29.76 299	60.27 278	73.58 269

UnsupCasMVSNet_eth		53.16 269	52.47 267	55.23 280	59.45 315	33.39 303	59.43 287	69.13 237	45.98 253	50.35 287	72.32 271	29.30 273	58.26 298	42.02 244	44.30 315	74.05 266

pmmvs3		44.92 287	41.95 292	53.86 286	52.58 322	43.55 242	62.11 277	46.90 325	26.05 321	40.63 314	60.19 312	11.08 325	57.91 299	31.83 288	46.15 312	60.11 311

test-LLR		58.15 242	58.13 234	58.22 268	68.57 269	44.80 229	65.46 260	57.92 291	50.08 218	55.44 254	69.82 286	32.62 254	57.44 300	49.66 186	73.62 147	72.41 279

test-mter		56.42 250	55.82 249	58.22 268	68.57 269	44.80 229	65.46 260	57.92 291	39.94 297	55.44 254	69.82 286	21.92 305	57.44 300	49.66 186	73.62 147	72.41 279

test1235678		45.66 284	44.46 289	49.26 299	59.88 313	28.68 315	56.36 296	55.54 305	39.12 300	40.89 313	63.40 306	14.41 316	57.32 302	21.05 318	49.47 308	61.78 307

new-patchmatchnet		47.56 282	47.73 280	47.06 303	58.81 316	9.37 335	48.78 313	59.21 286	43.28 275	44.22 303	68.66 289	25.67 294	57.20 303	31.57 291	49.35 309	74.62 262

EPMVS		53.96 262	53.69 262	54.79 284	66.12 287	31.96 308	62.34 276	49.05 318	44.42 268	55.54 252	71.33 277	30.22 266	56.70 304	41.65 247	62.54 258	75.71 248

dp		51.89 272	51.60 270	52.77 292	68.44 272	32.45 305	62.36 275	54.57 307	44.16 270	49.31 288	67.91 290	28.87 276	56.61 305	33.89 280	54.89 291	69.24 297

Anonymous20231206		55.10 260	55.30 252	54.48 285	69.81 263	33.94 300	62.91 273	62.13 279	41.08 288	55.18 258	75.65 252	32.75 252	56.59 306	30.32 294	67.86 220	72.91 271

testmv		42.25 292	40.11 295	48.66 300	53.23 320	27.02 319	56.62 295	55.74 304	37.25 303	33.10 319	59.52 313	7.78 330	56.58 307	19.61 322	38.13 320	62.40 306

wuykxyi23d		28.12 305	22.54 310	44.87 308	34.97 335	32.11 306	37.96 326	47.31 323	13.32 330	9.29 334	23.72 330	0.45 341	56.58 307	21.85 316	13.98 328	45.93 321

sss		56.17 253	56.57 243	54.96 282	66.93 280	36.32 289	57.94 291	61.69 280	41.67 285	58.64 234	75.32 255	38.72 199	56.25 309	42.04 243	66.19 230	72.31 282

RPSCF		55.80 256	54.22 260	60.53 261	65.13 292	42.91 248	64.30 268	57.62 293	36.84 306	58.05 239	82.28 134	28.01 278	56.24 310	37.14 265	58.61 283	82.44 171

test0.0.03 1		53.32 267	53.59 264	52.50 293	62.81 300	29.45 313	59.51 286	54.11 310	50.08 218	54.40 265	74.31 262	32.62 254	55.92 311	30.50 293	63.95 247	72.15 284

testgi		51.90 271	52.37 268	50.51 298	60.39 311	23.55 327	58.42 289	58.15 289	49.03 225	51.83 279	79.21 203	22.39 303	55.59 312	29.24 301	62.64 256	72.40 281

test2356		45.61 285	44.66 287	48.47 302	60.15 312	28.08 317	52.44 305	52.83 314	38.01 302	46.13 298	60.98 310	15.08 315	55.54 313	20.43 321	55.85 289	61.78 307

TESTMET0.1,1		55.28 258	54.90 254	56.42 276	66.56 284	43.67 241	65.46 260	56.27 300	39.18 299	53.83 269	67.44 293	24.21 300	55.46 314	48.04 196	73.11 154	70.13 292

YYNet1		50.73 275	48.96 274	56.03 278	61.10 307	41.78 253	51.94 307	56.44 298	40.94 290	44.84 300	67.80 292	30.08 268	55.08 315	36.77 267	50.71 303	71.22 287

MDA-MVSNet_test_wron		50.71 276	48.95 275	56.00 279	61.17 306	41.84 252	51.90 308	56.45 297	40.96 289	44.79 301	67.84 291	30.04 269	55.07 316	36.71 269	50.69 304	71.11 290

tpm		57.34 246	58.16 232	54.86 283	71.80 241	34.77 295	67.47 252	56.04 302	48.20 234	60.10 215	76.92 236	37.17 213	53.41 317	40.76 251	65.01 238	76.40 241

testus		44.59 288	43.87 290	46.76 304	59.85 314	24.65 325	53.86 301	55.82 303	36.26 307	43.97 306	63.42 305	8.39 329	53.14 318	20.70 320	52.52 298	62.51 305

ADS-MVSNet		48.48 280	47.77 279	50.63 297	66.02 289	29.92 312	50.90 309	50.87 317	36.90 304	50.74 283	66.18 299	26.38 289	52.47 319	27.17 305	54.76 292	69.50 294

FPMVS		42.18 293	41.11 293	45.39 305	58.03 317	41.01 259	49.50 311	53.81 312	30.07 316	33.71 318	64.03 302	11.69 321	52.08 320	14.01 327	55.11 290	43.09 322

test12356		36.16 300	35.94 300	36.83 313	50.82 324	8.52 336	44.84 320	53.49 313	32.72 313	30.11 321	55.08 316	7.11 332	49.47 321	16.60 324	32.68 322	52.50 317

CHOSEN 280x420		47.83 281	46.36 282	52.24 295	67.37 278	49.78 188	38.91 325	43.11 327	35.00 309	43.27 308	63.30 307	28.95 274	49.19 322	36.53 271	60.80 271	57.76 314

Patchmatch-test		49.08 278	48.28 278	51.50 296	64.40 295	30.85 311	45.68 317	48.46 321	35.60 308	46.10 299	72.10 272	34.47 233	46.37 323	27.08 307	60.65 272	77.27 232

1111		44.40 289	45.00 286	42.61 310	57.55 318	17.33 332	53.82 303	57.05 295	40.78 291	44.11 304	66.57 296	13.37 317	45.77 324	22.15 314	49.58 307	64.73 304

.test1245		34.88 301	39.49 296	21.04 322	57.55 318	17.33 332	53.82 303	57.05 295	40.78 291	44.11 304	66.57 296	13.37 317	45.77 324	22.15 314	0.00 335	0.03 334

DSMNet-mixed		39.30 298	38.72 297	41.03 311	51.22 323	19.66 329	45.53 318	31.35 333	15.83 329	39.80 316	67.42 294	22.19 304	45.13 326	22.43 313	52.69 297	58.31 313

LF4IMVS		42.95 291	42.26 291	45.04 306	48.30 326	32.50 304	54.80 298	48.49 320	28.03 318	40.51 315	70.16 284	9.24 327	43.89 327	31.63 289	49.18 310	58.72 312

PNet_i23d		27.88 306	25.99 306	33.55 316	47.54 327	25.89 321	47.24 316	32.91 332	21.44 326	15.90 328	38.09 325	0.85 340	42.76 328	16.90 323	13.03 330	32.00 326

N_pmnet		39.35 297	40.28 294	36.54 314	63.76 297	1.62 339	49.37 312	0.76 340	34.62 310	43.61 307	66.38 298	26.25 291	42.57 329	26.02 311	51.77 299	65.44 301

E-PMN		23.77 308	22.73 309	26.90 320	42.02 330	20.67 328	42.66 322	35.70 329	17.43 327	10.28 332	25.05 329	6.42 333	42.39 330	10.28 330	14.71 327	17.63 328

EMVS		22.97 309	21.84 311	26.36 321	40.20 331	19.53 330	41.95 324	34.64 330	17.09 328	9.73 333	22.83 331	7.29 331	42.22 331	9.18 332	13.66 329	17.32 329

PMMVS2		27.40 307	25.91 307	31.87 318	39.46 333	6.57 337	31.17 328	28.52 334	23.96 322	20.45 326	48.94 324	4.20 335	37.94 332	16.51 325	19.97 325	51.09 318

new_pmnet		34.13 303	34.29 302	33.64 315	52.63 321	18.23 331	44.43 321	33.90 331	22.81 324	30.89 320	53.18 317	10.48 326	35.72 333	20.77 319	39.51 317	46.98 320

MVE	17.77 23	21.41 310	17.77 312	32.34 317	34.34 336	25.44 323	16.11 331	24.11 335	11.19 331	13.22 330	31.92 326	1.58 339	30.95 334	10.47 329	17.03 326	40.62 323
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuyk23d		13.32 312	12.52 313	15.71 323	47.54 327	26.27 320	31.06 329	1.98 339	4.93 333	5.18 335	1.94 336	0.45 341	18.54 335	6.81 334	12.83 331	2.33 332

DeepMVS_CX				12.03 324	17.97 337	10.91 334		10.60 338	7.46 332	11.07 331	28.36 327	3.28 337	11.29 336	8.01 333	9.74 334	13.89 330

tmp_tt		9.43 313	11.14 314	4.30 325	2.38 338	4.40 338	13.62 332	16.08 337	0.39 334	15.89 329	13.06 332	15.80 313	5.54 337	12.63 328	10.46 333	2.95 331

cdsmvs_eth3d_5k		17.50 311	23.34 308	0.00 328	0.00 341	0.00 341	0.00 333	78.63 151	0.00 337	0.00 338	82.18 135	49.25 86	0.00 338	0.00 337	0.00 335	0.00 336

pcd_1.5k_mvsjas		3.92 317	5.23 318	0.00 328	0.00 341	0.00 341	0.00 333	0.00 341	0.00 337	0.00 338	0.00 339	47.05 120	0.00 338	0.00 337	0.00 335	0.00 336

pcd1.5k->3k		30.06 304	30.56 305	28.55 319	78.81 112	0.00 341	0.00 333	82.07 68	0.00 337	0.00 338	0.00 339	39.61 191	0.00 338	0.00 337	74.56 136	85.66 69

sosnet-low-res		0.00 318	0.00 319	0.00 328	0.00 341	0.00 341	0.00 333	0.00 341	0.00 337	0.00 338	0.00 339	0.00 344	0.00 338	0.00 337	0.00 335	0.00 336

sosnet		0.00 318	0.00 319	0.00 328	0.00 341	0.00 341	0.00 333	0.00 341	0.00 337	0.00 338	0.00 339	0.00 344	0.00 338	0.00 337	0.00 335	0.00 336

uncertanet		0.00 318	0.00 319	0.00 328	0.00 341	0.00 341	0.00 333	0.00 341	0.00 337	0.00 338	0.00 339	0.00 344	0.00 338	0.00 337	0.00 335	0.00 336

Regformer		0.00 318	0.00 319	0.00 328	0.00 341	0.00 341	0.00 333	0.00 341	0.00 337	0.00 338	0.00 339	0.00 344	0.00 338	0.00 337	0.00 335	0.00 336

testmvs		4.52 316	6.03 317	0.01 327	0.01 339	0.00 341	53.86 301	0.00 341	0.01 335	0.04 336	0.27 337	0.00 344	0.00 338	0.04 335	0.00 335	0.03 334

test123		4.73 315	6.30 316	0.02 326	0.01 339	0.01 340	56.36 296	0.00 341	0.01 335	0.04 336	0.21 338	0.01 343	0.00 338	0.03 336	0.00 335	0.04 333

ab-mvs-re		6.49 314	8.65 315	0.00 328	0.00 341	0.00 341	0.00 333	0.00 341	0.00 337	0.00 338	77.89 219	0.00 344	0.00 338	0.00 337	0.00 335	0.00 336

uanet		0.00 318	0.00 319	0.00 328	0.00 341	0.00 341	0.00 333	0.00 341	0.00 337	0.00 338	0.00 339	0.00 344	0.00 338	0.00 337	0.00 335	0.00 336

sam_mvs1												34.74 229

sam_mvs												33.43 243

MTGPA								80.97 96

MTMP								17.08 336

test9_res														75.28 14	88.31 16	83.81 137

agg_prior2														73.09 29	87.93 23	84.33 115

test_prior4						62.51 17	82.08 57

test_prior2							81.75 59		60.37 78	75.01 20	89.06 33	56.22 17		72.19 32	88.96 8

新几何2							76.12 158

旧先验1					83.04 53	53.15 125		67.52 246			87.85 48	44.08 152			80.76 72	78.03 225

原ACMM2							79.02 95

test222					83.14 52	58.68 56	72.57 213	63.45 268	41.78 283	67.56 125	86.12 72	37.13 214			78.73 106	74.98 256

segment_acmp												54.23 33

testdata1							72.65 211		60.50 75

plane_prior7					81.41 70	55.96 93

plane_prior6					81.20 77	56.24 88						45.26 142

plane_prior4											86.10 73

plane_prior3						56.09 90			63.92 30	69.27 95

plane_prior2							84.22 22		64.52 24

plane_prior1					81.27 75

plane_prior						56.31 84	83.58 31		63.19 37						80.48 78

n2								0.00 341

nn								0.00 341

door-mid								47.19 324

test11								83.47 43

door								47.60 322

HQP5-MVS						54.94 106

HQP-NCC					80.66 82		82.31 52		62.10 54	67.85 117

ACMP_Plane					80.66 82		82.31 52		62.10 54	67.85 117

BP-MVS														67.04 58

HQP3-MVS								83.90 32							80.35 81

HQP2-MVS												45.46 136

NP-MVS					80.98 80	56.05 92					85.54 85

MDTV_nov1_ep13_2view						25.89 321	61.22 281		40.10 295	51.10 281		32.97 247		38.49 259		78.61 220

ACMMP++_ref															74.07 143

ACMMP++															72.16 169

Test By Simon												48.33 105

High-resolution multi-view benchmark